Advanced Modeling of Permeability Changes During CO ... · at the lowest abandonment pressure possible, and at a rate slow enough that reservoir pressure barely rises. Note: although

Higgs-Palmer Technologies

Advanced Modeling of Permeability Changes During CO2 Sequestration

Final Technical Report

Reporting Period: October 1, 2009 to December 31, 2012

Prepared by:

Ian Palmer and Nigel Higgs Higgs-Palmer Technologies

Albuquerque, NM 87114

March 24, 2013

Performed Under Contract DE-FE0001560

Report Number DOE/FE0001560-6 (Task 5)

HIGGS-PALMER Technologies, LLC

10140 Arroyo Crest Drive NW

Albuquerque, NM 87114

Prepared for:

Advanced Resources International, Inc.

Houston, Texas 77043

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DISCLAIMERS

This report was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. The Principal Investigators agreed to undertake this research on a best effort basis. Neither Higgs-Palmer Technologies and the Principal Investigators, nor any of their employees, make any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed or represents that its use would not infringe privately owned rights. Meaningful information on interpretation of lab stress/strain data, and prediction of coal failure and permeability changes in lab and field has been funded by Coal-Seq, but the new Palmer-Higgs (P-H) model equations remain proprietary to BP America.

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ABSTRACT

Coal-Seq III is a DOE sponsored public-private consortium with the goal to evaluate the technical feasibility of utilizing CO2 sequestration to enhance methane production in deep coal and tight shales. The consortium is sponsored by the U.S. Department of Energy (DOE) with research performed by Advanced Resources International (ARI) in partnership with Higgs-Palmer Technologies, Southern Illinois University (SIU), and Oklahoma State University (OSU). The objective of the work conducted by Higgs-Palmer Technologies is to advance modeling techniques for permeability changes of coal and shale during CO2 sequestration. Using a combination of field and laboratory data, relationships between geomechanical factors influencing coal failure and permeability are assessed. This research aims to develop robust simulation modules that model coal weakening by the adsorption of CO2 and permeability changes induced by CO2 injection. The first objective of this work is to study changes in the mechanical properties (weakening/failure) for coal samples from various U.S. basins under lab-based, high-pressure CO2 injection and depletion experiments. Laboratory experiments include the investigation of coal shrinkage during production and injection induced swelling under field replicated conditions. Quantitative relationships guided by previous geomechanical formulations of permeability change models are devised among various coal parameters using this data. Based on the laboratory and theoretical results, three new geochemical and geo-mechanical modules are developed to be incorporated into an advanced, coupled simulation model. These modules address: (1) coal weakening/failure and associated permeability changes due to changes in mechanical properties and from dilatancy associated with failure, (2) anisotropy of coal cleats, and (3) prediction of strain change associated with matrix swelling when no lab data are available. The accuracy of these modules are to be benchmarked and calibrated with data from large-scale field studies, such as the DOE sponsored CO2 injection demonstration within the San Juan basin’s Fruitland coal. The end result will be improved simulation tools informed by Coal-Seq laboratory efforts and tuned with field injection data.

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TABLE OF CONTENTS

DISCLAIMERS ................................................................................................................................ II

ABSTRACT .................................................................................................................................... III

EXECUTIVE SUMMARY ................................................................................................................. V

LIST(S) OF GRAPHICAL MATERIALS........................................................................................ VII

1.0 INTRODUCTION ....................................................................................................................... 1

2.0 WEAKENING OR FAILURE OF COAL BY CO2 ADSORPTION ............................................ 2

2.1 Background ................................................................................................................................... 2

2.2 General Behavior of Coal near Failure ......................................................................................... 8

2.3 New Model for Predicting Stress and Permeability changes in Coals .........................................22

3.0 PERMEABILITY CHANGES IN COAL DUE TO CO2 INJECTION ........................................ 34

3.1 Failure Associated with CO2 Injection into Depleted CBM Wells ..............................................34

3.2 Permeability Changes from Depletion to CO2 Injection ..............................................................42

3.3 How Permeability Changes Depend on Abandonment Pressure .................................................49

3.4 Model Rate of CO2 Injection into a Depleted CBM Reservoir ....................................................54

3.5 Regression Equations ...................................................................................................................62

4.0 CONCLUSIONS ...................................................................................................................... 71

5.0 ACKNOWLEDGEMENTS....................................................................................................... 73

6.0 NOMENCLATURE .................................................................................................................. 74

7.0 REFERENCES ........................................................................................................................ 75

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EXECUTIVE SUMMARY

This report reflects the predictive modeling work conducted in support of the Coal-Seq III Consortium’s effort to advance the science of CO2 sequestration in coal seam and gas shale reservoirs. An integral component of this research effort is to evaluate the technical feasibility of CO2 sequestration in deep coals and gas-bearing shale reservoirs. To best model CO2 injection in coal reservoirs, a comprehensive understanding of the effects of CO2 induced coal weakening and failure has on changes in permeability is necessary. However, models that can simulate CO2 sequestration currently lack a well-developed set of modules that account for these changes. Here, Higgs-Palmer improve the predictive capabilities of models by using empirically derived data to develop new modules for simulation of coal weakening by CO2 adsorption and the permeability changes induced by CO2 injection. The first objective of this report evaluates the effect of coal weakening on coal permeability in San Juan Basin coals. Causes for weakening include reservoir stress changes that occur by matrix swelling and pore-pressure changes from CO2 injection. These poro-elastic effects are essential components of the geomechanics used to model permeability changes against coal weakening. Quantitative relationships guided by previous geomechanical formulations of permeability change models are developed to assess reservoir changes and inform model development. These include: (1) coal permeability and the change in coal mechanical properties, (2) coal failure onset and coal rank, and (3) permeability change at/beyond failure, all as functions of coal rank, in-situ stress, and ash content.

A simulation module was formulated by Higgs-Palmer applying these relationships to model CO2 injection related weakening and permeability changes in coal. This research integrates three major components associated with CO2 injection in coals, including: 1) coal weakening (failure) and the associated permeability modification due to a change in mechanical properties and dilatancy associated with failure, 2) anisotropy of coal cleats, and 3) prediction of strain change associated with matrix swelling when no lab data are available. The model was benchmarked and calibrated against laboratory measurements of compressibility and permeability changes with CO2 injection, generated from efforts by Southern Illinois University during Tasks 2 and 3 of the Coal-Seq Consortium (and reported separately).

Key results from this work include:

The benchmarked model formulated here successfully matches an exponential permeability increase up to failure based on single-well, San Juan basin history matches. However, permeability changes after failure are less certain as post-failure behavior appears to vary by well, warranting further reservoir surveillance and laboratory investigation.

A general flattening behavior is observed of the exponential permeability increase with depletion. The flattening has been interpreted as a loss of permeability due to fines creation and movement, and would amount to a reduction of injectivity if CO2 were injected into the coal at a pressure below this failure pressure.

Some permeability increase after failure would indicate that matrix shrinkage has resumed, but it appears to occur under different circumstances. The modeling after

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failure is important in being able to better forecast long term gas rates and ultimate recovery in San Juan CBM wells.

If cleat porosity is greater than 0.5%, there appears to be no appreciable permeability increase with depletion. To model the permeability increase ratios derived here from 16 to 170, a cleat porosity less than 0.2% is required.

CO2 induced failure of coals is likely in a few cases. Shear failure of San Juan Basin coal in a depleted CBM reservoir should not happen during the injection of CO2. However, it might occur prior to CO2 injection if the reservoir is depleted to very low pressure (< 200 psi).

Tensile failure should occur if during CO2 injection the reservoir pressure reaches a pressure capable of lifting the overburden, and this would create horizontal cracks along bedding planes. This would also increase CO2 injectivity, unless the tensile failure created huge amounts of coal fines that moved and plugged the fractures.

When CO2 fill-up replaces methane at a low depletion pressure (200 psi in this work), the coal porosity and permeability are seriously reduced due to additional matrix swelling that exceeds the effect of pressure-induced cleat inflation (cleat inflation is suppressed by the anisotropic properties of coal). The amount of reduction is greater when the initial coal porosity is less. Although our model assumes instantaneous replacement of methane by CO2, we expect a slower replacement to lead to the same results and conclusions.

A cleat anisotropy factor (g ≈ 0.2), plus very small initial cleat porosity, are the main reasons why CO2 injectivity is predicted to be difficult in the San Juan basin (i.e., why CO2 permeability falls so quickly with pressure increase after injection). The exact same reasons are why strong permeability increases with depletion are observed in the San Juan basin.

This work provides a strategy for matrix injection of CO2 in depleted coalbed reservoirs.

To maintain better sweep unaffected by fracture stimulation at the wellbore, the ideal strategy is to inject CO2 at the lowest abandonment pressure possible, and at a rate slow enough that reservoir pressure barely rises. Note: although this is based on San Juan Basin coals where initial cleat porosity is < 0.3%, the strategy still applies (but not so strictly) for higher initial cleat porosities (which are a bit unlikely based on typical cleat spacing and aperture width).

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LIST(S) OF GRAPHICAL MATERIALS

LIST OF TABLES

Table 1: Parameters from Single-Well Matching of Permeability Increase Data Prior to Coal Failure in San Juan Basin...................................................................................... 20

Table 2: Cleat Intensity in San Juan Coals (Close and Mavor, 1991).......................................... 28

Table 3: Various ways to Infer UCS of Coal in Northern San Juan Basin. T. ............................... 29

Table 4: Four Stages of the Modeling in this Study ....................................................................... 35

Table 5: Input Parameters for CH4 Depletion. ............................................................................... 36

Table 6: Input Parameters for CO2 Injection.................................................................................. 38

Table 7: Four Stages for the Modeling in this Study ..................................................................... 43

Table 8: Input Parameters for CH4 Depletion. ............................................................................... 44

Table 9: Input Parameters for CO2 Injection.................................................................................. 45

Table 10: Results of Well Test Interpretation (Mavor and Gunter, 2004). ..................................... 51

Table 11: Input Parameters for P-H Model. ................................................................................... 51

Table 12: Four Stages for the Modeling in this Study ................................................................... 55

Table 13: All Results for a Cavity-Completed Vertical well (S = -3) which include Coal Failure at 225 psi Reservoir Pressure. ......................................................................... 63

Table 14: Skin Factors S at CO2 Injection.. ................................................................................... 65

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LIST OF FIGURES

Figure 1: The Fairway (Sweetspot) in San Juan Basin in Pink-Shaded Area. ................................ 2

Figure 2: Gas Permeability Kg (Blue Dots) Derived from PDA Calculation. ................................... 4

Figure 3: Kg Match (Green) to PDA Result (Blue) achieved by Single-Well Simulation ................. 5

Figure 4: Absolute Pressure-Dependent Permeability (PdP) Function Used as Model Input for History Match, Versus Reservoir Pressure........................................................ 6

Figure 5: Gridblock Perm-Ratio and Pressure from a Different Well Example ............................... 7

Figure 6: Rock Failure varying from Brittle to Ductile, Depending on the Confining Stress ............ 9

Figure 7: Typical Failure of Coal during Triaxial Test, which lies between Brittle and Ductile .............................................................................................................................. 9

Figure 8: Brittle Failure in Brown Coal in Unconfined State (Viete and Ranjith, 2006) ................. 10

Figure 9: Brittle Failure after Triaxial Testing (Viete and Ranjith, 2006) ....................................... 11

Figure 10: Permeability Changes vs. Reservoir Pressure in One Well in the San Juan Fairway (Okotie and Moore, 2010) ................................................................................ 12

Figure 11: Shear Dilation Concept, Resulting in a Permeability Increase (Chipperfield et al, 2007) ......................................................................................................................... 13

Figure 12: Permeability Increase in Coal due to Dilatancy depends on Initial Perm (TerraTek, 1996) ............................................................................................................ 13

Figure 13: Triaxial Test of more Ductile Brown Coal being flooded by CO2 Gas (Viete and Ranjith, 2006) ................................................................................................................. 14

Figure 14: Net Permeability change from Before to After Failure, as Measured by Triaxial Tests (Viete and Ranjith, 2006) ..................................................................................... 14

Figure 15: Spectrum of Fines Produced during a Cavity Completion Test in a Block of Coal in the Lab (TerraTek, 1996) ................................................................................... 15

Figure 16: Face Cleats in Coal, which can be plugged by Fines Creation and Movement as a Result of Coal Failure (Courtesy of TerraTek) ....................................................... 16

Figure 17: Absolute Permeability Increase with Depletion from Figure 4 versus Reservoir Pressure. ........................................................................................................................ 17

Figure 18: Clarkson and McGovern (2003) Fairway Data Averaged over a Group of Six Wells in San Juan Basin are shown by Red Squares. .................................................. 18

Figure 19: Values of Initial Cleat Porosity obtained by P-M Matches of Permeability Increases in Fairway Wells. ........................................................................................... 19

Figure 20: Pressure-Dependent Permeability Function (red curve) at Wellbore. Failure Pressure is ~280 psi ...................................................................................................... 19

Figure 21: Geomechanical Components of Cleat Porosity changing during Depletion (Courtesy of Nigel Higgs) ............................................................................................... 23

Figure 22: P-M Summary of Cleat Porosity change, Cleat Permeability change, and Horizontal Stress change during Depletion (Palmer, 2009) .......................................... 23

Figure 23: General Equations for a Transversely-Isotropic Material (Courtesy of Nigel Higgs) ............................................................................................................................. 24

Figure 24: Shear Failure Predicted in a Lab Test of Coal during Methane Depletion, using the new P-H Model ........................................................................................................ 26

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Figure 25: How UCS depends on Coal Rank (Adapted from Jones et al, 1988) .......................... 27

Figure 26: Cleat Intensity (Cleats per Inch) versus Coal Rank. .................................................... 28

Figure 27: Shear Failure Predicted in a Coal Reservoir during Methane Depletion, for Sh = SH = 0.66 psi/ft and UCS = 500 psi, using the new P-H Model Equations ................ 30

Figure 28: Shear Failure Predicted in a Coal Reservoir during Methane Depletion for Sh = SH = 0.70 psi/ft and UCS = 500 psi ............................................................................ 30

Figure 29: Shear Failure Predicted in a Coal Reservoir during Methane Depletion for Sh = SH = 0.66 psi/ft and UCS = 300 psi. ........................................................................... 31

Figure 30: Shear Failure Predicted in a Coal Reservoir during Methane Depletion for Sh = 0.66 psi/ft, SH = 0.70 psi/ft, and UCS = 500 psi. ........................................................ 31

Figure 31: Shear Failure Predicted in a Coal Reservoir during Methane Depletion for Sh = 0.66 psi/ft, SH = 0.75 psi/ft, and UCS = 500 psi. ........................................................ 32

Figure 32: The Depletion Stress Path for CH4 using the Stress Equations from the new P-H model ...................................................................................................................... 37

Figure 33: Shear Failure of Coal during CO2 injection, abandonment pressure 200 psi. ............. 39

Figure 34: Shear Failure of Coal during CO2 injection, abandonment pressure = 25 psi. ........... 40

Figure 35: Shear Failure of Coal during CO2 injection, abandonment pressure = 400 psi.. ......... 40

Figure 36: Shear Failure of Coal during CO2 injection, abandonment pressure = 800 psi. .......... 41

Figure 37: Shear Failure of Coal during CO2 injection, abandonment pressure =1,400 psi.. ................................................................................................................................. 41

Figure 38: Permeability changes for Depletion of Methane-Filled Reservoir starting from Po = 1,500 psi (Red Curve on left). ............................................................................... 44

Figure 39: Permeability changes for Depletion of Methane-filled Reservoir starting from Po = 1500 psi (red curve on left), followed by fill-up and Injection of CO2 starting from Pdep = 200 psi (blue curve below) ........................................................................ 46

Figure 40: Permeability Changes with Pressure (relative to starting perm at that pressure) for Depletion of Methane-filled Reservoir starting from Po = 1,500 psi (red curve on left), followed by fill-up and Injection of CO2 starting from Pdep = 200 psi (blue curve on left). ........................................................................................................ 46

Figure 41: Permeability Changes versus Reservoir Pressure induced by CO2 Injection started at 200 psi Reservoir Pressure (after Methane Depletion from Initial Reservoir Pressure of 1,500 psi). .................................................................................. 48

Figure 42: Permeability Changes versus Reservoir Pressure Induced by CO2 Injection, starting from Different Abandonment Pressures (after Methane Depletion from Initial Reservoir Pressure of 1500 psi).. ......................................................................... 50

Figure 43: Permeability Profiles from Mavor and Gunter (2004). .................................................. 52

Figure 44: Permeability Profiles from the P-H Model .................................................................... 53

Figure 45: Plotted is Permeability change K/Ko Representing CH4 Permeability change Relative to Initial CH4 Permeability (Blue Curve), and Separately CO2 Permeability change Relative to Initial CO2 Permeability after CO2 fillup (Green Curve). ........................................................................................................................... 57

Figure 46: Exponential Permeability Increase with Depletion for Po = 1,500 psi and ϕo = 0.1% (Predicted by P-H Model using Anisotropic Mechanical Parameters shown by Inset). ............................................................................................................. 58

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Figure 47: CO2 Injection Rate versus Differential Wellbore Pressure for Different Abandonment Pressures: ϕo = 0.1% and S = -3. .......................................................... 59

Figure 48: Exponential Permeability increase with Depletion for Po = 1,500 psi and ϕo = 0.2%. .............................................................................................................................. 60

Figure 49: CO2 Injection Rate versus Wellbore Pressure for Different Abandonment Pressures: ϕo = 0.2% and S = -3. .................................................................................. 60

Figure 50: Exponential Permeability Increase with Depletion for Po = 1,500 psi and ϕo = 0.3% ............................................................................................................................... 61

Figure 51: CO2 Injection Rate versus Wellbore Pressure for Different Abandonment Pressures: ϕo = 0.3% and S = -3. .................................................................................. 61

Figure 52: Geometry for Vertical Well with Cavity Completion. .................................................... 64

Figure 53: Permeability Change Due to CH4 depletion: Shi-Durucan Model with Anisotropy in both Swelling and Mechanical Properties. ............................................... 67

Figure 54: Permeability Change Due to CO2 Injection: Shi-Durucan Model with Anisotropy in both Swelling and Mechanical Properties. ............................................... 68

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1.0 Introduction Coal-Seq III is a 3-year public-private consortium primarily sponsored by the U.S. Department of Energy (DOE) and performed by Advanced Resources International (ARI) in partnership with Southern Illinois University (SIU), Oklahoma State University (OSU), and Higgs-Palmer Technologies. The consortium has a primary objective to advance scientifically-based simulation capabilities for CO2 storage in coalbed methane and gas shale reservoirs in the presence of multi-component gases and other fluids in order to improve how current simulation tools model the effects of high pressure CO2 on the integrity and swelling/shrinkage of the coal matrix and its permeability as well as proper algorithms for the adsorptive capability of wet coals. To accomplish this goal, coal samples from various U.S. basins are being used in the laboratory to study the potential existence of a change in mechanical properties for the coal (weakening/failure) under high-pressure CO2 injection and depletion. Laboratory experiments also include the investigation of coal shrinkage (during production) and swelling (during injection) under field replicated conditions. In addition; new improved adsorption models are being developed to realistically simulate sequestration in wet coal and gas shale reservoirs. Based on the laboratory and theoretical results, three new geochemical and geo-mechanical modules will be developed. Finally, the feasibility of storing CO2 in shale reservoirs will be studied using actual datasets, leveraging the basic science work developed by this effort. To do so, the Coal-Seq III Consortium work will calibrate the accuracy of these modules with data from large-scale field studies, such as the DOE sponsored CO2 injection demonstration within the San Juan basin’s Fruitland coal, and incorporate these modules into an advanced, coupled simulation model. The end result will be improved tools that are informed by Coal-Seq laboratory efforts and that have been tuned with field injection data. This report will describe the efforts to date in meeting research goals in two areas or predictive modeling. They are: 1) weakening or failure of coal by CO2 adsorption and 2) permeability changes in coal due to CO2 injection.


2.0 Weakening or Failure of Coal by CO2 Adsorption

2.1 Background

This work was jointly supported by BP America and the USDOE-NETL funded Coal-Seq Consortium. The work on behalf of BP is summarized in Moore et al (2011). It serves as an introduction to field data from coalbed methane (CBM) wells which include (1) permeability increase with primary depletion, and (2) change of permeability trend at low reservoir pressure due to coal failure. These are important elements of coalbed behavior that are complementary to lab measurements, which also provide a truth case upon which to develop theory and models. The wells studied in this paper are located in the Colorado portion of the fairway (Figure 1), and the data has been generously provided by BP America in support of Coal-Seq. The Fruitland coals in the fairway are well-cleated, with cleat spacing typically less than 1 cm. Cleat porosity of coal refers to the porosity of the natural fractures (cleats) in coal. This is distinguished from the porosity of the matrix. While the matrix porosity is responsible for diffusive transport of gas molecules from matrix into cleats, the cleat porosity is responsible for Darcy flow to the well. In commercial CBM projects, Darcy flow generally governs the gas flowrate, and matrix porosity has little influence. Relative to other producing areas of the San Juan basin, the fairway has high permeability. It is characterized by wells with high rates of production, high cumulative recoveries, a rapid de-watering signature, and produced gas with high CO2 and low BTU content. The total coalbed thickness in the fairway is relatively high, on the order of 70-100 ft, compared to 30-60 ft in other parts of the basin.

Figure 1: The Fairway (Sweetspot) in San Juan Basin in Pink-Shaded Area. The Wells Studied in this Area are in the Colorado Portion of the Fairway. The Log Section Shows the Thickness and

Distribution of the Coal Seams Typical of the Fairway


Cleat permeability changes with reservoir depletion. The pressure-dependent permeability property of the Fruitland Coal is well documented. Absolute permeability increases when reservoir pressure decreases (Palmer and Mansoori, 1998; Palmer et al., 2007; Gierhart et al., 2007; Clarkson et al., 2008; Palmer et al 2011). The permeability increase is caused by shrinkage of the coal matrix when methane and other gases are extracted, resulting in an increase in the width of the coal cleat apertures. The ultimate magnitude of permeability increase determined by direct measurement (Gierhart et al., 2007) and through performance history matching can be 10-100 times the original permeability. In addition, the de-watering of the reservoir at this late stage of reservoir life is almost complete. The low residual water saturation in the cleats has increased the effective permeability to gas to near the absolute permeability.

Working against these positive trends is an apparent failure of the coal associated with the declining reservoir pressure (Palmer et al., 2005; Okotie and Moore, 2010). This would be shear failure, not tensile, since the pore pressure is decreasing. Coal is a weak rock, and failure is accompanied by fines creation. If the fines move, they may plug the cleats and reduce reservoir permeability. The coal type found in the fairway is generally weak, and this characteristic helped to make cavity completions successful (Palmer et al., 1993; Palmer and Cameron, 2003).

Finding the pressure-permeability relationship from field data

The objective here was to determine how permeability changes with declining reservoir pressure using field production data. Once the permeability-pressure relationship was independently established, the P-M model could then be tested in how well it matched the field data. The six wells selected for this test were chosen because of their maturity, or high degree of pressure depletion, and their close proximity to two monitor wells which provided accurate reservoir pressures.

The field production data used in the analysis were historical daily gas rate, flowing wellhead pressure, and reservoir pressure from the monitor wells. We calculated gas permeability (Kg) as a function of time and reservoir pressure depletion using the production data analysis (PDA) method (Clarkson et al, 2007). The PDA included the conversion of flowing wellhead pressure to flowing bottomhole pressure using a vertical lift correlation. Gas permeability was calculated using the following equation:

(1)

The results of the PDA revealed for all wells a steady exponential increase in gas permeability during the early de-watering phase of production, and especially after water production has virtually ceased. This inclining trend is then followed by a sudden drop in permeability when reservoir pressure falls below 250 – 300 psi, which occurred in this part of the field in 1996-97 (Figure 2). After the drop in permeability, for the example of Figure 2, Kg flattens.

)]()([1003.7

]75.0/[ln4

wfR

gweg

gpmpmhx

DqsrrTqk


Figure 2: Gas Permeability Kg (Blue Dots) Derived from PDA Calculation. A Sudden Drop in Kg Occurs at a Reservoir Pressure (Yellow Curve) of about 250 psi.

The second step in the history match process was to match the PDA-derived Kg trend with a numerical simulator. The simulation work was planned to be done in two parts: first, each well’s history was matched by a single-well model, and secondly the group of wells were to be matched by a multi-well model to better account for well interference. Only the first part is reported here; the second part is pending a modification to the simulator software needed to complete this portion of the study.


Figure 3: Kg Match (Green) to PDA Result (Blue) achieved by Single-Well Simulation. The Gas Rate (Red) is also shown against the Left-Hand Scale (Units of Mcfd)

We performed the history match in the single-well models with gas rate and reservoir pressure (from the monitor wells) as the control parameters. Initial permeability and the shape of the pressure-dependent permeability curve were adjusted to achieve a match of both the flowing bottomhole pressure history and the Kg trend from the PDA calculation. The Kg match for the data of Figure 2 is shown in Figure 3.


Figure 4: Absolute Pressure-Dependent Permeability (PdP) Function Used as Model Input for History Match, Versus Reservoir Pressure (Initial Reservoir Pressure was 1450 psi). This Function

is applied at every Gridblock

To obtain this match, we used the pressure-dependent permeability (PdP) relationship shown in Figure 4 for this example well. Note that this is absolute permeability, after Kg has been adjusted to absolute permeability by accounting for gas-water relative permeability. The relationship depicted in Figure 4 is unique to this well. PdP relationships used to match the other wells in the study differed somewhat from this example. However, what are common to all matches are (1) the exponentially increasing trend prior to the drop, and (2) the presence of the drop itself at a reservoir pressure ranging from around 250 psi to 300 psi. Following the drop, some wells had the increasing trend shown in Figure 4, while others demonstrated either flat or slightly declining trends. The slope of the curve after the drop was very sensitive to the original controlling conditions of the single-well models, primarily the OGIP used in the model initialization. We expect that the PdP trend after the drop will be better resolved by the multi-well model.

Figure 5 shows two cross-section views from a different example, representing a snapshot of the reservoir conditions for a well around the time and pressure of the permeability drop. The slide on the left shows the absolute permeability ratio, K/K0, for each gridblock. The slide on the right shows the gridblock pressures on the same date. The gridblocks in region A, penetrated by the wellbore, are at a pressure of 240 psi, which is below the pressure (250 psi in this case) of the permeability drop. Therefore gridblocks in region A reflect the situation after the permeability drop, and the permeability increase ratios are in the range of 60:1. However, gridblocks in region B have a pressure of 251 psi, slightly above the permeability drop pressure (250 psi), and


are therefore at the maximum permeability increase ratio of 120:1. Gridblocks in region C have pressures near 300 psi and a permeability increase ratio of 100:1. This sequential perm-drop behavior is what we think actually happens at every point in the reservoir following coal failure.

The absolute permeability at any point in the reservoir at a given time will depend on the reservoir pressure at that same point (i.e. not the average reservoir pressure). The region closest to the well is at the lowest pressure and will therefore be further along the permeability-pressure relationship (see Figure 4) than the region, say, 1,500 ft away from the well. The permeability drop first occurs in the near-wellbore region and then radiates out from the wellbore, with time and pressure depletion, until it reaches the well’s drainage area boundary.

Figure 5: Gridblock Perm-Ratio (Left Panel) and Pressure (Right Panel) from a Different Well Example

Summary • Successful history matching of the pressure-dependent permeability relationship in

CBM wells can be improved by first doing production data analysis (PDA).

• From pressure build-up measurements in the field and history matches of production data, permeability initially increases exponentially with reservoir depletion.

• An interruption of exponential permeability increase is attributed to coal failure at low reservoir pressure, and a drop in cleat permeability may be due to fines plugging.

• Based on single-well history matches, permeability after failure is less certain and appears to vary from well-to-well, warranting further reservoir surveillance and laboratory investigation. Some permeability increases after failure would indicate that matrix shrinkage has resumed, but under different circumstances.

• The modeling after failure is important in being able to better forecast long term gas rates and EUR in CBM wells, which can be profitable for decades after coal failure.

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Pressure - Fracture (psi) 1997-10-01 I layer: 14

SO UTE GU NN#1

-3,000 -2,000 -1,000 0 1,000 2,000 3,000 4,000

-3,000 -2,000 -1,000 0 1,000 2,000 3,000 4,000

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34

46

58

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PermRatio 1997-10-01 I layer: 14

A AB B

C C


2.2 General Behavior of Coal near Failure

The failure of coal during depletion of CBM wells is a rare opportunity to find out what happens in the field to coal permeability during and after coal failure. It is an analog to coal failure during CO2 injection, in the sense that the effect of coal failure on permeability should be the same in the same coal. And this permeability change may be critical to the injectivity of CO2 and other greenhouse gases. The findings are significant to this project, particularly because we are the first to investigate this failure phenomenon in the field, as far as we know. However the findings will also be of interest to operators within Coal-Seq in that they relate to the forecasting of rates and reserves in late-life CBM wells. From Figures 6-9, and other information, we can generalize the behavior of rock (coal) failure as follows:

• SJB coals are expected to be more brittle than ductile (like Mannville coal at ~3000 ft)

• Shear failure occurs at peak of stress/strain curve, when stress increase starts to slow (called stress relief)

• But some yielding is expected before actual shear failure (see bending of stress/strain curve before the peak)

• The yielding implies a reduction of E (Youngs modulus) and an increase of v (Poissons ratio)

• This yielding and failure is also manifested by a permeability increase before actual failure in TerraTek curves, even under high stress (see later)


Figure 6: Rock Failure varying from Brittle to Ductile, Depending on the Confining Stress

Figure 7: Typical Failure of Coal during Triaxial Test, which lies between Brittle and Ductile


Figure 8: Brittle Failure in Brown Coal in Unconfined State (Viete and Ranjith, 2006)

From plots like Figures 7 and 8, we can summarize changes in mechanical properties during/after coal failure (Martin, 2010):

• We typically see an increase in Poisson’s ratio as the rock approaches failure – coal can be highly variable though.

• In some cases for competent coal, modulus and Poisson’s ratio are nearly unchanged just before failure.

• In “softer” coals there is more softening with significant decreases in modulus and with corresponding increases in Poisson’s ratio approaching 0.5. Note: Poisson’s ratio for coal is typically very high to start with: often 0.3-0.4.

We will return to this subject later, when we model permeability changes that occur when coal fails in the field.


Figure 9: Brittle Failure after Triaxial Testing (Viete and Ranjith, 2006)

General behavior of permeability near coal failure Our first purpose is to see if coal failure onset can be detected in gas production data, and there is evidence that it can (Figure 10 and Moore et al, 2011). Our second purpose is to predict whether coal failure can occur during CO2 injection (see later).


Figure 10: Permeability Changes vs. Reservoir Pressure in One Well in the San Juan Fairway (Okotie and Moore, 2010). Coal Failure is inferred to occur at ~320 psi, when Coal Permeability

Starts to Decrease

The literature reveals there are two opposing permeability effects that can occur near failure:

Permeability can increase due to dilatancy (brittle failure) Permeability can decrease due to changes of mechanical properties (E and v), or

due to fines creation, movement, and plugging. Which one wins will depend partly on the rank of the coal, as illustrated below. Dilatancy applies to any brittle rock, and commercial CBM coals are a semi-brittle rock. We expect a permeability increase due to dilatancy (see Figure 11). For coal, shearbox tests in Figure 12 reveal quite large permeability increases, depending on the normal stress acting to resist shearing, and on the related initial permeability of the coal. The permeability can start to increase well before shear failure, and the total permeability rise up to shear failure varies from 60-600 times the initial perm. But what happens after failure? Although Figure 12 offers no information, Figure 13 does. With this more ductile brown coal, there is a dilatant permeability increase at shear failure, but it declines quickly as shearing continues. This lies in contrast to hard rock, where the permeability continues to increase with continued shearing (Barton et al, 1985). Because coal is a softer rock, evidently the dilatancy is reduced due to changes in mechanical properties or to fines creation and plugging. With semi-brittle coal (e.g., San Juan basin), we would expect the dilatant permeability increase to be larger, and last longer, but it still may only be temporary.

SOUTHERN UTE TRIBAL OO #1

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Reservoir Pressure, Psi

Eff

ecti

ve P

erm

eab

ilit

y t

o G

as, m

d

Kg from PDA, Clarkson et al (2007) Permeability Function (PdP) From History Match

The declining permeability trend

is interpreted to be caused by

progressive coal failure beginning

near the well and extending out

into the reservoir.

Maximum Kg is reached prior to

coal failure at ~ 320 psi.

Kg is less than absolute

permeability in early time due to

relative permeability effects

Inclining permeability trend

follows that predicted by

Palmer-Mansoori model.

This group of points not honored by model.

They may be an indication of large, immediate

reduction in k followed by a rebound.

Well001SOUTHERN UTE TRIBAL OO #1

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into the reservoir.












Well001


Figure 11: Shear Dilation Concept, Resulting in a Permeability Increase (Chipperfield et al, 2007)

Figure 12: Permeability Increase in Coal due to Dilatancy depends on Initial Perm, but varies from 60-600 times Initial Permeability in these Lab Experiments (TerraTek, 1996)


Figure 13: Triaxial Test of more Ductile Brown Coal being flooded by CO2 Gas (Viete and Ranjith, 2006). A Dilatant Permeability Increase occurs at Shear Failure, but declines quickly due to Over-

Shearing

Figure 14: Net Permeability change from Before to After Failure, as Measured by Triaxial Tests (Viete and Ranjith, 2006). Brown Coal and Mudstone Reveal a Net Loss of Permeability

Original perm retained after failure

0.1

1.0

10.0

100.0

1000.0

Brown coal Mudstone Sandy shale Fine grained SS Med-grained SS

Perm

aft

er

fail

ure

/ i

nit

ial

perm


We have looked at triaxial tests, and made a comparison between soft brown coal and hard rock (see Figure 14), and the conclusions appear to be:

• Commercial CBM plays are mostly semi-brittle coals (more brittle than soft brown coal)

• We expect commercial CBM coals to exhibit larger permeability increases associated with dilatancy than in brown coal, but not as much as hard rock.

• We expect commercial CBM coals to retain after failure more of the enhanced permeability than brown coal, but less than hard rock.

• It is not clear that coal failure due to depletion in commercial CBM coals will permanently enhance permeability like it does in hard rock (eg, one reason for the success of shale gas well stimulations). We have looked to the field for an answer, and it appears that permeability flattens or decreases after failure occurs at low reservoir pressure (Okotie and Moore, 2010; Moore et al, 2011).

• Thus it is also unclear that any failure induced by CO2 injection will increase injectivity…..it may reduce it instead.

Second, when rock fails, we might expect some permeability decrease due to fines creation, movement, and plugging, especially in a soft rock such as coal. In fact, when coal fails there is a large spread of particle size distribution (Figure 15), and the ability to plug an equally widespread distribution of cleat apertures... It is easy to envisage coal fines plugging cleats that are only hairline in width (Figure 16). This could induce a rapid drop in permeability, due to a sudden flurry of fines created by semi-brittle failure.

Figure 15: Spectrum of Fines Produced during a Cavity Completion Test in a Block of Coal in the Lab (TerraTek, 1996)


Figure 16: Face Cleats in Coal, which can be plugged by Fines Creation and Movement as a Result of Coal Failure (Courtesy of TerraTek)

Palmer-Mansoori model match of the pressure-dependent permeability function

With this improved understanding of coal failure mechanisms, we return to matching of the derived permeability-pressure relationship of Figure 4 using the Palmer-Mansoori (P-M) model (Palmer, 2009). The permeability drop in Figure 4 is associated with coal failure, and will be discussed more below. The P-M model is matched to the permeability increase of Figure 17, using the parameters listed within that figure. Note that the initial cleat porosity is 0.13%, and the matrix shrinkage parameter combination, ePe, is 9. The other P-M parameters are g = 0.2, f = 0.8, E = 300,000 psi, and v = 0.4. We have settled on these values of g and f based on successfully matching many such CBM wells (over 20) in the San Juan basin. Prior to coal failure, we also consistently use E = 300,000 psi, and a v value close to 0.4 (ranging from 0.3 – 0.4). Note: in the matrix shrinkage parameter, e is the strain at infinite pressure, and Pe is the Langmuir pressure for the strain curve (definitions are the same as for a Langmuir isotherm curve). Four other wells located offset to the one in Figure 3 have been history-matched in the same manner. In addition, a group of six other wells in the fairway has been analyzed by Clarkson and McGovern (2003), with their average permeability increase with depletion is indicated in Figure 18. Unfortunately, the original permeability values in this data set are relative to the permeability at 600 psi reservoir pressure, not the permeability at the initial reservoir pressure of 1,450 psi. This means the set of data points can be arbitrarily shifted up or down (Palmer, 2009). Our interpretation is that the points are elevated as shown in Figure 18, and we have matched the data using the same g, f, E, and v constraints that we used in the match of Figure 17. The maximum point-by-point error in all the P-M matches listed above is < 17%, except for one case


where it is 33%, and the average error is much less, which suggests these are all good matches by the P-M model to the field data.

We now summarize all these single-well matches, keeping in mind that these results may change when we undergo multi-well history matching. The data set includes five wells that we have analyzed, and an “average” of six wells analyzed by Clarkson and McGovern. The range of matrix shrinkage factors deduced from all the P-M matches is ePe = 9-10. This is quite consistent with a lab-measured value of 8 (Levine, 1993), but higher than a theoretical prediction of 4 (Clarkson et al, 2008). Initial cleat porosity lies in the range 0.055 – 0.17%, as displayed in Figure 19, and agrees with independent values from history matching of water rates: 0.04 – 0.14% (lower limits from Clarkson et al, 2008). The permeability increase ratio, defined by the permeability just before the permeability drop over the permeability at initial reservoir pressure, varies from 16-170. These permeability increases are in accord with previous measurements in the field by pressure buildup tests (Gierhart et al, 2007). The permeability increases with depletion are enormous, and have no precedent in the oil and gas industry as far as we know. It is remarkable how sensitive the permeability increase is to the initial cleat porosity (Palmer et al, 2011). First, if porosity is > 0.5%, there is no appreciable permeability increase with depletion. Second, the permeability increase ratios that are observed require a cleat porosity < 0.2%. For a fixed change of porosity, a lower initial porosity will induce a larger change in permeability, because k α ϕ3.

Figure 17: Absolute Permeability Increase with Depletion from Figure 4 versus Reservoir Pressure. The Red Line is from the History Match, while the Blue Line is a Good Match by the P-M Model. Matching Parameters for the Permeability Increase before the Permeability Drop are listed

within the Plot Area.

1

10

100

0 200 400 600 800 1000 1200 1400

k/k

o

P (psi)

Gridblock pressure-dependent permeability function

Pre-failure: ϕo = 0.13%, g = 0.2, ePe = 9, E = 300,000, v = 0.4, f = 0.8, Po = 1470

Well history match

P-M match

Initial perms: BM = 6.9 md, P-M = 6.6 md


Figure 18: Clarkson and McGovern (2003) Fairway Data Averaged over a Group of Six Wells in San Juan Basin are shown by Red Squares. A Good Match to this Data is shown by the Blue Line.

Matching Parameters are listed within the Plot Area

There are a couple of implications. First, the initial coal permeabilities in the Colorado portion of the fairway appear to lie mostly in the range of 3-12 md. However, the initial cleat porosities are 0.055 - 0.17%. Substantial permeabilities coupled with very low porosities are a signature of naturally-fractured formations (Nelson, 1985), which makes sense because gas and water flow in coal is governed by natural fractures in the form of cleats and larger joints. Second, in many wells north-east of the fairway, the permeability increases with depletion are in fact similar to that seen in the fairway wells. In several of these wells, matches by the P-M model gave matching parameters quite consistent with Figures 17, 18, and 19. This argues that coal cleat porosities north-east of the fairway are also less than roughly 0.3%.


Figure 19: Values of Initial Cleat Porosity obtained by P-M Matches of Permeability Increases in Fairway Wells. The Porosity Range is 0.055 – 0.17%. The Pink Bar is the 6-Well Average from Clarkson and McGovern (2003), and the Blue Bars are the 5-Well Spread of the Study Wells

Figure 20: Pressure-Dependent Permeability Function (red curve) at Wellbore. Failure Pressure is ~280 psi. Blue Curve is Match by P-M Model


Interpreting the pressure-dependent permeability function From Figure 20, elements of the gridblock permeability function are:

• Exponential permeability increase with depletion up to coal failure • Sudden drop of permeability at failure • Resumption of exponential increase of permeability with depletion after failure

We now briefly discuss each of these. Exponential permeability increase with depletion up to coal failure: In more than 20 wells, both in the fairway and north-east of the fairway, we have matched permeability increases with depletion by the P-M model using parameter ranges in Table 1. In general the parameter ranges are supported by independent data. The matches overall are very good. Note that since doing this work we have updated the P-M model to a model called P-H (see later), which rigorously incorporates coal anisotropy in mechanical properties and cleat orientation. This does alter the matching parameters of Table 1, but not in a major way (e.g., cleat porosity from P-H modeling is greater than P-M by


another way: there is a potential permeability increase due to dilatancy, accompanied by a potential permeability decrease due to fines creation, movement, and plugging. The latter appears to win when failure occurs due to depletion in San Juan basin coals. Permeability changes with depletion after failure: After failure, we have found a wide range of permeability slopes – from increasing to flat to decreasing. A flattening or decreasing of the permeability ratio has been interpreted as a loss of permeability due to fines creation and movement (Moore et al, 2011). New data from lab tests support this contention (Duan et al, 2011). In the case of an increasing trend of the permeability ratio after failure, this is thought to indicate that matrix shrinkage has resumed, but under different circumstances. In such cases, Poisson’s Ratio, v, appears to be a controlling factor, while Young's modulus, E, has less effect. Such behavior can be matched by a v that increases up to 0.5 (starting from a range of 0.3 - 0.4), and a range of E which is generally lower than the pre-failure value of 300,000 psi. Note that v = 0.5 corresponds to a perfectly plastic material, i.e., an increase in vertical strain leads to the same increase in lateral strain. Caveat: the P-M model is not strictly applicable after failure, when non-elastic conditions exist. However, if we define E and v to be “effective” parameters, we can justify using P-M to predict future permeability trends.

Summary

• The Palmer-Mansoori (P-M) model is successful in matching an exponential permeability increase up to failure. Initial cleat porosities are in the range of 0.055 – 0.17%, which agrees with independent values from history matching of water rates.

• If cleat porosity is > 0.5%, there is no appreciable permeability increase with depletion. To model the permeability increase ratios that we have derived requires a cleat porosity < 0.2%.

• The range of matrix shrinkage factors deduced from all the P-M matches is ePe = 9-10. This is quite consistent with a lab-measured value of 8 and other recent lab measurements.

• In many wells north-east of the fairway, the permeability increases with depletion are similar to those seen in fairway wells. This argues that coal cleat porosities north-east of the fairway are also less than roughly 0.3%.

• Since doing this work we have updated the P-M model to a model called P-H (see later), which rigorously incorporates coal anisotropy in mechanical properties and cleat orientation. This does alter the matching parameters we obtained by using the P-M model, but not in a major way (eg, cleat porosity from P-H modeling is greater than from P-M modeling by


rates and EUR in CBM wells, which can be profitable for decades after coal failure.

2.3 New Model for Predicting Stress and Permeability changes in Coals

This portion of the work presents a new analysis of the fundamental geomechanics equations for transversely isotropic coal (i.e., cleat anisotropy when cleats are vertical, as they are in the San Juan basin). This includes matching of lab stress/strain data to derive geomechanics parameters for the new P-H model, which replaces the old Palmer-Mansoori (P-M) model. We also predict failure pressure in lab tests by the new Palmer-Higgs model, in addition to wells in the San Juan basin. The Palmer-Mansoori (P-M) model was revised in 2007 (Palmer et al, 2007) to include cleat anisotropy when the cleats were largely vertical, as appears to be the case in the San Juan basin. The cleat anisotropy manifested as the g-factor in the compaction term, which acted to suppress the permeability loss expected during depletion. A value for g of about 0.2 appeared to match the San Juan permeability increase data (Palmer, 2009 and Moore et al, 2011). A significant extension to the P-M model has been made by BP America, by including transversely-isotropic mechanical properties in a geomechanics analysis. The result, called the Palmer-Higgs (P-H) model, retains the low g-factor as before, but now implements two different Young’s moduli, and three different Poisson’s Ratios, all of which are needed to fully characterize these properties with respect to direction in a coal core.

P-M model The contributions to cleat porosity change when a coalbed is depleted are identified in Figure 21.The first term is the usual Poisson’s ratio effect, where vertical cleats are compressed by an increase in the vertical effective stress, and the matchsticks thicken as a result (i.e., cleat porosity decreases). This is the normal compaction term. The second term is called the poroelastic effect, and as pore pressure falls, the coal matrix (matchsticks) expands, which reduces the cleat porosity. So, the first two terms act to decrease the cleat porosity. The third term is the matrix shrinkage effect, where the matrix shrinks as gas desorbs, resulting in a cleat porosity increase. Note that the f-factor in the first term is normally expected to lie in the range of 0-1. This represents a measure (estimate) of the volume strain of the solid material associated with the increase in vertical effective stress. In sandstones, f ≈ 0.5 from finite element modeling studies, but in coals f should be larger, and empirical fitting of field data has favored larger values with the result that the compaction term is greatly reduced. The final P-M equations are summarized in Figure 22.


Figure 21: Geomechanical Components of Cleat Porosity changing during Depletion (Courtesy of Nigel Higgs)

Figure 22: P-M Summary of Cleat Porosity change, Cleat Permeability change, and Horizontal Stress change during Depletion (Palmer, 2009)

Approach for new P-H model The general equations for a transversely-isotropic coal are given in Figure 23. The complete geomechanical analysis reveals three major changes to the P-M model:

5Higgs-Palmer TechnologiesNigel Higgs, personal communicationCompaction

term

Higgs-Palmer Technologies 7

P-M Model

pp

p

pp

p

M

KppC

i

i

ii

im

i

11

3

iik

k

i

iihih

pp

p

pp

p

v

E

v

E

v

vppSS

)1(3)1(31

21)(

1f

M

K

M

gCm

Pressure-dependent

permeability perm ↓

as depletion ↑ But g


(1) g is defined by Ep/Ez, where Ep (measured normal to the cleats) is less than Ez (measured parallel to the cleats) due to cleat anisotropy (ie, vertical cleats).

(2) an increase in the g/M term of Figure 22. (3) adding the g-factor and three distinct v values to the K/M terms in Figure 22.

Figure 23: General Equations for a Transversely-Isotropic Material (Courtesy of Nigel Higgs)

Rock mechanics parameters from matching lab data Lab tests by SIU (Southern Illinois University) have been done on San Juan core under uniaxial strain conditions (SIU, 2011). These depletion tests, using both methane and helium gases, provide stress and strain versus pressure that can be matched by the new transversely isotropic P-H model to determine a unique and consistent set of elastic parameters:

• Ep = 125,000 psi, g = 0.2, and Ez = 625,000 psi • v_p = 0.192, v_pz = 0.086, v_zp = 0.429

The importance of this derivation, and unique determination of elastic parameters, is: (1) it confirms that coal is indeed a transversely-isotropic material (2) it provides guidelines for the parameters that should be tried when using the P-H

model to predict and match field data of permeability increase with depletion, or of the occurrence of coal failure.

Some of these parameters (eg, g = 0.2) take on values similar to those inferred earlier. For example, the theoretical concept of cleat anisotropy had led to the use of g ~0.2, and suppression of permeability loss in the field due to compaction (Palmer et al, 2007). However, the introduction of three Poisson’s ratios in place of one in the P-M model had not been appreciated.


The bulk rock parameters listed above and a coal strength (failure) envelope are all that is needed to predict when a coal will fail under depletion, which is what is relevant to this project. However, the cleat porosity change part of the P-H model requires another step in the theory to derive it from the bulk rock parameters (confidential to BP America). Also, the perm-change model still comes from K/Ko = ( )3 as shown in Figure 22, and this is a theory-based assumption (based on a uniform network of vertical cleats). The new P-H model has been used to match large permeability increases with depletion seen in lab tests and in the field, but this remains confidential to BP America. However, the task relevant to (and cost-shared with) Coal-Seq was to predict if and when failure would occur in lab tests and in the field, and this is discussed below. Coal failure prediction for lab tests This is based on a rigorous prediction of coal failure with depletion using an in-house (HPT) code called StressPATH. This model estimates when, during reservoir depletion, whole-scale yielding of the reservoir rock away from the wellbore should be expected. The model is based on a stress path calculation, beginning at the in-situ stress, and predicting when/where the stress path intercepts a failure envelope. Two things are integral to this prediction:

(1) An equation for the change in horizontal stresses during depletion to define the stress path (we use the new P-H model for this).

(2) A failure envelope for failure occurrence as a function of shear stress and normal stress. We have used one failure envelope called FEBP that was measured directly on San Juan coal core from north of the fairway, and a second one found by integrating several different failure envelopes in the published literature. The latter is a “universal” coal failure envelope normalized by the unconfined compressive strength UCS, which has to be known (Palmer et al, 2005).

The change in horizontal stress induced by matrix shrinkage during depletion is seen in Figure 22 for the P-M model. In the new P-H model, the stress equation has changed, and some of the inputs have also. For predicting when failure should occur in the lab tests above, we use the unique elastic parameters determined above:

• Ep = 125,000 psi, g = 0.2, and Ez = 625,000 psi • v_p = 0.192, v_pz = 0.086, v_zp = 0.429

Other inputs required are the initial minimum (Sh) and maximum (SH) horizontal stress (psi), the matrix shrinkage parameter (ePe, psi), the initial reservoir pressure (Po, psi), and the unconfined compressive strength (UCS, psi). All these inputs are contained in the inset to Figure 24.


Figure 24: Shear Failure Predicted in a Lab Test of Coal during Methane Depletion, using the new P-H Model. The Elastic Parameters are those given in the Section above. The Depletion Stress Path is shown in Pink, starting from the Initial Pressure of 1,125 psi. The Vertical Axis is a 3D

Form of Shear Stress while the Horizontal is a 3D Form of Normal Stress

Figure 24 reveals the stress path in pink, and its interception of two different failure envelopes: (1) FEBP is the curved line, while (2) the universal coal envelope is the straight line. Our predictions are:

• For the universal failure envelope with 1,075 psi UCS (the best lab measurement in one well north of the fairway), failure is predicted to begin at pressure of 173 psi (this output of the modeling is not shown in Figure 24, although it is implicit. For the curved FEBP, failure does not occur for positive reservoir pressure

• Failure would not occur for higher strength coals (UCS >1,600 psi), using either failure envelope (two lab measurements gave UCS >2,000 psi). This situation is not shown in Figure 24.

In summary, failure is predicted to occur in the lab testing of this report at


been described elsewhere (Moore et al, 2011). The context in that paper included a failure prediction based on the P-M model, which implied UCS values of ~5,000 psi. Here we update the failure prediction using the new P-H model. To start, we assume the rock mechanics parameters derived from the core matching also apply to the field. This assumption is based on no scale up from core size to reservoir size, which would be unusual for coal, and we shall return to this point later. There is uncertainty in a couple of field parameters: (1) UCS and (2) in-situ stresses, and these need to be addressed before making failure predictions.

Figure 25: How UCS depends on Coal Rank (Adapted from Jones et al, 1988)

Uncertainty of UCS: UCS is probably the most uncertain parameter in the failure prediction. UCS depends primarily on coal rank, and secondarily on cleat intensity (cleats/inch). As shown by Figure 25, the coal rank of the fairway is HvA (Meek and Levine, 2006), and this would imply a minimum UCS range of 1,000 – 4,500 psi (minimum UCS should govern failure). However, cleat intensity in San Juan basin coal is high (Table 2), and this can weaken the coal substantially (see Figure 8). For example, core or outcrops of coal with high cleat intensity (>10 cleats per inch) can be broken easily by hand. Therefore in the San Juan basin, and particularly in the fairway, UCS is expected to lie at the low end of the 1,000 – 4,500 psi range. This position is captured in Table 3, which summarizes different ways to infer UCS in San Juan coals.

HVA MVHVA LV

Fairway coals in this range

Carbon content (daf) = 100 – volatile matter (daf)

PR

HVB


Table 2: Cleat Intensity in San Juan Coals (Close and Mavor, 1991). Range of Cleats/Inch = 8-26

Figure 26: Cleat Intensity (Cleats per Inch) versus Coal Rank. The Left Axis is a Measure of the Pulverizability of Coal, which is an Inverse Measure of Coal Strength. Thus the Coal Strength

(UCS) has an Inverse Correlation with Cleat Intensity, as expected from the Physics

The other factor which can affect UCS is scaleup, where a reservoir-scale UCS is expected to be much smaller than a core-scale measurement in the lab. In fact, coal mine experience indicates a reservoir-scale UCS is 3-5 times smaller than a core-scale UCS (Wilson, 1982-1983). This position is also captured in Table 3. When these factors are taken into account, a review of the inferred large-scale UCS for coal in the northern San Juan basin suggests a range of 100-1,000 psi. This is the range of values that we use to predict coal failure during depletion of CBM reservoirs.

Well Av dip angle (º) Av cleat width

(µ)

Av cleat

frequency (/cm)

Hamilton 3 86 60 (10-210) 3

NE Blanco Unit

403

89 20 (10-100) 6

S. Ute Mobil 36-

1

86 60 (10-1,380) 10

Colorado 32-7

No 9

76 50 (10-210) 7

S. Ute Tribal H 89 20 (10-300) 6

S. Ute Tribal J 89 20 (10-70) 5


Table 3: Various ways to Infer UCS of Coal in Northern San Juan Basin. The Wellbore Stability Number is from Palmer et al, 2005. The C4 Seam Number is from an Internal BP Report. The UCS

Values Fall roughly in the Range of 100-1,000 psi and 500 psi is a Reasonable Average.

Uncertainty of in-situ stresses The minimum horizontal stress, Sh, has been measured in coals throughout the San Juan basin (Palmer, 1994). The minimum horizontal stress gradient was measured in the same coals as the wells in this study (the northern part of the fairway, Moore et al, 2011). At the nearby COAL Site measurements gave initial values of Sh = 0.66 - 0.70 psi/ft (McBane, 1991). At depths of ~3,000 ft, we take Sv = 3,000 psi, implying Sh = 1,980 – 2,100 psi, and typical Po = 1,500 psi. However, SH (maximum horizontal stress) has not been measured. The predominant view has been that the present-day stress state in the San Juan basin is either tectonically relaxed (i.e., SH ≈ Sh), or extensional (because of the Rio Grande rift system), but this has been challenged in recent publications (e.g., Lorenz and Cooper, 2003), which suggest that the present-day stress state may not be too different from the N-S to NNE-SSW compression thought to have existed in the geologic past, and responsible for the N-S to NNE-SSW oriented natural fractures found across the basin.

Method Location UCS range (psi) Comment

Coal rank (Jones et al 1988 ) (not scaled up)

Fairway 1000 - 4500 at highest rank of HvA

HvA

Coal rank adjusted for high cleat intensity (IDP)

Fairway 100 - 500 Some coals run

Core from BP well north

of fairway (not scaled up )

North of

fairway

1075 Coal density

~1.75

Wellbore stability SJB ~500

SIU lab measurements (not scaled up)

Mine samples

~2000 SLB and SIU

C4 seam log (weakest segment )

SJB 152 (scaled by 3x) 91 (scaled by 5x)

Already scaled


Figure 27: Shear Failure Predicted in a Coal Reservoir during Methane Depletion, for Sh = SH = 0.66 psi/ft and UCS = 500 psi, using the new P-H Model Equations. The input Parameters are those

given in the Section above. The Depletion Stress path is shown in pink, starting from an initial Pressure of 1500 psi

Figure 28: Shear Failure Predicted in a Coal Reservoir during Methane Depletion for Sh = SH = 0.70 psi/ft and UCS = 500 psi

Figure 27 illustrates the stress path in pink, and its interception of two different failure envelopes: (1) FEBP is the curved line, while (2) the universal coal envelope is the straight line. In this case, failure is predicted to occur at 277 psi for the universal failure


envelope, while no failure occurs for positive pressure for the FEBP envelope. From Figure 28, in comparison with Figure 27, a higher in-situ stress (0.66 to 0.70 psi/ft) reduces the failure pressure from 277 to 34 psi (i.e., failure occurs later). Several other cases have been run, covering the spread in variables, such as UCS, Sh, and SH and these are displayed in the figures below.

Figure 29: Shear Failure Predicted in a Coal Reservoir during Methane Depletion for Sh = SH = 0.66 psi/ft and UCS = 300 psi. A lower UCS (500 to 300 psi) Raises the Failure Pressure from 277 to

385 psi (i.e., failure occurs earlier).

Figure 30: Shear Failure Predicted in a Coal Reservoir during Methane Depletion for Sh = 0.66 psi/ft, SH = 0.70 psi/ft, and UCS = 500 psi. A small increase in SH (0.66 to 0.70 psi/ft) lowers the

failure pressure from 277 to 149 psi (i.e., failure occurs later).


Figure 31: Shear Failure Predicted in a Coal Reservoir during Methane Depletion for Sh = 0.66 psi/ft, SH = 0.75 psi/ft, and UCS = 500 psi. A Larger Increase in SH (0.66 to 0.75 psi/ft) Lowers the

Failure Pressure from 277 to 17 psi (i.e., failure occurs much later).

Here we summarize our predictions, and compare with failure pressures observed in this portion of the fairway: 175 - 275 psi (Moore et al, 2011). We predict no failure using the FEBP failure envelope (which comes from a well in Colorado north of the fairway). But, the universal failure envelope does predict failure as follows:

• For UCS = 500 psi, failure pressure varies from 277 - 34 psi as Sh increases from 0.66 to 0.70 psi/ft (and Sh = Sh). This covers the range of 175 - 275 psi observed in the field.

• For Sh = SH = 0.66 psi/ft, failure pressure varies from 277 – 385 psi for UCS = 500 – 300 psi. This suggests UCS would have to be 500 psi or a bit larger if we assume the minimum of the stress range.

• For UCS = 500 psi and Sh = 0.66 psi/ft, failure pressure varies from 277 – 17 psi as SH increases from 0.66 psi/ft to 0.75 psi/ft. That is, if SH is much greater than Sh, it snuffs out any chance of failure (unless UCS is


In summary, although there is some uncertainty in SH and in the coal strength in the five-well area of study, it appears the P-H model for stress changes can predict the onset of shear failure with depletion which agrees fairly well with the timing of the observed flattening of the exponential permeability increase. This adds validity to the general applicability of the P-H model in CBM plays (beyond just modeling the permeability increase with depletion).

Summary A new P-H model has been developed to describe the transversely-isotropic nature

of coals. This model has been matched to lab data to provide a unique set of elastic parameters. The equations are confidential to BP America.

One set of the new equations can be used to predict when failure will occur during depletion. The predictions of the new P-H model are not inconsistent with the lab data.

The predictions of coal failure in the field by the new P-H model are not inconsistent with observations from this northern portion of the fairway.

At coal failure, the general behavior is a flattening of the exponential permeability increase with depletion. The flattening has been interpreted as a loss of permeability due to fines creation and movement, and would amount to a reduction of injectivity if CO2 were injected into the coal at a pressure below this failure pressure.


3.0 Permeability Changes in Coal due to CO2 Injection

3.1 Failure Associated with CO2 Injection into Depleted CBM Wells

This section of the report utilizes a failure program that enables us to predict whether coal failure will occur if CO2 is injected into a CBM reservoir in a depleted state. The prediction is based upon the new Palmer-Higgs (P-H) model for cleat anisotropy in coal, which should give more realistic results than the P-M (Palmer-Mansoori) model. The P-H model predicts stress changes with CH4 depletion, followed by CO2 injection. In between, we model stress changes when CO2 replaces CH4 in the depleted reservoir. The modeling is geared to San Juan basin coals, although the conclusions should have application to other CBM plays. Again, this part of the project reflects a continuing collaboration with BP America, who has made available the stress changes for anisotropic coal, as well as the strain-pressure Langmuir plots for CH4 and CO2 in core from a San Juan well. HPT have provided the use of the failure prediction program StressPATH.

Method: injection into a depleted CBM reservoir The concept is as follows.

• Start with a San Juan basin CBM reservoir at original reservoir pressure. • Model depletion of CH4 down to a selected abandonment pressure (eg, 200 psi). • Replace all the CH4 by CO2 at this abandonment pressure. • Incrementally raise the static reservoir pressure, by adding CO2 until a new

sorption equilibrium has been established. • At each stage, calculate the changes in the minimum horizontal stress, Sh, due

to (1) pressure change, and (2) matrix shrinkage or swelling of coal. • Predict whether coal fails or not at each stage.

The method we follow references Table 4. We extend the approach and model for predicting coal failure during CH4 production (depletion) to CO2 injection. The model is able to predict in-situ stress changes during depletion or injection of CH4 or CO2. The stress changes are critical to coal failure. They define the stress path, and whether the stress path intercepts a failure envelope, in which case the coal would fail in shear. The stress changes are calculated using the new P-H (Palmer-Higgs) model (unpublished): a model which includes anisotropy in cleats and mechanical properties (eg, cleats that are nominally vertical as in San Juan basin). The study is focused on San Juan basin, because we have a good amount of information on the reservoir and rock parameters. But the general conclusions should be applicable to other coal formations.


Table 4: Four Stages of the Modeling in this Study

There are several approximations that we make:

• We assume pressure and stresses are constant across the reservoir, i.e. these are static calculations and we do not consider temporal changes that lead to pressure that vary with radial distance from the well.

• We assume Shmin = Shmax in all the runs here. • In a depleted CH4 reservoir, we assume CO2 replaces CH4 instantaneously. • This approximation should provide a first estimate for the effects of CO2 injection,

and whether the coal is likely to fail. • At the abandonment pressure we assume the CO2 displaces all of the CH4, so

there is no residual CH4 to deal with. This is justifiable because the matrix swelling of the CO2 injected will dominate that due to any residual CH4. A residual component of CH4 would not alter the conclusions, since both the swelling and pressure increase associated with CO2 injection move the stress path away from the failure envelope.

Results for abandonment pressure of 200 psi Stage 1: CH4 depletion This is based on a rigorous prediction of coal failure with depletion using StressPATH (proprietary to HPT). This model estimates when, during reservoir depletion, whole-scale failure of the reservoir rock away from the wellbore should be expected. The model is based on a stress path calculation, beginning at the in-situ stress, and predicting when/where the stress path intercepts the failure envelope (see Figure 32). Three things are integral to this prediction:

1. Knowledge of the in-situ stress state. Sh (minimum horizontal stress) has been measured in coals throughout the San Juan basin (Palmer, 1994). The minimum horizontal stress gradient was measured in one area of the fairway, at the COAL


Site, where measurements gave initial values of Sh = 0.66 - 0.70 psi/ft (McBane, 1991). At depths of ~3,000 ft, we take Sv = 3,000 psi, implying Sh = 1,980 – 2,100 psi, and typically Po = 1,500 psi. However, SH (maximum horizontal stress) has not been measured, and there is some uncertainty around this (see previous discussion).

2. An equation for the change in horizontal stresses during depletion to define the stress path. We use the new P-H model for this.

3. A failure envelope for when failure occurs as a function of shear stress and normal stress. We have used one determined by integrating several different failure envelopes in the published literature. This is essentially a “universal” coal failure envelope normalized by the unconfined compressive strength, UCS, which has to be known (Palmer et al, 2005). Note that we chose UCS = 500 psi as an input in Table 5, and this comes from Table 3 (500 psi is a reasonable average of the range 100-1,000 psi).

To execute this approach, we start with a CBM reservoir at original reservoir pressure (1,500 psi) at a depth of 3,000 ft. We model depletion of CH4 down to a selected abandonment pressure (i.e., 200 psi). The calculation of horizontal stress change comes from an equation like that in Figure 22. The stress path follows the change in horizontal stress as calculated from the input parameters in Table 5 and the results can be seen in Figure 32.

Table 5: Input Parameters for CH4 Depletion. The Langmuir Parameters for Strain versus Pressure have been corrected for Grain Compressibility (Harpalani, 2010)


Figure 32: The Depletion Stress Path for CH4 is shown in pink, starting from the Initial Reservoir Pressure of 1500 psi, using the Stress Equations from the new P-H model. The Elastic Parameters for CH4 are given in Table 5. For this First Illustrative Case, the Stopping Point of the Stress Path

is shown at an Abandonment Pressure of 200 psi. The Straight Line Represents the Univers

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Advanced Modeling of Permeability Changes During CO ... · at the lowest abandonment pressure possible, and at a rate slow enough that reservoir pressure barely rises. Note: although