05 Triaxial Induction

7/24/2019 05 Triaxial Induction

1/21

64 Oilfield Review

Triaxial InductionA New Anglefor an Old Measurement

Barbara Anderson

Consultant

Cambridge, Massachusetts, USA

Tom Barber

Rob Leveridge

Sugar Land, Texas, USA

Rabi Bastia

Kamlesh Raj Saxena

Anil Kumar TyagiReliance Industries Limited

Mumbai, India

Jean-Baptiste Clavaud

Chevron Energy Technology Company

Houston, Texas

Brian Coffin

HighMount Exploration & Production LLC

Houston, Texas

Madhumita Das

Utkal University

Bhubaneswar, Orissa, India

Ron Hayden

Houston, Texas

Theodore Klimentos

Mumbai, India

Chanh Cao Minh

Luanda, Angola

Stephen Williams

StatoilHydro

Stavanger, Norway

For help in preparation of this article, thanks to Frank Shray,Lagos, Nigeria; and Badarinadh Vissapragada, Stavanger.

AIT (Array Induction Imager Tool), ECS (Elemental CaptureSpectroscopy Sonde), ELANPlus, FMI (Fullbore FormationMicroImager), MR Scanner, OBMI (Oil-Base MicroImager),OBMI2 (Integrated Dual Oil-Base MicroImagers) andRt Scanner are marks of Schlumberger.

Excel is a mark of Microsoft Corporation.

Westcott is a mark of Acme United Corporation.

A new induction resistivity tool provides 3D information about formations far from the

wellbore. It improves the accuracy of resistivity measurements in deviated wells and

in dipping beds, and can measure formation dip magnitude and direction without

having to make contact with the wellbore. The tools highly accurate triaxial

resistivity measurement means fewer missed opportunities and better understanding

of the reservoir.

Triaxial induction resistivity is rejuvenating an

old measurement. Formation resistivity, the

fundamental property log analysts use to evaluate

oil and gas wells, was the first measurement

acquired with wireline logging tools. As the

equipment to provide resistivity measurements

evolved, induction resistivity logging became the

standard measurement technique for acquiring

formation resistivity. However, the accuracy of

tool response at high resistivities and in deviated

wells or dipping reservoirs was limited by thephysics of the measurement. A new tool

overcomes many of the limitations of previous

induction logging techniques. This 3D triaxial

induction measurement enables petrophysicists

to better understand and evaluate the types of

reservoirs where, before the new technology,

hydrocarbons could have easily been

underestimated or overlooked.

The resistivity story began a century ago,

when Conrad Schlumberger developed a

technique for measuring the resistivity of the

subsurface layers of the Earth. His experiments

demonstrated a practical application with

commercial possibilities. The concept was

promising enough that he formed a business

venture to put the technique into practice.1 On

September 5, 1927, with equipment designed and

built by Henri-Georges Doll, the first electrical

logging experiment, a measurement of formation

resistivity, was conducted in a well in the

Pechelbronn oil region, Frances only large oil

field (next page, bottom).2

The fledgling oil and gas industry adopted

this electrode-based resistivity measurement,

and, with modifications, used it to identify

hydrocarbon deposits. Porous, permeable zoneswith high resistivity indicated the potential for

oil or gas; low resistivity suggested the presence

of salt water. Then, in the 1940s, Doll introduced

the principles of induction resistivity logging to

the industry.3 This technique acquired formation

resistivity in wells without a conductive path,

notably in oil-base mud, overcoming a major

limitation of electrode-based measurements.

The process of measuring formation

resistivity is not as simple as taking a direct

reading from a tool or a measurement from

Point A to Point B; however, in the past half-

century, great strides have been made in

accurately measuring this critical parameter.

Because induction logging tools provide

1. Gruner Schlumberger A: The Schlumberger Adventure.New York City: Arco Publishing, Inc., 1982.

2. Oristaglio M and Dorozynski A: A Sixth Sense: The Lifeand Science of Henri-Georges Doll Oilfield Pioneer andInventor. Parsippany, New Jersey, USA: The HammerCompany, 2007.

3. Doll HG: Introduction to Induction Logging andApplication to Logging of Wells Drilled with Oil-BasedMuds, Petroleum Transactions, AIME1, no. 6(June 1949): 148162.

4. For more on induction tool response: Gianzero S andAnderson B: A New Look at Skin Effect, The LogAnalyst 23, no. 1 (JanuaryFebruary 1982): 2034.


2/21

Summer 2008 65

apparent formation resistivity by taking a

measurement from a large volume of material

beyond the borehole, all the components within

that sensed region influence the final reading.Some of these interactions can negatively impact

the quality and accuracy of the measured

resistivity value.4 This is especially true when the

layers are not perpendicular to the axis of the

tool, as is the case with dipping beds and

deviated wells. Because of the effects of adjacent

conductive layers, the resistivity measured by

induction logging tools in dipping beds may beconsiderably lower than the true resistivity,

resulting in an underestimate of the hydrocarbon

in place. Heterogeneity between the subsurface

strata, and even within individual layers, also

affects tool response.

To account for these and other effects, log

analysts first used manual corrections and later

developed computer-based, forward-modeling

and inversion techniques to more closelyapproximate the true formation resistivity

However, they could not resolve all the

unknownsparticularly formation dip. Despite

these unresolved errors in the measurement, the

Rh

Rv

Rh

Rv

Z

X

z

x

y

Y

Transmitter

Receiver

> The first resistivity log. The first carottage lectrique(electrical coring) from a well in Frances Pechelbronn oil field was recorded on September 5,1927. The equipment to provide this resistivity log was based on tools used for surface mapping. The log is scaled in ohm.m, as are modern resistivitylogs. The high-resistivity interval correlated with a known oil sand in a nearby well, validating the use of log data to evaluate wells.

High resistivity


3/21

industry has successfully discovered much of the

worlds hydrocarbon resources using induction

logging tools. Unfortunately, some reservoirs

have been overlooked or underestimated

because of the measurement limitations.

Another difficult formation property for

induction tools to contend with is electrical

anisotropyvariations in properties that change

with the direction of the measurement.5

Anisotropy is prevalent in shales as well as in the

parallel bedding planes of laminated sand-shale

sequences. When the beds are thinner than the

vertical resolution of the induction logging tool,

the measurement becomes a weighted average of

the properties of the individual layers,

dominated by the elements with the lowest

resistivities. This phenomenon may mask the

presence of hydrocarbons.

The effects of anisotropy on the induction

resistivity measurement have been known since

the 1950s, but until recently there has been no

way to resolve the horizontal and vertical

components.6 By taking a 3D measurementin

essence a tensor rather than a scalar approach

these types of ambiguities and errors can be fully

resolved. However, sensors with the ability to

measure induction resistivity in three dimensions

in tensor form had been beyond the limits of

existing hardware. Similarly, the processing

required to model and invert the measurement

was extremely time-consuming, even when using

supercomputers or distributed networks.7

Many of the limitations inherent in induction

logging have now been overcome with the

Rt Scanner triaxial induction service. Currently

available computational-processing power has

been combined with a new tool design to create

a step change in the evolution of induction

logging. This new tool is solving problems and

providing the industry with answers to questions

that have plagued log analysts and geologistsfrom the beginning of well logging.

Three primary applications of triaxial induc-

tion tools are accurate resistivity measurements

in dipping formations, identification and

quantification of laminated pay intervals and a

new structural dip measurement that requires no

pad contact. This article describes how these

measurements are made and demonstrates their

applications. Also included are case studies from

Africa, India and North America.

Induction Resistivity Basics

A two-coil array demonstrates the physics of atraditional uniaxial induction resistivity measure-

ment. Alternating current excites a transmitter

coil, which then creates an alternating-

electromagnetic field in the formation (left).8

This field causes eddy currents to flow in a

circular path around the tool. The ground loops of

current are perpendicular to the axis of the tool

and concentric with the borehole. They are at

least 90 out of phase with the transmitter

current, and their magnitude and phase depend

on the formations conductivity.

The current flowing in the ground loop

generates its own electromagnetic field, which

then induces an alternating voltage in the

receiver coil. The received voltage is at least 90

out of phase with the ground loop and more than

180 out of phase with the transmitter current.

Induction resistivity from the formation is derived

from this voltage, referred to as the R-signal.

Direct coupling of the tools primary transmitter

66 Oilfield Review

> The concept of induction resistivity. The basic physics of the inductionresistivity measurement is represented by a two-coil array. A continuousdistribution of currents, generated by the alternating-electromagnetic fieldof the transmitter (T), flows in the formation beyond the borehole. Theseground loops of current generate electromagnetic fields that are sensed bythe receiver coil (R). A phase-sensitive detector circuit, developed originallyfor land-mine detection during World War II, separates the formation signal(R-signal) from the directly coupled signal coming from the transmitter(X-signal). The R-signal is converted to conductivity, which is then convertedto resistivity. (Adapted with permission from Doll, reference 3.)


4/21

Summer 2008 67

field in the receiver coil, the X-signal, combines

with the formation R-signal; however, the directly

coupled signal is out of phase with the

contribution from the formation. This phase

difference, detected using phase-sensitive

circuitry, permits the rejection of the X-signal and

measurement of the R-signal.

Conversion of the R-signal voltage to

conductivity was first accomplished by equations

based on the Biot-Savart law, which assumes the

major contribution of a single ground loop will

have a maximum value at the midpoint of the

transmitter and receiver coils.9 Schlumberger

mathematicians later developed equations

based on the complete solution for Maxwells

equationsthat provided more accurate measure-

ments.10 This solution can be visualized using a

simplified version of Maxwells equationsthe

Born approximationwhich is an accepted

method of determining the source and location

of the formation signal. For the two-coil axial

array, the response is essentially a toroid shape

surrounding the tool and perpendicular to its axis,with maximum values near the midpoint of the

transmitter and receiver (right).11

In vertical wells with thick homogeneous

horizontal beds, standard resistivity logging

tools, such as the AIT Array Induction Imager

Tool, work reasonably well. These uniaxial tools

measure apparent resistivity, Ra, in a horizontal

plane, which is equivalent to horizontally

measured resistivity, Rh. Resistivity measured in

a vertical plane, Rv, cannot be measured with

uniaxial induction tools in a vertical well.

Because the ground loops of induction tools

intersect a huge volume of the formation, theymay traverse a path that includes several different

layers with varying electrical properties.

Anisotropy results in a resistivity measurement

that changes based on the direction of the

measurement. This limitation in the measurement

was one of the factors that led to the development

of the Rt Scanner tool.

The Impetus for Triaxial Measurements

Although the concepts underlying triaxial

induction measurements first appeared in the

literature in the mid 1960s, the tools to make this

measurement were not developed. There were

three main reasons for the delay: a triaxial tool

could not be built with the existing technology,

the data processing required was beyond the

capability available at the time, and the tools

response to conductive fluids in the borehole

could be much larger than the signal from

the formation.

Interest in triaxial induction was renewed

chiefly because of the recognized limitations ofuniaxial resistivity measurements in two areas:

anisotropic reservoirs and bedding planes that

are not perpendicular to the axis of the tool.12

Although both of these limitations were

identified in the 1950s, there was then no direct

method of measuring anisotropy with an

induction logging tool, and the solution tonegative effects of real or relative dipping bed

on induction resistivity was not trivial.13 A

technology advanced, measurement under

standing, processing power and tool design al

played key roles in solving for these effects

5. For more on anisotropy: Anderson B, Bryant I, Lling M,Spies B and Helbig K: Oilfield Anisotropy: Its Origins andElectrical Characteristics, Oilfield Review6, no. 4(October 1994): 4856.

Tittman J: Formation Anisotropy: Reckoning with ItsEffects, Oilfield Review2, no. 1 (January 1990): 1623.

6. Kunz KS and Gianzero S: Some Effects of FormationAnisotropy on Resistivity Measurements in Boreholes,Geophysics23, no. 4 (October 1958): 770794.

Moran JH and Gianzero S: Effects of FormationAnisotropy on Resistivity-Logging Measurements,Geophysics44, no. 7 (July 1979): 12661286.

7. Anderson B, Druskin V, Habashy T, Lee P, Lling M,Barber T, Grove G, Lovell J, Rosthal R, Tabanou J,Kennedy D and Shen L: New Dimensions in ModelingResistivity, Oilfield Review9, no. 1 (Spring 1997): 4056.

8. For a detailed explanation of induction theory: Moran JHand Kunz KS: Basic Theory of Induction Logging andApplication to Study of Two-Coil Sondes, Geophysics27,no. 6, part I (December 1962): 829858.

9. The Biot-Savart law describes the magnetic fieldgenerated by an electric current.

10. Maxwells equations, named for physicist James ClerkMaxwell, are a set of four partial differential equationsthat explain the fundamentals of electric and magneticfield relationships.

11. Habashy T and Anderson B: Reconciling Differences inDepth of Investigation Between 2-MHz Phase Shift andAttenuation Resistivity Measurements, Transactions ofthe SPWLA 32nd Annual Logging Symposium, Midland,Texas, June 1619, 1991, paper E.

12. Moran and Gianzero, reference 6.

13. For the theoretical solution to Maxwells equations asapplied to induction logging: Moran and Kunz,reference 8.

Anderson B, Safinya KA and Habashy T: Effects ofDipping Beds on the Response of Induction Tools,paper SPE 15488, presented at the SPE AnnualTechnical Conference and Exhibition, New Orleans,October 58, 1986.

> Born approximation for a uniaxial induction logging tool. The sensed regionfor uniaxial induction tools is a toroid shape (red), perpendicular to the tool.The maxima are located approximately at the midpoint between the transmitter(T) and receiver (R). This rendering shows the Born approximation of the fullsolution to Maxwells equations. The shape is valid for thick beds andhomogeneous, isotropic formations. This region sampled by the uniaxialinduction tool corresponds to only one of the nine modes measured by thetriaxial Rt Scanner tool.

T

R


5/21

ultimately resulting in the development of a

triaxial induction tool (below left).

Developing such a tool involved understanding

the effects of the borehole on the measurement. 14

There is a great sensitivity to eccentricity in the

borehole: the more conductive the mud, the

greater the effect. The sensitivity results in the

formation signal being overwhelmed by the

borehole signal. This situation, the effects of

which can be two orders of magnitude greater for

triaxial tools than for uniaxial induction tools,

would have been an insurmountable obstacle

without intensive computer modeling.

Iterative modeling allowed various triaxial

tool designs to betested without having to build

and test physical tools. Final tool design included

a sleeve with electrodes connected to a

conductive copper mandrel. This configuration

returned the borehole currents through the tool,

reducing the large signals caused by the

transverse eccentricity to a level equivalent to

that of the AIT tool. The correction for borehole

effects could then be handled in a manner

similar to that used for the AIT measurement.15

After engineers solved for borehole effects,

tool response to various geometrical scenarios

was investigated. For most of their history,

induction measurements have had to contend

with geometry, both in the borehole and in the

formation. Geometry was regarded by inter-

preters as a major nuisance or, at best, something

to be coped with.16 However, after the AIT tools

response was modeled, tool designers discovered

that the formation-geometry effects are the

strongest contributor to the induction signal.

When properly resolved and modeled, geometry

now provided a key to accurate measurement of

formation resistivity. In addition, dipping beds

those that are not perpendicular to the axis of

the logging toolcould be properly measured.

Dipping beds are the result of geological

tilting of formations, deviation of the wellbore

trajectory from vertical, or combinations of both.

Fast analytical codes, developed in the 1980s,

estimate resistivity in dipping beds using data

from uniaxial induction tools, but the processing

68 Oilfield Review

> Rt Scanner triaxial induction service. The RtScanner tool comprises a triaxial transmitter,three short-spacing axial receivers for boreholecorrections and six triaxial receivers. Electrodeson the tool and the Rm sensor in the bottom nose,which measures the mud resistivity, are alsoused for borehole corrections. An internal metalmandrel (not visible in the drawing) provides aconductive path for borehole currents to returnthrough the electrodes on the exterior of the tool.

Electronics housing

Triaxial transmitter

Three short uniaxialreceivers for boreholecorrection

Six triaxial receivers

Metal mandrel

Sleeve with shortelectrodes

Rmsensor

Triaxial transmitter

Triaxial receiver

Axial receiver

Electrode> Three-dimensional arrays. The Rt Scanner service produces a nine-elementarray for each transmitter and receiver pair. Traditional induction measurements

are made by passing current through coils that are wrapped around the axisof the tool, also called the z-axis (blue), which induces current to flow in theformation concentrically around the tool. Triaxial induction tools also includecoils that are wrapped around the x-axis (red) and y-axis (green), whichcreate currents that flow in planes along the tools x- and y-axes. The x, y andz components of the transmitter couple with the x, y and z receivers. Forvertical wells with horizontal beds, only the xx, yy and zz couplings respond tothe conductivity () of the formation. In deviated wells or wells with dippingbeds, all nine components ofthe array are needed to fully resolve theresistivity measurement. The multiple triaxial transmitter and receiver pairsgenerate 234 conductivity measurements for each depth frame.

Tz

Rz

Tx

Rx

Ry

Ty

xx xy xz

yx yy yz

zx zy zz

=


6/21

Summer 2008 69

relies on inputs from other sources.17

Unfortunately, the uniaxial measurement may

become unreliable or provide nonunique

solutions when external data sources are used.All these issues posed problems for uniaxial

induction tools. In most cases, there was not

enough information to fully correct the data.

Triaxial induction tools, however, make the

necessary measurements to resolve the ambi-

guities and properly measure the resistivity of

anisotropic reservoirs, correct for nonuniform

filtrate invasion, correct for the effects of

dipping beds and deal with geometrical effects

on the measurement.18

Triaxial Resistivity Theory

Previous induction logging tools, such as those

from the AIT family, measure horizontal

resistivity (uniaxially). The Rt Scanner tool

measures in three dimensions (triaxially).

Although the physics of measurement are

similar, triaxial tools are much more complex

(previous page, bottom right).

The Rt Scanner tool consists of a collocated

triaxial transmitter array, three short axial

receivers and three collocated triaxial receiver

arrays. The triaxial transmitter coil generates

three directional magnetic moments in the x, y

and z directions. Each triaxial receiver array hasa directly coupled term and two terms cross-

coupled with the transmitter coils in the other

directions. This arrangement provides nine

terms in a 3x3 voltage tensor array for any given

measurement. All nine couplings are measured

simultaneously. An advanced inversion

technique extracts resistivity anisotropy, bed-

boundary positions and relative dip from the

tensor voltage matrix. The receiver arrays are

located at different spacings to provide multiple

depths of investigation.

The Born approximation for the triaxial

induction tools response provides a graphical

representation for the solution of the equations

representing the sensed region (above). The

uniaxial induction tools response was shown

earlier to have a single toroid shape; the triaxial

tool delivers nine responses superimposed on

each other. The zz term from the Rt Scanner tool

is essentially the same response as that

measured by the uniaxial induction tool.

Collocation of the coils is an important

feature of the Rt Scanner tool: when the

transmitter or receivers are not at the same

position, the spacings for the cross-terms will bedifferent from those of the direct terms. Because

the entire ensemble of measurements is made

within a single depth frame, no measurement

14. Rosthal R, Barber T, Bonner S, Chen K-C, Davydycheva SHazen G, Homan D, Kibbe C, Minerbo G, Schlein R,Villegas L, Wang H and Zhou F: Field Test Results of anExperimental Fully-Triaxial Induction Tool, Transactionsof the SPWLA 17th Annual Logging Symposium,Galveston, Texas, June 2225, 2003, paper QQ.

15. For details on Rt Scanner design and modeling:Barber T, Anderson B, Abubakar A, Broussard T,Chen K-C, Davydycheva S, Druskin V, Habashy T,Homan D, Minerbo G, Rosthal R, Schlein R and Wang H:Determining Formation Resistivity Anisotropy in thePresence of Invasion, paper SPE 90526, presented at

the SPE Annual Technical Conference and Exhibition,Houston, September 2629, 2004.

16. Moran and Gianzero, reference 6.

17. Barber TD, Broussard T, Minerbo G, Sijercic Z andMurgatroyd D: Interpretation of Multiarray Logs inInvaded Formations at High Relative Dip Angles, TheLog Analyst 40, no. 3 (MayJune 1999): 202217.

18. During the drilling process, fluids from the drilling mudleave the wellbore and enter permeable formations. Themud filtrate alters the electrical characteristics of theformation around the wellbore. The depth of filtrate inva-sion, and its associated geometry, may be unpredictable

> Born approximation for a triaxial induction tensor voltage array. The Born response function for a triaxial induction tool ismuch more complex than that for a uniaxial induction tool. There are nine elements, one for each component of the tensorvoltage array. Each transmitter-receiver pair has positive (red) and negative (blue) responses. The surfaces represent theregions where 90% of the signal measured by the receiver coil originates. Each of the nine components is superimposed atthe measure point of the tool. The xx, yy and zz elements are derived from the direct coupling of a triaxial transmitter and itsassociated triaxial receiver. The other six elements represent cross-coil responses. The zz response (bottom right) is theonly one measured by the simpler uniaxial induction tool.

50

50

0z-axis

y-axis

xx

x-axis

10050

050

100 10050

050

100

50

50

0z-axis

y-axis

yx

x-axis

10050

050

100 10050

050

100

50

50

0z-axis

y-axis

zx

x-axis

10050

050

100 10050

050

100

50

50

0z-axis

y-axis

xy

x-axis

10050

050

100 10050

050

100

50

50

0z-axis

y-axis

yy

x-axis

10050

050

100 10050

050

100

50

50

0z-axis

y-axis

zy

x-axis

10050

050

100 10050

050

100

50

50

0z-axis

y-axis

xz

x-axis

10050

050

100 10050

050

100

50

50

0z-axis

y-axis

yz

x-axis

10050

050

100 10050

050

100

50

50

0z-axis

y-axis

zz

x-axis

10050

050

100 10050

050

100


7/21

have to be depth-shifted to form the measure-

ment tensors. When all nine components are at

the same spacing and location, the matrix can be

mathematically rotated to solve for relative

formation dip. A change from one coordinate

system to another is also greatly simplified

because it involves a simple transformation, and

all measurements are made along the same

coordinate system as well as at the same depth.

Collocation is especially important when bedding

planes are not perpendicular to the relative

position of the tool.

Power in the Processing

Collocated orthogonal transmitter and receiver

pairs made the triaxial resistivity measurement

feasible, but advancement in processing power

was the enablerthat spurred the development of

the tool. Even in the late 1990s, triaxial induction

was referred to as a theoretical concept, prima-

rily because the computing power needed to

model and develop fast processing codes was not

readily available.19 Moores law, the observation

that computing power doubles every two years, is

evidenced in the progression that has occurred

with induction resistivity logging.

The first induction resistivity tools converted

conductivity measured downhole to an analog

voltage that was measured at the surface. The log

analyst read the resistivity from the logs and

applied corrections from charts to account for

the effects of adjacent beds and filtrate invasion,

generally ignoring borehole effects. Borehole

correction charts were then developed based on

geometrical-factor curves obtained from labora-

tory measurements made in plastic pipes

immersed in waters of varying salinity.20 In the

mid 1980s, these empirically derived charts were

reproduced using computer modeling.

70 Oilfield Review

02,500 2,000

1 10 100

1,5001,000 500

Conductivity, mS/m

Resistivity, ohm.m

Conductivity, mS/mConductivity, mS/m

0 500 1,000 1,500 2,000 2,500 2,000 1,500 1,000 500 0 500 1,000 1,500 2,000 2,500 2,000 1,500 1,000 500 0 500 1,000 1,500 2,000

10 xxxyxzyxyyyzzxzyzzhv

20

30

40

Depth,

ft

50

60

70

80

0

10

20

30

40

Depth,

ft

50

60

70

80

RhRv

Rh(inverted)

Rv(inverted)

80 ft

50 ft

40 ft

30 ft

20 ft

0 ft

Rh= 1.9 ohm.m

Rv= 11.0 ohm.m

Rh= 1 ohm.m

Rv= 2 ohm.m

Rh

= Rv= 50 ohm.m

Rh

= Rv= 0.5 ohm.m

Rh

= Rv= 1 ohm.m

> Modeling the triaxial induction response. A 1D horizontally layered,transversely isotropic (TI) model was used to validate the triaxial inductionresponse to known conditions (bottom right). The five layers used in themodel consist of two low-resistivity homogeneous layers, a high-resistivityhomogeneous layer, and two anisotropic layers with high- and low-contrast beds. The first measurement is conducted with a vertical tool inhorizontal beds (top left). The zz (blue) and yy (green) components react tothe resistivity of the beds, but the xx and all cross-components are zero.Prior to inversion, none of the curves indicates the correct horizontal (pinkdash) and vertical (black dash) conductivity. Next, the model well is

deviated 75 () and the tool position is rotated 30 () from the high sideof the wellbore. All nine components become active (center) and nonereads the same as the vertical model. The zz (blue) componentcorresponds to a uniaxial induction measurement, and although it is similarto the curve in the vertical response model, the curves shape andamplitude have changed. The data are then rotated mathematically ( topright) to zero the yx and yz (green dash) cross-coil contributions. Theangle of rotation required to zero these components corresponds to therelative dip of the beds. Finally, the data are inverted, correcting for bedthickness and deviation, and converted from conductivity to resistivity(bottom left). In the three lower layers, which are homogeneous, Rv(blue)and Rh(red) are equal and match the input resistivity. In the laminatedlayers, the curves separate as a result of anisotropy.


8/21

Summer 2008 71

The manual process of correcting induction

log data was carried out sequentially: apply

borehole corrections, correct for shoulder-bed

effects and correct for invasion. With the advent of

data recorders, log data could be processed using

computers. Codes were developed to perform 1D

corrections automatically, first at mainframe-

equipped computing centers and then as

processing power continued to grow, at the

wellsite using computer-equipped logging units.

Advances in computer technology rendered

the manual corrections obsolete, but there was a

problem in the methodology. The codes weredeveloped assuming horizontal, homogeneous

beds, and corrections were applied with the

same linear approach used by log analysts.

However, the ground loops produced by induction

tools intersect and interact with all the media

they come into contact with in a complex,

nonlinear fashion.21 The sequential approach,

used for decades, was found to be inadequate.

This situation was improved when fast 2D

asymmetric forward-modeling codes were

developed in the mid 1980s. They revealed just

how inaccurate sequential chartbook corrections

were for determining the true resistivity, Rt,

especially in thin beds invaded by mud filtrate.

Development of the AIT tool was a result of

lessons learned from those models. Since then,

various techniques have been applied to obtain

Rt, including iterative forward modeling and

inversion.22 Models have been developed that

include 1D corrections as well as corrections for

invasion and nonhorizontal bedding (2D) and

nonlinear invasion in tilted reservoirs (3D). Only

recently has advanced computer-processing

power enabled inversion codes that fully correct

the induction measurement. These codes allow

simulations to be run in hours instead of weeks.

If Moores law holds true, hours for processing

induction measurements will eventually be

reduced to seconds.

Induction resistivity data, acquired with a

triaxial tool, could now be processed in a

reasonable time frame. All the pieces of the

puzzle were available; the next step was to put

the triaxial toolto the test.

Testing the Code

To test the validity of the acquisition and

inversion algorithm for triaxial induction data, a

1D horizontally layered, transversely isotropic

(TI) model was constructed (previous page).

Five layers simulated a complex reservoir

comprising two low-resistivity sands, a high-

resistivity sand, an anisotropic low-resistivity

shale and a laminated sand-shale sequence.

This simulated reservoir included features

that present limitations for uniaxial resistivity

tools. The testing proved that a triaxial

resistivity measurement overcomes these

limitations and provides accurate resistivity in

challenging environments.

The outputs of the processing are true

resistivity corrected for dip in the nonlaminated

layers and a shale-affected resistivity in

laminated layers. Rv is provided from the

processing, although it is equivalent to Rh in the

isotropic intervals.

For the two laminated layers, Rv and Rh are

not equal, and the curves have separation based

on the degree of anisotropy. Neither Rh nor Rprovides the true resistivity of the modeled

reservoir in the case of laminated sections, but

techniques have been developed to provide the

resistivity of the sand layers.

True Resistivity

The true resistivity of a formation, Rt, is a

characteristic of an undisturbed, or virgin

region. Much study and research have been

carried out in the name of acquiring this elusivemeasurement. The measurement of induction

resistivity in a virgin zone is predicated on some

degree of homogeneity, consistent perpendicula

beds and isotropic reservoirs. In nature, this is

rarely the case.

The concept of vertical and horizonta

resistivities evolved early in the development o

electrical logging. Measured apparent resistivity

Ra, of stacked rock layers differs with changes in

the measurement direction. If the measurement

is made parallel to the layers, the result is

similar to measuring resistors in parallelthe

lowest resistances dominate (above). For a

parallel resistor circuit, more current flow

through the smaller resistors, and each resistor

19. Anderson BI: Modeling and Inversion Methods for theInterpretation of Resistivity Logging Tool Response. DelftThe Netherlands: Delft University Press, 2001.

20. Moran and Kunz, reference 8.

21. Anderson, reference 19.

22. Howard AQ: A New Invasion Model for Resistivity LogInterpretation, The Log Analyst33, no. 2 (MarchApril 1992): 96110.

> Direction matters. Under the right conditions, the deep-induction response to a homogeneous, isotropic bed ( left) is the same as that to an anisotropic,laminated bed (center). This occurs when beds are thinner than the vertical resolution of the measurement. For the 90-in. deep-induction array, thevertical resolution is 1 to 4 ft [0.3 to 1.2 m]. Horizontal resistivity (Rh) measurements are analogous to parallel resistor circuits, so the resistivity value of thelaminated bed is primarily influenced by the layer with the lowest resistivity, Rshale. With standard induction tools, hydrocarbon-bearing sand layers caneasily be overlooked. Vertical resistivity (Rv) is analogous to a series resistor circuit (right), and its value is dominated by the layer with the highestresistivity. A large difference between Rvand Rh indicates anisotropy.

1,800

Depth

ft

Computed Deep Induction

ohm.m0.2 2,000

1,810

1,820

1,830

1,840

1,800

Depth

ft

1,810

1,820

1,830

1,840

Computed Deep Induction

Model RtProfile Model R

tProfile Model R

h-R

vProfile

Rh

Rv

ohm.m0.2 2,000

Horizontal Resistivity, Rh

Vertical Resistivity, Rv

ohm.m0.2 2,000

Rsand

Rshale

Rsand

Rshale

Rshale

Rsand

Rsand


9/21

divides the current according to the reciprocalof its resistance.

When the measurement is made across the

stack, the measured resistance is similar to

measuring resistors in series. In an electrical

series circuit, the resistance values are added

together. Higher resistance, which is the case for

the layers containing hydrocarbon, is dominant.

The concept that the measured resistance

depends on the direction in which it is made is

referred to as electrical anisotropy. Since well

logging began in vertical wells with stacks of

more or less horizontal layers, the resistivity

parallel to the layers was called the horizontal

resistivity, Rh, and the resistivity measured

across the layers was called the vertical

resistivity, or Rv. In an isotropic, thick sand Rh =

Ra = Rv. If, however, the thickness of the bedding

layers is less than the tools vertical resolution,

the Rh measurement is analogous to the parallel

electrical circuit.

Most of the technology for determiningformation resistivity measured the horizontal

component, giving rise to difficulties in

evaluating thin layers comprising shale and

hydrocarbon-bearing sands. For a uniaxial

induction measurement the formation currents

flow in horizontal loops, and the resulting

sensitivity is to the horizontal resistivity. For

most laminated reservoirs,Rh Rv. Based on the

parallel circuit analogy, Ra will be similar in

value to that of the layer with the lower

resistivity, usually the shale. Therein lies the

problem with interpreting induction resistivity in

laminated reservoirs: the dominant nature of the

less-resistive layers masks the more-resistive

layers that may have hydrocarbon potential. The

result is that pay zones may be overlooked or

underestimated.23 The Rv/Rh ratio is a useful

measurement for determining the level of

anisotropy, and when the ratio is higher than 5,

it alerts the log analyst to look for potential

laminated-pay reservoirs.

For a laminated sand-shale sequence, theportion of the reservoir that is of interest is the

sand. Although Rv does not provide the actual

resistivity of the hydrocarbon-bearing sand layer,

Rsand, it can be combined with other

measurements to derive it. The shale effects

must be removed from the volumetric

measurement to obtain the resistivity of the sand

layers (above). Calculating Rsand from Rh and Rv

requires a secondary source to determine the

volume of shale before its effects can be

eliminated. Shale volume can be obtained from

several sources, including the ECS Elemental

Capture Spectroscopy sonde. Once determined,

Rsand can be used to calculate water saturation,

Sw, using Archies equation. The full derivation of

the formula for Rsand and Sw in the presence of

anisotropy can be found in the literature.24

72 Oilfield Review

> Hidden saturation. Rhand Rvare outputs from the Rt Scanner tool. The resistivity of the sand layers can beresolved from these measurements in combination with fractional volumes of sand and shale. For this example,the conventional induction tool would have measuredRh= 2.3 ohm.m. Rv from the triaxial induction measurementis 12.8 ohm.m. The volume fractions, Fshaleand Fsand, could come from an ECS Elemental Capture Spectroscopytool. Because shales often exhibit anisotropy without the presence of sand laminations, two different shalevalues are used in this example: vertical Rshale-v is 2 ohm.m and horizontal Rshale-h is 1 ohm.m. These values shouldbe determined within an anisotropic shale interval. This method gives an Rv/Rh ratio in the shale of 2, comparedwith the 5.6 ratio of the entire sand-shale sequence. Solving the equations (right) for Rsandyields a value of 20 ohm.m.The 2.3 ohm.m measured by a conventional induction tool would considerably underestimate the hydrocarbon volume.

Rsand

Rsand

Rsand

Rshale-h

Rsand

Rshale-h

Rshale-h

Rshale-v

Rshale-v

Rshale-v

Rsand

R

sand

Rshaleh

= 1 ohm.m

Rshalev

= 2 ohm.m

Rv= 12.8 ohm.m

Rh= 2.3 ohm.m

1

Rh

= +Fsand

Rsand

Fshale

Rshale-h

Rv

= +x xFsand

Rsand

Fshale

= 40%

Fsand

= 60%

Rsand

= 20 ohm.m

Fshale

Rshale-v


10/21


11/21

basin, off the east coast of India, is a deepwater

example of a thin sand-shale turbidite sequence

(above). Reliance Industries experienced initial

success in the area, but evaluating the reservoir

potential in the presence of anisotropy made in

situ hydrocarbon volume difficult to quantify.

Thin beds, by definition, are reservoir layers

that are thinner than the vertical resolution of

the tool. The thicknesses of the sand-shale-silt

sequences of the Krishna-Godavari basin were in

the millimeter range, well below the minimum

1-ft [0.3-m] resolution available from induction

tools, and even less than the 1.2-in. [3-cm]

vertical resolution of porosity devices. Logs

acquired using conventional tools did not provide

enough information to evaluate the anisotropic

zones (above right). Theinterval above X,X65 m,

where cleaner, productive sandstone sections

end, has resistivity values of 1 to 2 ohm.m. With

such low resistivity, hydrocarbon production

would not be expected.

74 Oilfield Review

> Krishna-Godavari basin off the east coast ofIndia. The KG-1 well is located in the KG-DWN-98/3 block. The laminations in this core example(above) are about a millimeter [0.04 in.] thick,typical of the turbidite sequences found in theKrishna-Godavari basin. The minimum verticalresolution for induction tools is 0.3 m. Evaluationand calculation of recoverable hydrocarbon aredifficult because of the low-resistivity, anisotropicnature of the reservoir.

INDIA

PAKISTAN

AFGHANISTAN C H I N A

SRI LANKA

KG-DWN-98/3

> Underestimated reserves. Typical of logs run in the field, the ELANPlus analysis calculateshydrocarbon (Track 5, red) in the sands (Track 6, yellow), but the volumes are low, considering thenet footage. Above X,X65 m the water saturation and hydrocarbon volumes indicate little oil or gaswould be produced. But, this zone is known to be a laminated sand-shale turbidite sequence. Atriaxial induction tool can help determine the degree of anisotropy and the hydrocarbon potential.

X,X45

Depth

m

Sigma

Resistivity

0.2 ohm.m 1000 cu 50

0 gAPI 150

6 in. 16

Sw

EffectivePorosity

X,X50

X,X55

X,X60

X,X65

X,X70

X,X75

X,X80

90-in. Array

Gamma Ray

Caliper

0.2 ohm.m 100

60-in. Array

0.2 ohm.m 100

30-in. Array

60 % 0

Neutron Porosity

60 % 0

Crossplot Porosity

1.65 g/cm3 2.65

Bulk Density

0.2 ohm.m 100

20-in. Array

0.2 ohm.m 100

10-in. Array

Crossover Hydro-carbon

Montmorillonite

Bound Water

Quartz

Gas

Water

100100

50 0%

%%

Lithology

00

Anisotropiczone


12/21

Summer 2008 75

For its KG-1 well, Reliance acquired high-

resolution log suites and OBMI Oil-Base

MicroImager data (below). The OBMI images

revealed thin laminations, corroborated by the

core. A synthetic resistivity log was generated

from the high-resolution OBMI data, which

indicated anisotropy. The AIT resistivity

measurement was 1 to 2 ohm.m. The Rt Scanner

tool was added to the logging program because of

the low AIT resistivity measurements in the

laminated reservoir.

The log data from the Rt Scanner too

indicated a high degree of anisotropy in the

reservoir and provided an accurate measuremen

of sand resistivity. Several promising zones

denoted by an Rv/Rh ratio greater than 5, were

identified as areas for further evaluation. In the

> Logs and core from the KG-1 well. The core at right shows fine laminations, which can be seen on the OBMI image (Track 4). All fiveAIT curves (Track 2) overlay, but the spiky nature of the reconstructed resistivity from the OBMI data (green) indicates laminations. Thisis because the OBMI tool has better vertical resolution. Curves from the density-neutron tools (Track 3) are separated over most of theinterval, indicating high shale content. There are a few places where the density and neutron cross (yellow shading), indicating thepossibility of light oil or gas, but these zones are less than a meter [3 ft] thick. Low resistivity measurements from the AIT tool and littlesand content would result in a pessimistic evaluation of hydrocarbon production in this interval.

in. m

Bit Size Depth

6 16

in.

Caliper

6 16

cu

Formation Sigma

0 50

%

Neutron Porosity

60 0

g/cm3

Bulk Density

OBMI Image

Conductive Resistive

0 360240120

1.65 2.65

gAPI

Gamma Ray

0 150

ohm.m

OBMI Data

Resistivity

0.2 200

ohm.m

90-in. Array

0.2 200

ohm.m

60-in. Array

0.2 200

ohm.m

30-in. Array

0.2 200

ohm.m

20-in. Array

0.2 200

ohm.m

10-in. Array

0.2 200

73

74

75

76

77

78

79

Crossover


13/21

KG-1 well, zones where the Rv/Rh ratio is below 5

lack laminations. Corroboration by core data

validated the Rt Scanner measurement (above).

The ELANPlus advanced multimineral log

analysis identified approximately 8 m [26.2 ft] of

quality reservoir using conventional inter-

pretation techniques. After the triaxial induction

data over the complete logging interval were

incorporated into the analysis, the net-pay

thickness, using 7% porosity and 80% water

saturation for cutoffs, was increased by 35%.

Calculated reserves values were 55.5% higher

than those previously obtained using traditional

logs and petrophysical evaluation programs

(next page).

76 Oilfield Review

> Anisotropy using Rv/Rh ratio. The Rt Scanner service provides an Rv/Rh ratio (Track 1, black) that is above 5 inseveral intervals (red arrow). These zones correspond to laminations in the core (left). In intervals where the Rv/Rhratio is low (black arrow), the core has few or no laminations ( right). Throughout this section, Rh (Track 3, blue)rarely measures above 2 ohm.m, although the Rv (red) and Rsand (black) curves are measuring much higher. The

density-neutron logs (Track 4) indicate hydrocarbon (red shading) below 100 m but do not provide much help inevaluating the reservoir above 100 m. Although the Rhvalues suggest little productive potential, the higher values ofRsand indicate hydrocarbon.

Density-Neutron

%

Neutron Porosity

1.65g/cm3

Bulk Density

2.65

60 0

%

Crossplot Porosity

60 0

Thin beds are

visible in core.

From Rt Scanner

tool, the Rv/Rhratio = 9. This

zone has high

electrical

anisotropy.

No thin beds

are visible in

the core.

The Rv/Rhratio

is low. This zone

has negligible

electrical

anisotropy.

80

90

100

110

120

m

Depth

0

Rv/RhRatio

20

8 in.

Bit Size

18

0 gAPI

Gamma Ray

100

8 in.

Caliper

18

Bad Hole

0 .2 ohm. m

Rsand

200

0 .2 ohm. m

Rv

200

0 .2 ohm. m

Rh

200

0.2 ohm.m

90-in. Array

200

0.2 ohm.m

60-in. Array

200

0.2 ohm.m

30-in. Array

200

0.2 ohm.m

20-in. Array

200

0.2 ohm.m

10-in. Array

Resistivity

200


14/21

Summer 2008 77

> Incorporating Rt Scanner data. The AIT curves (Track 2) are approximately 1 ohm.m with a few 2-ohm.m sections. Rh(Track 3, blue) is equivalent to the AIT 90-in. curve. Rv (red) measures above 10 ohm.m in several intervals. Rsand (black),calculated from the Rt Scanner outputs, is used as an input for water saturation, Sw. Water saturation from the Rt Scanneroutputs (Track 5, red) is lower than the Sw from AIT data (blue). This finding indicates that more hydrocarbon is in thereservoir than originally computed.

0

Rv/RhRatio

m

Depth

30

40

50

60

70

20 0.2 ohm.m

90-in. Array

200

8 in.

Bit Size

18

8 in.

Caliper

18

Bad Hole Density-

Neutron

Montmorillonite

Bound Water

Quartz

Gas

Water

0.2 ohm.m

60-in. Array

200

0.2 ohm.m

30-in. Array

200

0.2 ohm.m

Rsand

200

0.2 ohm.m

Rv

200 60 %

Neutron Porosity

0

60 %

Crossplot Porosity

0

1.65 g/cm3

Bulk Density

2.65

100 %

AIT Sw

0 100 %

Lithology

0

100 %

Rt Scanner Sw

0

0.2 ohm.m

Rh

200

0.2 ohm.m

20-in. Array

200

0.2 ohm.m

10-in. Array

Resistivity

200


15/21

Resolving Anisotropy in West Africa

Interpretation of electrically anisotropic reser-

voirs has been difficult with traditional

petrophysical analysis techniques. Klein et al

were the first to propose a framework for using

graphical crossplots to evaluate these reservoirs.27

The technique was further adapted to incorporate

data from additional logging tools, including

nuclear magnetic resonance (NMR) and triaxial

induction resistivity.28 The original Klein plots

assume a layering of isotropic, macro- and

microporous material, and layering of coarse-

grain and fine-grain sandsa condition that does

not commonly occur in laminated sand-shale

sequences surrounded by anisotropic shales.

Compaction, which typically increases with depth,

has been shown empirically to increase the level

of shale anisotropy (right).

To account for the more-realistic scenario of

anisotropic shales, a modified Klein plot has

been developed that graphically solves for Rv and

Rhwhile adjusting for shale anisotropy.29 Because

anisotropic shales can create false expectationsof low-resistivity pay if not accounted for

properly, NMR data are also used to differentiate

laminated shales from sand-shale sequences.

NMR tools measure free-fluid volume, or porosity,

in the reservoir. Shales usually have high fluid

volumes, but the fluid is bound to the clays that

make up the shales. By incorporating the NMR

porosity, which ignores the fluids in the shales,

log analysts can identify laminated sand-shale

sequences with hydrocarbon potential while

eliminating laminated shale sequences from

the analysis.

The modified Klein plots are similar to

density-neutron crossplots, and an anisotropic

shale point can be graphically determined from

them (below). Because of their characteristic

shape, these modified crossplots are referred to

as butterfly plots. From them, log analysts

graphically choose parameters, perform quality

checks and assess the potential for production

from laminated reservoirs.

Logs from an offshore West Africa well

demonstrate the modified Klein plot technique.30

The addition of NMR data further enhanced the

evaluation. The operator elected to run the

Rt Scanner tool, MR Scanner expert magnetic

78 Oilfield Review

> Klein plots. The traditional Klein plot ( left) does not take shale anisotropy into account. The modified butterfly plot (center) includes shale anisotropy andcan be partitioned into pay and nonpay regions, pivoting at the shale point. The crossplot Rv and Rh data fall into specific regions that can be analyzedquickly (right). The water point (blue circle) indicates 100% water saturation. The shale point indicates 100% shale.

101

Rh, ohm.m

Rv,

ohm.m

101

101

100

101

102

103

100

102

103

101

Rh, ohm.m

Rv,

ohm.m

101

101

100

101

102

103

100

102

103

101

Rh, ohm.m

Rv,

ohm.m

101

101

100

101

102

103

100

102

103

No shale anisotropyWater With shale anisotropy Water

Nonpay

Shale Pay

Water

Fshale Fshale

Rshale-v= 1

Rshale-h= 1

Shale

Rshale-v= 10

Rshale-h= 1

Shale

Rsand Rsand

> Anisotropy in sands and shales. As compaction (red) increasesthetypical case with deeper depositional environmentsthe clay porositydecreases and the shale Rv/Rh ratio increases. Triaxial induction tools alonecannot distinguish between compaction-induced shale anisotropy and thatmeasured in a laminated sand-shale sequence. And, while the NMR tool isbeneficial in identifying zones with movable fluids and differentiatinganisotropic shales from laminated sand-shale sequences, the volume of sandand shale must be determined from other sources, such as the ECS tool.

0

2

4

6

8

1

3

5

7

9

Rv

/R

h

0 10 20 30

Porosity, %

40 50 60

Com

paction


16/21

Summer 2008 79

resonance service, and density-neutron and OBMI

tools. In one zone, the triaxial induction

measurement resulted in an 80% increase in net-

to-gross pay calculation and increased the calcu-

lated net hydrocarbon interval by 15 ft [5 m]

from 23 to 38 ft [7 to 11.6 m] compared with

calculations using conventional logs and traditional

petrophysical techniques (above).

The butterfly plots identified the shale point

and distinguished the anisotropic shales from

anisotropic sand-shale-silt sequences. Based on

their Rv/Rh ratio, nonproductive shale intervals

exhibited anisotropy that was similar to that of

the sand-shale laminated sequences. This case

study demonstrates how NMR data can be used

with triaxial induction data to differentiate

nonproductive shales from potentially productive

sand laminations.

Another West Africa example featured two

very different shale types, and modified Klein

plots differentiated reservoir-quality rock from

shales. Two hydrocarbon-productive interval

27. Klein JD, Martin PR and Allen DF: The Petrophysics ofElectrically Anisotropic Reservoirs, The Log Analyst38,no. 3 (MayJune 2007): 2536.

28. Fanini ON, Kriegshuser BF, Mollison RA, Schn JHand Yu L: Enhanced, Low-Resistivity Pay, ReservoirExploration and Delineation with the Latest

Multicomponent Induction Technology Integrated withNMR, Nuclear, and Borehole Image Measurements,paper SPE 69447, presented at the SPE Latin Americanand Caribbean Petroleum Engineering Conference,Buenos Aires, March 2528, 2001.

29. For more on the use of modified Klein plots: Cao Minh C,Clavaud J-B, Sundararaman P, Froment S, Caroli E,Billon O, Davis G and Fairbairn R: Graphical Analysis ofLaminated Sand-Shale Formations in the Presence ofAnisotropic Shales, World Oil228, no. 9 (September2007): 3744.

30. Cao Minh C, Joao I, Clavaud J-B and Sundararaman P:Formation Evaluation in Thin Sand/Shale Laminations,paper SPE 109848, presented at the SPE AnnualTechnical Conference and Exhibition, Anaheim,California, USA, November 1114, 2007.

This paper is one of a three-part series. See also:

Cao Minh C and Sundararaman P: NMR Petrophysicsin Thin Sand/Shale Laminations, paper SPE 102435,presented at the SPE Annual Technical Conference andExhibition, San Antonio, Texas, September 2427, 2006.

Cao Minh C, Clavaud JB, Sundararaman P, Froment S,Caroli E, Billon O, Davis G and Fairbairn R: GraphicalAnalysis of Laminated Sand-Shale Formations in thePresence of Anisotropic Shales, Transactions of theSPWLA 21st Annual Logging Symposium, Austin, Texas,June 36, 2007, paper MM.

> Modified Klein plot in action. The crossplot of Rv and Rh values is shown in the butterfly plot (right). The log analyst selects thedata points that fall in the hydrocarbon region (magenta), in water-productive regions (blue) and at the shale point (green). Thecolor-coding along the resistivity track (Track 3) of the ELANPlus log corresponds to the data points manually selected by the loganalyst. Points that are not selected (black) are not presented. The water saturation values change (Track 5, yellow shading) whenRsand(red) is used rather than the uniaxial resistivity, Rh (black). The interval above 700 m has significant anisotropy (Track 4, green)but little hydrocarbon. One of the advantages of the modified Klein plots is the ability to quickly identify these nonproductive zones.

101

Rh,ohm.m

Rv,

ohm.m

101

101

100

101

102

103

100

102

103

Fshale0 0.5 1.0

Neutron Density Rh, Rv,Rsand,Rsh Anisotropy

500

Depth,

m

600

700

800

900

1,000

1,100

1,200

1,300

40 30 20 10 100

0 5 10 15

Water Saturation

100 50 0101

102

SwRsandSwRh

Rshale-v= 3.27Rshale-h= 0.51

Shale

Fshale

Rsand


17/21

were separated by a nonproductive shale section,

but a zone with similar characteristics had

production potential (below). Triaxial induction

data were instrumental in properly evaluating

the well. In the upper interval, the sand count

increased by 54% and the net-to-gross ratio by

70% compared with values obtained with

conventional techniques. In the lower interval,

the increase was not as pronounced because the

sands were not as heavily laminated. Still, the

net-to-gross ratio was approximately 20% greater

after incorporating the triaxial induction data

(next page, top left). The nonproductive

anisotropic shale was identified and eliminated

from further analysis. The MR Scanner tool

provided an independent verification of net

footage of hydrocarbon.

80 Oilfield Review

> Variable shale anisotropy. These examples are from intervals with twodifferent shale types that were logged with Rt Scanner, density-neutron,OBMI and MR Scanner tools. The NMR tool and the density-neutron toolswere used as sand-shale indicators (Track 1). Anisotropy is present, asindicated by the separation between Rv and Rh (Track 3) and the Rv/Rh ratiocurve (Track 4, green shading). Rh ranges from 1 to 2 ohm.m, whereas Rsand(Track 7, red) is consistently greater than 10 ohm.m in the upper interval.Because higher resistivity corresponds to greater hydrocarbon volume,

the calculated hydrocarbon (HC) volume (Track 9) is greater when calculatedusing Rsand (red) than uniaxial induction resistivity (black). In the upper log,the anisotropy values (Track 4, green) from X,680 to X,720 look similar tothose from Y,760 to Y,820 in the lower log. Although there is high anisotropy inboth intervals, it is the result of anisotropic shales in the lower log, nothydrocarbon. The butterfly plots quickly isolate and identify thesenonproductive zones from the pay zone (magenta) as shown on theELANPlus plots.

PhisandPhisandNMR Rv ,Rh Anisotropy

OBMIGR

T2Fsand

FsandNMRRt Scanner Rsand

NMR Rsand NMR Fluids HC Volume

PayZones

X,700

X,740

Depth,

m

Depth,

m

X,660

X,620

0.5 10 0.4 0.2 0 0 0 0 0 0 0 0.2 0.4 0 0.2 0.410 1000.5 11 0 1 00 1 ,0 005 10 1510 100

40m

Shale

Cutoff

Sand

Oil

OBM

Water

NMR Fluids

0 0.2 0.4

Oil

OBM

Water

PhisandPhisandNMR NeutronDensity

NeutronDensity

Rv ,Rh Anisotropy

OBMIGR

T2Fsand

FsandNMR

Rt Scanner RsandNMR Rsand HC Volume

PayZones

PayZones

Y,850

Y,900

Y,800

Y,750

0.5 10 0.4 0.2 0 0 0 0 0 0 0 0.2 0.410 1000.5 11 0 1 00 1 ,0 005 10 1510 100

10m

Shale

Cutoff

Sand

Rt ScannerData

AIT DataNMR Data

Rt ScannerDataAIT Data

NMR Data

101

Rh,ohm.m

Rv,

ohm.m

101

101

100

101

102

103

100

102

103

101

Rh,ohm.m

Rv,

ohm.m

101

101

100

101

102

103

100

102

103

Fshale

Rsand


Shale

Fshale


Shale

Rsand


18/21

Summer 2008 81

In the final analysis, hydrocarbon net footage

and net-to-gross ratio were more accurately

quantified from data derived from the

Rt Scanner tool and information from the

MR Scanner service. Compared with traditional

AIT induction results, there were significant

gains in calculated reserves. Modified Klein plots

were also shown to be a powerful quicklook tool

for the log analyst.

Induction DipmeterThe final two case studies demonstrate the utility

of dipmeter data derived from the Rt Scanner

service. Using induction measurements to

provide formation dip is not newthe concept

was first patented in the 1960sbut there had

been no practical application. Triaxial induction

tools provide dipmeter data as a natural by-

product of their standard data processing.

Traditional dipmeter tools are equipped with

several pads that measure small resistivity

changes occurring along the borehole wall.

Software programs correlate similar readings

from adjacent sensors and pads to compute the

dip magnitude and direction of the formation

bedding planes. Data from the sensors on the

pads produce an electrical image of the wellbore

from which structural dip, stratigraphic features

and fractures can be visualized and manually

identified using software applications.Dipmeter tools have a vertical resolution less

than 0.5 in. [1.3 cm], whereas a triaxial induction

tool has a vertical resolution measured in feet.

Although fine details cannot be resolved with the

accuracy of the FMI Fullbore Formation

MicroImager or OBMI and OBMI2 tools, the

Rt Scanner service can provide structural dip.

Dipmeter imaging tools require a conductive

mud system to acquire readings, which are then

converted into images. Because the electrica

insulating properties of oil-base-mud drilling

systems create difficulty in acquiring data

engineers developed solutions, such as the OBM

and the OBMI2 tools, to overcome the problem

Pad contact with the formation is critical

especially when tools are used in oil-base muds.

Hole conditions, such as washouts and

rugosity, make pad contact difficult and degrade

the quality of the measurement. This is true in

both oil-base and water-base muds. Tools logging

in deviated wells can experience floating pads

caused by the weight of the tool collapsing the

caliper arms and preventing the pad from

contacting the borehole wall. In addition

irregular tool motion negatively affects the

quality of the images.

The Rt Scanner tool is insensitive to borehole

conditions such as rugosity and washouts, and i

can log up orwith a modified caliperdown

By contrast, because of the need to push thepads against the borehole wall, dipmeter tools

almost always log in an upward direction. The

exception is drillpipe-conveyed FMI tools run in

horizontal wells.

Conventional dipmeter tools take thei

measurements at a very shallow depth o

investigation, which is the region most affected

by the drilling process (below). A triaxia

> Padless dipmeter. The triaxial induction measurement senses a very large volume (left). The conventional dipmeter tool (right) provides a high-resolutioimage but sees a small electrical diameter. It must also make contact with the borehole wall to acquire usable data.

Dip

Azimuth

Electricaldiamete

r90in

.

Rh

Rv

Rh

Rv

Dip

Azimuth

Interval143 m (top) NMR ToolRt Scanner ToolAIT Tool

Summary of Results

Hydrocarbon (HC), m

Net to gross (NTG)

Net change, HC/NTG

8.2

0.26

12.6

0.44

54%/70%

12.5

Interval163 m (bottom) NMR ToolRt Scanner ToolAIT Tool

Hydrocarbon, m

Net to gross

Net change, HC/NTG

18.0

0.47

20.6

0.57

14%/21%

21.3


19/21

induction tool surveys the region beyond the

near-wellbore and is less affected by the drilling-

induced damage. Induction-derived dipmeter

data are also available from multiple arrays. The

ability to compare dips from different depths of

investigation is useful for quality control,

although variations in the dips may result

from distortions in the bedding planes away from

the wellbore.31

Because the Rt Scanner tool requires no

conductive fluid to acquire data, structural dipcan be obtained in wells where it was difficult or

impossible in the past. Induction-derived

dipmeter data do not replace information from

conventional dipmeter imaging tools, but

complement their measurement, as for example,

when bad borehole conditions degrade the data

acquired with pad contact devices.

The workflow for generating dip information

is part of the data inversion and correction

process. Bed boundaries are defined using

borehole-compensated raw data that have been

corrected for tool rotation. As a first-order

approximation to define bed boundaries, a

second derivative technique produces a squared

log from the induction array (above). The

squared log has sharper boundary edges than

conventional smoothed curves, and the sharp

transition points are used to determine where to

output dip information.

Next, the rotated, borehole-corrected curve

from a single array is output with an initial

estimation of conductivity, bed dip and borehole

azimuth. Typically a 20-ft [6.1-m] window is

inverted, but this depends on how rapidly the dip

is changing. Rv, Rh and bed boundaries are

refined with this inversion step. The software

again solves for dip and azimuth for the best fit

over the entire window. The program then moves

one-half the window length and inverts with a

generous overlap of the previous interval toeliminate edge effects. This process continues

over the entire logged interval. The result is

borehole-corrected, dip-corrected resistivity

along with structural dip and borehole azimuth,

which are presented using conventional tadpoles

and azimuth plots.

Dipmeter in Air and Water

In the USA, an Rt Scanner tool provided

formation dip and direction in an air-drilled

prospect well. Air is used instead of drilling fluid

in formations that react with the drilling mud or

in hard-rock areas where conventional drilling

techniques are less effective. Because there is no

liquid in the wellbore, conventional dipmeter

tools do not workincluding the OBMI tool.

For the well in question, two intervals with

very different characteristics are shown (next

page). The zone from X,X00 to X,X50 ft has

consistent 15 dip oriented to the south-

southeast with little variation. Although difficult

to see, there are three independent measure-

ments from three depths of investigation

presented. Throughout the interval, the tadpoles

from all three measurements overlay, indicating

agreement among the different datasets.

In a deeper interval, the data show very high-

angle formation dips, which corroborated the

geologists interpretation and expectations. Such

high-angle dipsapproaching 70might be

considered questionable were it not for core data

from nearby wells showing similar charac-teristics. An unconformity can clearly be

identified on the log at Y,Y40 ft. Also, despite

considerable hole rugosity in the Y,Y00 to Y,Y50

interval, the dipmeter data are available; a pad

contact tool may have been affected by the

condition of the borehole.

In a second example, the operator, drilling

with water-base mud, ran the Rt Scanner tool in a

deepwater Gulf of Mexico exploration well. The

FMI tool was run for comparison. The well was

deviated 60, and the true formation dip,

corrected for well deviation, was approximately

30. A comparison of the data derived from FMI

measurements and data from the Rt Scanner tool

82 Oilfield Review

31. Amer A and Cao Minh C: Integrating Multi-Depths ofInvestigation Dip Data for Improved Structural Analysis,Offshore West Africa, presented at the OffshoreAsia Conference and Exhibition, Kuala Lumpur,January 1618, 2007.

> Steps in the process, induction to dipmeter. Dipmeter information from the triaxial induction tool is an automatic output of the processing used for dipcorrection and calculating Rv (red) and Rh (blue). In block intervals, the raw data (Track 1) are corrected for borehole effects and then inverted. Bedboundaries are identified from square logs (black curve), which are the result of a second derivative technique, output to show the bed boundaries. The dipis calculated where resistivity changes are apparent. Homogeneous, isotropic intervals produce no dips because there are no step changes of resistivityin the interval. After each section is fully processed, succeeding intervals are computed with a 25% overlap to eliminate bed-boundary effects.

300

200

100

Depth

0500 0 0 10 100 1,000500

R-signal, mS/m Resistivity, ohm.m

1,000 1,500 500 0 0 10 100 1,000500

R-signal, mS/m Resistivity, ohm.m

1,000 1,500 0 10 100 1,000

Resistivity, ohm.m

25% overlap

xx

xy

xz

yx

yy

yz

zx

zy

zz

Square log

xx

xy

xz

yx

yy

yz

zx

zy

zz

Square log

Rh

Rv

Rh

Rv

Rh

Rv


20/21


21/21

shows excellent agreement (above). A low-resistivity laminated pay section, present in this

well, could easily be overlooked using

conventional methods. Incorporating the triaxial

resistivity data in the logging suite identified the

potentially productive zones.

Future Developments

Although many enhancements have been added to

induction logging tools since the first commercial

tool was introduced more than 50 years ago, the

basic theory of the measurement has changed

little. Advancements in computer simulations and

modeling have greatly improved the industrys

understanding of the measurement. The triaxial

induction measurement of the Rt Scanner toolbrings new information to the petrophysicist, such

as dip-corrected resistivity, laminated-reservoir

properties and induction-derived dipmeter data,

as discussed in this article.

This advanced technology has opened new

possibilities and presented new needs to the

industry. Development of fast inversion routines

applied at the wellsite would provide more

accurate resistivity measurements for calcu-

lating water saturation in real time. This

additional information would improve the ability

to make informed decisions, such as in

identifying optimum locations for measuring

pressure and taking fluid samples. Also,

laminated sand-shale sequences that may have

potential as hydrocarbon reservoirs could be

identified more quickly and reliably.

Potential application has been shown for

incorporating seismic data with induction

measurements.32Although the concept is promis-

ing, it remains unclear whether multiple deep

imaging of formations can be extended to resolveseismic structures from surface-acquired data.

Commercial processing of triaxial data is

currently limited to 1D inversion and includes

the assumption that invasion does not impact the

measurement. By using 2D and 3D inversion, the

invasion effects can be determined, including the

dip of the invasion.33 This is a nontrivial task;

currently it takes a week to process 100 ft [30.5 m]

of data on a high-end PC compared with half a

minute for 1D inversion. Commercial imple-

mentation will require time and innovation

both in the processing software and in hard-

ware configurations.

Resistivity is the oldest wireline logging

measurement, but interest has been renewed in

this technology because of the triaxial induction

tool. This advance presents exciting possibilities

for petrophysical evaluation and the potential to

locate and produce previously bypassed pay. TS

> Gulf of Mexico example. This high-angle Gulf of Mexico well had 30 dip and thinly laminated sands (Track 9). The induction-derived dipmeter data(Track 8, green) show excellent agreement with the FMI data (red) in both direction and magnitude of dip. This zone includes a low-resistivity pay intervalfrom X,820 to Y,000. The conventional resistivity data used to compute water saturation indicate little hydrocarbon content (Track 6, green). Using thetriaxial induction data to compute water saturation (Track 7, green) yields considerably more oil volume.

X,750

Depth

ft

Shale

Lithology

X,800

X,850

X,900

X,950

Y,000

Y,050

Y,100

Fsand

Gamma Ray

gAPI

ft3/ft3 1.51.5

Bound Water

% 050 deg

Rt Scanner Dip

QualityFMI Image

900

Bound Water

% 050

Bulk Density

g/cm3 2.651.65

Neutron Porosity

% 060

Sand Laminated Sw

Clay-Bound Water Clay-Bound Water

ELANPlus SwRh

ohm.m 2000.2

Rv

ohm.m 2000.2

90-in. Array

ohm.m 2000.2 Water

% 050

Water

% 050

Total Porosity

% 050

Total Porosity

AIT Saturation Rt Scanner

Saturation

% 050

Quality

deg

FMI Dip

Quality

900

Quality

32. Amer and Cao Minh, reference 31.

33. Abubakar A, Habashy TM, Druskin V, Davydycheva S,Wang H, Barber T and Knizhnerman L: A Three-Dimensional Parametric Inversion of Multi-ComponentMulti-Spacing Induction Logging Data, ExtendedAbstracts, SEG International Exposition and 74th AnnualMeeting, Denver (October 1015, 2004): 616619.

Date post:	20-Feb-2018
Category:	Documents
Upload:	carlos
View:	223 times
Download:	0 times

05 Triaxial Induction

Documents