Appendix M Aquitard Kv literature review

International Aquitard Vertical Hydraulic Conductivity Review Report for Queensland Gas Company

Final 1

17 April 2012

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International Aquitard Vertical Hydraulic Conductivity Review

Final 1

17 April 2012

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Aquitard Vertical Hydraulic Conductivity Review and Analysis

SINCLAIR KNIGHT MERZ

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Contents

1. Introduction 3

2. Terminology 4

3. Objective 6

4. Surat Basin Conceptualisation 7

4.1. Regional Geological Setting 7

4.2. Hydrogeology 10

4.2.1. Major aquifers and aquitards 10

4.2.2. Vertical Hydraulic properties 10

5. Method 13

5.1. Data Search 13

5.2. Data Compilation 13

5.3. Permeability and hydraulic conductivity 14

6. Results 15

6.1. Distribution of Kv’ 15

6.2. Comparison of Kv’ and K 16

6.3. Effect of lithology on Kv’ 17

6.4. Effect of data source on Kv’ 21

7. Discussion 23

7.1. Effect of test methods on Kv’ 23

7.1.1. Laboratory tests 23

7.1.2. Field tests 24

7.1.3. Conductivity estimated from models 25

7.2. Effect of discontinuities, bores, and multiphases on Kv’ 26

7.2.1. Discontinuities (joints, fractures, and faults) 26

7.2.2. Bores 27

7.2.3. Multiphase conductivity 29

8. Conclusions 31

9. References 33

Appendix A Documents consulted 36



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Executive Summary

An international literature review of 180 published papers has investigated the range of vertical

hydraulic conductivity (Kv’) for aquitards in sedimentary basins with lithology similar to those

encountered in the Surat Basin, such as sandstone, silt, siltstone, mudstone, clay, claystone and

shale.

The international literature review showed that around the world, the range of measured or

estimated vertical hydraulic conductivities of sedimentary facies typical of the Surat Basin is

extremely wide, ranging between 1 x 10-12

m/day (1 x 10-9

mD) and 3 m/day (3 x 10+3

mD).

The results of the literature review are summarised in the following table:

Median of lower values

Median of upper values

All lithologies (sandstone, coal, silt, siltstone, mudstone, clay, claystone,

shale)

All methods (285 citations)

10-5

m/day (10

-2 mD)

5 x 10

-4 m/day

(0.5 mD)

Fine grained lithology (mudstone, clay, claystone, shale)

All methods (193 citations)

10-6

m/day (10

-3 mD)

2 x 10-5

m/day (2 x 10

-2 mD)

Laboratory tests (47 citations)

10-8

m/day (10

-5 mD)

4 x 10-7

m/day (4 x 10

-4 mD)

Field Tests (45 citations)

4 x 10-5

m/day (4 x 10

-2 mD)

10-3

m/day (1 mD)

Field measurements are shown to yield systematically higher values of Kv’ (of approximately three

orders of magnitude) than laboratory testing of core samples. It is fair to assume that a large

proportion of field values collected in this review will contain results that are derived from shallow

depths (because many more tests will have been undertaken at shallow depths). It should also be

noted that as depth of burial increases, hydraulic conductivity typically decreases. These values

therefore may not be as representative of aquitards that are located at large depths.




Rock defects were shown to have a significant impact on regional Kv’. A simple set of vertical

non-intersecting vertical fractures of 0.1 mm (100 μm) openings spaced every 10km in a virtually

impervious matrix results in a regional Kv’ of 5.8 x 10-3

mD (5 x 10-6

m/day). Poorly constructed,

poorly decommissioned, abandoned or failed bores or those screened across multiple units, could

be considered to have a similar impact on regional Kv’ as those caused by rock defects.

The median Kv’ value of 1 x 10-3

mD (1 x 10-6

m/day) used in the GEN 2 model would appear to

be reasonable. However, the upper bound of the Kv’ range used in the GEN 2 groundwater model

(5 x 10-6

m/day) may be too low if the aquitard is fractured or contains poorly constructed bores.

The lower value of the range (5 x 10-7

m/day) can be regarded as appropriate.

Notes:

In the literature, hydraulic conductivities are reported in a large variety of forms. Some articles

provide single hydraulic conductivity estimation while most provide ranges of values. Single

values were considered as a range whose lower and upper values were equal. Therefore, hydraulic

conductivities are reported by two distributions: the first is constituted by the lower values of the

ranges and the second by the upper value of the reported ranges. The ―median of lower values‖ is

the median of the first distribution (i.e. all the ranges lower values) and the ―median of upper

values‖ is the median of the second distribution (i.e. all the ranges upper values).

Laboratory tests are reported regardless of the methodology used. It is important to note that

the methodology (particularly whether it is a permeability to gas or to water) yields outputs

that can range over 1 order of magnitude for the same samples.

Values were rounded to 1 significant figure and the conversion factor used in this document is

1mD = 10-3

m/day.




1. Introduction

Extraction of gas and water from the Walloon Coal Measures (WCM) will result in pressure

changes within this unit and has the potential induce vertical leakage from overlying and/or

underlying units. The amount and rate of potential leakage is predicted in the GEN2 model

(Golder Associates, 2011) to be small and the effects relatively localised. It is recognised,

however, that the model is based on assumed hydraulic properties, albeit a broad range.

Queensland Gas Corporation’s (QGC’s) Connectivity Programme (QGC, 2011) is designed to

provide much greater confidence in the predicted hydraulic impacts of pumping from the WCM.

The objectives of the Connectivity Programme are to:

1. Develop a scientifically robust and defensible understanding of the nature of the vertical

leakage induced by CSG development across the QGC tenements and adjacent areas

2. Demonstrate, through a comprehensive monitoring programme, the nature of the vertical

leakage

3. Characterise the key factors, both natural and anthropogenic, affecting vertical leakage

4. Characterise the spatial and temporal variation in vertical leakage

5. Identify any risks associated with unacceptable vertical leakage and develop response plans

for any risks

6. Develop a detailed understanding of the potential for extraction from the WCM on QGC

leases to affect vertical leakage from the Condamine alluvium.

The studies proposed to be undertaken to determine the hydraulic connectivity between the WCM

and the overlying and underlying aquifers, the leakage rates in and out of these aquifers and the

resulting impacts, are summarised in the Stage 1 CSG Water Monitoring and Management Plan

(WMMP).

This report presents the findings of the first task in the Stage 1 WMMP, Aquitard Vertical

Hydraulic Conductivity Review section.




2. Terminology

Aquifer Geological formation that comprises materials that have a moderate to high hydraulic

conductivity. Water supply wells are usually sunk into aquifers because the high

hydraulic conductivity enables moderate to high pumping rates

Aquitard Geological formation that comprises materials that have a low hydraulic conductivity.

Water supply wells are not usually sunk into aquitards because the low hydraulic

conductivity enables only low pumping rates

Intrinsic

permeability (k)

Intrinsic permeability is the portion of hydraulic conductivity which is representative of

the properties of the porous medium (not the fluid) and is a function of the size of the

openings through which the fluid moves

k = C d2 (dimensions are L

2 or Area)

C = dimensionless constant

d = mean pore diameter

dimensions are L2 or Area

Relationship between hydraulic conductivity and intrinsic permeability is K = k (ρg/µ)

ρ = density of fluid (g/cm3)

µ = dynamic viscosity of fluid

density units = g/cm3

viscosity units = centipoise

1 centipoise = 0.01 g/(cm sec)

g = acceleration constant due to gravity = 9.80665 m/s2

Hydraulic

conductivity

(K)

Hydraulic Conductivity is a term used for permeability of geologic material to water flow

K =Q/Ai (dimensions are L/T)

Q = discharge (L3/T)

A = cross sectional area of groundwater flow (L2)

i = groundwater gradient (L/L)

Kv vertical hydraulic conductivity of an aquifer

Kv’ vertical hydraulic conductivity of an aquitard

Kh horizontal hydraulic conductivity of an aquifer

Kh’ horizontal hydraulic conductivity of an aquitard




Millidarcy

(mD)

Intrinsic permeability (1 mD = 8.64 x 10-4

m/day).

m/day Hydraulic conductivity (1 m/day = 1,157.4 mD)

L/sec litres per second

a x 10-n scientific notation equivalent to a x 10-n

aE-N scientific notation equivalent to a x 10-n




3. Objective

The purpose of this project is to search international literature for documented values of vertical

conductivities related to leakage in confined aquifers, including existing CSG fields in North

America, Asia and Europe, major groundwater basins and geothermal fields. The literature search

aimed to identify the bounds (absolute minimal and maximal values) of vertical hydraulic

conductivities (i.e. coefficient of permeability) of aquitards overlying and underlying the producing

aquifer. It aimed to identify most likely values of vertical hydraulic conductivities for lithologies

comparable to the Surat Basin. It also aimed to document the main criteria controlling vertical

conductivities in order to provide some insight in the Surat Basin vertical hydraulic conductivities.




4. Surat Basin Conceptualisation

The geological setting of the Surat Basin has been described in detail in various previous QGC

reports, notably in the groundwater impact assessment report for the Queensland Curtis Liquefied

Natural Gas QCLNG (Golder Associates, 2011), from which most of the information below has

been sourced.

4.1. Regional Geological Setting

The Surat Basin is a sub-basin of the GAB, located across central southern Queensland and central

northern New South Wales (Figure 1). The Surat Basin is a complex multilayered sedimentary

sequence of fluvially deposited sandstone units interspersed with marginal-marine mudstone and

siltstone units. The GAB basin sediments extend to more than 3,000m in thickness, but the coal

measures targeted by the CSG extraction are generally at depth less than 1,200m. Figure 1

summarises the representative stratigraphic column of the Surat Basin units at QGC tenements. The

coal seams within the WCM unit are not present as laterally continuous seams or layers but as

numerous thin, disconnected coal plies in a matrix of generally low permeability sediments (Figure

2). The coal seams comprise 10% to 15% of the full thickness of the WCM and include up to 40 to

45 laterally discontinuous individual coal seams of varying thicknesses, extent and variable

permeability. These are the layers which are targeted for their CSG resource. The coal is

interbedded with shales, siltstones and mudstones, which comprise 85% to 90% of the full

thickness of the WCM.

Structurally, the lithological units are continuous across large areas within the basin although some

faulting, capable of locally displacing or disconnecting aquifers, is present. It has been suggested

that such faults can act as preferential permeable zones or alternatively as impermeable barriers to

groundwater movement (Habermehl, 2002 cited in WorleyParsons 2010). The sediments often dip

in a south-westerly direction. The WCM, outcropping on the eastern side of the basin, are found at

depths ranging from 100m to 800m along QGC tenements (Figure 3).




Figure 1. Surat Basin location (from QGC 2011)

Table 1. Lithology characteristics and hydrogeological role of the main units

Formation Dominant

behaviour

Lithology

Mooga

Sandstone

Aquifer Fluvial quartzose sandstone with thinly interbedded mudstone and

siltstone

Orallo

Formation

Confining Medium to coarse grained sandstone interbedded with

carbonaceous siltstone, silty mudstone, tuffs and coals

Gubberamunda Aquifer Medium to coarse grained quartz rich sandstone interbedded with

fine grained sandstone, siltstone and shale

Westbourne

Formation

Confining Interbedded shales, silstones and fine grained sandstone

Springbok

Sandstone

Poor Aquifer Sandstone, interbedded with carbonaceous siltstones, mudstone,

tuff and occasional coal beds

Walloon Coal

Measures

Coal measures Coal seams interbedded with shale, siltstone and mudstone

Confining layers Sandstone, siltstone and mudstone with high clay content.

Durabilla

Formation

Confining Fine to coarse grained sandstone interbedded with siltstone and

mudstone

Hutton

Sandstone

Aquifer Fluvial sandstone beds with minor thin conglomerate beds,

interbedded silts, and beds of mudstone rich in clay

Evergreen

Formation

Confining Thinly bedded mudstone, siltstone and sandstone intervals

Precipice

Sandstone

Aquifer Fine to coarse quartzose sandstone. Minor siltstone and clay matrix.

Bowen Basin




Figure 2. Coal Seam distribution within WCM

Figure 3. Schematic north-east to south-west cross section of the Surat Basin (from University of Southern Queensland, 2011)




4.2. Hydrogeology

4.2.1. Major aquifers and aquitards

As illustrated on Table 1, most formations within the Surat Basin comprise interbedded sandstone,

siltstone and mudstone. The formations that are dominated by Sandstones form the main aquifers,

with the aquitards dominated by shales, mudstones and siltstones. Due to the interbedded nature

within the formations, significant variability of hydraulic conductivity would be expected to occur

within each aquifer and aquitard. This variability may be greater within an aquifer or aquitard than

between aquifers and aquitards. For conceptualisation purposes and subsequent numerical

modelling, every unit was classified (Golder Associates, 2011) into aquifer and aquitard units

according to its most representative facies. The hydrogeological role played by each unit are

summarised in Table 1. The Surat Basin deposits can then be conceptualised by 5 main aquifers

(Mooga Sandstone, Gubberamunda, Springbok, Hutton, Precipice) separated by as many aquitard

(Orrallo, Westbourne, Durabilla, Evergeen formations). The WCM is also considered as an

aquitard despite the aquifer properties of the coal seams.

4.2.2. Vertical Hydraulic properties

According to Habermehl (2002, quoted in Worley Parsons, 2010) the representative horizontal

hydraulic conductivity for the GAB aquifers ranges from 0.1 to 10m/day (1 x 102 to 1.2 x 10

4 mD),

while the average vertical hydraulic conductivities for the leaky, low permeability, confining beds

range from 1 x 10-4

m/day to 1 x 10-1

m/day (0.12 to 120 mD).

Routine core analyses carried out on Walloon Coal Measure sediments from a range of wells across

the QGC tenements in the Surat Basin provide a range of hydraulic conductivities as summarised in

Table 2. All measurements were carried out at overburden pressure. Both vertical and horizontal

hydraulic conductivities show variation in hydraulic conductivities ranging over several order of

magnitudes. Downhole field estimates provide higher conductivities than laboratory core analyses.

This database formed a source of information upon which the hydraulic conductivities of the GEN2

numerical model were determined. The range of values used in the GEN2 model are summarised in

Table 3.

The University of Southern Queensland, in an attempt to assess the cumulative impacts in the Surat

Basin associated with the coal seam gas industry ( University of Southern Queensland, 2011), has

done a comparative study of hydraulic conductivities used in groundwater numerical models

among the four main CSG companies. Even though hydraulic conductivity values used in the four

models are mostly consistent, they vary by several orders of magnitude between models and up to 5

orders of magnitude for the Evergreen Formation. This emphasizes the difficulty in accurately

assessing hydraulic conductivities. The reason may be partly due to the lack of test results for some

of the units, but even results for well documented units such as the WCM are also spread over




several orders of magnitude. Well documented units are usually based on laboratory core sampling,

which do not account for rock fractures that are important to regional flow. Aquifer hydraulic tests

are often conducted over a too short a period to induce vertical flow through aquitards and obtain

estimates of vertical conductivity.

Table 2. QGC WCM hydraulic conductivity test results

Test method Lithology

Horizontal intrinsic

permeability and hydraulic

conductivity

Vertical intrinsic

permeability and hydraulic

conductivity

[mD] [m/day] [mD] [m/day]

Laboratory

core testing

Sandstone and

siltstones 0.01 to 128

8.6 x 10-6

to

1.1 x 10-1




Impacts, as identified by the numerical groundwater model (GEN2 in Golder Associates 2011), are

sensitive to hydraulic conductivity parameters and particularly for the vertical hydraulic

conductivity of confining layers separating pumped coal seams and GAB aquifers. The large

uncertainty associated with these parameters reduces the confidence of the potential impacts. The

current study aims at determining the extent to which this uncertainty can be reduced.




5. Method

5.1. Data Search

A review of existing literature and information on vertical hydraulic conductivity and leakage rates

for aquitards within major fractured rock and sedimentary basins throughout the world was

undertaken using the Science Direct On-line Reference Database and Willey Online Library.

Google and Google Scholar search engines were also used to search relevant literature. The search

was implemented by using either separately, or in combination, the following key words: Vertical

hydraulic conductivity, permeability, aquitard, coal seam gas, coal seam gas impacts, shale, clay,

mudstone, coal, siltstone, sandstones, Surat Basin, Bowen Basin, Shale gas, shale gas impact,

Barnett shale, Marcellus shale, Utica, geological nuclear waste management, etc.

After, collecting relevant articles some extended literature was researched using the references

quoted in articles, or by using search engines to search literature from authors identified as being

specialists on the hydrogeology of aquitards, such as C.E. Neuzil.

To manage the volume of material to be reviewed, emphasis was placed on major journals (e.g.

Groundwater). Relevant information quoted on free access abstracts was also considered.

Although the amount of reference material that could be obtained and reviewed is limited by the

timeframe for the study, a substantial resource comprising 180 references was compiled. The

documents consulted are referenced in Appendix A.

5.2. Data Compilation

In the literature, hydraulic conductivities are reported in a large variety of forms and units. The

reported hydraulic conductivities were obtained by a large variety of means, including several

laboratory techniques, field experiments, derived from modelling, or simply stated without

reference. They refer to various scales, ranging from decimetre large core samples to regional

aquitards comprising several stratigraphic units. Lithological descriptions of a single unit for which

a value of hydraulic conductivity is provided can also be very detailed (e.g. Fluvial sandstone beds

with minor thin conglomerate beds, interbedded silts, and beds of mudstone rich in clay) and such a

detailed description cannot be practically kept for a statistical analysis of hydraulic conductivity

references as it would generate as many categories as there are references. Consequently, for the

scope of this study it was necessary to group the references into explicit categories. Lithology was

grouped into the following six categories: clay, coal, mudstone, sandstone, shale and silt &

siltstone. For a complex lithological description the main lithology was adopted when it was clearly

stated; otherwise the lithology corresponding to the finest grain size was considered (e.g. the Kv’

for the unit given above as an example would then be put in the ―sandstone‖ category).




Results were categorised as ―laboratory‖, ―model‖ or ―field‖ obtained values irrespective of the

laboratory, modelling, or field testing methods used. Articles or book extracts referring to ranges of

conductivities without providing details on how the values were obtained were labelled ―text

book‖.

Some documents provide a range of values as they refer to several laboratory tested samples, or to

the uncertainty of the Kv’ estimation determined from field methods, whereas other articles provide

only a single value (which could be the average or the median value of a sample). So as not to

exclude any information, the distinction between Kv’ min and Kv’ max was retained and articles

providing single Kv’ values were given a Kv’ min and Kv’ max equal to that value.

Many references mentioned hydraulic conductivity (K) without discriminating between vertical

(Kv’) and horizontal conductivity (Kh’). References that did not make this distinction were

included if the material was considered relevant to this study. Thus in the collected literature, 132

references to vertical hydraulic conductivity were considered, along with 159 references to

hydraulic conductivity alone (i.e. where hydraulic conductivity was not categorised as horizontal or

vertical).

It is widely recognised that, due to the nature of sediment deposition and diagenesis, horizontal

conductivity can be up to several order of magnitude larger than vertical conductivity. Including

values of K in this study, which focuses on estimation of Kv’, would not underestimate Kv’ but

could potentially lead to an overestimation of the upper end of Kv’.

5.3. Permeability and hydraulic conductivity

It is important also to emphasize that permeability is an intrinsic property of a rock regardless of

the fluid (gas or liquid) flowing through it, and hydraulic conductivity characterises both the rock

and the viscosity of the fluid. Hydrogeologists tend to consider hydraulic conductivity to water

(expressed in m/day) while petrophysicists consider the intrinsic permeability expressed in

millidarcy (mD) which are usually measured on core sample with gas. The Darcy (and

consequently MilliDarcy) is not an SI (International System of Units). A medium with a

permeability of 1 Darcy permits a flow of 1 cm/sec of a fluid with a viscosity of 1 centipoise under

a pressure gradient of 1 atmosphere/cm. To convert to equivalent values of hydraulic conductivity

for water at 20ºC and at normal atmospheric conditions 1mD = 8.64 x 10-4

m/day and inversely,

1m/day = 1,157.4 mD. However, in this report, using that conversion factor, all units are presented

both in terms of hydraulic conductivity using units of m/day, and in terms of permeability using the

Millidarcy. Values were rounded to two significant figures.




6. Results

6.1. Distribution of Kv’

The distribution of all the data obtained from the literature review are presented in Figure 4. This

shows there is significant overlap between the minimum and maximum Kv’ values. The upper and

lower bound values of the min and max datasets are offset by approximately 2 orders of magnitude.

The median of the minimum and maximum value are 1 x 10-5

m/day (1 x 10-2

mD) and 5 x 10-4

m/day (5 x 10-1

mD).

Figure 4 Distribution of minimum and maximum Kv’

0

5

10

15

20

25

30

35

40

45

50

-12 -11 -10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 1 2

Co

un

t o

f va

lue

s

Log Kv' (m/day)

log Min (Kv')

Log Max (Kv')




6.2. Comparison of Kv’ and K

It is evident that the distributions of Kv’ and K (ie those that are not identified as Kv’ or Kh’)

values are similar as illustrated by Figure 5 and Figure 6. The inclusion of K references in the

report is therefore not considered to introduce any significant bias towards larger values of

hydraulic conductivity, but offers the advantage of increasing the pool of references. Also

noticeable, the lower value of hydraulic conductivity found in the literature refers to K and not to

Kv’.

Figure 5. Distribution of minimum hydraulic conductivity according to their references as Kv’ or K in the literature




Figure 6 Distribution of maximum hydraulic conductivity according to their references as Kv’ or K in the literature

6.3. Effect of lithology on Kv’

For this study the values of hydraulic conductivities presented in the literature, independently of the

methodology used to derive the values (laboratory testing, field tests, modelling, text books), have

been grouped into six relevant lithological categories. Figure 7 and Figure 8 represents the

distribution for all the lithologies in a combined graph. Figure 9 and Table 4 represent the

distribution for each of the lithologies separately. Note: sandstones are present within the aquitard

units of the study area and have therefore been included in the assessment.

Each lithology distribution of Kv’ ranges across several order of magnitudes and intersects. The

whole spectrum of Kv’ value ranges over 13 orders of magnitude. The breakdown into individual

lithology exhibits the same wide range of conductivities of over 10 orders of magnitude.




All lithologies except coal range over values of that are associated with both aquifer and aquitard

behaviour. It is therefore not possible on the basis of lithology alone to determine whether a

hydrogeological unit is primarily an aquitard or an aquifer.

Table 4. Distribution of Kv’ by lithology in mD (a) and in m/day (b).

Lithology Min Kv’ [mD] Max Kv’ [mD] Range, in order of

magnitude [mD]

Sandstone 1 x 10-5

1 x 10+4

10

Silt & Siltstone 1 x 10-8

1 x 10+5

14

Mudstone 1 x 10-9

1 x 10+4

14

Shale 1 x 10-9

1 x 10+3

13

(a)

Lithology Min Kv’ [m/day] Max Kv’ [m/day] Range, in order of

magnitude [m/day]

Sandstone 1 x 10-8

1 x 10+1

10

Silt & Siltstone 1 x 10-11

1 x 10+2

14

Mudstone 1 x 10-12

1 x 10+1

14

Shale 1 x 10-12

1 x 100 13

(b)




Figure 7 Distribution of minimum value of Kv’ by lithology in m/day

Figure 8. Distribution of maximum value of log Kv’ by lithology in m/day




Figure 9. Distribution of minimum and maximum log Kv’ in m/day for each lithology by their number of citation in literature




6.4. Effect of data source on Kv’

Values of hydraulic conductivity can be derived from field tests (eg pumping tests), laboratory

tests, or they can be derived from models and other reference material. The distribution of Kv’ per

acquisition method is presented in Figure 10 and Figure 11. These show that Kv’ derived from

field tests tend to be greater than those derived from laboratory tests, particularly for the minimum

Kv’ values. If we include only the lithologies that are most likely to form an aquitard (ie mudstone,

clay, claystone and shale this results in a significant 3 to 4 order of magnitude difference between

laboratory derived values and field test derived values (Table 5).

Figure 10 Distribution of minimum log Kv’ [in m/day] in literature for different methods of value derivation




Figure 11 Distribution of maximum log Kv’ [in m/day] in literature for different methods of value derivation

Table 5 Median of minimum and maximum Kv’ of fine grained lithologies derived from laboratory and field test methods

Aquisition method

Median of lower values (m/day)

Median of upper values (m/day)

all methods 10-6

2 x 10-5

Laboratory tests

10-8

4 x 10-7

Field Tests 4 x 10-5

10-3




7. Discussion

7.1. Effect of test methods on Kv’

Hydraulic conductivity can be determined using a number of different methods including

laboratory tests on core samples, field tests using boreholes, and from groundwater models.

7.1.1. Laboratory tests

In a laboratory, hydraulic conductivity is tested on a small core sample which usually has a

diameter and length of decimetre scale. Various laboratory techniques are available, but the main

method consists of placing the core sample in a cell and applying the overburden pressure to the

core. An air pressure (or alternatively another gas like helium or methane or a liquid like water) is

then applied to one face of the sample, creating a flow of air through the core. By measuring the air

flow and the viscosity of air (or used gas), the conductivity can be derived using Darcy’s law.

The measure of hydraulic conductivity from core testing can provide lower hydraulic conductivity

values compared to other methods for the following reasons:

The integrity of a core sample relies on the absence of open fractures, thus fracture zones tend

not to be sampled for laboratory testing (Ahmed et al, 1989)

Non-cohesive materials (i.e. solid containing a high proportion of sand or silt) tend to be easily

damaged or disturbed during collection of the core and hence are less likely to be sampled for

testing (Hammenneister et al)

The fluids/muds that are used during drilling can alter the properties of the formation which

can lead to a reduction in hydraulic conductivity (Sharma and Wunderlich, 1985)

The measure of permeability depends on the laboratory technique used. Permeability obtained

by standard core analysis techniques using gas are different from those using water. Measuring

intrinsic permeability of sandstone and shale cores, Bloomfield (Bloomfield et al. 1995)

obtained an average permeability to gas one order magnitude greater than the permeability to

water (5.1 x 10-1

mD or 4.4 x 10-4

m/day and 4.3mD or 3.7 x 10-3

m/day respectively).

However, using three different laboratory methods to measure matrix gas permeability, Luffel

(1993) reported that one of the techniques yielded permeability estimations 3 to 10 times

greater than the two others. This emphasises that despite the controlled environment of a

laboratory and despite the potential biases in the core sampling, results from permeability

measurements remain uncertain. Any proposed values of permeability from laboratory tests

encompass an uncertainty of at least one order of magnitude.

The difference between Kv’ derived core tested in the laboratory and Kv’ from field tests described

in Section 6.4 and Table 5 indicate that core samples do not account for hydraulic conductivity




provided by discontinuities such as fractures and bedding joints which on a regional scale have a

significant effect on Kv’. Laboratory results, unless a large number of samples are tested, also do

not take into account the variability of lithology that occurs within an aquitard. Laboratory

measurements are precise, but provide little insight into large scale hydraulic conductivity besides

providing an absolute minimum for regional Kv’. This is consistent with Hart (2006), who showed

that while measurements of Kv’ from a core of the Moquoteka Formation ranged from 1.6 x 10-9

to

3.5 x 10-7

m/day (1.8 x 10-6

mD to 4.1 x 10-4

mD), the regional behaviour suggested that regional

Kv’ was more likely around 1.6 x 10-6

m/day (1.8 x 10-3

mD).

In general, therefore, laboratory results should be considered to represent a lower bound value for

regional Kv’.

7.1.2. Field tests

Field estimation of aquitard hydraulic conductivity can be undertaken directly by testing the

aquitard, or indirectly by inducing flow from an aquitard into an aquifer by pumping. These are

described below:

Rowe (1993) describes a pumping test method to evaluate the hydraulic conductivity of

aquitards. It consists of pumping the aquifer while monitoring the aquitard. The pumping test

should extend over a long enough period to trigger leakage in the aquitard. A pumping test

that is too short, which is often the case due to time and cost limitations, tends to result in an

under-estimate of Kv’ because there has been insufficient time for leakage from the aquitard to

occur during the test (Kruseman and de Ridder, 1991). Pumping tests within an aquitard can

provide an estimate of aquitard properties but tend to test only a small area due to the low

hydraulic conductivity of the aquitard.

Geochemical or isotopic method exist to evaluate groundwater age, flow path, transmissivity

and hence conductivity, of low permeable aquitards.

Estimation of the vertical hydraulic gradient across an aquitard, assuming steady state

conditions, can be used to estimate aquitard vertical permeability. Usually this technique is

applied with a numerical model for which the vertical conductivity of the aquitard is adjusted

as part of the calibration process to match observed heads.

Slug tests within a portion of an aquitard separated by packer have also been successfully used

(Ayan et al., 1994).

Methods using earth tides and barometric fluctuation can also be used to derive Kv’ (Cutillo

and Bredehoeft, 2011).

Compared to laboratory techniques, a major advantage of field testing is that discontinuities such as

joints, faults, bedding planes fractures, and heterogeneity are included in the resultant Kv’. Some

methods, such as long term pumping test can also determine Kv’ values that are representative of




large areas or thicknesses. Laboratory tests in comparison generally only represent a discrete

location within the test site (i.e. aquitard).

Field tests generally become increasingly difficult and expensive to conduct as the depth of

investigation increases. The duration of tests for deep wells tend to be short due to the difficulties

encountered in managing hot and/or saline/corrosive water, and limits on the power of bore pumps

to lift water from large depths which can result in an underestimation of Kv’. It is fair to assume

that a large proportion of field values collected in this review contain results that are derived from

shallow depths, because many more tests will have been undertaken at shallow depths. It should

also be noted that as depth of burial increases, hydraulic conductivity typically decreases (McKee

et al. 1986). These values therefore, may not be as representative of aquitards that are located at

large depths. However, it is difficult to make generalisations about the reliability of field tests

without knowing the full details of how the test site was configured, how the test was conducted, its

duration and how the data was collected. Usually this information is not available in reference

material such as that used in the study.

7.1.3. Conductivity estimated from models

Numerical groundwater modelling can be used to infer the value of vertical conductivity at a

regional scale. Indeed, every model needs to be calibrated to obtain a good match between

observed and calculated heads. The calibrated parameters can be used as an estimation of the real

parameter value. The most important limitation of this approach resides in the fact that

groundwater models generally do not have a unique solution. Various combinations of parameters

can calibrate a model and uncertainty in the parameter estimation occurs as a result. The quality of

the parameter estimation relies on a proper conceptualisation of the hydrogeological system. The

numerical model links all model parameters. The estimation of one parameter, in this case Kv’, will

directly rely on the estimation of the other parameters, which may also have levels of uncertainty

similar to those of Kv’, such as groundwater recharge and evaporation. The method also relies

directly on the quality and quantity of observed heads. Transient observations recorded over a large

number of years contribute to narrowing down the distribution of calibrating parameters and to the

success of this method.

If a system is well understood conceptually and well documented through proper long term

monitoring, groundwater modelling, by incorporating all the hydrogeological information

available, has the potential to reliably estimate accurate bounds for Kv’ across aquitards at a

regional scale (Macfarlane, 1993).

Hydraulic conductivity can also be obtained from grain size analysis models. This method has

been excluded from this assessment because they are only applicable to unconsolidated sediments,

which are not present in the formations of the GAB.




7.2. Effect of discontinuities, bores, and multiphases on Kv’

7.2.1. Discontinuities (joints, fractures, and faults)

Discontinuities play a key role in aquitard Kv’. If discontinuities form an interconnected network

they are likely to be a significant control on regional hydraulic parameters. If the discontinuities

can be considered as isolated features in a bulk mass of low conductivity material, the regional

conductivity will be only partially influenced by those features, depending on their spacing

(frequency) and width.

According to a simple parallel plate model from Snow (1968) and reported in (Hart, 2006), a

simple set of non-intersecting fractures of 0.1 mm (100 μm) openings spaced every 10km is enough

to produce an aquitard of a virtually impermeable matrix with a regional Kv’ of 5 x 10-6

m/day (5.8

x 10-3

mD, Figure 12). Similarly, assuming a negligible matrix Kv’, fractures with openings of 0.1

mm (100 μm) would need to be spaced every 100km to give the aquitard a regional Kv’ of 5 x 10-7

m/day (5.8 x 10-4

mD). Thinner fractures with 0.01 mm (10μm) openings would need to be spaced

every 100m for a similar Kv’. Consequently, the chosen minimal value of 5 x 10-7

m/day (5.8 x 10-4

mD) is likely to be associated with a virtually unfractured rock, while a value of 5 x 10-6

m/day (5.8

x 10-3

mD) would indicate little fracturing. A fractured rock aquitard with more open fractures

would have greater Kv’ values. The range of Kv’ values used in the GEN2 groundwater model for

some confining units (between 5 x 10-7

and 5 x 10-6

m/day or 5.8 x 10-4

and 5.8 x 10-3

mD) may

therefore be too limited to represent a fractured aquitard.




Figure 12 Combination of fracture aperture and spacing that creates regional hydraulic

conductivities of 5.7 x 10-4

, 5.7 x 10-3

and 5.7 x 10-2

mD (resp. 5 x 10-7

, 5 x 10-6

and

5 x 10-5

m/day)

7.2.2. Bores

As with natural discontinuities, poorly constructed, poorly decommissioned, abandoned failed

bores, or bores screened across multiple units, may also act as sites of preferred flow which can

potentially affect regional vertical hydraulic conductivity values (Figure 13).

Bore construction requirements vary depending on the legislation under which a bore is licensed

and as a result, bores (including recently drilled bores) may be constructed to standards that are not

suitable for the prevention of inter-aquifer flow. For example, bores drilled for water supply are

regulated under the Queensland Water Act (2000) which has stringent controls on bore design to

prevent inter-aquifer flow. Bores drilled under the Petroleum and Gas Act (2004) have different

controls on bore design for the prevention of inter-aquifer flow.




In a study of the Maquoketa Aquitard in Wisconsin (Hart, 2006) estimated that only 50 wells of 0.1

m radius open to aquifers above and below a shale unit and evenly spaced 10 km apart across the

~60 km x 100 km extent of the Aquitard would be sufficient to provide a Kv’ of 1.6 x 10

-6 m/day

(1.8 x 10-3

mD), while laboratory estimates of Kv’ from core samples from the same unit ranged

from 1.6 x 10-9

to 1.6 x 10-7

m/day (1.8 x 10-6

mD to 4.1 x 10-4

mD ).

A total of 1,158 flowing bores in the GAB have been capped between 1999 and 2010 resulting in

an ongoing reduction in discharge of 298,778 ML/year or 258 ML/year/bore (GABCC, 2010). A

further 537 bores were due to be decommissioned as part of the Phase 3 Basin renewal program.

When this is completed a total of 1,695 bores will have been decommissioned. Divided over the

full GAB area of 1.7 million km2 results in one bore per 1,468 km

2 (it is likely that this is an over-

estimate of the area per bore because the artesian area will be smaller than the total basin). Using

an average pressure head of 160 m, an assumed drawdown to ground surface (i.e. 160 m of

drawdown), and an average aquifer depth of 1,000 m, the vertical gradient is 0.16. Using Darcy’s

equation the resultant Kv’ is 3.0 x 10-6

m/day (3.5 x 10-3

mD) from bore discharge alone. If matrix

Kv’ is included the Kv’ would be expected to be greater than 3.0 x 10-6

m/day (3.5 x 10-3

mD).

Although this is a relatively crude analysis it demonstrates that flow through bores could have a

significant effect on Kv’.




Figure 13. Diagrammatic representation of possible leakage pathways through an abandoned well. a) Between casing and cement b) between cement plug and casing c) through the cement pore space as a result of cement degradation d) through casing as a result of corrosion e) through fractures in cement and f ) between cement and rock (from Gasda 2004)

7.2.3. Multiphase conductivity

Hydraulic conductivity of a porous medium is reduced when a gas phase appears in the bulk rock

(Kissel, 1975). With the porosity being jointly shared by the two phases, the volume of voids

available for water decreases as the volume of gas increases and thus the hydraulic conductivity

decreases. Figure 14 shows an example of a gas and water relative permeability curves derived

experimentally by Kissel (1975). It is noticeable that with a water saturation of 80%, the

permeability of the water phase is reduced by one order of magnitude compared to its value at

100% saturation. At 50% of water saturation the permeability to water becomes virtually zero

compared to the fully saturated value.




Figure 14 Example of gas and water relative permeability curves (from Kissel 1975)




8. Conclusions

The international literature review determined that around the world, measured or estimated

vertical hydraulic conductivities of facies similar of those encountered in the Surat Basin, such as

sandstone, siltstone, mudstone and shale, range over 14 orders of magnitude. The lowest vertical

hydraulic conductivity from core samples was 1 x 10-12

m/day (1 x 10-9

mD). The lowest vertical

hydraulic conductivities from field tests were one order of magnitude higher than laboratory tests.

The higher hydraulic conductivity, as determined from field tests, is potentially due to the influence

of defects (i.e. joints, faults, bedding planes) that cannot be represented in laboratory samples.

Short duration field tests (e.g. slug tests, packer tests or short duration pumping tests) may also

underestimate vertical hydraulic conductivity. The shallow depth that many of the field values in

this review may have been derived may lead to an over-estimate of Kv’ for aquitards that occur at

greater depths, such as those in the Surat Basin. In general laboratory results should be considered

to represent a lower bound value for regional Kv’.

Snow (1968) demonstrated the significance of defects on hydraulic conductivity by calculating that

a simple set of vertical non-intersecting fractures of 0.1 mm (100 μm) openings spaced every 10km

in an theoretical impervious matrix results in a regional Kv’ of 5 x 10-6

m/day (5.8 x 10-3

mD). With

the defects spaced at 100 km apart the Kv’ reduces to 5 x 10-7

m/day (5.74 x 10-4

mD), which is still

significantly greater than the lowest values identified in the literature search. This indicates that

Kv’ values less than 5 x 10-6

m/day (5.8 x 10-3

mD) are not likely to be representative of the

regional Kv’ because they do not take into account defects within the rock mass. Even if defects are

widely spaced they can have a significant impact on Kv’.

In addition to natural defects, poorly constructed, poorly decommissioned, abandoned or failed

bores, or bores screened across multiple units, may contribute to Kv’ by allowing flow between

aquifers. Hart (2006) estimated that only 50 wells evenly spaced 10 km apart would be sufficient to

provide a Kv’ of 1.5 x 10-6

m/day (1.8 x 10-3

mD), while laboratory estimation of Kv’ from core

samples ranged from 1.5 x 10-9

m/day to 3.5 x 10-7

m/day (1.8 x 10-6

to 4.1 x 10-4

mD).

Discharge from the 1,158 flowing bores in the GAB that have been capped between 1999 and 2010

is equivalent to a Kv’ of 3.0 x 10-6

m/day (3.5 x 10-3

mD), if the bores are assumed to be uniformly

spaced across the GAB. Given that the bores are not uniformly spaced, the Kv’ in some areas

would be greater than 3.0 x 10-6

m/day (3.5 x 10-3

mD) and in other areas less than 5.6 x 10-6

m/day

(6.5 x 10-3

mD). The number of poorly constructed, poorly decommissioned, abandoned or failed

bores and the nature of natural defects, potentially has a large influence on Kv’.

The literature review supports the current range of conductivities used in the GEN2 numerical

models (which were between 1 x 10-6

m/day to 1 x 10-5

m/day or 1.2 x 10-3

and 1.2 x 10-2

mD). The

range is within the expected values for Kv’ used for similar modelling approaches by 4 major




companies in the CSG industry in the Surat Basin, as investigated by the University of Southern

Queensland (2011).




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