Density of Oil-related Systems at High Pressures

Experimental measurements of HPHT density

Vasos Vasou s131031

MASTER THESIS

DEPARTMENT OF CHEMISTRY

Lyngby, Denmark JULY 2015

         

Supervisors: Senior researcher

Wei Yan

Post Doc. Teresa Regueira Muñiz

Acknowledgment

Upon the completion of my Master of Science’s thesis I would like, first and foremost, to express the deepest appreciation to my supervisors senior researcher Wei Yan and Post Doc.Teresa Regueira Muñiz for their continuous advice and guidance throughout the project. In addition, a thank you to the administration and the technicians at CERE for their help and assistance throughout the experimental work of this project. This work as part of a bigger project is funded by the Danish National Advanced Technology Foundation (Maersk Oil and DONG E&P are partners), which is gratefully acknowledged. Last but not least, a special thank to all my friends and family for their unconditional support and understanding throughout writing this thesis and my life in general.

ABSTRACT

The need for more energy recourses in combination with the gradual decrease of easily accessible hydrocarbons has led the industry to exploit deeper reservoirs, which are associated with higher pressures and temperatures. The correct identification of the physical properties of the reservoir hydrocarbons, such us density, is a significant parameter for estimating the amount of recourses in place and forecasting the production. Therefore in this work the measurement of the density of the binary system methane - n-decane for four different compositions (xmethane = 0, 0.227, 0.6016, 0.8496) and under a wide range of pressure (up to 1400 bar) and temperature (up to 190 °C) was carried out with the use of an Anton Paar DMA-HPM densimeter. The calibration of the DMA-HPM densimeter was performed for pressures up to 140 MPa (1400 bar) and temperatures up to 190 °C (463.15 K) with a modified Lagourette equation proposed by Comuñas et al and for the validation of the apparatus, the density of n-decane was measured and compared with the literature. The results were then compared with the data from NIST and they were in good agreement with an AAD of 0.08%. For the mixture with a mole fraction of methane xmethane = 0.227 and after a correlation with the Tait equition the experimental data had an AAD of 0.17% with the literature. For the mixture with a mole fraction of methane xmethane = 0.6017 the AAD was between 0.19% and 0.30% with the literature. The last mixture under study had a mole fraction of methane xmethane = 0.8496 and gave an expected high AAD around 11% because it was compared with a mixture with lower methane mole fraction (xmethane = 0.799). Finally a comparison of two cubic EoS (SRK and PR) with two non-cubic EoS (PC SAFT and SBWR) was performed. PC SAFT was the one that performed better with AADs lower than 1.2%. The SRK, on the other hand, showed very high deviations between 10% and 20%. For the pure n-decane the non-cubic equations performed much better with lower deviations. For the mixture with methane mole fraction xmethane = 0.227 the non-cubic equations performed better with AADs around 1%. For the mixture with methane mole fraction xmethane = 0.6017 PC SAFT had an AAD around 0.6% and both PR and SBWR showed an AAD around 4%. Finally, for the mixture with methane mole fraction xmethane = 0.8496 PC SAFT and PR showed the lowest deviations with an AAD of 0.67% and 0.87%, respectively.

Table of Contents

Acknowledgment  .....................................................................................................  2  

ABSTRACT  ................................................................................................................  3  

Table  of  Contents  ....................................................................................................  5  

List  of  figures  ...........................................................................................................  7  

List  of  tables  ............................................................................................................  9  

1   Introduction  .......................................................................................................  1  

1.1   HPHT  reservoirs  .......................................................................................................................................  1  1.2   Scope  of  this  thesis  ...................................................................................................................................  4  1.3   Literature  review  ......................................................................................................................................  4  

2   Density  ..............................................................................................................  7  

2.1   Introduction  ................................................................................................................................................  7  2.2   Density  measurement  methods  .........................................................................................................  8  2.2.1   Pycnometertic  densitometers  ..........................................................................................................  8  2.2.2   Hydrometers  ............................................................................................................................................  9  2.2.3   Refractometer  and  index  of  refraction  densitometers  .......................................................  10  2.2.4   Vibrating  tube  densitometers  .......................................................................................................  11  

3   HPHT  Density  Measurements  ...........................................................................  13  

3.1   U-­‐tube  basic  principle  ..........................................................................................................................  13  3.2   Calibration  procedure  ..........................................................................................................................  16  3.3   Experimental  setup  ...............................................................................................................................  19  3.4   Experimental  procedure  .....................................................................................................................  25  3.4.1   Apparatus  cleaning  procedure  .....................................................................................................  25  3.4.2   Mixture  preparation  .........................................................................................................................  26  3.4.3   Performing  a  measurement  ...........................................................................................................  27  

4   Density  modelling  ............................................................................................  29  

4.1   Cubic  EoS  ....................................................................................................................................................  29  4.2   Non-­‐cubic  EoS  ..........................................................................................................................................  30  

5   Results  and  discussion  .....................................................................................  32  

5.1   Densimeter  calibration  and  validation  results  ..........................................................................  32  5.2   Mixture  methane  –  n-­‐decane  (xmethane  =  0.227)  ..........................................................................  38  

5.3   Mixture  methane  –  n-­‐decane  (xmethane  =  0.6017)  .......................................................................  41  5.4   Mixture  methane  –  n-­‐decane  (xmethane  =  0.8496)  .......................................................................  44  5.5   Density  modeling  ....................................................................................................................................  48  

6   Conclusion  and  future  work  .............................................................................  49  

7   Bibliography  .....................................................................................................  51  

8          Appendix    ………………………………………………………………………………………………………56  

 

List of figures

Figure  1:  HPHT  tiers  classification  from  Baker  Hughes  (BakerHughes,  2005)  __________________________  1  Figure  2:  HPHT  tiers  classification  from  Schlumberger  (Belani  &  Orr,  2008)  ___________________________  2  Figure  3:  Technology  Gaps,  2012  (Shadravan  &  Amani,  2012)  ___________________________________________  2  Figure  4:  Most  important  challenges  of  HPHT  reservoirs  (Shadravan  &  Amani,  2012)  _________________  3  Figure  5:  Oil  in  Water  _______________________________________________________________________________________  7  Figure  6:  Schematic  of  a  pycnometer  (Eren,  1999)   _______________________________________________________  8  Figure  7:  Schematic  of  a  Hydrometer  (Paar,  2015)  _______________________________________________________  9  Figure  8:  Index  of  refraction  densitometer  (Eren,  1999)   _______________________________________________  10  Figure  9:  (a)  Single  vibrating  tube  densitometer,  (b)  Two-­‐tube  vibrating  densitometer  (Eren,  1999)

 _____________________________________________________________________________________________________________  11  Figure  10:  U-­‐tube  filled  with  water  (Paar,  2015)   _______________________________________________________  13  Figure  11:  U-­‐tube  filled  with  air  (Paar,  2015)  ___________________________________________________________  13  Figure  12:  U-­‐tube  measurement  cell  (Paar,  2015)  ______________________________________________________  14  Figure  13:  U-­‐tube  setup  of  the  Anton  Paar  DMA-­‐HPM  measuring  cell  (Paar,  2015)  __________________  14  Figure  14:  Five  key  points  of  the  Mass  Spring  Model  ____________________________________________________  15  Figure  15:  Graph  for  air  and  water  adjustment  (Paar,  2015)  __________________________________________  16  Figure  16:  Anton  Paar  DMA-­‐HPM  measuring  cell  (Paar,  2015)  ________________________________________  19  Figure  17:  Anton  Paar  DMA-­‐HPM  (DTU  laboratory)  ____________________________________________________  20  Figure  18:  PolyScience  advanced  programmable  temperature  controller  with Swivel  180™  Rotating  

Controller  (DTU  laboratory)  _____________________________________________________________________________  20  Figure  19:  (a)  Anton  Paar  mPDS  5  (Paar,  2015),  (b)  Anton  Paar  mPDS  5  (DTU  laboratory)   ________  21  Figure  20:  Snapshot  of  the  recording  window  from  the  Microsoft  Excel®  spreadsheet  provided  by  

Anton  Paar  ________________________________________________________________________________________________  21  Figure  21:  Snapshot  of  the  data  transfer  section  and  the  stability  slope  section  of  the  recording  

window  ____________________________________________________________________________________________________  22  Figure  22:  Snapshot  of  the  data  spreadsheet  of  the  Microsoft  Excel®  tool  _____________________________  22  Figure  23:  SIKA  digital  pressure  gauge  Type  P  (DTU  laboratory,  left)  (SIKA,  2015,  right)  ___________  23  Figure  24:  Edwards  E2M1.5  two-­‐stage  oil  sealed  rotary  vane  pump  and  Edwards  Active  Digital  

Controller  (ADC)  gauge  (DTU  laboratory)   ______________________________________________________________  23  Figure  25:  Teledyne  Isco  260D  syringe  pump  (DTU  laboratory)  _______________________________________  24  Figure  26:  Experimental  setup  (DTU  laboratory)  _______________________________________________________  24  Figure  27:  Schematic  of  the  experimental  density  measurement  setup  ________________________________  25  Figure  28:  Mixture  (top)  and  Nitrogen  cylinder  (bottom)  (DTU  laboratory)  __________________________  26  Figure  29:  Methane  weighing  with  Mettler  Toledo  PR1203  balance  (DTU  laboratory)   ______________  27  Figure  30:  Period  of  the  evacuated  densimeter  for  temperatures  from  5°C  to  190°C)  ________________  34  Figure  31:  Water  measured  period  for  temperatures  from  5°C  to  190°C  and  pressures  from  1  bar  to  

1400  bar  ___________________________________________________________________________________________________  34  Figure  32:  Characteristic  parameter  A(T)  for  temperatures  from  5°C  to  190°C  ______________________  35  

Figure  33:  Ratio  between  parameter  A(T)  and  parameter  B(T,p)  _____________________________________  35  Figure  34:  n-­‐decane  measured  period  for  temperatures  from  5°C  to  190°C  and  pressures  from  1  bar  

to  1400  bar  ________________________________________________________________________________________________  36  Figure  35:  Relative  deviations  between  the  experimental  density  values  of  n-­‐decane  and  the  data  

from  Lemmon  &  Span  (2006)  as  a  function  of  temperature  ____________________________________________  37  Figure  36:  Relative  deviations  between  the  experimental  density  values  of  n-­‐decane  and  the  data  

from  Lemmon  &  Span  (2006)  as  a  function  of  pressure  _________________________________________________  37  Figure  37:  Surface  ρ(T,p)  for  our  experimental  results  for  the  mixture  methane  –  n-­‐decane  (xmethane  =  

0.227)  ______________________________________________________________________________________________________  39  Figure  38:  Surface  ρ(T,p)  for  the  results  from  Audonnet  &  Pádua  (2004)  for  the  mixture  methane  –  n-­‐

decane  (xmethane  =  0.227)  __________________________________________________________________________________  39  Figure  39:  Relative  deviations  between  the  experimental  density  values  of  the  mixture  methane  –  n-­‐

decane  (xmethane  =  0.227)  and  the  data  from  Audonnet  &  Paduá  (2004)  (xmethane  =  0.227)  as  a  function  

of  temperature  ____________________________________________________________________________________________  40  Figure  40:  Relative  deviations  between  the  experimental  density  values  of  the  mixture  methane  –  n-­‐

decane  (xmethane  =  0.227)  and  the  data  from  Audonnet  &  Paduá  (2004)  (xmethane  =  0.227)  as  a  function  

of  pressure  _________________________________________________________________________________________________  40  Figure  41:  Surface  ρ(T,p)  for  our  experimental  results  for  the  mixture  methane  –  n-­‐decane  (xmethane  =  

0.6017)   ____________________________________________________________________________________________________  42  Figure  42:  Surface  ρ(T,p)  for  the  results  from  Audonnet  &  Pádua  (2004)  for  the  mixture  methane  –  n-­‐

decane  (xmethane  =  0.601)  __________________________________________________________________________________  42  Figure  43:  Relative  deviations  between  the  experimental  density  values  of  the  mixture  methane  -­‐  n-­‐

decane  (xmethane  =  0.6017)  and  the  data  from  Audonnet  &  Paduá  (2004)  (xmethane  =  0.601)  and  Canet  et  

al.  (2002)  (xmethane  =  0.6)  as  a  function  of  temperature  __________________________________________________  43  Figure  44:  Relative  deviations  between  the  experimental  density  values  of  the  mixture  methane  -­‐  n-­‐

decane  (xmethane  =  0.6017)  and  the  data  from  Audonnet  &  Paduá  (2004)  (xmethane  =  0.601)  and  Canet  et  

al.  (2002)  (xmethane  =  0.6)  as  a  function  of  pressure  ______________________________________________________  44  Figure  45:  Surface  ρ(T,p)  for  our  experimental  results  for  the  mixture  methane  –  n-­‐decane  (xmethane  =  

0.8496)   ____________________________________________________________________________________________________  45  Figure  46:  Surface  ρ(T,p)  for  the  results  from  Audonnet  &  Pádua  (2004)  for  the  mixture  methane  –  n-­‐

decane  (xmethane  =  0.799)  __________________________________________________________________________________  45  Figure  47:  Relative  deviations  between  the  experimental  density  values  of  the  mixture  methane  -­‐  n-­‐

decane  (xmethane  =  0.8496)  and  the  data  from  Audonnet  &  Paduá  (2004)    (xmethane  =  0.799)  as  a  

function  of  temperature  __________________________________________________________________________________  46  Figure  48:  Relative  deviations  between  the  experimental  density  values  of  the  mixture  methane  -­‐  n-­‐

decane  (xmethane  =  0.8496)  and  the  data  from  Audonnet  &  Paduá  (2004)  (xmethane  =  0.799)  as  a  function  

of  pressure  _________________________________________________________________________________________________  47  Figure  49:  Density  as  a  function  of  pressure  for  all  compositions  at  5  °C  and  190  °C  _________________  47  Figure  50:  AAD  of  the  comparison  between  the  experimental  densities  and  those  calculated  with  the  

EOS  for  the  whole  temperature  and  pressure  range  ____________________________________________________  48  

 

List of tables

Table  1:  HPHT  applications  categories  ____________________________________________________________________  1  Table  2:  Experimental  uncertainty  of  density  (Segovia  et  al.,  2009)  ___________________________________  19  Table  3:  Mixture  compositions  ___________________________________________________________________________  26  Table  4:  Mixture  composition,  pressure  and  temperature  range  _______________________________________  28  Table  5:  Pressure  steps   ___________________________________________________________________________________  28  Table  6:  Temperature  steps  ______________________________________________________________________________  28  Table  7:  Tc,  Pc,  ω  and  Zc  for  methane  and  n-­‐decane  _____________________________________________________  30  Table  8:  Interaction  parameters  for  the  methane  –  n-­‐decane  binary  mixture  (Wei  et  al.,  2015)  _____  30  Table  9:  Values  for  ρw,  τw,  ρd,  τv  ___________________________________________________________________________  32  Table  10:  Experimental  density  values  (kg/m3)  of  n-­‐decane  ___________________________________________  36  Table  11:  Experimental  density  values  (kg/m3)  of  the  mixture  methane  -­‐  n-­‐decane  (xmethane  =  0.227)  38  Table  12:  Parameters  obtained  in  the  Tait  equation  with  the  results  from  Audonnet  &  Pádua  (2004)  

(xmethane  =  0.227)  and  our  experimental  results  (xmethane  =  0.227)  _______________________________________  39  Table  13:  Experimental  density  values  (kg/m3)  of  the  mixture  methane  -­‐  n-­‐decane  (xmethane  =  0.6017)

 _____________________________________________________________________________________________________________  41  Table  14:  Parameters  obtained  in  the  Tait  equation  with  the  results  from  Audonnet  &  Pádua  (2004)  

(xmethane  =  0.601),  our  experimental  results  (xmethane  =  0.6017)  and  those  from  Canet  et  al.  (2002)  

(xmethane  =  0.6)   _____________________________________________________________________________________________  41  Table  15:  Experimental  density  values  (kg/m3)  of  the  mixture  methane  -­‐  n-­‐decane  (xmethane  =  0.8496)

 _____________________________________________________________________________________________________________  44  Table  16:  Parameters  obtained  in  the  Tait  equation  with  the  results  from  Audonnet  &  Pádua  (2004)  

(xmethane  =  0.799)  and  our  experimental  results  (xmethane  =  0.8496)  _____________________________________  46  Table  17:  AAD  and  MAD  of  the  comparison  between  the  experimental  densities  and  those  calculated  

with  the  EOS  for  the  whole  temperature  and  pressure  range  __________________________________________  48  Table  18:  Technical  specifications  of  the  External  Measuring  Cell  DMA-­‐HPM  (Paar,  2015)  __________  56  Table  19:  Technical  specifications  of  the  PolyScience  advanced  programmable  temperature  

controller  with Swivel  180™  Rotating  Controller  (PolyScience,  2015)  _________________________________  57  Table  20:  Technical  specifications  of  the  evaluation  unit  mPDS  5  (Paar,  2015)  _______________________  57  Table  21:  Technical  specifications  of  the  SIKA  digital  pressure  gauge  Type  P  (SIKA,  2015)  (SIKA,  

2015)  ______________________________________________________________________________________________________  58  Table  22:  Technical  specifications  of  the  Edwards  E2M1.5  two-­‐stage  oil  sealed  rotary  vane  pump  

(Edwards,  2015)  __________________________________________________________________________________________  59  Table  23:  Technical  specifications  of  the  Edwards  Active  Digital  Controller  (ADC)  gauge  (Edwards,  

2015)  ______________________________________________________________________________________________________  60  Table  24:  Technical  specifications  of  the  Teledyne  Isco  260D  Syringe  Pump  (Isco,  2013)  ____________  61  

Table  25:  Chemical  and  physical  properties  of  Ethanol  (VWR,  2015)  __________________________________  62  Table  26:  Chemical  and  physical  properties  of  Toluene  (SIGMA-­‐ALDRICH,  2014)  ____________________  62  Table  27:  Chemical  and  physical  properties  of  n-­‐decane  (SIGMA-­‐ALDRICH,  2014)  ___________________  63  Table  28:  Chemical  and  physical  properties  of  methane  (AGA,  2015)   _________________________________  63  

1

1 Introduction

1.1 HPHT  reservoirs  

In a constantly growing world due to the increase of global population and the technological advancement of new emerging technologies energy demand is, subsequently, rising. The need for more energy recourses in combination with the gradual decrease of easily accessible hydrocarbons has drawn the attention of the industrial world into the exploration of less accessible, deeper and more technologically challenging formations. This pursuit for more hydrocarbons has led the industry to exploit deeper reservoirs, which are associated with higher pressures and temperatures. Several studies have defined reservoirs as High Pressure High Temperature (HPHT) when they are associated with pressures exceeding 700 bar (10000 psi) and temperatures over 150 °C (300 °F) (Cullen, 1993; Guilory, 2005; Ling et al., 2009; Primio & Neumann, 2007). Even though, HPHT drilling is not rigorously pursuit during times of decreased oil price due to high cost, there are a lot of HPHT fields around the world mainly in the Gulf of Mexico, Middle East, South Asia, Africa and the North Sea (Bland et al., 2006). A tier structure categorizing the various HPHT applications is widely accepted in the industry (Table 1). This way the details and the limitations of available technology in each category are specified. (Thompson et al., 2012; Shadravan & Amani, 2012). Table 1: HPHT applications categories

Tier category Pressure - bar (psi) Temperature - °C (°F) Tier 1 (HPHT) 700 (10000) < p < 1400 (20000) 150 (300) < T < 205 (400)

Tier 2 (ultra HPHT) 1400 (20000) < p < 2100 (30000) 205 (400) < T < 260 (500) Tier 3(extreme HPHT) p > 2100 (30000) T > 260 (500)

An example of how the industry defines the tiers for HPHT applications can be seen in Figure 1 and Figure 2 from Baker Hughes and Schlumberger, respectively.

Figure 1: HPHT tiers classification from Baker Hughes (BakerHughes, 2005)

2

Figure 2: HPHT tiers classification from Schlumberger (Belani & Orr, 2008)

On April 2010 methane gas under high pressure from the Macondo HPHT well in the Gulf of Mexico was shot up from the well into the platform where it expanded and ignited leading to a devastating explosion (Garg & Gokavarapu, 2012). This shocking accident alerted the industry and brought the risk and challenges of drilling in deep, unconventional formations into perspective (Shadravan & Amani, 2012). The industry is constantly improving the technologies required for drilling and producing in such harsh formations but the gap between the available technology and the demands for production from HPHT fields still remains. In the 2012 HPHT well summit in London, the technological gaps were identified as depicted in Figure 3.

Figure 3: Technology Gaps, 2012 (Shadravan & Amani, 2012)

3

In general, the initial challenge when it comes to the decision-making process regarding HPHT reservoirs is the high cost. The Rate of Penetration (ROP) in HPHT wells is 10% slower than normal drilling conditions and in combination with the increased depth of the reservoir, the average drilling time for HPHT wells can be up to 30% longer (Proehl & Sabins, 2006). The slower drilling increases the rental time of the rig and the drilling equipment, which essentially skyrockets the overall cost. The most important challenges that contribute to the increased cost of HPHT wells can be seen in Figure 4.

Figure 4: Most important challenges of HPHT reservoirs (Shadravan & Amani, 2012)

During the design of the well, the stability of the borehole can be especially complicated because of the thermal effect on the fracture gradient. Increasing temperatures can induce high tensile or compressive stresses on the formation. In addition, the high temperature can affect the density of the drilling mud and the well cementing operations with altering the chemical and physical behaviour of the cement (Radwan & Karimi, 2011). Materials under high temperatures expand, leading to a more general well growth that can result to an elevation of the whole structure during production. One more problem the industry faces is the effect of the extreme temperature to the downhole equipment. Most of the tools in the market are rated to 150 °C so when the temperature exceed that the tools won’t be applicable. Also, the equipment’s failure rate when operates above 140 °C is much higher than in cooler environments (Gjonnes & Myhre, 2005). Finally another important challenge is the lack of experienced personnel, which can be an even greater problem during decision-making processes and safety measures especially regarding the handling of the drilling fluids in high temperatures.

4

1.2 Scope  of  this  thesis  

As already mentioned, the development of HPHT reservoirs can be a particularly challenging and risky endeavour but if done successfully can also be highly rewarding. A successful operation in the oil industry is one with positive revenue and to achieve that in a highly cost and demanding HPHT reservoir the technical risks must be reduced. In order to accomplish that, a better understanding of the behaviour of the hydrocarbon reservoir fluids is crucial. The correct identification of the physical properties of the reservoir hydrocarbons is a significant parameter for estimating the amount of recourses in place and forecasting the production. Under this work the property that is studied is density. The experimental data for density in high pressures and temperatures are insufficient, so further experimentation under extreme conditions is needed. As mentioned before, most of the tools in the market are not designed to withstand such extreme conditions making the gathering of data extremely difficult. For the industry to be able to predict with accuracy the physical properties of hydrocarbon related systems under HPHT conditions, the development of predictive models is required. Under this thesis the five major tasks presented below are considered:

• Literature review of the existing relevant data on density of alkane binary mixtures under high pressures and temperatures.

• Calibration of the densimeter for pressures up to 140 MPa (1400 bar) and temperatures up to 190 °C (463.15 K).

• Validation of the apparatus through the use of n-decane. • Measurement of the density of the binary system methane - n-decane for three

different compositions and under a wide range of pressure and temperature. • A comparison of two cubic Equations of State (EoS) (Soave–Redlich–Kwong

and Peng–Robinson) with two non-cubic EoS (Perturbed Chain Statistical Associating Fluid Theory and Benedict–Webb–Rubin).

1.3 Literature  review  

Canet et al. (2002) used an Anton Paar DMA 60 densimeter to measure the density of the binary mixture methane – n-decane over the temperatures from 20 °C to 100 °C with a 20 °C step. They covered the whole composition range of the binary mixture by measuring the density for compositions with methane mole fraction equal to: xmethane = 0.3124, 0.4867, 0.6, 0.7566, 0.9575. The pressure range under experimentation was between 200 bar and 650 bar and then the results were extrapolated up to 1400 bar. The experimental densities were then, compared with those generated by the Lee & Kesler (1975) equation with an absolute average deviation of 3.3% with the mixing rules proposed by Spencer & Danner (1972) and 7.3% with the mixing rules proposed by Joffe (1947).

5

Audonnet & Pádua (2004) also measured the density of the methane – n-decane binary mixture in a temperature range from 30 °C to 120 °C and for pressures up to 750 bar. They covered the whole composition range of the binary mixture by measuring the density for compositions with methane mole fraction equal to: xmethane = 0, 0.227, 0.410, 0.601, 0.799. The obtained results were then correlated using the Tait equation (Dymond & Malhotra, 1988) and compared with literature. For the composition xmethane = 0.601 the experimental results were compared with Canet et al. (2002) and found to have a standard deviation of 0.17% and with De Sant’ Ana (2000) and found to have a standard deviation of 0.3%. Another work, from Amorim et al (2007), used a densimeter provided by Anton Paar. The densimeter DMA 512 P was used in a temperature range of 45 °C to 140 °C and for pressures between 68.95 bar and 620.53 bar. The calibration fluids were toluene, cyclohexane and n- heptane and the density of the binary mixture of n-hexadecane – cyclohexane was measured with an experimental error of 0.5 kg.m-3. The deviation of the density measurements with the literature was 0.75 kg.m-3. All data were correlated successfully with a modified EoS from Peng & Robinson (1976). Gil et al. (2007) discussed the measurement of the density for the binary mixture CO2 – ethane for pressures between 100 bar and 200 bar with a pressure step of 5 bar. The Anton Paar DMA 512 P that was used was calibrated from 5 °C to 45 °C and for pressures up to 200 bar with mili-Q water as the reference fluid. The densities of the mixture were calculated with the use of the cubical EoS suggested from Peng & Robinson (1976) and Patel & Teja (1982) and after comparison between the experimental values and the calculated values the root-mean-square deviation was 3.67% for Peng-Robinson and 4.33% for Patel-Teja. The mean standard deviation of density was 0.09%. Many authors used the Anton Paar densimeters to measure densities of pure compounds. The Anton Paar DMA-HPM densimeter was used from Comuñas et al. (2008) to measure the density of diethyl adipate over the temperatures from 20 °C to 130 °C and pressures up to 1400 bar. To calculate density a modified equation from Lagourette et al. (1992) was used and the uncertainty was 0.05%. For the validation of the densimeter the results for the densities of 1-butanol and toluene were compared with the literature and the average absolute deviation was lower than 0.08%. Caudwell et al. (2004) used a vibrating-wire instrument for the measurement of the density of n-dodecane and n-octadecane for temperatures between 25 °C to 200 °C and pressures up to 2000 bar. For the calibration procedure measurements of vacuum, air and toluene at 25 °C were taken. After comparison with the experimental data from Harris et al. (1997) and Kashiwagi et al. (1982) the uncertainty was 0.2%. Segovia et al. (2009) also used the DMA-HPM densimeter from Anton Paar, which was calibrated in the temperature region between 10 °C and 125 °C and for pressures

6

up to 700 bar. The Lagourette et al (1992) equation as modified by Comuñas et al (2008) was used and vacuum, water and n-decane were the calibration fluids. The density of toluene and n-decane were then measured and the absolute average deviation with Cibulka & Hnedkovsky (1996) was 0.03% and 0.07%, respectively. After literature review and research the fact that the industry lacks experimental data for high-pressures over 700 bar was confirmed. More experimental data are necessary to enhance the knowledge around the density of alkane binary mixtures over extreme pressure and temperature conditions.

7

2 Density

2.1 Introduction  

Viana et al. (2002) identifies density as a fundamental parameter that contributes to the characterization of the product. Density is defined as the exact mass of a solid, gas or liquid that is occupying a specific volume and the SI unit is kilogram per cubic meter (kg/m3). The most common symbol for density is the Greek letter ρ and it can be mathematically defined as: ρ = !

! [1]

where m is the mass and V is the volume. The effects of density can be observed on both solids and fluids. An example can be seen in Figure 5. Oil and water don’t mix and oil swim on top creating a two layer liquid. The water has higher density and less buoyancy than the oil, so it will sink while the oil with the lesser density swims on top.

Figure 5: Oil in Water

The effects of density on gases is less visible but equally important. For example the fact that helium has lesser density that the atmospheric air it might not be easy to grasp but it can become very obvious when a Helium balloon is let go and rises up into the sky. Another effect of density can be seen when even the slightest change in the density of the air directly influence the weather. Pressure and temperature are two important parameters that affect density. An increase on pressure will cause an increase on density whereas, on the other hand, for most materials the temperature affects density inversely proportional. In petrochemistry the density of oil is very important because with precise measurements a material characterization and quality control of oil products can be achieved.

8

2.2 Density  measurement  methods    

In general, the measurement of fluids densities is a much more complex science than the measurement of the density of solids. Density measurements on fluids are divided into two forms, static and dynamic. Sydenham (1999) defines the static characteristics of the instrumentation as the performance criteria for the measurement of quantities that remain constant, or vary only quite slowly while dynamic characteristics are the set of criteria defined for the instrument, which are changing rapidly with time. Static density measurements are well developed and usually more precise and with greater resolution than dynamic measurements. Commonly, dynamic-type measurements are used for real-time experiments where the properties of the fluids are not constant. Static density measurements, on the other hand, are employed in laboratory conditions (Eren, 1999). A quick review of the basic available density measurement methods and a comparison between them regarding precision, speed, cost and applications is presented. These methods include:

• Pycnometric densitometers • Hydrometers • Refractometer and index of refraction densitometers • Vibrating tube densitometers

2.2.1 Pycnometertic  densitometers  

Pycnometers are static devices with a container of fixed volume and a capillary bore. They are commonly used in the chemical and pharmaceutical industry and in research facilities or universities (Paar, 2015). A schematic of a pycnometer can be seen in Figure 6.

Figure 6: Schematic of a pycnometer (Eren, 1999)

The first step to measure the density of a liquid is to find out the mass of the empty pycnometer by weighing it. Then, to determine the volume, a liquid with well-known density, such as distilled water, is used. The rise of the capillary will give the volume. The pycnometer is then weighed again to get the mass of the water by subtracting it with the mass of the empty pycnometer. This procedure is repeated with the liquid of the unknown density to determine its mass (measured weight minus weight of empty

9

pycnometer) and its volume with the capillary bore. Finally, with equation (2) the density of the unknown liquid is calculated. ρunknown = !!"#"$%"

!!!!   .𝜌!!! [2]

Pycnometers are usually made of glass or sometimes metal when the density of the fluid is measured under extremely high pressure. To assure the accuracy of the measurement pycnometers have to be nonmagnetic, because even the slightest ambient magnetic effect can alter the calculation of the density (Eren, 1999). The most important advantage of the pycnometer is precision. If they used correctly they can provide accurate results. Also, pycnometers can be used to measure both the density and the specific gravity of fluids. Pycnometers, though, have a number of disadvantages like the fact that the precision of the measurement depends on the operator and only a skilled operator can achieve an accurate measurement. The overall apparatus for the determination of the density with a pycnometer can be very expensive if an extremely precise measurement is needed. The high cost arises from the requirement of a very precise weighing scale and the need for controlled laboratory conditions. In addition, is a slow and time-consuming method (Eren, 1999).

2.2.2 Hydrometers  

Hydrometer (Figure 7) is one of the oldest density measuring techniques and is also the most commonly used in the beverage and the chemical industry to ensure good quality control (Paar, 2015).

Figure 7: Schematic of a Hydrometer (Paar, 2015)

The hydrometer consists of a main floating glass body, with a cylindrical stem with a scale and a bulb filled with metal weight. The measurement procedure is very simple since it only involves the immersion of the hydrometer in the sample and the reading of the density directly from the scale. The deeper the hydrometer sinks the less dense

Scale

Fluid vessel

Weight bulb

10

the sample is. The principle used for determining the density with the hydrometer is buoyancy. Hydrometers have both advantages and disadvantages. The main advantages are the low cost and the simplicity and speed of the procedure. Because hydrometers are so commonly used their specifications are traceable to international standards. On the other hand their reliability is debatable because it is easy for the scale to be misread. In addition, a temperature correction and a large sample volume (up to a 100 mL) are required. Finally, hydrometers are made of glass, which makes them extremely fragile (Eren, 1999).

2.2.3 Refractometer  and  index  of  refraction  densitometers  

Refractometers can measure what is commonly known as index of refraction (n). The refraction index is the dimensionless number of the comparison between the speed of light in a vacuum and the velocity of light through a medium, which basically describes how much of the light, is refracted when entering a sample. n = !

! [3]

where c is the speed of light in vacuum and u is the velocity of light in a medium. The index of refraction densitometer, as can be seen in Figure 8, consists of a transparent cell that the liquid or gas flows through, a laser or light beam and a sensor. As the laser beam passes through the cell and the sample is refracted with an angle. That angle of refraction depends on the shape, size and thickness of the container and on the density of the sample. Since, the container’s characteristics are constant and well known the only unknown variable is the density of the sample. An accurate measurement of the position of the beam and the refraction angle can relate to the sample’s density (Eren, 1999).

Figure 8: Index of refraction densitometer (Eren, 1999)

11

Refractometers can find applications in industry such as the control of adulteration of liquids (oils, wines, gasoline) and in the chemical industry.

2.2.4 Vibrating  tube  densitometers  

The effectiveness of vibrating densitometers is based on the principle that every fluid has a unique natural frequency. This resonance frequency (f) depends on the stiffness of the body and the combined mass of the body and the fluid and is described with equation (4) (Tropea et al., 2007): f =   !

!!!

!!(!.!) [4]

where K is the elasticity constant of the body, m is the mass of the body containing the fluid, ρ is the fluid density and V is the volume of the body. The frequency is also related to oscillation period (τ) as: τ = !

! [5]

There are two types of vibrating tube densitometers, the single tube and the two tube vibrating densitometer as can be seen in Figure 9. The single tube has pressure losses and some obstruction on the natural flow. The two-tube densitometer is designed in a way that the two tubes are vibrating in an antiphase, which provides higher accuracy (Eren, 1999).

Figure 9: (a) Single vibrating tube densitometer, (b) Two-tube vibrating densitometer (Eren, 1999)

The vibrating tube densitometer can be applied on research and on huge variation of applications in the industry such as quality control or R&D investigations (Paar, 2015). The most important advantage of the vibrating tube densitometer is that in the right instrument setup can provide very high accuracy and repeatability. Some other advantages are the high measurement speed (a few minutes) and the very little sample

(a) (b)

12

volume that is needed (1 mL). The only limiting factor is the possible dynamic influence of viscosity on the results. In general, the vibrating tube densitometer method is the most advanced, precised and fast method for measuring the density of fluids. The experimental apparatus that was used for the determination of the density for this report uses the oscillating U-tube method, which is an advanced vibrating tube method. More details about the oscillating U-tube method are provided in HPHT Density Measurements.

13

3 HPHT Density Measurements

3.1 U-­‐tube  basic  principle  

The Anton Paar DMA-HPM measuring cell measures the density of fluids based on the oscillating U-tube method introduced by Dr. Hans Stabinger in the 1960s. The overall idea of the oscillating U-tube method is based on the principle that every fluid has it’s own characteristic frequency and that frequency is directly related to the sample’s density. A hollow U-shaped tube is filled with the sample fluid then, the tube is subjected to an electromagnetic force and is excited into periodic oscillation (Furtado et al., 2009). Then, the frequency as a function of time is recorded and a sin-wave of a certain period and amplitude is created as can be seen in Figure 10 and Figure 11.

Figure 10: U-tube filled with water (Paar, 2015)

Figure 11: U-tube filled with air (Paar, 2015)

14

The classic way the U-tube oscillator operates is by a magneto-electrical system as can be seen in Figure 12. Alternating voltage is sent through the electric coil on the tube, which creates an alternating magnetic field. The magnet on the tube reacts to the alternating current and as a result an excitation is generated. The frequency of the magnet’s oscillation that is caused is measured with an amplifier.

Figure 12: U-tube measurement cell (Paar, 2015)

The constant search for faster, more precise and more accurate measurements and the technological advancements of the 21st century lead to a constant redevelopment and improvement of the U-tube. One of the most advanced U-tube setups in the market is the one in the Anton Paar DMA-HPM measuring cell, which was used for the series of experiments for this report. The tube is made of Hatelloy C-276, which is a nickel-based super alloy widely used in the industry because of its high corrosion resistance and high temperature strength (Ahmad et al., 2005). The U-tube is kept oscillating continuously at a characteristic frequency because of an electronic excitation generated from a piezoelement. Two optical pick-ups record the oscillation and an extra tube acts as a reference oscillator and speeds up the measurement. The U-tube setup of the Anton Paar DMA-HPM measuring cell can be seen in Figure 13.

Figure 13: U-tube setup of the Anton Paar DMA-HPM measuring cell (Paar, 2015)

The physical background of this principle is based on the Mass Spring Model (MSM), which is a vertical system that consists of a spring attached on an unwavering point on

15

the upper end and has an attached mass on the lower end (Figure 14). When the mass is pulled down and let go, the MSM oscillates and the period of the oscillation can be described with equation (6).

Figure 14: Five key points of the Mass Spring Model

τ = 2π . !!(!  .!)!

[6]

where m is the mass of the sphere, ρ is the density, V is the volume of the sphere and K is the spring constant. Solving equation (6) for density: ρ = τ2 . !

!  .    !!!− !

! [7]

Hans Stabinger (1994) studied the relation between the period of oscillation and the density and found a way to implement the MSM mechanically. To achieve this, Stabinger introduced two adjustment constants namely A and B described from equations (8) and (9), respectively. A = !

!  .    !!! [8]

B = !

! [9]

16

Replacing the two adjustment constants in equation (7): ρ = A . τ2 - B [10] Now to relate these equations to the oscillation U-tube method the two adjustment constants are different for each instrument so the unique A and B constants need to be calculated and stored into every oscillator. In order to achieve that two different samples of a precisely known density should be used. Typically, double distilled freshly degased water at 20 °C and dry and clean air are used. The water must be very well distilled before inserted in the tube to avoid gas bubbles; otherwise the lack of quality in the adjustment process can give incorrect density values (Paar, 2015). Figure 15 illustrates the graph of the formula for the air and water adjustment as a function of density and square period. Because the density of the water and the air are known the adjustment constants A and B can be calculated as they define a straight line in the graph. Now, for the calculation of the density for a sample that is inserted in the tube the instrument measures the period of oscillation and then applies that value to the adjustment line and converts it to the corresponding density.

Figure 15: Graph for air and water adjustment (Paar, 2015)

3.2 Calibration  procedure  

The vibrating tube densitometer is calibrated through the oscillation period measurement of two fluids with well-known densities. As mentioned before Hans Stabinger (1994) studied the relation between the period of oscillation and the density and introduced equation (10), which can be also written, for the two reference fluids, as: 𝜌!(T,p) = A(T,p) . 𝜏!!(T,p) - B(T,p) [11]

17

𝜌!(T,p) = A(T,p) . 𝜏!!(T,p) - B(T,p) [12] where 𝜌! and 𝜌! are the known densities of fluids 1 and 2 and τ1 and τ2 are the measured oscillation periods of the two fluids at each temperature and pressure. Solving the system of the above two equations, parameters A(T) and B(T,p) are derived:

𝐴(𝑇,𝑝) =  𝜌! 𝑇,𝑝 − 𝜌!(𝑇,𝑝)  𝜏!! 𝑇,𝑝 −  𝜏!!(𝑇,𝑝)

[13]

𝐵(𝑇,𝑝) =  𝐴(𝑇,𝑝)  . 𝜏!!(𝑇,𝑝)  −  𝜌!(T,p) [14] Lagourette et al. (1992), proposed a calibration method that is based on the hypothesis that parameter A(T) is only temperature dependent, while parameter B(T,p) is both temperature and pressure dependent. If water was used as the first reference fluid and instead of a second reference fluid the tube was used under vacuum and by taking into account that the density of vacuum is zero then: 𝜌!(T,p) = A(T,p) . 𝜏!! (T,p) - B(T,p) [15] 0   =  𝐴(𝑇). 𝜏!!(𝑇, 0)  −  𝐵(𝑇, 0) [16] where the subscript w refers to water and the subscript v refers to vacuum. Parameter B(T,p) can then be obtained: 𝐵(𝑇,𝑝) =  𝐴(𝑇). 𝜏!! (𝑇,𝑝)  −  𝜌!(T,p) [17] Lagourette et al. (1992) proposed that B(T,0) ≈ B(T,0.1MPa) therefore equation (17) can be written as: 𝜌!(T,0.1MPa) = A(T) . 𝜏!! (T,p) - 𝜌!(T,p) [18] Parameter A(T) is then, described as:

𝐴(𝑇) =  𝜌! 𝑇, 0.1𝑀𝑃𝑎  

𝜏!! 𝑇, 0.1𝑀𝑃𝑎 −  𝜏!!(𝑇, 0)

[19]

Finally, Lagourette et al. (1992) described the density of any fluid with the following equation:

𝜌 𝑇,𝑝 =  𝜌! 𝑇,𝑝 + 𝜌! 𝑇, 0.1𝑀𝑃𝑎𝜏! 𝑇,𝑝 − 𝜏!! 𝑇,𝑝

   𝜏!! 𝑇, 0.1𝑀𝑃𝑎 − 𝜏!! 𝑇, 0

[20]

18

where τ is the oscillation period of the measured fluid. For this work, the calibration method is summarised below:

• Equations (15) to (20) were used for the densimeter calibration at pressures between 0.1 MPa and 140 MPa and temperatures between 5 °C and 75 °C. The density of water was taken from NIST (National Institute of Standards and Technology) that uses the equation of state from Wagner and Pruss (2002) and the period of water and vacuum were measured.

The limitations, on the temperature range, of the above equation are due to the fact that water over 100 °C is at a vapour state.

• For the extension of the calibration to temperatures up to 190 °C and for atmospheric pressure, equations (21) to (23) that were suggested from Comuñas et al. (2008) were used:

𝐴(𝑇) =  𝜌! 𝑇, 0.1𝑀𝑃𝑎  

𝜏!! 𝑇, 0.1𝑀𝑃𝑎 −  𝜏!!(𝑇, 0)

[21]

𝐵(𝑇, 0.1𝑀𝑃𝑎) =  𝐴(𝑇). 𝜏!!(𝑇, 0.1𝑀𝑃𝑎)  −  𝜌!(T,0.1MPa) [22]

ρ T,0.1MPa =  ρd T,0.1MPa . 1+τ2 T,0.1MPa -­‐τd2 T,0.1MPa

τd2 T,0.1MPa -­‐τv2 T

[23]

where τd is the measured oscillation period of n-dodecane and ρd is the density of n-dodecane.

• For the temperatures 100 °C and 150 °C and pressures higher than 0.1 MPa and

for the temperature 190 °C and pressures higher than 1 MPa equations (17), (21) and (24) were used:

ρ T,p =  ρw T,p + ρd T,0.1MPa . τ2 T,p -­‐τw2 T,p

τd2 T,0.1MPa -­‐τv2 T

[24]

For this equation the density of water was taken from NIST that uses the equation of state from Wagner and Pruss (2002), the density of n-dodecane was taken from NIST that uses the equation of state from Lemmon & Huber (2004) and the oscillation periods of water and vacuum were measured. The oscillation period of n-dodecane was measured in a previous work (Chasomeris et al., 2015).

19

• Finally, for the temperature of 190 °C and the pressure of 1 MPa the following equation was used:

ρ T,p =  ρd T,p + ρd T,0.1MPa . τ2 T,p -­‐τd2 T,p

τd2 T,0.1MPa -­‐τv2 T

[25]

Segovia et al. (2009) suggested the following experimental uncertainties for the density, which are adopted for this work: Table 2: Experimental uncertainty of density (Segovia et al., 2009)

Temperature (°C) T <100 T =100 & T=150 T =190 100 < T <190 Pressure (bar) 1 < p < 140 p=1 p=1 & p=10 10< p Uncertainty (kg/m3) 0.7 5 5 3 The relative deviation, the absolute deviation and the absolute average deviation (AAD) were calculated with equations (26) to (28). 𝑅𝑒𝑙𝑎𝑡𝑖𝑣𝑒  𝑑𝑒𝑣𝑖𝑎𝑡𝑖𝑜𝑛   % =

𝜌!"# − 𝜌!"#𝜌!"#

  . 100 [26]

𝐴𝑏𝑠𝑜𝑙𝑢𝑡𝑒  𝑟𝑒𝑙𝑎𝑡𝑖𝑣𝑒  𝑑𝑒𝑣𝑖𝑎𝑡𝑖𝑜𝑛   % =

𝜌!"# − 𝜌!"#𝜌!"#

  . 100 [27]

𝑅𝑒𝑙𝑎𝑡𝑖𝑣𝑒  𝑑𝑒𝑣𝑖𝑎𝑡𝑖𝑜𝑛   % =1𝑛

𝜌!"# − 𝜌!"#𝜌!"#

  . 100!

!!!

[28]

where 𝜌!"# is the experimental density (kg/m3), 𝜌!"#  is  the  density  from  literature (kg/m3) and n is the number of measurements.

3.3 Experimental  setup  

For the determination of the density for this report the External Measuring Cell DMA-HPM (Density Measuring Apparatus) from Anton Paar was used.

Figure 16: Anton Paar DMA-HPM measuring cell (Paar, 2015)

20

The DMA-HPM can provide reliable density measurements for a sample at extreme conditions with high pressures up to 1400 bar and at a wide range of temperatures extending from -10 °C up to 200 °C.

Figure 17: Anton Paar DMA-HPM (DTU laboratory)

The DMA-HPM is commonly used in reservoir studies because of its high accuracy, which can be up to 0.0001 g/cm3 (Paar, 2015). An extended version of the specifications of the DMA-HPM can be found in Table 18 in Appendix A: Technical Specifications. For the temperature regulation of the DMA-HPM measuring cell a circulating bath thermostat provided by PolyScience was used. In particular, the PolyScience advanced programmable temperature controller with Swivel 180™ Rotating Controller that was used for the experiments can be seen in Figure 18.

Figure 18: PolyScience advanced programmable temperature controller with Swivel 180™ Rotating Controller

(DTU laboratory)

With a temperature range from -20 °C to 200 °C and temperature stability and precision of 0.01 °C the PolyScience advanced programmable temperature controller was ideal for regulating the apparatus temperature through the whole range required for this set of experiments. An extended version of the specifications of the PolyScience advanced programmable temperature controller can be found in Table 19 in Appendix A: Technical Specifications. The temperature of the densimeter was measured with a PT100 platinum thermometer.

21

In order to get the density measurements the DMA-HPM is connected to the evaluation unit mPDS 5 from Anton Paar (Figure 19). The mPDS 5 continuously records the density of the sample and converts the raw values from the sensors into application specific results. The mPDS can display a number of parameters such as the oscillation period, the temperature and the pressure of the sample in the measuring cell. An extended version of the specifications of the mPDS 5 can be found in Table 20 in Appendix A: Technical Specifications.

Figure 19: (a) Anton Paar mPDS 5 (Paar, 2015), (b) Anton Paar mPDS 5 (DTU laboratory)

The user has access to the recorded measurements from a Microsoft Excel® spreadsheet installed on a computer which, is connected to the mPDS 5. The spreadsheet that is provided by Anton Paar and records all the measurements can be seen in Figure 20.

Figure 20: Snapshot of the recording window from the Microsoft Excel® spreadsheet provided by Anton Paar

The most important features to understand from the recording window are the date transfer section and the stability slope section (Figure 21). The data window box under the data transfer section corresponds to the number of measured points in one cycle that are used to calculate the average deviation values for the pressure, the temperature and the period of oscillation. The stability slope section allows the user to define the maximum deviations above which the average deviation of the measured values for the

(a) (b)

22

pressure, the temperature and the period of oscillation should not exceed. The recording window continuously records measurements and only stops when the average deviations of all three parameters for two consecutive cycles don’t exceed the maximum deviations defined by the user.

Figure 21: Snapshot of the data transfer section and the stability slope section of the recording window

Finally, when the stability slope criteria are met and the recording process ends, the user can access the recorded values from the data spreadsheet of the Microsoft Excel® tool (Figure 22). On this particular spreadsheet the recorded average values for temperature (°C), period of oscillation (/µs) and pressure (bar) can be found.

Figure 22: Snapshot of the data spreadsheet of the Microsoft Excel® tool

During the experimental procedure the user had to manually change the pressure of the mixture. The pressure is measured through a digital pressure gauge. The SIKA digital pressure gauge Type P (Figure 23) can read high pressures up to 1500 bar, fast and with high accuracy. The temperature effect on the pressure measurements is lower than ±0.002%. More detailed specifications can be found in Table 21 in Appendix A: Technical Specifications. The fluid piston cylinder can be seen along with the overall experimental setup in Figure 26.

23

Figure 23: SIKA digital pressure gauge Type P (DTU laboratory, left) (SIKA, 2015, right)

For the calibration of the equipment and the calculation of the mixture’s density the oscillation period under vacuum needed to be measured. Also, for cleaning purposes the whole system needed to be under vacuum. To achieve vacuum in the experimental system the Edwards E2M1.5 two-stage oil sealed rotary vane pump was used and the Edwards Active Digital Controller (ADC) gauge was used to display the pressure, in order to verify that the system was indeed under vacuum. Both Edwards’ products can be seen in Figure 24 and their specifications can be found in Table 22 and Table 23 in Appendix A: Technical Specifications.

Figure 24: Edwards E2M1.5 two-stage oil sealed rotary vane pump and Edwards Active Digital Controller (ADC)

gauge (DTU laboratory)

In addition, two 260D syringe pumps from Teledyne Isco were used to ensure constant pressure and constant flow during the mixture insertion process. The Teledyne Isco 260D syringe pump (Figure 25) is designed specifically for refilling under high

24

pressure (Isco, 2013). More detailed specifications can be found in Table 24 in Appendix A: Technical Specifications.

Figure 25: Teledyne Isco 260D syringe pump (DTU laboratory)

For the effective blend of the mixture a steel cylinder of variable volume was used (Figure 28). To achieve better homogeneity for the mixture the cylinder contains a steel ball as an agitator and a piston separating the mixture and the hydraulic water. The overall experimental setup can be seen on the two photos taken at the DTU laboratory during the experiments period in Figure 26.

Figure 26: Experimental setup (DTU laboratory)

25

A detailed schematic of the density measurement setup with all the components used for the experiments is depicted in Figure 27.

Figure 27: Schematic of the experimental density measurement setup

3.4 Experimental  procedure  

3.4.1 Apparatus  cleaning  procedure  

The cleaning of the equipment between the experiments is essential for the quality of the measurement. After the sample is removed some residues and contaminants might reside in the apparatus. It is very important that they are removed by rinsing before the new sample is inserted. The cleaning procedure was repeated every time after the measurements of each sample were finished. Cleaning of the densitometer and the fluid piston cylinder: The sample already inserted in the densitometer was removed from the outlet valve. To make sure the entire sample was out of the system the fluid piston cylinder was moved back and forth several times. Then, for the cleaning of the densitometer, two rinsing fluids were used. The first fluid that was used was toluene. Toluene is an aromatic hydrocarbon and a strong organic solvent, which makes it ideal for cleaning petroleum mixtures. After the equipment was rinsed with toluene several times, ethanol was inserted in the system. The use of ethanol as the second rinsing fluid was chosen because ethanol is a volatile fluid that can clean toluene. The fact that it is volatile is

Inlet valve

Outlet valve

26

important because after rinsing several times the ethanol was evaporated without leaving any residue. Before putting the system under vacuum, pressurized air was inflated to confirm the removal of any last residue. Finally, the system was put under vacuum for an hour in 75 °C to dry out and then left under vacuum over night at ambient temperature. Cleaning of the mixture cylinder and peripheral lab equipment: The sample already in place was carefully ejected from the cylinder in a fume hood. Toluene and ethanol were used as rinsing fluids like before. All the parts of the cylinder were rinsed thoroughly several times with the cleaning fluids, then dried out with pressurized air and eventually put under vacuum.

Figure 28: Mixture (top) and Nitrogen cylinder (bottom) (DTU laboratory)

All the peripheral equipment used during the experimental procedure was cleaned thoroughly with both cleaning agents and then dried out under pressurized air. Such equipment included: Beakers, funnel, pipet, Erlenmeyer flask and burette.

3.4.2 Mixture  preparation  

The first step for the mixture preparation is the calculation of the quantities of each component to achieve the desired composition. The details for each mixture composition can be seen in Table 3. Table 3: Mixture compositions

Methane mole fraction

n-decane mole fraction

Methane mass (g)

n-decane mass (g)

n-decane volume (mL)

Mixture molar mass (g/mol)

0.2270 0.7730 3.376 101.862 140.2 113.631 0.6017 0.3983 13.392 78.613 108.2 66.325 0.8496 0.1504 35.597 55.799 76.8 35.028

27

The density of n-decane used for the calculations was ρdec = 726.55 kg/m3 at Tambient = 24.97 °C (Lemmon & Span, 2006). The first fluid to be transferred in the evacuated cylinder was n-decane. For the transfer, a 50 mL burette with readability ± 0.01 mL was connected to the cylinder and carefully the desirable volume of n-decane was transferred. Methane is a gas and the transfer was more complicated. Initially, the methane was transferred from the gas pressurized-bottle into the gas cylinder in Figure 29. Safety goggles were used because of the danger of methane leaking during the transfer. Then, the gas cylinder was placed on Mettler Toledo PR1203 balance (readability 0.001g) and was connected to the mixture cylinder. The methane mass transferred in the mixture cylinder was read from the balance.

Figure 29: Methane weighing with Mettler Toledo PR1203 balance (DTU laboratory)

During the insertion of the mixture from the cylinder to the evacuated densimeter attention was paid on potential pressure drop. To maintain constant pressure and constant flow during the insertion of the sample two Isco pumps were used. As can be seen in Figure 27, the first pump was connected to the mixture cylinder that led to the inlet valve and the second was connected to the nitrogen cylinder that led to the outlet valve. Finally, to ensure the homogeneity throughout the whole system the mixture was purged five times before closing the inlet and outlet valves and begin the experiments. All the chemical and physical properties of the fluids that were used can be found in Appendix B: Fluids properties.

3.4.3 Performing  a  measurement  

Under this thesis the density of the binary system methane - n-decane is measured for different compositions and under a wide range of pressure and temperature. The mixture compositions under study and the pressure and temperature range for each mixture can be seen in Table 4. The decision of the starting pressure point for each

28

fluid was made based on the two-phase region because for the oscillating U-tube to function the mixture has to be in a single liquid phase. Table 4: Mixture composition, pressure and temperature range

Methane mole fraction

Pressure range (bar)

Temperature range (°C)

0 1 - 1400 5 - 190 0.227 100 - 1400 5 - 190 0.6017 400 - 1400 5 - 190 0.8496 400 - 1400 5 - 190

In order to cover the whole range of pressure and temperature specific steps were chosen. The temperature steps and the pressure steps can be found in Table 5 and Table 6, respectively.

Table 5: Pressure steps

Pressure steps (bar) 100 200 400 600 800 1000 1200 1400

Table 6: Temperature steps

Temperature steps (°C)

5 25 50 75 100 150 190

Firstly, the desirable temperature was set on the PolyScience advanced programmable temperature controller from the user. After the temperature was stabilized, the first pressure step was manually reached. Once the pressure was stabilized the user could initiate the measurement from the Microsoft Excel® spreadsheet provided by Anton

29

Paar. On the Microsoft Excel® spreadsheet the values for the data transfer and the slope stability were added by the user for all the experiments as can be seen in Figure 21. After the recording process ended, the user could access the recorded values from the data spreadsheet of the Microsoft Excel® tool (Figure 22). Finally, the pressure was increased and after all the pressure steps were measured the same procedure was repeated for the remaining temperatures.

4 Density modelling

Nowadays the most accepted and implemented models for PVT modelling of reservoir fluids are the cubic EoS such us the Soave–Redlich–Kwong (SRK) (Soave, 1972) EoS and the Peng–Robinson (PR) (Peng & Robinson, 1976) EoS. On the other hand though, recently developed non-cubic EoS such us the Perturbed Chain Statistical Associating Fluid Theory (PC-SAFT) (Gross & Sadowski, 2001) EoS and the Soave modified Benedict–Webb–Rubin (Soave-BWR) (Soave, 1999) EoS could potentially replace this classical cubic equations (Wei et al., 2015). For the purpose of this work a comparative study of the aforementioned cubic and non-cubic equations will be attempted regarding the measured densities for the pure n-decane and the binary mixture of methane - n-decane for the different compositions.

4.1 Cubic  EoS  

The non-cubic EoS under study are the SRK (Soave, 1972) EoS and the PR (Peng & Robinson, 1976) EoS. The SRK EoS gives, in general, very accurate results for density for an empirical equation (Wei et al., 2015). The initial RK equation introduced by Redlich & Kwong (1949) is: p = !"

!!!− !

!(!!!) ! [29]

The modified SRK EoS that is under examination in this work and introduced by Soave (1972) reads as: p = !"

!!!− !(!,!)

!(!!!) [30]

where p is the absolute pressure, R is the universal gas constant (=8.3144621 J/mol*K), T is the absolute temperature, v is the specific volume, ω is the acentric factor, α(Τ) is the modified parameter for SRK and α and b are the parameters from original Redlich-Kwong.

30

The parameters α and b are estimated based on the acentric factor, the critical temperature (Tc) and critical pressure (pc) of the mixture. The critical properties of the fluids studied in this work can be seen in Table 7: Table 7: Tc, Pc, ω and Zc for methane and n-decane

Component Tc (K) pc (bar) ω Zc methane 190.56 45.99 0.0115 0.2897 n-decane 617.70 21.10 0.4923 0.2518

The PR EoS introduced by Peng & Robinson (1976) reads: p = !"

!!!− !(!,!)

! !!! !!(!!!) [31]

4.2 Non-­‐cubic  EoS  

Gross & Sadowski (2001), modified the initial SAFT EoS introduced by Chapman et al. (1990) and the main difference between the original SAFT and the modified PC-SAFT according to Wei et al. (2015) is that the modified version of the equation uses the mixture of hard-sphere chains as the reference system and then introduces the dispersive attractions achieving this way to be more accurate when modeling asymmetric and highly non-ideal systems. PC-SAFT EoS requires only three parameters that are not directly associated with the component and those are the chain length m, the segment diameter s and the segment energy ε. The Soave-BWR was introduced by Soave (1999) and has the following form: Z = !

!"#= 1+ 𝐵𝜌 + 𝐷𝜌! + 𝛦𝜌! 1+ 𝐹𝜌! 𝑒𝑥𝑝  (−𝐹𝜌!) [32]

where Z is the compressibility factor, p is the absolute pressure, R is the universal gas constant (=8.3144621 J/mol*K), T is the absolute temperature, ρ is the density and A, B, D, E, and F are the five model parameters. The critical parameters needed for the Soave-BWR regarding the binary mixture of methane – n-decane can be seen in Table 7. Finally, Table 8 presents the interaction parameters for the binary mixture of methane – n-decane: Table 8: Interaction parameters for the methane – n-decane binary mixture (Wei et al., 2015)

EoS kij SRK 0.0411 PR 0.0422

PC-SAFT 0.0167 SBWR -0.0366

31

After a comprehensive research and study Wei et al. (2015) concluded that both the non-cubic EoS are much better than the cubic ones regarding the density calculation for the light and heavy components of a reservoir fluid. For further reading about the four EoS under study the reader is referred to see the article from Wei et al. (2015)

32

5 Results and discussion

5.1 Densimeter  calibration  and  validation  results  

For the calibration of the densimeter the oscilation periods of the tube when filled with water and under vaccum were measured. In addition, the density of water was taken from NIST that uses the EoS from Wagner and Pruss (2002) and the density of n-dodecane was taken from NIST that uses the EoS from Lemmon & Huber (2004). All the values mentioned above can be seen in Table 9. The oscillation period of n-dodecane was measured in a previous work (Chasomeris et al., 2015). Table 9: Values for ρw, τw, ρd, τv

Temperature (°C)

Pressure (bar)

ρw (kg/m3)

τw (µs)

ρd (kg/m3)

τv (µs)

5 1 999.97 2665.303 759.94 2586.522 5 10 1000.40 2665.346 760.38 2586.522 5 50 1002.40 2665.517 762.94 2586.522 5 100 1004.80 2665.732 766.13 2586.522 5 200 1009.50 2666.161 771.89 2586.522 5 400 1018.70 2666.996 777.36 2586.522 5 600 1027.60 2667.796 782.45 2586.522 5 800 1036.00 2668.631 787.04 2586.522 5 1000 1044.10 2669.385 791.73 2586.522 5 1200 1051.90 2670.103 745.67 2586.522 5 1400 1059.30 2670.791 746.55 2586.522 25 1 997.05 2672.023 749.40 2593.217 25 10 997.45 2672.061 752.63 2593.217 25 50 999.25 2672.222 759.22 2593.217 25 100 1001.50 2672.421 764.97 2593.217 25 200 1005.80 2672.820 770.45 2593.217 25 400 1014.30 2673.600 775.62 2593.217 25 600 1022.50 2674.347 780.52 2593.217 25 800 1030.30 2675.148 727.70 2593.217 25 1000 1037.90 2675.874 728.72 2593.217 25 1200 1045.20 2676.565 732.00 2593.217 25 1400 1052.20 2677.238 735.92 2593.217 50 1 988.03 2680.148 743.19 2601.720 50 10 988.43 2680.170 749.84 2601.720 50 50 990.16 2680.331 755.88 2601.720 50 100 992.31 2680.526 761.56 2601.720 50 200 996.53 2680.915 766.91 2601.720 50 400 1004.70 2681.676 709.00 2601.720

33

50 600 1012.60 2682.406 710.07 2601.720 50 800 1020.10 2683.209 713.88 2601.720 50 1000 1027.40 2683.920 718.36 2601.720 50 1200 1034.50 2684.600 726.66 2601.720 50 1400 1041.30 2685.261 734.10 2601.720 75 1 974.84 2688.125 740.82 2610.395 75 10 975.24 2688.158 747.11 2610.395 75 50 977.01 2688.322 753.03 2610.395 75 100 979.19 2688.522 759.94 2610.395 75 200 983.48 2688.915 760.38 2610.395 75 400 991.76 2689.687 762.94 2610.395 75 600 999.69 2690.425 766.13 2610.395 75 800 1007.30 2691.192 771.89 2610.395 75 1000 1014.60 2691.902 777.36 2610.395 75 1200 1021.70 2692.585 782.45 2610.395 75 1400 1028.50 2693.253 787.04 2610.395 100 1 - - 690.00 2619.218 100 10 958.77 2696.000 692.01 2619.218 100 50 960.63 2696.168 696.05 2619.218 100 100 962.93 2696.380 701.17 2619.218 100 200 967.44 2696.792 710.54 2619.218 100 400 976.10 2697.593 718.82 2619.218 100 600 984.34 2698.358 726.40 2619.218 100 800 992.22 2699.196 733.23 2619.218 100 1000 999.76 2699.919 739.69 2619.218 100 1200 1007.00 2700.623 651.13 2619.218 100 1400 1014.00 2701.313 652.88 2619.218 150 1 - - 659.07 2637.323 150 10 917.31 2711.462 665.99 2637.323 150 50 919.56 2711.665 678.15 2637.323 150 100 922.32 2711.919 688.58 2637.323 150 200 927.69 2712.408 697.71 2637.323 150 400 937.86 2713.336 705.93 2637.323 150 600 947.38 2714.209 713.50 2637.323 150 800 956.35 2715.156 617.73 2637.323 150 1000 964.85 2715.955 619.74 2637.323 150 1200 972.93 2716.727 628.01 2637.323 150 1400 980.64 2717.485 636.98 2637.323 190 1 - - 651.93 2652.243 190 10 - - 664.25 2652.243 190 50 878.72 2723.847 674.89 2652.243 190 100 882.16 2724.157 684.26 2652.243

34

190 200 888.77 2724.749 692.78 2652.243 190 400 901.04 2725.860 690.00 2652.243 190 600 912.29 2726.885 692.01 2652.243 190 800 922.70 2727.923 696.05 2652.243 190 1000 932.44 2728.833 701.17 2652.243 190 1200 941.59 2729.706 710.54 2652.243 190 1400 950.24 2730.542 718.82 2652.243

The relation between the oscillation period of the tube under vacuum and the temperature can be observed in Figure 30. The oscillation period is increasing with the increase of temperature.

Figure 30: Period of the evacuated densimeter for temperatures from 5°C to 190°C)

The water oscillation period was measured for temperatures from 5°C to 190°C and pressures from 1 bar to 1400 bar and can be seen in Figure 31. It can be observed that for each temperature the oscillation period is increasing with the increase of pressure.

Figure 31: Water measured period for temperatures from 5°C to 190°C and pressures from 1 bar to 1400 bar

2580  

2590  

2600  

2610  

2620  

2630  

2640  

2650  

2660  

0   20   40   60   80   100   120   140   160   180   200  

Period  (μs)  

Temperature  (°C)  

2655  

2665  

2675  

2685  

2695  

2705  

2715  

2725  

2735  

0   200   400   600   800   1000   1200   1400   1600  

Period  (μs)  

Pressure  (bar)  

5  °C     25  °C     50  °C     75  °C     100  °C     150  °C     190  °C    

35

The characteristic parameter A(T), on the other hand, is decreasing with the increase of temperature. The relation between the characteristic parameter A(T) and the temperature can be seen in Figure 32.

Figure 32: Characteristic parameter A(T) for temperatures from 5°C to 190°C

The ratio of parameter A(T) with parameter B(T,p) was also calculated and can be seen in Figure 33. It can be observed that for each temperature the ratio is slightly decreasing with the increase of pressure.

Figure 33: Ratio between parameter A(T) and parameter B(T,p)

2,26  

2,28  

2,30  

2,32  

2,34  

2,36  

2,38  

2,40  

2,42  

2,44  

0   20   40   60   80   100   120   140   160   180   200  

 A  (T)  (10^9kg  s-­‐1  m

-­‐3)  

Temperature  (°C)    

1,41  

1,42  

1,43  

1,44  

1,45  

1,46  

1,47  

1,48  

1,49  

1,5  

0   200   400   600   800   1000   1200   1400  

A(T)/B(T,p)(10

5 s-­‐2)  

Pressure  (bar)  

5°C  

25°C  

50°C  

75°C  

100°C  

150°C  

190°C  

36

Various authors, including Lugo et al. (2001) and Segovia et al. (2009), have presented their results in similar way and the trends observed in Figure 32 and Figure 33 are in agreement with both authors. The oscillation period of n-decane was also measured and as can be seen in Figure 34 it is increasing with the increase of pressure and temperature.

Figure 34: n-decane measured period for temperatures from 5°C to 190°C and pressures from 1 bar to 1400 bar

For the validation of the densimeter the density of n-decane was calculated with equations (20), (23), (24) and (25) and the results can be seen in Table 10. Table 10: Experimental density values (kg/m3) of n-decane

Pressure (bar)

Temperature (°C) 5 25 50 75 100 150 190

1 741.52   726.79   707.99   688.13   668.01   626.02   -­‐  10 742.10   727.33   708.71   689.15   669.50   627.77   591.07  50 745.01   730.49   712.32   693.41   674.51   634.86   600.80  100 748.34   734.20   716.60   698.41   680.29   642.76   611.37  200 754.34   741.00   724.39   707.38   690.52   656.34   628.47  400 765.38   753.18   737.94   722.52   707.62   677.72   653.92  600 775.29   763.90   749.70   735.33   721.71   694.57   673.11  800 783.41   772.30   758.80   745.85   732.59   707.19   687.87  1000 791.32   780.67   767.67   755.69   743.15   719.41   701.26  1200 798.88   788.45   776.14   764.58   752.68   730.14   712.93  1400 806.00   795.67   783.80   772.72   761.15   739.68   723.30  

2640  

2650  

2660  

2670  

2680  

2690  

2700  

2710  

2720  

0   200   400   600   800   1000   1200   1400   1600  

Period  (μs)  

Pressure  (bar)  

5  °C   25  °C   50  °C   75  °C   100  °C   150  °C   190  °C  

37

The results were then compared with the data from NIST, where an EoS proposed by Lemmon and Span (2006) was used and they were in good agreement with an AAD of 0.08%. The relative deviations as a function of temperature and pressure can be seen in Figure 35 and Figure 36, respectively.

Figure 35: Relative deviations between the experimental density values of n-decane and the data from Lemmon & Span (2006) as a function of temperature

Figure 36: Relative deviations between the experimental density values of n-decane and the data from Lemmon & Span (2006) as a function of pressure

-­‐0,25  

-­‐0,2  

-­‐0,15  

-­‐0,1  

-­‐0,05  

0  

0,05  

0,1  

0,15  

0,2  

0   20   40   60   80   100   120   140   160   180   200  

Relative  deviation  (%

)  

Temperature  (°C)  

Lemmon  &  Span  (2006)  

-­‐0,25  

-­‐0,2  

-­‐0,15  

-­‐0,1  

-­‐0,05  

0  

0,05  

0,1  

0,15  

0,2  

0   200   400   600   800   1000   1200   1400   1600  

Relative  deviation  (%

)  

Pressure  (bar)  

Lemmon  &  Span  (2006)  

38

5.2 Mixture  methane  –  n-­‐decane  (xmethane  =  0.227)  

After considering the two-phase region of this mixture the starting point for the experimental measurements was set to 100 bar. The measured densities for the mixture can be seen in Table 11. Table 11: Experimental density values (kg/m3) of the mixture methane - n-decane (xmethane = 0.227)

Pressure (bar)

Temperature (°C) 5 25 50 75 100 150 190

100 719.65   704.51   685.50   665.36   645.32   602.72   565.48  200 726.66   712.33   694.89   676.13   657.89   620.21   588.86  400 739.10   726.16   710.05   693.79   677.79   645.84   620.23  600 749.90   737.96   723.07   708.12   693.58   665.10   642.60  800 758.69   747.16   733.05   719.85   705.82   679.31   659.24  1000 767.22   756.35   742.76   730.37   717.49   692.67   674.08  1200 775.28   764.63   751.76   739.93   727.59   704.21   686.78  1400 782.73   772.09   759.81   748.59   736.76   714.39   698.00  

The experimental results were then compared with the results obtained from Audonnet & Pádua (2004). Because their work was measuring the density of the mixture under a different pressure and temperature region a correlation with the use of the Tait equation (Dymond & Malhotra, 1988) was performed. The Tait equation: ρ(T,p) = !!(!,!!)

!!!!" ! ! !!! ! !!!(!)

[33]

where: 𝐵 𝑇 = 𝑎 + 𝑏𝑇 𝐾 𝑐𝑇!(𝐾) [34] 𝜌!(𝑇,𝑝!) = 𝑎! + 𝑏!𝑇(𝐾) [35] and p0 is the reference pressure equal to 100 bar (10 MPa). The standard deviation (σ) of the fit and the parameters obtained in the Tait equation for the correlation for both our experimental results and those from Audonnet & Pádua (2004) can be seen in Table 12. The surface ρ(T,p) as a function of pressure and temperature for our results and those from Audonnet & Pádua (2004) can be seen in Figure 37 and Figure 38, respectively.

39

Table 12: Parameters obtained in the Tait equation with the results from Audonnet & Pádua (2004) (xmethane = 0.227) and our experimental results (xmethane = 0.227)

Audonnet & Pádua (2004) Experimental results from this work Parameter Value Parameter Value a (MPa) 226.4559 a (MPa) 662.7

b (MPa/K) -0.6141 b (MPa/K) -2.507 c (MPa/K2) 0.000277 c (MPa/K2) 0.002468 a1 (g/cm3) 0.94161 a1 (g/cm3) 0.9529

b1 (g/cm3K) -0.000792 b1 (g/cm3K) -0.000812 C (-) 0.088353 C (-) 0.115981

σ (g/cm3) 0.0004 σ (g/cm3) 0.0049

Figure 37: Surface ρ(T,p) for our experimental results for the mixture methane – n-decane (xmethane = 0.227)

Figure 38: Surface ρ(T,p) for the results from Audonnet & Pádua (2004) for the mixture methane – n-decane

(xmethane = 0.227)

40

The comparison of the experimental results with the results obtained from Audonnet & Pádua (2004) was possible for the temperatures of 50 °C, 75 °C and 100 °C and the pressures between 100 bar and 600 bar. The relative deviations as a function of temperature and pressure can be seen in Figure 39 and Figure 40, respectively. The experimental results are in good agreement with those from Audonnet & Pádua (2004) with an AAD of 0.17%.

Figure 39: Relative deviations between the experimental density values of the mixture methane – n-decane (xmethane = 0.227) and the data from Audonnet & Paduá (2004) (xmethane = 0.227) as a function of temperature

Figure 40: Relative deviations between the experimental density values of the mixture methane – n-decane (xmethane = 0.227) and the data from Audonnet & Paduá (2004) (xmethane = 0.227) as a function of pressure

-­‐0,2  

-­‐0,1  

0,0  

0,1  

0,2  

0,3  

0,4  

0   20   40   60   80   100   120  

Relative  deviation  (%

)  

Temperature  (°C)  

Audonnet  &  

-­‐0,2  

-­‐0,1  

0,0  

0,1  

0,2  

0,3  

0,4  

0   100   200   300   400   500   600   700  

Relative  deviation  (%

)  

Pressure  (bar)  

Audonnet  &  Padua  (2004)  

41

5.3 Mixture  methane  –  n-­‐decane  (xmethane  =  0.6017)  

After considering the two-phase region of this mixture the starting point for the experimental measurements was set to 400 bar. The measured densities for the mixture can be seen in Table 13. Table 13: Experimental density values (kg/m3) of the mixture methane - n-decane (xmethane = 0.6017)

Pressure (bar)

Temperature (°C) 5 25 50 75 100 150 190

400 653.14   635.15   616.25   596.81   582.46   539.57   510.36  600 667.75   651.73   634.75   617.86   605.90   568.99   544.38  800 678.97   666.25   648.77   633.80   622.46   589.47   568.15  1000 689.76   675.81   661.15   647.59   637.24   606.82   587.47  1200 699.17   685.79   672.41   659.54   649.91   621.59   603.54  1400 707.55   695.16   683.31   669.86   660.88   634.60   617.76  

The Tait equation was used again to correlate the results with those from Audonnet & Pádua (2004) and Canet et al. (2002). The standard deviation (σ) of the fit and the parameters obtained in the Tait equation for the correlation for both our experimental results and those from Audonnet & Pádua (2004) and Canet et al. (2002) can be seen in Table 14. Table 14: Parameters obtained in the Tait equation with the results from Audonnet & Pádua (2004) (xmethane = 0.601), our experimental results (xmethane = 0.6017) and those from Canet et al. (2002) (xmethane = 0.6)

Audonnet & Pádua (2004)

Experimental results from this work

Canet et al. (2002)

Parameter Value Parameter Value Parameter Value a (MPa) 226.4559 a (MPa) 112.8 a (MPa) 123.4

b (MPa/K) -0.6141 b (MPa/K) -0.5697 b (MPa/K) -0.1635 c (MPa/K2) 0.000277 c (MPa/K2) 0.0005512 c (MPa/K2) -0.0004013 a1 (g/cm3) 0.94161 a1 (g/cm3) 0.8645 a1 (g/cm3) 0.870269

b1 (g/cm3K) -0.000792 b1 (g/cm3K) -0.000848 b1 (g/cm3K) 0.000824 C (-) 0.088353 C (-) 0.07272 C (-) 0.1066

σ (g/cm3) 0.003 σ (g/cm3) 0.0058 σ (g/cm3) 0.0007 The surface ρ(T,p) as a function of pressure and temperature for our results and those from Audonnet & Pádua (2004) can be seen in Figure 41 and Figure 42, respectively.

42

Figure 41: Surface ρ(T,p) for our experimental results for the mixture methane – n-decane (xmethane = 0.6017)

Figure 42: Surface ρ(T,p) for the results from Audonnet & Pádua (2004) for the mixture methane – n-decane

(xmethane = 0.601)

43

The comparison of the experimental results with the results obtained by Audonnet & Pádua (2004) was possible for the temperatures of 50 °C, 75 °C and 100 °C and the pressures 400 bar and 600 bar. The experimental results have an AAD of 0.30% with those obtained from Audonnet & Pádua (2004). The comparison of the experimental results with the results obtained from Canet et al. (2002) was possible for the temperatures of 25 °C, 50 °C, 75 °C and 100 °C and the pressures between 400 bar and 1400 bar. It is important to mention that Canet et al. (2002) only measured experimental densities up to 600 bar. The measurements from 600 bar to 1400 bar were extrapolated and therefore they are not experimental. The AAD with the values obtained from Canet et al. (2002) is 0.19%. The relative deviations as a function of temperature and pressure can be seen in Figure 43 and Figure 44, respectively.

Figure 43: Relative deviations between the experimental density values of the mixture methane - n-decane (xmethane = 0.6017) and the data from Audonnet & Paduá (2004) (xmethane = 0.601) and Canet et al. (2002) (xmethane = 0.6) as a function of temperature

-­‐0,4  

-­‐0,2  

0,0  

0,2  

0,4  

0,6  

0,8  

1,0  

0   20   40   60   80   100  

Relative  deviation  (%

)  

Temperature  (°C)  

Audonnet  &  Padua  (2004)   Canet  et  al.  (2002)  

44

Figure 44: Relative deviations between the experimental density values of the mixture methane - n-decane (xmethane = 0.6017) and the data from Audonnet & Paduá (2004) (xmethane = 0.601) and Canet et al. (2002) (xmethane = 0.6) as a function of pressure

5.4 Mixture  methane  –  n-­‐decane  (xmethane  =  0.8496)  

After considering the two-phase region of this mixture the starting point for the experimental measurements was set to 400 bar. The measured densities for the mixture can be seen in Table 15. Table 15: Experimental density values (kg/m3) of the mixture methane - n-decane (xmethane = 0.8496)

Pressure (bar)

Temperature (°C) 5 25 50 75 100 150 190

400 494.66   472.29   450.75   426.98   405.39   364.81   334.45  600 521.06   505.01   485.38   465.12   449.22   412.75   390.26  800 539.24   524.48   507.40   490.46   476.43   444.28   425.01  1000 553.96   541.21   525.24   509.94   497.59   468.78   451.16  1200 566.76   553.90   540.18   526.00   514.30   488.41   470.83  1400 577.99   565.54   552.81   539.67   527.66   503.89   486.86  

The Tait equation was used again to correlate the results with those from Audonnet & Pádua (2004). The standard deviation (σ) of the fit and the parameters obtained in the Tait equation for the correlation for both our experimental results and those from Audonnet & Pádua (2004) can be seen in Table 16. The surface ρ(T,p) as a function of pressure and temperature for our results and those from Audonnet & Pádua (2004) can be seen in Figure 45 and Figure 46, respectively.

-­‐0,4  

-­‐0,2  

0,0  

0,2  

0,4  

0,6  

0,8  

1,0  

0   200   400   600   800   1000   1200   1400  

Relative  deviation  (%

)  

Pressure  (bar)  

Audonnet  &  Padua  (2004)   Canet  et  al.  (2002)  

45

Figure 45: Surface ρ(T,p) for our experimental results for the mixture methane – n-decane (xmethane = 0.8496)

Figure 46: Surface ρ(T,p) for the results from Audonnet & Pádua (2004) for the mixture methane – n-decane

(xmethane = 0.799)

46

Table 16: Parameters obtained in the Tait equation with the results from Audonnet & Pádua (2004) (xmethane = 0.799) and our experimental results (xmethane = 0.8496)

Audonnet & Pádua (2004) Experimental results from this work Parameter Value Parameter Value a (MPa) 59.35 a (MPa) 45.02

b (MPa/K) -0.04397 b (MPa/K) -0.3238 c (MPa/K2) -0.0002849 c (MPa/K2) 0.0003153 a1 (g/cm3) 0.861934 a1 (g/cm3) 0.7293

b1 (g/cm3K) -0.00082 b1 (g/cm3K) -0.000912 C (-) 0.0937 C (-) 0.09733

σ (g/cm3) 0.0004 σ (g/cm3) 0.0068 It should be mentioned here that our mixture with methane mole fraction xmethane = 0.8496 has significantly more methane than the mixture prepared from Audonnet & Pádua (2004), which has a methane mole fraction xmethane = 0.799. The comparison of the experimental results with the results obtained from Audonnet & Pádua (2004) was possible for the temperatures of 50 °C, 75 °C and 100 °C and the pressures of 400 bar and 600 bar. The relative deviations as a function of temperature and pressure can be seen in Figure 47 and Figure 48, respectively. The experimental results have an AAD of 11.11% with those obtained from Audonnet & Pádua (2004). The high negative deviations are due to the fact that our mixture has significantly lower methane than the mixture prepared from Audonnet & Pádua (2004), which results in lower density values.

Figure 47: Relative deviations between the experimental density values of the mixture methane - n-decane (xmethane = 0.8496) and the data from Audonnet & Paduá (2004) (xmethane = 0.799) as a function of temperature

-­‐14  

-­‐12  

-­‐10  

-­‐8  

-­‐6  

-­‐4  

-­‐2  

0  0   20   40   60   80   100   120  

Relative  deviation  (%

)  

Temperature  (°C)  

Audonnet  &  Padua  (2004)  

47

Figure 48: Relative deviations between the experimental density values of the mixture methane - n-decane (xmethane = 0.8496) and the data from Audonnet & Paduá (2004) (xmethane = 0.799) as a function of pressure

The density, for all compositions at 5 °C and 190 °C, as a function of pressure can be seen in Figure 49. Three parameters that have an effect on density are the methane mole fraction in the mixture, the pressure and the temperature. The effect of those three parameters on the density can be observed in Figure 49. The density is increasing with the increase of pressure and decreasing with the increase of temperature. Finally, the increased amount of methane in the mixture decreases the density.

Figure 49: Density as a function of pressure for all compositions at 5 °C and 190 °C

-­‐14  

-­‐12  

-­‐10  

-­‐8  

-­‐6  

-­‐4  

-­‐2  

0  0   100   200   300   400   500   600   700  

Relative  deviation  (%

)  

Pressure  (bar)  

Audonnet  &  Padua  (2004)  

300  

400  

500  

600  

700  

800  

300   500   700   900   1100   1300  

Density  (kg/m

3 )  

Pressure  (bar)  

n-­‐decane  at  5  °C   Xmethane=0.227  at  5  °C   Xmethane=0.6017  at  5  °C   Xmethane=0.8496  at  5  °C  n-­‐decane  at  190  °C   Xmethane=0.227  at  190  °C   Xmethane=0.6017  at  190  °C   Xmethane=0.8496  at  190  °C  

48

5.5 Density  modeling  

As mentioned before a comparison of two cubic (SRK & PR) and two non-cubic (PC-SAFT & Soave-BWR) EoS was performed. As far as the pure n-decane is concerned the two non-cubic EOS performed better than the cubic ones. SRK showed the highest AAD with 19.36% and PC SAFT the lowest with 1.12%. For the binary mixture the best-performed equation for all methane fractions was PC SAFT and the worst-performed was SRK. SBWR performed well with the mixture with the lowest methane mole fraction, while PR performed better with the mixture with the highest methane mole fraction. The AAD of the comparison between the experimental densities and those calculated with the EOS for the whole temperature and pressure range can be seen in Table 17 and Figure 50. Table 17: AAD and MAD of the comparison between the experimental densities and those calculated with the EOS for the whole temperature and pressure range

Fluid

SRK PR PC SAFT SBWR AAD (%)

MAD (%)

AAD (%)

MAD (%)

AAD (%)

MAD (%)

AAD (%)

MAD (%)

n-decane 19.4 24.7 6.80 12.1 1.12 2.82 0.69 2.70 xmethane=0.227 18.6 23.4 6.41 10.9 1.03 2.44 1.07 2.51 xmethane=0.6017 15.8 19.1 4.11 7.15 0.65 1.50 4.09 6.31 xmethane=0.8496 9.92 12.6 0.87 4.41 0.67 4.10 5.46 7.45 * MAD: Maximum Absolute Deviation

Figure 50: AAD of the comparison between the experimental densities and those calculated with the EOS for the whole temperature and pressure range

0  

5  

10  

15  

20  

25  

SRK   PR   PC  SAFT   SBWR  

Xmethane  =  0.227   Xmethane  =  0.6017   Xmethane  =  0.8496   Decane  

49

6 Conclusion and future work

The calibration of the DMA-HPM densimeter from Anton Paar was performed for pressures up to 140 MPa (1400 bar) and temperatures up to 190 °C (463.15 K) with a modified Lagourette equation proposed by Comuñas et al. For the validation of the apparatus, the density of n-decane was measured and compared with the literature. The results were then compared with the data from NIST, where an EoS proposed by Lemmon and Span (2006) was used and they were in good agreement with an AAD of 0.08%. The measurement of the density of the binary system methane - n-decane for three different compositions and under a wide range of pressure and temperature was carried out. For the first mixture with a composition of methane xmethane = 0.227 and after a correlation with the Tait equition the experimental data were compared with the results obtained from Audonnet & Pádua with an AAD of 0.17%. The second mixture under study had a composition of methane xmethane = 0.6017 and the density measurements were again correlated with the Tait equation and compared with the results from Audonnet & Pádua with an AAD of 0.30% and with those from Canet et al. (2002) with an AAD of 0.19%. The third mixture under study had a mole fraction of methane xmethane = 0.8496 and the densities were compared with those obtained from Audonnet & Pádua (2004) for their mixture with methane mole fraction xmethane = 0.799. The experimental results have an AAD of 11.11%. A high negative deviation like this was expected because of the different methane mole fraction in the two mixtures. Finally a comparison of two cubic EoS (SRK and PR) with two non-cubic EoS (PC SAFT and SBWR) was performed. In general, PC SAFT was the one that performed better with AADs lower than 1.2%. The SRK, on the other hand, showed very high deviations between 10% and 20%. For the pure n-decane the non-cubic equations performed much better with lower deviations. For the mixture with methane mole fraction xmethane = 0.227 the non-cubic equations performed better with AADs around 1%. For the mixture with methane mole fraction xmethane = 0.6017 PC SAFT had an AAD around 0.6% and both PR and SBWR showed an AAD around 4%. Finally, for the mixture with methane mole fraction xmethane = 0.8496 PC SAFT and PR showed the lowest deviations with an AAD of 0.67% and 0.87%, respectively. The fact that on the one hand the non-cubic EoS showed better results but on the other hand the cubic PR performed better than the non-cubic SBWR for some of the mixtures, is an indicator that further study is necessary.

50

The experimental data regarding the density of oil related binary systems are rare in the literature. Further study is therefore necessary to acquire a more extensive knowledge about the physical properties of such systems and their behavior under extreme conditions. The measurement of the density of a different alkane binary mixture containing methane such us methane - n-tetradecane under the same, wide range, of pressure and temperature would be a good starting point for future experimental work.

51

7 Bibliography

AGA, 2015. http://www.aga.se/sv/index.html. [Online]. Ahmad, M. et al., 2005. Microstructure and hardness studies of the electron beam welded zone of Hastelloy C-276. Journal of Alloys and Compounds, 390(1-2), pp.88-93. Amorim, J.A., Chiavone-Filho, O., Paredes, M.L.L. & Rajagopal, K., 2007. High-Pressure Density Measurements for the Binary System Cyclohexane + n-Hexadecane in the Temperature Range of (318.15 to 413.15) K. Journal of Chemical Engineering Data, 55(2), pp.613–18. Audonnet, F. & Pádua, A.A.H., 2004. Viscosity and density of mixtures of methane and n-decane from 298 to 393 K and up to 75 MPa. Fluid Phase Equilibria, 216(2), pp.235–44. BakerHughes, 2005. bakerhughes.com. [Online] Available at: http://public.bakerhughes.com/environment/downloads/25601%20HPHT%20Dilling%20Fluids%20Brochure_1209.pdf. Belani, A. & Orr, S., 2008. A Systematic Approach to Hostile Environments. JPT SPE Journal Paper, 60(07), pp.34-39. Bland, R.G. et al., 2006. HPHT Drilling Fluid Challenges. IADC/SPE Asia Pacific Drilling Technology Conference and Exhibition, pp.13-15. Canet, X., Baylaucq, A. & Boned, C., 2002. High-Pressure (up to 140 MPa) Dynamic Viscosity of the Methane+Decane System. International Journal of Thermophysics, 23(6). Caudwell, D.R., Trusler, J.P.M., Vesovic, V. & Wakeham, W.A., 2004. The viscosity and density of n-dodecane and n-octadecane at pressures up to 200 MPa and temperatures up to 473 K. International Journal of Thermophysics, 25(5), pp.1339-52. Chapman, W., Gubbins, K., Jackson, G. & Radosz, M., 1990. New reference equation of state for associating liquids. INDUSTRIAL and ENGINEERING CHEMISTRY RESEARCH, 29(8), pp.1709-21. Chasomeris, Pantelakis & Pantelide, 2015. Special course: Study of volumetric properties of alkanes and their binary mixtures under high pressure. DTU.

52

Cibulka, I. & Hnedkovsky, L., 1996. Liquid Densities at Elevated Pressures of n-Alkanes from C5 to C16: A Critical Evaluation of Experimental Data. Journal of Chemical Engineering Data, 41, pp.657-68. Comuñas, M.J.P., Bazile, J.-P., Baylaucq, A. & Boned, C., 2008. Density of Diethyl Adipate using a New Vibrating Tube Densimeter from (293.15 to 403.15) K and up to 140 MPa. Calibration and Measurements. Journal of Chemical and Engineering Data, 53(4), pp.986-94. Cullen, L.W.D., 1993. The public inquiry into the Piper Alpha disaster. Drilling Contractor, 49:4. Dymond, J.H. & Malhotra, R., 1988. The Tait Equation: 100 Years On. International Journal of Thermophysics, 9(6). Edwards, 2015. https://www.edwardsvacuum.com. [Online] Available at: https://shop.edwardsvacuum.com/products/d39590000/view.aspx. Edwards, 2015. https://www.edwardsvacuum.com. [Online] Available at: https://shop.edwardsvacuum.com/products/a37132919/view.aspx. Eren, H., 1999. Density Measurement. In Eren, J.G.W.a.H. Measurement, Instrumentation, and Sensors Handbook, Spatial, Mechanical, Thermal, and Radiation Measurement. 2nd ed. CRC Press 2014. pp.45.1-45.18. Furtado, A., Batista, E., Spohr, I. & Filipe, E., 2009. Measurement of density using oscillation-type density meters. Calibration, traceability and Uncertainties. Caparica, 2009. Garg, T. & Gokavarapu, S., 2012. Lessons Learnt From Root Cause Analysis of Gulf of Mexico Oil Spill 2010. SPE Kuwait International Petroleum Conference and Exhibition. Gil, L. et al., 2007. Experimental setup to measure critical properties of pure and binary mixtures and their densities at different pressures and temperatures Determination of the precision and uncertainty in the results. Journal of Supercritical Fluids, 44, pp.123-38. Gjonnes, M. & Myhre, I.G., 2005. High Angle HPHT Wells. SPE Latin American and Caribbean Petroleum Engineering Conference. Gross, J. & Sadowski, G., 2001. Perturbed-chain SAFT: An equation of state based on a perturbation theory for chain molecules. Industrial and Engineering Chemistry Research, 40(4), pp.1244-60.

53

Guilory, C.M., 2005. Reservoir evaluation program planning in HPHT environments. Harris, K.R., Malhotra, R. & A.Woolf, L., 1997. Temperature and density dependence of the viscosity of octane and toluene. Journal of Chemical and Engineering Data , 42(6), pp.1254-1260. Isco, T., 2013. http://www.isco.com. [Online] Available at: http://www.isco.com/products/products3.asp?PL=1051030. Joffe, J., 1947. Compressibilities of gas mixtures. Industrial Engineering Chemistry, 39(7). Kashiwagi, H. et al., 1982. Thermal conductivity and density of toluene in the temperature range 273-373 k at pressures up to 250 mpa.. International Journal of Thermophysics, 3(3), pp.201-15. Lagourette, B. et al., 1992. Densimeter calibration method versus temperature and pressure. Measurement Science and Technology , pp.699-703. Lee, B.I. & Kesler, M.G., 1975. A generalized thermodynamic correlation based on three-parameter corresponding states. AIChE Journal, 21(3), pp.510–27. Lemmon, E.W. & Huber, M.L., 2004. Thermodynamic Properties of n-Dodecane. Energy Fuels, 18(4), pp.960–67. Lemmon, E.W. & Span, R., 2006. Short Fundamental Equations of State for 20 Industrial Fluids. Journal of chemical and engineering data, 51(3), pp.785-850. Ling, K., Teodoriu, C., Davani, E. & Falcone, G., 2009. Measurement of gas viscosity at HPHT. International Petroleum Technology Conference. Lugo, L., Comuñas, M.J.P., López, E.R. & Fernández, J., 2001. (p, Vm, T, x) measurements of dimethyl carbonate + octane binary mixtures I. Experimental results, isothermal compressibilities, isobaric expansivities and internal pressures. Fluid Phase Equilibria, 186, pp.235–55. Paar, A., 2015. http://www.anton-paar.com/us-en/. [Online] Available at: http://www.anton-paar.com/us-en/products/group/density-meter/. Patel, N. & Teja, A., 1982. A new cubic equation of state for fluids and fluid mixtures. Chemical Engineering Science, 37(3), pp.463-73. Peng, D.-Y. & Robinson, D.B., 1976. A new two-constant equation of state. Industrial and Engineering Chemistry, Fundamentals, 15(1), pp.59-64.

54

PolyScience, 2015. https://www.polyscience.com. [Online] Available at: https://www.polyscience.com/products/circulating-baths/temperature-controllers/advanced-programmable-controller. Primio, R.d. & Neumann, V., 2007. HPHT reservoir evolution: a case study from Jade and Judy fields, Central Graben, UK North Sea. International Journal of Earth Sciences (Geol Rundsch), 97(5), pp.1101–14. Proehl, T. & Sabins, F., 2006. Drilling and completion gaps for hpht wells in deep water. Minerals Management Service. Radwan, A.M. & Karimi, M., 2011. Feasibility Study of Casing Drilling Application in HPHT Environments; a Review of Challenges, Benefits, and Limitations. SPE/IADC Middle East Drilling Technology Conference and Exhibition. Redlich, O. & Kwong, J.N.S., 1949. On the Thermodynamics of Solutions. V. An Equation of State. Fugacities of Gaseous Solutions.. Chemical Reviews, 44(1), pp.233-44. Segovia, J.J. et al., 2009. Automated densimetric system: Measurements and uncertainties for compressed fluids. Journal of Chemical Thermodynamics, 41, pp.632–38. Shadravan, A. & Amani, M., 2012. HPHT 101-What Petroleum Engineers and Geoscientists Should Know About High Pressure High Temperature Wells Environment. Energy Science and Technology, 4(2), pp.36-60. SIGMA-ALDRICH, 2014. http://www.sigmaaldrich.com. [Online] Available at: http://www.sigmaaldrich.com/Graphics/COfAInfo/fluka/pdf/PDF525421.pdf. SIGMA-ALDRICH, 2014. http://www.sigmaaldrich.com. [Online] Available at: http://www.sigmaaldrich.com/Graphics/COfAInfo/SigmaSAPQM/COFA/D9/D901/D901-BULK_________MKBR2528V_.pdf. SIKA, 2015. http://www.sika.net/en/. [Online] Available at: http://www.sika.net/en/products/electronic-measuring-and-calibration-instruments/pressure-calibrators/digital-pressure-gauges/item/1086-digital-pressure-gauge-type-p.html#product-description. Soave, G., 1972. Equilibrium constants from a modified Redlich-Kwong equation of state. Chemical Engineering Science, 27(6), pp.1197–203. Soave, G., 1999. An effective modification of the Benedict – Webb – Rubin equation of state, Fluid Phase Equilibria. Fluid Phase Equilibria, 164(2), pp.157–72.

55

Spencer, C.F. & Danner, R.P., 1972. Improved Equation for Prediction of Saturated liquid Density. Journal of Chemical Engineering, 17(2), pp.236–41. Stabinger, H., 1994. Density measurement using modern oscillating transducers. South Yorkshire Trading Standards Unit. Sydenham, P.H., 1999. Static and Dynamic Characteristics of Instrumentation. Measurement Techniques. Thompson, G., Patterson, R. & Sloan, J., 2012. Design and Development Considerations for HP/HT Subsurface Safety Valves. Offshore Technology Conference. Tropea, C., Yarin, A.L. & Foss, J.F., 2007. Handbook of experimental fluid mechanics. Springer. Viana, M., Juannin, P., Pontier, C. & Chulia, P., 2002. About pycnometric density measurements. TALANTA, 57(3), pp.583-93. VWR, 2015. https://sg.vwr.com/store/. [Online] Available at: https://sg.vwr.com/store/asset?assetURI=https://sg.vwr.com/stibo/hi_res/std.lang.all/94/45/14909445.pdf. Wagner, W. & Pruss, A., 2002. The IAPWS Formulation 1995 for the Thermodynamic Properties of Ordinary Water Substance for General and Scientific Use. Journal of Physical and Chemical Reference Data, 31(2), pp.387-535. Wei, Y., Stenby, E.H. & Varzandeh, F., 2015. PVT modeling of reservoir fluids using PC-SAFT EoS and Soave-BWR EoS. Fluid Phase Equilibria, 386, pp.96–124.

56

Appendix A: Technical Specifications Table 18: Technical specifications of the External Measuring Cell DMA-HPM (Paar, 2015)

Measuring range Density 0 to 3 g/cm3 Pressure 0 to 1400 bar (0 to 140 MPa) Temperature -10 to +200 °C

(263.15 K to 473.15 K) Accuracy

Density Up to 0.001 g/cm3

Repeatability s.d. Density Up to 0.0001 g/cm3

Resolution Density Up to 0.0001 g/cm3

Weight DMA-HPM 8.3 Kg (18.3 lbs.) Interface module 1.5 Kg (3.3 lbs.)

Dimensions DMA-HPM 210 x 78 x 86 mm

(8.3 x 3.1 x 3.4 inches) Interface module 220 x 120 x 80 mm

(8.7 x 4.7 x 3.1 inches) Additional information

Cell material Hastelloy C-276 Volume of the cell Approximately 2 mL Connections Pressure fittings for metal

tubes with 1/4” outer diameter Density error 0.001 g/cm3 to 0.0001 g/cm3 Temperature error < 0.1 °C Environmental conditions

Indoor use only

57

Table 19: Technical specifications of the PolyScience advanced programmable temperature controller with Swivel 180™ Rotating Controller (PolyScience, 2015)

Table 20: Technical specifications of the evaluation unit mPDS 5 (Paar, 2015)

Maximum Temperature 200°C Minimum Temperature -20°C Temperature Stability ±0.01°C Pump Variable-speed Pump Pressure (maximum) psi (bar) 4.3 (0.3) Pressure Flow Rate gpm (l/min) 5.3 (20.1)

Suction Flow Rate gpm (l/min) 3.9 (14.7) Display Type & Size SmartTouch Color LCD

4.3" Enhanced Data Display Capability 7 selectable views

Multi-Language Menus or Prompts 6 languages Automatic Loss of Power Reset Selectable

Safety Class (DIN 12876-1) III Alarm and Fault Indicators Message

Transducer input DPRn, SPRn, DSRn, Carbo, Oxygen Sensor, Conductivity Sensor

Analog inputs 0/4 to 20 mA active or passive Digital inputs For filler stop, detection of empty line Counter inputs For bottle counter Relays for limit monitoring 24 V, 0.7 A Analog outputs 4 to 20 mA active Graphic LCD display 640 x 480 pixel Serial interface Ethernet (LAN), USB, Profibus DP Power consumption 60 Watt Dimensions (W x H x D) 275 x 215 x 249 mm (10.83 x 8.47 x 9.8 in) Weight Max. 4.6 Kg

58

Table 21: Technical specifications of the SIKA digital pressure gauge Type P (SIKA, 2015) (SIKA, 2015)

Functions Adjustment options

Linearization 6 points Tare/Zero Yes Selectable units Pressure bar, mbar, kPa, MPa, PSI

Features Measuring inputs 1 x direct PC connection RS232 (optional) Analogue output 0(4)...20mA / 0...10 V Relay output 2 x 24 VDC/1A Built-in version (Optional)

Display / Representation Multi-functional 4 digit (0.5 % / 0.2 %),

5 digit (0.05 % / 0.025 %) LCD Bargraph Yes Display filter Yes Min/max value Yes

Measuring rate Standard 100 msec.

Process connection Connection options G1⁄2 Material 1.4542 Medium temperature 0...50 °C For aggressive media Yes

Housing Degree of protection IP65 (front) / IP40 Dimension 80 x 80 mm T=50 mm

H=130 mm Material Aluminium Operating temperature 0 - 50 °C Weight 900 g

Power Auto-off function Yes Battery type 2x 1.5 V AAA Ext. power 24 VDC Battery operation 8000 h

59

Table 22: Technical specifications of the Edwards E2M1.5 two-stage oil sealed rotary vane pump (Edwards, 2015)

Displacement (swept volume) 50 Hz 1.8 m3h-1 / 1 ft3min-1 60 Hz 2.2 m3h-1 / 1.3 ft3min-1

Speed (Pneurop 6602) 50 Hz 1.6 m3h-1 / 0.8 ft3min-1 60 Hz 2.0 m3h-1 / 1.2 ft3min-1

Ultimate vacuum (total pressure) Without gas ballast 3 x 10-3 mbar / 2.3 x 10-3 Torr With gas ballast 2.5 x 10-2 mbar / 1.9 x 10-2 Torr

Connection Inlet connection NW10 flange Outlet connection Nozzle 11 mm external diameter

removable from 3/8 inch BSP tapped hole Pressure

Maximum permitted pressure at outlet 0.5 bar gauge / 7 psig Maximum inlet pressure for water vapor 15 mbar / 11 Torre Maximum water vapor pumping rate 16 gh-1

Motor Motor power 50/60 Hz (IP54) 0.16 kW Nominal rotation speed 50/60Hz 2800/3400 rpm Power connector ICE EN60320 C13

Temperature Operating temperature range 12 - 40 °C

Weight Weight 10 kg / 22 lbs

Noise Noise 54 dB (A) @ 50 Hz Noise with acoustic enclosure 47 dB(A) @ 50Hz

Oil capacity Maximum 0.28 litre Minimum 0.2 liter Recommended oil (supplied) Ultra grade 15

60

Table 23: Technical specifications of the Edwards Active Digital Controller (ADC) gauge (Edwards, 2015)

Active gauge compatibility

Standard APG100, APG-L, APG-MP, APG-M, APGX-H, APGX-L, WRG

Enhanced Up to two gauges from the standard version plus AIM-X, AIM-S & ASG

Display High brightness green LED display (0.47 inch high)

Units mbar/Torr/Pa/Volts

Electrical supply 100 to 240V AC 47 to 63 Hz

Dimensional Data

Panel cut-out 92 + 0.8 x 45 + 0.6 mm (3.62inch x 1.77 inch) to DIN43700

Panel thickness 1.5mm (0.06 inch) Min

Weight 0.33Kg

Operating and storage data

Operating temperature +0 to +40°C

Storage temperature -30 to +70°C

Max ambient operating humidity 90% RH non condensing at 40°C

Standards

Electrical safety BS EN 61010-1

Electrical noise immunity BS EN 61326 (Industrial location, class B emissions)

Flame retardant case materials UL94 V1

Enclosure rating IP40

Enhanced features

Two analogue output 0-10V d.c.

Two set-point relays, volt free single pole change-over

1A at 48V d.c. / 2A at 24V d.c.

Serial output RS232

61

Table 24: Technical specifications of the Teledyne Isco 260D Syringe Pump (Isco, 2013)

Capacity 266 ml Flow Range (ml/min) 0.001 - 107 Flow Accuracy 0.5% of set point Displacement Resolution 16.6 nl Motor Stability ± 0.001% per year Pressure Range (psi) 0- 7500 Standard Pressure Accuracy 0.5% FS Optional Pressure Accuracy 0.1% FS Wetted Materials (standard) Nitronic 50, PTFE, Hastelloy C-276 Plumbing Ports 1/8" Valco Operating Temperature 5 - 40° C Ambient Power required 100 Vac, 117 Vac, 234 Vac, 50/60 Hz (specify) Dimensions (HxWxD, cm) 103 x 27 x 45 Weight Pump module - 33 kg; controller - 3 kg Standards conformity UL

62

Appendix B: Fluids properties

Table 25: Chemical and physical properties of Ethanol (VWR, 2015)

Table 26: Chemical and physical properties of Toluene (SIGMA-ALDRICH, 2014)

Company VWR BDH PROLABO PRODUCT NAME Ethanol 96 % vol GPR RECTAPUR Material 20824.296 Batch 15B090514 Expiration 02/2020 SPECIFICATIONS MEASURED VALUES Assay (anhydrous substance) Min. 99,8 % 0,999 Assay (V/V) 96,0 --> 96,3 % 0,963 Acidity Max. 0,0002 meq/g Max. 0,0002 meq/g Aldehydes (as CH3CHO) Max. 15 ppm 5 ppm Evaporation residue Max. 20 ppm 1 ppm

Product Name TOLUENE CHROMASOLV®, for HPLC, 99.9 % Product Number 34866 Batch Number STBF0798V Brand Sigma-Aldrich CAS Number 108-88-3 Formula C6H5CH3 Formula Weight 92.14 Expiration Date JUL 2019 Quality Release Date 03 SEP 2014 TEST SPECIFICATION RESULTS APPEARANCE (COLOR) COLORLESS COLORLESS APPEARANCE (FORM) LIQUID LIQUID TITRATABLE ACID FREE ACID < 0.001 % AS HCL < 0.001% PURITY (GC AREA %) ≥ 99.85 % 99.96 % WATER (COULOMETR.) < 0.02 % < 0.01% RESIDUE (EVAPORATION) < 0.0005 % < 0.0002% INFRARED SPECTRUM CONFORMS TO STRUCTURE CONFORMS UV-ABSORBANCE < 0.004 AT 350NM 0.004 UV-ABSORBANCE < 0.05 AT 310NM 0.03 UV-ABSORBANCE < 0.30 AT 290NM 0.17 MISCELLANEOUS TESTS THIOPHENE < 0.0005 % < 0.0005 %

63

Table 27: Chemical and physical properties of n-decane (SIGMA-ALDRICH, 2014)

Table 28: Chemical and physical properties of methane (AGA, 2015)

Product Name Scientific methane 5.5 Product Number D901 Brand AGA CAS Number 74828 Formula CH4 Appearance (color) COLORLESS Appearance (form) LIQUID Purity (%) 99.9995

Product Name Decane  -­‐  ReagentPlus,  >99% Product Number D901     Batch Number MKBR2528V Brand SIAL CAS Number 124-­‐18-­‐5   Formula C10H22 Formula Weight 142.28  g/mol   Density 0.730  g  mL  -­‐  (20°C) Expiration Date FEB  2017   Quality Release Date 20  FEB  2014   TEST SPECIFICATION RESULTS APPEARANCE (COLOR) COLORLESS COLORLESS APPEARANCE (FORM) LIQUID LIQUID Refractive  index  at  20  °  C   1.409  -­‐  1.413   1.412 PURITY (GC AREA %) ≥ 99.0 % 99.6 % INFRARED SPECTRUM CONFORMS TO STRUCTURE CONFORMS