# A Probabilistic Assessment Methodology for the

Evaluation of Geologic Carbon Dioxide Storage

By Sean T. Brennan, Robert C. Burruss, Matthew D. Merrill, Philip A. Freeman, and Leslie F. Ruppert

Open

- File Report 2010

– 1127

U.S. Department of the Interior U.S. Geological Surveyii 

### U.S. Department of the Interior

KEN SALAZAR , Secretary

U.S. Geological Survey

Marcia K. McNutt

, Director

U.S. Geological Survey, Reston, Virginia: 2010

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Suggested citation: Brennan, S.T.

, Burruss, R.C., Merrill, M.D., Freeman, P.A., and Ruppert, L.F., 2010 , A p robabilistic a ssessment

m ethodology for the e valuation of g eologic c arbon d ioxide s torage : U.S. Geological Survey Open

- File Report

2010

– 1127

, 3 1 p., available only at http://pubs.usgs.gov/of/2010/1127

.

Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government

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Although this report is in the public domain, permission must be secured from the individual copyright owners to reproduce any copyrighted material contained within this report.iii 

## Contents

1. Introduction

................................................................................................ ............................................................. 1 1.1. Purpose and Scope

................................................................................................ .......................................... 1 1.2. The Legislation

................................................................................................ ................................................. 2

2. Assessment Framework

................................................................................................ ......................................... 4 2.1. Assessment Methodologies

............................................................................................................................. 4

2.2. Model for CO 2 Storage Resources

................................................................................................................... 5

2. 3. Geologic Framework

................................................................................................ ........................................ 7 2.3.1. Storage Assessment Unit (SAU)
– Storage Formation

.............................................................................. 7 2.3.2. Storage Assessment Unit (SAU)
– Seal Formation

................................................................................... 8 3. Storage Resource Calcula tions

.............................................................................................................................. 8 3.1. Storage Formation Pore Volume

...................................................................................................................... 9 3.2. Buoyant Trapping Calculation

........................................................................................................................ 10 3.3. Residual Trapping Calculation

....................................................................................................................... 11 3.4. Technically Accessible Storage Resource

..................................................................................................... 13 3.5. Storage in Oil and Gas Reservoirs

................................................................................................................. 13

3.6. Final Assessment Products

............................................................................................................................ 14 4. Example Storage Resource Calculation

............................................................................................................... 14

4.1. Data Sources

................................................................................................ ................................................. 14 4.2. Example Storage Assessment Unit

................................................................................................................ 15 4.3. Form Inputs

................................................................................................ .................................................... 15

4.4. Results

................................................................................................ ........................................................... 17

5. Conclusions

................................................................................................ .......................................................... 18 Acknowledgments

................................................................................................ ..................................................... 18

References Cited

................................................................................................ ...................................................... 19 Glossary

................................................................................................ ................................................................... 24 Appendix A. Assessment Input Forms

...................................................................................................................... 27 Storage Formation (SF) Assessment Method: Input Data Form

........................................................................... 27 Appendix B. GIS Data Manipulations: Creating the SAU

.......................................................................................... 30 B.1. Required Data Rasters

................................................................................................ .................................. 30 B.2. Creation of Required Data Rasters

................................................................................................................ 30 B.3. Generating SAU Extent and Modification of [DepthTop]

................................................................................ 30 B.4. Isopach Generation and Modification

............................................................................................................ 31



## Figures

1. A resource triangle depicting the relation between buoyant and residual storage resources that schematically illustrates the relation between uncertainties in knowledge of the resource and the relative

volume of the resource.

................................................................................................ ................................ . 6

2. A schematic cross section through a storage assessment unit illustrating the relation between buoyant and residual trapping styles in the storage formation..

.......................................................................................... 7

3. Flow diagram of key steps for calculating buoyant trapping storage resources and residual trapping storage

resources

. ................................................................................................ ...................................................... 9iv 4. Map showing the example of the Tensleep Sandstone storage assessment unit in the Wind River Basin, Wyoming

. ................................................................................................ ..................................................... 16



## Tables

1. S torage resource values of CO 2 for five different classifications within the Tensleep Sandstone storage

assessment unit.

................................................................................................ .......................................... 18

2. Storage resource values of CO 2 for petroleum reservoirs in the Tensleep Sandstone storage ass essment

unit

. ................................................................................................ .............................................................. 18v 

## Conversion Factors

Multiply By To obtain

Length

inch (in.) 2.54 centimeter (cm)

foot (ft) 0.3048 meter (m)

mile (mi) 1.609 kilometer (km)

meter (m) 3.281 foot (ft)

kilometer (km) 0.6214 mile (mi)

Are a

square inch (in 2 ) 6.452 square centimeter (cm 2 )

square foot (ft 2 ) 0.09290 square meter (m 2 )

acre 0.4047 hectare (ha)

acre 0.004047 square kilometer (km 2 )

square meter (m 2 ) 0.0002471 acre

Volume

gallon (gal) 3.785 liter (L)

barrel (bbl), (petr oleum, 1 barrel=42 gal) 0.1590 cubic meter (m 3 )

cubic foot (ft 3 ) 0.02832 cubic meter (m 3 )

1,000 cubic feet (MCF) 28.32 cubic meter (m 3 )

liter (L) 0.2642 gallon (gal)

cubic meter (m 3 ) 6.290 barrel (petroleum, 1 barrel = 42 gal)

Mass

pound, avoirdup ois (lb) 0.4536 kilogram (kg)

ton, short (2,000 lb) 0.9072 megagram (Mg)

ton, long (2,240 lb) 1.016 megagram (Mg)

milligram (mg) 0.00003527 ounce, avoirdupois (oz)

gram (g) 0.03527 ounce, avoirdupois (oz)

kilogram (kg) 2.205 pound avoirdupois (lb)

megagram (Mg) = 1 metric ton (t) (1,000 kg) 1.102 ton, short (2,000 lb)

megagram (Mg) 0.9842 ton, long (2,240 lb)

million metric tons 1.102 million short tons

Pressure

atmosphere, standard (atm) 101.3 kilopascal (kPa)

bar 100 kilopascal (kPa)

poun d

- force per square inch (lbf/in 2 or psi) 6.895 kilopascal (kPa)

kilopascal (kPa) 0.009869 atmosphere, standard (atm)vi Multiply By To obtain

kilopascal (kPa) 0.01 bar

kilopascal (kPa)

kilopascal (kPa)

megapascal (MPa) 0.2961

0.1450

145 inch of mercury at 60°F (in Hg)

pound

- force per square inch ( lbf/in 2 )

2 ) pound

- force per square inch (lbf/in

Pressure gradient

pound

- force per square inch per foot (lb/in 2 /ft or psi/ft) 22.62 kilopascal per meter (kPa/m)

Density

pound per cubic foot (lb/ft 3 )

pound per cubic foot (lb/ft 3 )

kilogram per cubic meter (kg/m 3 )

3 ) gram per cubic centimeter (g/cm 16.02

0.01602

0.06242

62.4220 3 ) kilogram per cubic meter (kg/m

3 ) gram per cubic centimeter (g/cm

pound per cubic foot (lb/ft 3 )

pound per cubic foot (lb/ft 3 )

Electric power

megawatt electrical (MWe) 3,600,000,000 joule per hour (J/hr)

Hydraulic conduct i vity

meters per second (m/s) 3.281 foot per second (ft/s)

Hydraulic diffusivity

square meter per second (m 2 /s) 10.76 square foot per second (ft 2 /s)
Temperature in degrees Celsius (°C) may be converted to degrees Fahrenheit (°F) as follows:
°F=(1.8×°C)+32 Temperature in degrees Fahrenheit (°F) may be converted to degrees Celsius (°C) as follows:
°C=(°F

– 32)/1.8 Concentrations of chemical constituents in water are given in parts per million (ppm). and milligrams per liter (mg/L)

.

## Abbreviations, Acronyms, and Symbols

A SF area of the storage formation

AU assessment unit (NOGA)

bbl petroleum barrel or barrels

B PV buoyant trapping pore volume; see glossary

B SE buoyant trapping storage e fficiency ; see glossary

B SR buoyant trapping storage resource ; see glossary

B SV buoyant trapping storage volume; see glossary

BOE barrel s of oil equivalent; see glossary

CO 2 carbon dioxide

D Darcy
DOE U.S. Department of Energy

EISA Energy Independence and Security Act

EPA U.S. Environmental Protection Agency

FVF formation volume factor

FVFs formation volume factors

FVF GAS formation volume factor for gas

FVF OIL formation volume factor for oil and natural gas liquids

GIS geographic information system

GOR gas: oil ratio ; see glossary

k permeability ; see glossary

KR known recovery production volumes; see glossary

KR GAS known recovery production volumes of gas

KR NGL known recovery production volumes of natural gas liquids

KR OIL known recovery production volumes o f oil

KR RES known recovery production volumes converted to volumes at reservoir conditions

KRR SR known recovery replacement storage resource ; see glossary

mD millidarcy

MMbbl million barrels

MMBOE million barrels of oil equivalent

mst million short tons

Mt million metric tons

NOGA National Oil and Gas Assessment ; see glossary

ppm parts per million psi pounds per square inch

R PV residual trapping pore volume ; see glossary

R SE residual trapping storage efficiency; see glossary

R SR residual trapping storage r esource; see glossary

R SV residual trapping storage volume; see glossary

R1 PV residual trapping class 1 pore volume

R1 SE residual trapping class 1 storage efficiency

R1 SR residual trapping class 1 storage resource

R1 SV residual trapping class 1 storage vol ume R2 PV residual trapping class 2 pore volume

R2 SE residual trapping class 2 storage efficiency

R2 SR residual trapping class 2 storage resource

viiviii R2 SV residual trapping class 2 storage volume

R3 PV residual trapping class 3 pore volume

R3 SE residual trapping class 3 storage efficiency

R3 SR residual trapping class 3 storage resource

R3 SV residual trapping class 3 storage volume

SAU storage assessment unit ; see glossary
SAUs storage assessment units

SF s torage formation ; see glossary

SF PV storage formation pore volume ; see glossary

TA SR technically accessible storage resource ; see glossary

TA SV technically accessible storage volume ; see glossary

TDS total dissolved solids ; see glossary

T PI thickness of the porous interval ; see glossary

USGS U.S. Geological Surve y

**ρ** CO 2 density of carbon dioxide **φ** porosity ; see glossary **φ** PI porosity of the porous interval

# A Probabilistic Assessment Methodology for Evaluation

of Geologic Carbon Dioxide Storage

By Sean T. Brennan, Robert C. Burruss, Matthew D. Merrill, Philip A. Freeman, and Leslie F. Ruppert



## 1. Introduction

1.1. Purpose and Scope

In 2007, the Energy Independence and Security Act (Public Law 110–140) authorized the U.S. Geological Survey (USGS) to conduct a national assessment of potential geologic storage resources for carbon dioxide (CO 2 ) in cooperation with the U.S. Environmental Protection Agency (EPA) and the U.S. Department of Energy (DOE). The first year of that activity was specified for development of a methodology to estimate storage potential that coul d be applied uniformly to geologic formations across

the United States. After its release, the methodology was to receive public comment and external expert review. An initial methodology was developed and published in March 2009 (Burruss and others, 2009), and public comments were received . The report was then sent to a panel of experts for external review. The external review report was received by the USGS in December 2009. This report is in response to those external comments and reviews and describes how the previous assessment methodology (Burruss and others, 2009) was revised. The resource that is assessed is the technically accessible storage resource , which is defined as the mass of CO 2 that can be stored in the pore volume of a storage formation. The methodology that is presented in this report is intended to

be used for assessments at scales ranging from regional to subbasinal in which storage assessment units

are defined on the basis of common geologic and hydrologic characteristics. The methodology does not apply to site- specific evaluation of storage resources or capacity (see section 1.2). Calculations of subsurface pore volume for potential CO 2 storage have been described in a number of publications (Bachu, 2003 ; Bradshaw, 2004; Bachu and others, 2007; U.S. Department of Energy, National Energy Technology Laboratory, 2008; van der Meer and Egberts, 2008). The methodology in this report is

different in that it uses fully probabilistic methods to incorporate geologic uncertainty in calculations o f storage potential. Oil and gas assessments conducted by the USGS evaluate the resource that is estimated to be technically recoverable using current and projected technologies. These assessments are fractions of the

total in

- place resource that may be r ecoverable with technological advances or unforeseen changes in economic factors. Similarly, this assessment methodology for CO 2 storage resources focuses on the technically accessible resource, not a total in

- place resource volume. The technically accessible storage
resource is one that may be available using present -day geological and engineering knowledge and technology for CO 2 injection into geologic formations. The methodology is not an economic assessment, nor does it incorporate engineering constrain ts in the estimation of the volume of the resource. However, the methodology does take into account the U.S. Environmental Protection Agency (2008) proposed limit of 10,000 ppm (parts per million; mg/L (milligrams per liter)) total dissolved2 solids (TDS) f or injection of CO 2 into storage formations. Potential storage formations with salinities less than 10,000 ppm ( mg/L ) TDS will not be assessed using this methodology. The methodology described in this report is for estimating the storage resource of an in dividual storage assessment unit , and it is designed as a guide for geologists to follow in the USGS national geologic CO 2 storage assessment. During the course of the assessment we will develop additional methods to combine, or aggregate, resources of mul tiple storage assessment units within a basin and multiple regions and develop statistical algorithms that can address dependencies. The reporting of aggregated resource values ensures that policymakers and the public have access to information about

CO 2 s torage resources for the Nation at a variety of scales.



### 1.2. The Legislation

Section 711 of the Energy Independence and Security Act ( Public Law 110–140) ( hereafter

referred to as “EISA” ) specifies these requirements for the methodology:



### SEC. 711. CARBON DIOXIDE SEQUESTRATION CAPACITY ASSESSMENT.

(a) D EFINITIONS

.— In this section

— (1) A SSESSMENT

.— The term ‘‘assessment’’ means the national assessment of onshore capacity for carbon dioxide completed under subsection (f).

(2) C APACITY

.— The term ‘‘capacity’’ means the por tion of a sequestration formation that can retain

carbon dioxide in accordance with the requirements (including physical, geological, and economic requirements) established under the methodology developed under subsection (b).

(3) E NGINEERED HAZARD

.— The term ‘‘engineered hazard’’ includes the location and completion history of any well that could affect potential sequestration.

(4) R ISK .—The term ‘‘risk’’ includes any risk posed by geomechanical, geochemical, hydrogeological, structural, and engineered hazards.

(5) S ECRETARY

.— The term ‘‘Secretary’’ means the Secretary of the Interior, acting through the

Director of the United States Geological Survey.

(6) S EQUESTRATION FORMATION

.— The term ‘‘sequestration formation’’ means a deep saline formation, unmineable coal seam, or oi l or gas reservoir that is capable of accommodating a volume

of industrial carbon dioxide.

(b) M ETHODOLOGY

.— Not later than 1 year after the date of enactment of this Act, the Secretary shall develop a methodology for conducting an assessment under subsection ( f), taking into

consideration—

(1) the geographical extent of all potential sequestration formations in all States;

(2) the capacity of the potential sequestration formations;

(3) the injectivity of the potential sequestration formations;

(4) an estimate of potential volu mes of oil and gas recoverable by injection and sequestration of industrial carbon dioxide in potential sequestration formations;

(5) the risk associated with the potential sequestration formations; and

(6) the work done to develop the Carbon Sequestration Atlas o f the United States and Canada that was completed by the Department.3 A complete version of the EISA can be found at http://frwebgate.access.gpo.gov/cgibin/getdoc.cgi?dbname=110_cong_public_laws&docid=f:publ140.110.pdf

. Th e EISA requires the USGS to assess the capacity of the sequestration formations ; however, this term has become synonymous with “reserves” in the CO 2 community (Burruss, 2009; Frailey and Finley, 2009; Gorecki and others, 2009). The USGS assesses resources, which are considered to be independent of economic constraints. R eserves are the fraction of the resource that has economic value (Juanes and others, 2010). The definition of “ capacity ” as specified in the EISA is equivalent to the term “resource"; therefore, this methodology describes a method to assess the storage resource, which is

the mass of the free

- phase CO 2 that can be retained within a sequestration formation. S olubility trapping and mineral trapping of CO 2 (Benson and Cook, 2005; Bradshaw and others, 2007) are not included in this methodology. The legislative definition of “ risk ” contains two distinct classes of risk factors : geologic and engineering. The first, as stated in section 711(a)(4) of the EISA, includes “geomechanical, geochemical, hydrogeological, [and] structural . . . hazards. ” These are naturally occurring, geologically based parameters , which are accounted for in the methodology through the input distributions for geologic parameters and storage efficiency that are described in section 3 of this report. In addition, we assume that sound engineering practices will be employed on a site

- specific scale to minimize structural and environmental hazards. This assumption is necessary, because the quantification of risk is more appropriately a site -specific process that requires time and resources to yield meaningful results. The se resources are not available for the investigation of the storage formation s in this national assessment. Wiprut and Zoback (2000) and Lucier and Zoback (2008) provide examples of the potential interaction

between CO 2 injection and faults as an example of this research. The second risk is “engineered

hazards

, ” which are primarily a result of the impact of drilling procedures, drilling history, and drilling density. Such hazard s are potential engineering constraints that are not considered in this methodology’s evaluation of the probability of CO 2 retention in the storage formation. However, illustrations of drilling density will be generated as part of the assessment process to provide information about the potential scale of engineered hazards. A sequestration formation, as defined in section 711(a)(6) of EISA, is “a deep saline formation, unmineable coal seam, or oil and gas reservoir that is capable of accommodating a volume of industrial carbon dioxide.” These three geologic environments may occur within the same geologic interval and may share common geologic characteristics th at affect the size of the potential storage resource. This report only addresses the potential storage resource of two of these environments: deep saline formations and oil and gas reservoirs. Because there is no standard definition of “unmine able coal

sea ms,” the potential storage resource of this environment will not be addressed in this report. The DOE, however, has published estimates for CO 2 storage capacity in coal seams (U.S. Department of Energy, National Energy Technology Laboratory, 2008). When a commonly accepted definition of unmineable coal is determined, the USGS will incorporate the potential storage resource of this

environment in future CO 2 storage assessment reports

. As described in detail in the following sections of this report, we will u se the term “storage

formation ” (SF) for sequestration formation. The SF together with enclosing seal formations constitute a storage assessment unit (SAU) that is the fundamental geologic unit to be assessed for CO 2 storage

resources. Section 711(b)(3) o f the EISA also specifies that the methodology consider “the injectivity of

the potential sequestration formations

. ” Quantification of injectivity, as defined in the hydrologic and petroleum reservoir literature, requires measurement of pressure changes in a well resulting from injection of a known volume of fluid for a known period of time (Craft and Hawkins, 1991). Although4 large volumes of fluid are injected into the subsurface during oil field and waste disposal operations,

data from such operations , as reported by State and Federal agencies, are limited. This l ack of adequate injection and associated pressure data from geologic formations across the country makes the development of performance- based, numerical “injectivity” criteria for an assessment me thodology difficult. As a proxy, this assessment uses permeability categories in addition to lithologic information to more appropriately select the storage efficiencies used to calculate the storage resource values.

Sect ion 711(b)(4) of the EISA directs the USGS to provide “an estimate of potential volumes of oil and gas recoverable by inj ection and sequestration of industrial carbon dioxide in potential sequestration formations.” Methodologies for calculating enhanced oil recovery and enhanced gas

recove ry estimates are not included in this report . However, estimates of the volume of petroleum that

can be recovered by CO 2 sequestration to meet this requirement of the EISA will be discussed at a later

time in a separate document

.



## 2 . Assessment Framework

2. 1. Assessment Methodologies

Storage resources for geologic sequestration of CO 2 have been estimated using many methodologies

for a variety of scales , ranging from global to single basins. A review of many of these estimates (Bradshaw and others, 2005 ) con cluded that assessments of similar areas varied by as much as a factor

of 100 or more . In an attempt to provide consistent methods that are based on clearly defined input parameters, a working group of the “Carbon Sequestration Leadership Forum” created de terministic methods (Bradshaw and others , 2007; Bachu and others, 2007) that could be applied anywhere in the

world . A group of researchers le d by Scott Frailey at the Illinois State Geological Survey developed the methodologies for CO 2 storage capacity that were used in the DOE Regional Carbon Sequestration Partnership program “National Carbon Atlas” (U.S. Department of Energy, National Ener gy Technology Laboratory, 2008, their appendix B.) Another important assessment method, formulated by

van der Meer an d Egberts (2008), incorporates the impact of the pressure front created by the injection

of CO 2 . This pressure front propagates away from the injection site in advance of the plume of injected

CO 2 , thereby affecting a much larger area of a storage formatio n. The methods described above are not fully probabilistic

. However, probabilistic methods have been used to calculate storage efficiency values (see definition and discussion below) but do not account for the full range of geologic

uncertaint y in the resource calculation (U.S. Department of Energy, National Energy Technology Laboratory, 2008 ; Gorecki and others, 2009). Over a number of years, the USGS has developed probabilistic methods for assessing energy

resources (Charpentier and Klett, 2005; Schmoker and Klett, 2005) that can be applied to environments ranging from mature exploration provinces to relatively unexplored areas such as those found in the

circum

- Arctic (Bird and others, 2008; Gautier and others, 2009). Assessments of natural resources can be performed in many ways

, and each method has advantages and disadvantages that are related to

differen t input parameters, resource models, treatment of geologic uncertainty, and propagation of uncertainty to the results. Ahlbrandt and Klett (2005) reviewed and quantitatively compared seven methods of oil and gas resource assessment with the USGS methods used in the 2000 World Energy Project . They concluded that the probabilistic methods used by the USGS are robust and reproducible.

Probabilistic methods a re needed for assessments because geologic data for large areas are rarely complete . Because rocks are heterogeneous, approximations are required to fill gaps in the data

. Probabilistic methods provide a statistically sound method to make these approximations. However, as emphasized by Charpentier and Klett (2005) and demonstrated by Ahlbrandt and Klett (2005), a critical5 component of probabilistic resource assessment is careful integration of the geologic model of the resource with the statistical analyses of the probabilistic methods.



### 2.2. Model for CO 2 

### Storage Resources

This methodology is designed to assess the storage resources in mappable subsurface bodies of

rock into which CO 2 is injected and trapped ; in this methodology, these mappable subsurface bodies of rock are referred to as storage assessment unit s (SAU s). The total volume of pore space within a SAU

can be described as the total in

- place resource. This report addresses the fraction of that total resource that may retain CO 2

. The mass retained in that fraction is the technically accessible storage resource (TA SR ). The technically accessible storage resource is defined as the mass of CO 2 that can be stored in the pore volume of the SF taking into account present-day geologic knowledge and enginee ring practice and experience. The TA SR is analogous to the term “technically recoverable resource” used in USGS oil and gas assessments.

Carbon dioxide is injected into the subsurface as a separate fluid phase that is less dense than formation water, migrate s by buoyancy, and is retained in the subsurface by capillary forces. CO 2 will rise buoyantly until it encounters a rock unit that has a capillary entrance pressure that is greater than the buoyancy or hydrodynamic forces. Additional CO 2 will accumulate until the buoyancy force exceeds the capillary entrance pressure of the pore space vertically or laterally adjacent to the CO 2 plume. If the overlying rock unit has sufficiently high capillary entrance pressure, it will act as a seal, allowing CO 2 to accumulate in any structural or stratigraphic feature that has both vertical and lateral seals. In the geologic model for this assessment methodology, the pore space within large geologic

structures that will retain CO 2 in this manner is called the buoyant trap p ing storage resource (B SR ). In basins that have produced oil and gas, many of these structures involve petroleum reservoirs. Buoyant trapping storage resource estimates are based on data from petroleum reservoirs that have more than 500,000 barrels of oil equivalent ( BOE ) and , if available , information from other similar

- size enclosures (for example, dry traps).

A mass of CO 2 injected into a volume of rock will form a plume that migrates buoyantly and will continue to migrate after injection stops. The capillary entrance pressures of the pore spaces within the SF are heterogeneous. These heterogeneities within the SF may impede the flow of the migrating plume of CO 2 , causing some of the CO 2 to be retained within the pore spaces. These heterogeneities

range in size

— as small as individual pores (Juanes and others, 2006) through meter- size features like clay drapes within crossbedded sandstones (Saadatpoor and others, 2010) to petroleum reservoir

- size enclosures, which house the buoyant pore volume. The key co ncept is that the plume must migrate and

leave behind some fraction of the CO 2 trapped in these heterogeneities. The plume will continue to migrate until the mass of CO 2 within the plume is so small that the buoyancy forces within the plume

are less than t he capillary injection pressures of the formation. In other words, these volumes of trapped

CO 2 from the migration of the CO 2 plume are the residues of the migration process. The fraction of the pore space that physically traps CO 2 in volumes less than pet roleum reservoir

- size enclosures is most typically referred to as residual CO 2 trapping (Benson and Cook, 2005; Bradshaw and others, 2007; Gorecki and others, 2009), al though Saadatpoor and others (2010) subdivide the pore- size and meter

size retention mec hanisms into residual and capillary trapping , respectively . In this methodology, all potential CO 2 trapp ing within the SF that is smaller than the petroleum reservoir- size enclosures is

defined as the residual trapping storage resource (R SR ).

The amount an d quality of information available to estimate the mass of CO 2 that could be

stored vary . In geologic provinces that have oil and gas production, detailed information is available on some or most of the structural and stratigraphic features that are part of the buoyant trapping storage6 resource. However, such features are but a small fraction of the storage formation. T he rest of the

storage formation is a candidate for residual storage. The residual trapping storage resource is potentially much larger than the buoyant trapping storage resource, but within petroleum reservoir- size enclosures, the trapping processes and the relative fraction of pore space in which residual storage

resource s may occur are not as well understood as buoyant storage resources . Th e relative size of the

two resources and the relative certainty with which we may be able to estimate the resource s are illustrated in figure 1 . The top part of the triangle represents the resource that is most understood but

has the smaller resource ; the bottom part of the triangle represents the resource that is least understood but has the larger resource. In provinces with no oil and gas production, most of the resou rce could be residual storage.

Figure 1. A resource triangle depicting the relation between buoy ant and residual trapping storage resources

that schematically illustrates the relation between uncertainties in knowledge of the resource and the relativ e volume of the resource

.

Thi s general discussion of buoyant and residual trapping does not supplant the rich and diverse datasets and geologic models for petroleum entrapment that are based on 100 years of exploration and production. There is no comparable dataset for CO 2 sequestration; only a few field trials have been undertaken thus far. As a conseque nce, the mechanics of assessing CO 2 storage resources incorporates parameters that are poorly known due to limited data from CO 2 injection projects . Adopting a probabilistic method does not serve as a cure for lack of knowledge, but merely quantifies the h igher level of uncertainty that is necessarily inherent in CO 2 storage resource assessments.7 

### 2.3. Geologic Framework

2.3.1. Storage A ssessment U nit

— Storage Formation

The storage assessment unit ( SAU ) is a mappable volume of rock that consists of a porous flow

storage unit and a bounding regional sealing formation . Within the SAU, the porous flow unit is defined as the storage formation (SF). A schematic cross section that extends downdip through a hypothetical SAU is shown in figure 2. The pore volume with in the SF that contain s the buoyant trapping storage
resources and the residual trapping storage resources are shown in color.

Figure 2. A schematic cross section through a storage assessment unit (SAU) illustrating the relation between buoyant and residual trappi ng styles in the storage formation

. Recommended SAU depth limits of 3,000 ft (914 m) and 13,000 ft (3,962 m) also are included.

The exte nt of the SF is defined by the physical properties of CO 2 . The upper vertical limit chosen for this methodology is 3,000 feet (914 m) (Burruss and others, 2009) because CO 2 at this depth is typically subjected to temperatures and pressures that maintain the CO 2 in a supercritical state

. Supercritical CO 2 has density values much higher than those of gaseous CO 2 (National Ins titute of Standards, 2009). The lower vertical limit for the SAU of 13,000 feet (3,962 m) is based on the potential CO 2 injection depth at pipeline pressures without additional compression at the surface. The justification for these limits is discussed in more detail in Burruss and others (2009). If rock properties

suggest that a viable storage resource is present at depths below 13,000 ft, the assessment geologist may8 add an additional SAU for this deeper reservoir. The areal extent of the SAU on a map is defined by depth contours, from the land surface to the top of the SF, at 3,000 and 13,000 feet (914 and 3,962 m). Additional factors may limit the areal extent of the SF. For example, any formation water with salinities lower than 10,000 ppm (mg/L) TDS, regardless of depth, has the potential to be used as a potable water supply (U.S. Environmental Protection Agency, 2009). The U.S. Environmental Protection Agency (2008) has proposed the 10,000 ppm (mg/L) TDS limit for injection of CO 2

. Therefore, the potential storage resources for CO 2 in formations with salinities less than 10,000 ppm (mg/L) TDS will not be assessed at this time , except to illustrate the methodology in section 4. Although salinities of formation water commonly increase with depth, formation water within an assessment unit may be less saline than the 10,000 ppm ( mg/L ) limit near the updip extent of the SF, eliminating a p art of the SAU.



### 2.3. 2 . Storage A ssessment U nit

— Seal Formation

Seal formations (confining units, aquitards, cap rock) are r egional geologic strata that inhibit the migration of fluids between adjacent geologic strata. The seal formation must be present for identification of the mappable extent of the SAU. Therefore, a ny area of the SF that is not beneath the

seal formation is excluded from the area of the SAU. A seal may consist of single or multiple

formations.

Seals need to be evaluated for the leakage potential of CO 2 and formation water from the SF. The two primary pathways of fluids through a seal that may account for sea l failure are (1) leakage through fractures and faults and (2) diffuse porou s flow where the capillary entrance pressure of the seal is exceeded by the pore pressure as determined by the column height of the fluids (Hermanrud and others, 2005). Diffuse porous flow is not considered to be a significant factor in the movement of fluids through seals (Couples, 2005). However, studies of seal fractures in oil and gas fields indicate that

fracture flow can account for large volumes of fluid movement through the seal (Skerlec, 1999). The integrity of the fault seal may be affected by the juxtaposition of the strata within the fault plane, fluid pressures, mineralogy, and geometry of the fault system.



## 3. Storage Resource Calculations

This methodology estimates the technically accessible storage resource (TA SR ), which is the

mass of CO 2 that can be stored in the pore volume of the SF . This resource is the product of CO 2 density and storage volume, which is the fraction of the pore volume that will retain injected CO 2 . In order to estimate this fractional volume, the storage formation pore volume ( SF PV ) is calculated and then allocated between the pore volume available for buoyantly trapped CO 2 and residually trapped

CO 2 (B PV and R PV

, , respectively ). The B PV and R PV a re calculated separately because they are modified by different geologic uncertainties and storage efficiencies. Storage efficiency is the value that represents the fraction of the total available pore space that will retain free

- phase CO 2 . The following

s ections (3.1, 3.2, and 3.3) describe SF PV , B PV , and R PV and how they are derived and used to generate probabilistic assessment storage resource estimates ( fig. 3) using a Monte Carlo simulator. The assessment geologist is tasked with determining the input parameters using the information available. These input parameters are recorded on the input data form shown in appendix A. To facilitate the process, data, when available, will be provided to the geologist by the CO 2 assessment team

, a core group of USGS scientists working in support of the CO 2 storage assessment activities.9 Figure 3. Flow diagram of key steps for calculating buoyant trapping storage resources (left) and residual trapping storage resource s (right)

. Injectivity categories are represented as class 1 (R1), class 2 (R2), and class 3 (R3). See text for more information.



### 3.1. Calculating Storage Formation Pore Volume

The first step of the assessment process is to define the area of the SAU. Using available databases, the CO 2 assessment team provides the assessment geologist with values for the area, net porous thickness, and porosity. The area of the SAU is determined via GIS techniques (appendix B) by

the assessment team on the basis of the maps of the SF created using the parameters discussed in

secti on 2.3.1. The values for net porous thickness and poro sity can be further refined if relevant data are gathered by the assessment geologist during research for the framework geology of the SAU. Because10 the area of the SF is typically clearly defined, the uncertainty for mean area of the SF is likely to be relatively small. However, thickness and porosity data that are either localized, such as data primarily from oil and gas fields, or sparse to nonexistent, such as data from a formation with few well

penet rations, could lead to significant uncertainty about whether the mean values calculated from those data accurately represent the entire SF . These input values will be determined by the assessment geologist in consultation with the assessment team. The prob abilistic product of mean SAU area, mean thickness of the net porous interval , and mean porosity is the storage formation porous volume as shown in equation 1.

PV SF PI PI SF A T **φ = ××**  (1)

where SF PV is the pore volume of the storage formation (fraction);

A SF is the mean area of the storage formation (acres) ;
T PI is the mean thickness of the porous interval (feet), where the porous interval is

defined as the stratigraphic thickness of the storage formation with a porosity of 8 percent or higher ; and **φ** PI is the mean porosity of the porous interval (fraction).



### 3.2. Calculating Buoyant Trapping Pore Volume

The buoyant trapping pore volume (B PV ) is a geologically determined, probabilistic distribution

of the volume of the SF that can store CO 2 by buoyant trapping. The assessment geologist is tasked to generate the B PV distribution by using all available information. However, defaults may be used for the input data that define the B PV distribution

. The minimum B PV input can be the volume of known recovery of p etroleum, scaled to

subsurface volumes. The CO 2 assessment team will sum the known recovery production volumes (KR) of oil and gas reservoirs within the SAU from available databases and use formation volume factors (FVF s) to convert these surface vol umes t o volumes at reservoir conditions (KR RES ). The KR for oil and natural gas liquids will be corrected to subsurface volumes by using an appropriate range of FVFs for the SAU from the Standing correlation ( Beggs , 1987). The KR for gas will be corrected to subsurface volumes using appropriate compressibility factors for the range of temperatures and pressures ( Garb and Smith, 1987) within the SAU.


## ( **)** 

# ( **) (**  **)** RES OIL NGL OIL GAS GAS KR KR KR FVF KR FVF **  = +× +×** 

** ** (2)

where KR RES is the volume of known recovery corrected to reservoir conditions (vol ume) ;
KR OIL is t he known recovery of oil (volume);

KR NGL is t he known recovery of natural gas liquids (volume);

FVF OIL is the f ormation volume f actor for oil and natural gas liquids (fraction) ;
KR GAS is t he known recovery of gas (volume) ; and

FVF GAS is the formation volume f actor for gas (fraction)

.

An additional estimation of buoyant trapping that can be used in this methodology is the reported mean values fo r USGS National Oil and Gas Assessment ( NOGA ) undiscovered petroleum

resource volumes . NOGA mean re source volumes can be allocate d to the SF; these allocated volumes

are then corrected to reservoir conditions using equation (2). The corrected undiscovered NOGA

volumes can be added to the KR RES value to estimate a more robust buoyant trapping volume. If there

are any buoyant traps without petroleum production (“dry traps” within the SF), then it may be possible11 to incorporate their volumes in to t he KR RES and USGS NOGA undiscovered petroleum resource

estimates to determine a median B PV . However, because th ere are no known available datasets on “dry trap” characteristics, estimating any volume comparable to USGS NOGA or KR RES values will be

difficult. The maximum B PV input should likely include some estimate of the volume of the total pore space that is with in large enclosures. However, the assessment geologist can estimate the B PV distribution in any way using the data provided in conjunction with all other available geologic data.

The B PV is multiplied by the buoyant trapping storage efficiency ( B SE , fig . 3 ) to determine a buoyant trapping storage volume (B SV ), as shown in equation 3. Typically, B SE is lower than hydrocarbon saturation values in oil or gas fields. This difference is due to the inability of a low viscosity fluid, such as supercritical CO 2 , to efficiently displace a high viscosity fluid, such as oil or water, without exceeding the fracture pressure of the storage or seal formation. Also

, because there are

no CO 2 storage projects that have attempted to optimize the mass of CO 2 that can be retain ed within the pore volume of an enclosure, buoyant trapping storage efficiencies are difficult to estimate . The buoyant trapping storage efficiencies (B SE ) used in this study will be based on experimentally derived relative permeability curves (Bennion and Bachu, 2005, 2008; Burton and others, 2008). Values from such studies provide the best potential storage efficiencies that are currently available for buoyant storage, but these values could change with more research or field data.

SV PV SE B BB **= ×** (3)

where B SV is the v olume of CO 2 stored by buoyant trapping within the storage formation (volume);

B PV is the pore volume available for buoyant trapping (volume) ; and

B SE is the s torage efficiency of buoyant CO 2 storage (fraction)

.

T o determine th e buoyant trapping storage resource (B SR ), which is the mass of CO 2 that can be buoyantly trapped in the SF, the B SV is multiplied by the density of CO 2 (as shown in equation 4 and

illustrated in figure 3 ). A probabilistic distribution of the density of CO 2 is calculated by the assessment team based on the upper and lower depth boundaries of the SF , temperature and pressure gradients appropriate for the area, and an equation of state for CO 2

.

SR SV 2 B B CO **ρ = ×**  (4)

where B SR is the buoyant trappin g storage resource (mass) ;
B SV is the volume of CO 2 stored by buoyant trapping with the storage formation (volume) ; and

**ρ** CO 2 is the density of CO 2 (mass/volume)

.

With this step, the calculation for B SR is complete (fig. 3).



### 3.3. Calculating Residual Trappi ng Pore Volume

Residual trapping is the second type of storage in the s torage formation resource calculation. The pore volume available for residual trapping is the remaining SF PV that was not considered for the buoyant storage resource. During the iterati ve calculation s using the Monte Carlo simulator , a single

value is selected from the B PV distribution; this value is subtracted from the SF PV selected in the same

iteration and yields a remaining pore volume that is equal to the residual trapping pore volu me (R PV ) (fig. 3).12 PV PV PV R SF B **= −** (5)

This residual pore volume is apportioned into three rock classes or “injectivity category

allotments” ( fig . 3) on the basis of permeability. The CO 2 assessment team will provide permeability

values from available databases ; however, the assessment geologist should seek to augment these values with data available from literature, other databases, or other sources. These permeability values are used to estimate the percentages of the SF that comprise each class. Storage efficiencies associated with residual trapping are poorly understood because commercial

- scale injection projects into these

parts of the SF have not been undertaken . Because these values are not well constrained, we will use a

standard set of minimum, mode, and maximum values based on modeled values from Gorecki and others (2009) that have been modified by the injectivity and mobility of CO 2

. Class 1 rocks are defined as those parts of the remain ing SF that have very high permeabilities ( greater than 1 Darcy) and the highest injectivity values. T hese highly permeable rocks , however, typically have less pore -scale residual trapping (Juanes and others, 2006), due to the lack of small pore throats. Therefore, the majority of the trapping in these rocks will be the result of larger scale permeability heterogeneities (Saadatpoor and others, 2010) as described in section 2. In addition, CO 2 plumes would move quickly in a highly permeable unit, which would increase the potential for leakage along secti ons of the SF that crop out at the surface updip from the SAU boundary. The corresponding storage efficiency values for these rocks are typically lower than class 2 rocks due to the lack of pore

scale residual trapping of a highly mobile CO 2 plume.

Class 2 rocks are defined as parts of the remain ing SF that have ( 1) moderate permeabilities

, typically on the order of 1 millidarcy to 1 Darcy; (2) minor to no injectivity issues as discussed in the guidelines of the U.S. Environmental Protection A gency (2008); and (3) a high potential for all types of residual trapping ranging from pore scale to larger scales. C lass 2 rocks might have the highest storage efficiency values due to the full range of potential residual trapping types. Class 3 rocks are defined as parts of the remain ing SF that have low permeabilities , on the order

of less than 1 millidarcy , and have little to no injectivity. These rocks have low storage efficiency values, with minimum and mode values approaching or equal to zero, since little CO 2 w ill enter these

rocks without artificially fracturing the rock ; artificial fracturing of the SF may not be permitted under U.S. Environmental Protection Agency requirements (2008). The maximum value is taken from the appropriate sandstone, limestone, or dolomite values from Gorecki and others (2009) to account for the possibility that some mass of CO 2 could enter and be retained within this part of the SF. Using permeability data from the SF, t he R PV is then allocated between these three classes (R1, R2, and R3). During each iteration, the classes are then multiplied by a value from their fixed storage efficiency probability distributions to determine their residual volume resources (R SV ) (fig. 3).

SV PV SE R RR **= ×** (6)

where R SV is the r esidual trapping storage volume (volume);

R PV is the r esidual trapping pore volume (volume) ; and

R SE is the r esidual trapping storage efficiency ( fraction ).

The residual trapping storage resource (R SR ) is determined by multiplying the R SV by the density

of CO 2 (f ig. 3). A probabilistic distribution of the density of CO 2 is calculated by the assessment team based on the upper and lower depth boundaries of the storage formation, temperature and pressure gradients appropriate for the area, and an equation of state fo r CO 2

.13 SR SV 2 R R CO **ρ = ×**  (7)

where R SR is the residual trapping storage resource ( mass ) ; and

**ρ** CO 2 is the d ensity of CO 2 (mass/volume)

.

With this step, the calculation for R SR is complete ( fig. 3).



### 3.4 . T echnically A ccessible S torage R esource

In order to calculate the technically accessible storage resource (TA SV ) for the SF as a whole,

the stora ge volumes calculated using the equations in sections 3.2 and 3.3 are summed iteratively (fig. 3)

.

SV SV SV SV SV TA R1 R2 R3 B **=+++** (8)

where TA SV is the t echnically accessible storage volume;

R1 SV is the residual trapping class 1 storage volume;

R2 SV is t he residual trapping class 2 storage volume ; R3 SV is the residual trapping class 3 storage volume ; and

B SV is the b uoyant trapping storage volume.

The technically accessible storage resource (TA SR ) is determined by multiplying the TA SV by the density of CO 2 ( fig . 3). A probabilistic distribution of the density of CO 2 is calculated by the assessment team based on the upper and lower depth boundaries of the storage formation, temperature and pressure gradients appropriate for the area, and an equation of s tate for CO 2

.

SR SV 2 TA TA CO **ρ = ×**  (9)

where TA SR is the t echnically accessible storage resource ( mass ); and

**ρ** CO 2 is the d ensity of CO 2 (mass/volume)

.

With this step, the calculation for TA SR is complete ( fig. 3).



### 3.5. Storage in Oil and Gas Reservoirs

The EISA legislation defines a sequestration formation as a “deep saline formation ... or oil or gas reservoir

. ” Within SAUs that have petroleum production, the storage resource specific to petroleum

reservoirs can be estimated by using the KR RES values determined in the B PV section. To convert this

subsurface volume of KR RES to a storage resource, the total volume i s reduced by a storage efficiency value. The storage efficiency distribution for the oil and gas reservoirs used for this resource estimation will be the same as the buoyant storage efficiency values. The known recovery replacement storage resource (KRR SR ) is determined by multiplying the KR RES by the density of CO 2 . A probabilistic distribution of the density of CO 2 is calculated by the assessment team based on the upper and lower depth boundaries of the storage formation, temperature and pressure gradient s appropriate for the area, and an equation of state for CO 2

.14 

## ( **)** SR RES SE 2 KRR KR B CO **ρ = ××**  (10)

where KR RES is the known recovery corrected to a volume at subsurface conditions (volume), calculated in equation (2);

B SE is the buoyant storage efficiency (fraction) ; and

**ρ** CO 2 is the d ensity of CO 2 (mass/volume)

.

With this step, the calculation for KRR SR is complete.



### 3.6. Final Assessment Products

The final assessment products will include illustrations and storage resource values. The final

assessment of each SAU will include illustrations of structure, depth below the surface, and isopach maps as well as well penetration cell maps for each SAU. The cell maps will include the total number of well penetrations through the SF per square mile grid blocks. The storage resource values will be reported as the F95 (denotes a 95 percent chance that the amount reported will be present within the SAU) ; other fractiles are defined similarly), F50, F5, and mean values of the mass of CO 2 retained in

the:

1. The total buoya nt storage fraction ; in other words, the buoyant trapping storage resource (B SR ).

2. The residual storage fractions; in other words, the residual trapping storage resource (R SR ), with

classes 1, 2, and 3 reported separately (R1 SR , R2 SR , R3 SR ).

3. The total stora ge formation resource ; in other words, the technically accessible storage resource (TA SR ).

4. The oil and gas reservoir storage; in other words, the known recovery replacement storage resource (KRR SR ).



## 4. An Example of the Storage Resource Calculation

4.1. Data Sources

Geologic and assessment models are built on geologic framework studies from USGS oil and gas assessments. Such basin studies have resulted in structure and thickness models, stratigraphic columns, cross sections, and general knowledge of the geology that are used to identify the SAU. Additional comprehensive data searches from published and unpublished work by the USGS, State geological surveys, petroleum industry producer associations or agencies, commercial databases

, and the general literatur e are conducted to obtain additional information for use by assessment geologists. Quantitative data at the oil and gas reservoir level, including composition, porosity, permeability, size, thickness, depths, lithology, drive mechanism, and production data , are available in a commercial database, “Significant Oil and Gas Fields of the United States” (Nehring Associates, Inc., 2008). The

USGS CO 2 storage resource assessment calculations include data from fields with at least 0.5 million barrels of oil equiva lent ( MM BOE)

. This minimum size is the same as that used by the USGS NOGA methodology as well as Nehring Associates, Inc

. Maintaining the same volume limits as NOGA ensures the applicability of their undiscovered petroleum volumes for use in this assessmen t’s calculations

. Data at the individual well level, including location, producing formation, formation tops, bottom hole pressures, perforation zones, and production of oil, gas, and water, were obtained from the15 commercial database, “PI/Dwights PLUS on CD” (IHS Inc., 2008a). Volumes of produced and injected water, oil, gas, and natural gas liquid , along with core sample measurements, were obtained from a separate IHS database called “PIDM 2.5” (IHS Inc., 2008b). Nehring Associates , Inc.

, and IHS Inc.

, co m mercial databases are all proprietary. No data from these datasets, whether tabular or spatial in nature, will be published or made available to the public in any way throughout the assessmen t process

. Derivative aggregations of data and analytical result s that are not related to specific wells, reservoirs

, or fields will be included in assessment publications.



### 4. 2

. An Example

— The Tensleep Sandstone Storage Assessment Unit

The Pennsylvanian

- Permian Tensleep Sandstone of the Wind River B asin

, Wyoming

, was

s elected to demonstrate the USGS methodology for assessing CO 2 storage resources. The Tensleep Sandstone provides a straightforward test case as a storage assessment unit because it lies within a mature petroleum basin with available production data, has a broadly uniform thickness, and is discussed at length in the literatur e. The assessment focused on the upper 100 feet (30 m), approximately, of the Tensleep Sandstone where petroleum is produced from a massive eolian sandstone unit, which has high porosity and permeability values. Furthermore, the recent assessment of the petroleum potential of the Wind River B asin (Kirschbaum and others, 2007) provided up- to

- date data and interpretations that are highly useful for completing a CO 2 storage capacity assessme nt. However, because the formation waters of the Tensleep Sandstone SAU have TDS concentrations below 10,000 ppm (mg/L), this particular SAU cannot be used for sequestration under current EPA guidelines. Therefore, storage resource values presented for this example are for illustrative purposes only.



### 4.3. Form Inputs

Th is section describes what information needs to be entered on the input data form (appendix A) for the Tensleep Sand stone SAU example

. The first section of the SF assessment model form (Ident ification Information) includes a description of the SAU, as well as a section for notes from the

assess ment geologist. The characteristics of the SAU are entered in the second section of the form (Characteristics of the Storage Assessment Unit (SAU)) . The SAU was created following the guidelines outlined in section 2.3.1 using GIS software with datasets from Kirschbaum and others (2007), Fox and others (1975), Nehring Associates , Inc. (2008), and IHS Inc. (2008a). A map of the SAU with structure contours is presented in figure 4.16 Figure 4. The Tensleep Sandstone storage assessment unit in the Wind River Basin, Wyoming, is confined to

t he parts of the formation where the top of the unit is at least 3,000 ft (914 m) below land surface and the bottom of

the unit is no deeper than 13,000 ft (3

, 962 m)

. Figure modified from Kirschbaum and others (2007).

St orage formation pore volume (SF PV ) is the product of three inputs. First, GIS software was used to calculate the area of the Tensleep Sandstone SAU

. A mode value of 1,400,000 was entered on line 4 of the form

, and values were entered for the minimum and maximum areas (1,300,000 and 1,400,000, respectively) to account for the relatively limited uncertainty in the area calculation

. The

m ean n et porous interval thicknesses of 80, 100 and 120 feet (~24, 30, and 37 m) inputs were based on data from Fox and others (1975). Mean porosity distribution value s were also based on data from Fox and others (1975); however, reservoir values from the Nehring database (Nehring Associates, Inc., 2008) were also used. Buoyant trapping pore volume is determined by the CO 2 assessment team in conjunction with

the assessment geologist using a variety of sources of data. Known recovery production volumes from

reservoirs within the Tensleep Sandsto ne SAU from Nehring Associates, Inc. (2008), were converted to reservoir conditions using appropriate ranges of formation volume factors for both oil and gas (Beggs,

1987 ; Garb and Smith, 1987 ) (see section 3.5). A value of 190 MMbbl was entered as the minimum buoyant trapping pore volume. USGS NOGA results were scaled proportionally to the SAU size and

added to the minimum B PV to choose a mode B PV

. Published mean undiscovered oil and gas assessment figures from Kirs chbaum and others (2007 ) were modified using values determined from past17 production to isolate Tensleep Sandstone production only. T hose volumes were scaled to account for the areal discrepancy between the boundaries of the NOGA assessment unit (Kirschbaum and others, 2007) and the SAU (fig. 4) . A volume, at reservoir conditions, of 15 M Mbbl was calculated and added to the minimum of 190 MMbbl to produce the median of 205 MMbbl.

For this example, a maximum B PV value was chosen using a volumetric calculation method

similar to that used for SF PV , but for a much smaller area. The areas of potential enclosures, both dry traps and the water leg s of existing fields, w ere determined from structure contour maps to be approximately 2.5 percent of the SAU area. A value of 4,100 MMbbl, which approximates 2.5 percent
of the SF PV , was used as the maximum input for B PV . A log normal distribution is used for B PV in the probabilistic calculations. Injectivity category allotment is the only input required for the residual trapping storage

resource . Graphs of permeability information from Fox and others (1975) indicate that the majority of the porous interval in the Tensleep Sandstone has permeabilit y values between 1 milli d arcy ( mD ) and 1 Darcy (D)

. Only a small percentage of the formation exhibits permeabilit y value s indicative of class 1

or class 3 categories. The storage efficiency values used in this example are included to facilitate understanding of the

resource calculations but are not provided on the form and are not an input chosen by the assessment geologist . As stated in section 3.2, buoyant trapping storage efficiencies (B SE ) used in this methodology are based on experimentally derived relative permeability curves (Bennion and Bachu, 2005, 2008 ; Burton and others, 2008). In this example, values of 10 percen t, 30 percent, and 60 percent were used

for minimum, mode, and maximum B SE . Storage efficiencies associated with residual trapping are poorly understood as mentioned in section 3.3. Inputs based on modeled values for sandstones from Gorecki and others (200 9) modified by the injectivity and mobility of CO 2 and the likelihood of residual trapping were used in this example. Values of 1 percent , 5 percent , and 7 percent for R1 SE , 1
percent , 7 percent , and 15 percent for R2 SE , and 0 percent , 0 percent , and 7 percent for R3 SE were used for minimum, mode, and maximum residual storage efficiency.

The last three section s of the form cover the allocation of CO 2 storage resource by area for Federal, State, tribal, and private lands, and other classifications

. Areal allocations were designated using maps of these lands ; however, volume percentage allocations are derived from the geologic information collected and analyzed throughout the example assessment project . Some areas or land types contain more or less of the reso urce than would be determined with a straight areal allocation

.



### 4.4. Results

Results from the probabilistic assessment indicate that the Tensleep Sandstone SAU has mean CO 2 storage values of 13.4 million short tons ( mst ) (12.2 million metric tons ( Mt ) ) of buoyant trapping

storage resource, 36.9 mst ( 33.5 Mt) of residual trapping class 1 storage resource , 1,179 mst ( 1,070 Mt) of residual trapping class 2 storage resource , 19.9 mst ( 18.0 Mt) of resi dual trapping class 3 storage

resource, and 1,244 mst ( 1,129 Mt) of technically accessible storage resource (table 1) . In the Tensleep Sandstone, storage resources based on known recovery volumes are 7.6 mst ( 6.9 Mt) of CO 2 (table 2)

.18 Table 1. S torage resource values of CO 2 for five different classifications within the Ten sleep Sandstone storage

assessment unit.
[mst, million short tons; Mt, million metric tons]

Tensleep
Sandstone F95 F50 F5 Mean

Buoyant trapping

storage resource 4. 5 mst ( 4.1 Mt) 9.1 mst ( 8.3 Mt) 38.4 mst ( 34.8 Mt) 13.4 mst ( 12.2 Mt)

Residual trapping

cl ass 1 storage

resource 16.7 mst (15. 2 Mt) 38.0 mst (34.5 Mt) 58.6 mst (53.2 Mt) 36.9 mst (33.5 Mt)

Residual trapping class 2 storage

resource 450 mst (40 8 Mt) 1,200 mst ( 1

, 089 Mt) 2, 069 mst (1,877 Mt) 1, 179 mst (1,070 Mt)

Residual trapping

c lass 3 storag e

resource 1. 6 mst (1. 5 Mt) 19.0 mst (17.2 Mt) 47.1 mst (42.7 Mt) 19.9 mst (18 .0 Mt)

Technically

a ccessible

storage resource 514 mst (466 Mt) 1, 250 mst (1,134 Mt) 2, 125 mst (1,928 Mt) 1, 244 mst (1,129 Mt)

Table 2. S torage resource values of CO 2 for petroleum rese rvoirs in the Tensleep Sandstone storage

assessment unit.
[mst, million short ton

Tensleep
Sandstone
Known recovery s; Mt, million metric

F95

3. 9 mst (3.5 Mt) tons]

F50

7. 4 mst (6. 7 Mt) F5

11.6 mst ( 10. 5 Mt) Mean

7. 6 mst (6.9 Mt) replacement

storage resource



## 5 . Conclusions

This report describes a probabilistic methodology to assess the CO 2 storage resource of geologic

strata in sedimentary basins in the United States

. The fully probabilistic method capture s the uncertainty of (1) the geologic parameters which define the storage formation pore volume; (2) the fraction of that pore space in which CO 2 will be retained ; and (3) the mass of the CO 2 retained in that pore volume. The resulting products created using this methodology include the storage resources, reported in mass of

CO 2 , of (1) the entire storage formation; (2) the buoyant trapping and residual trapping within the storage formation; and (3) the storage within oil and gas reservoirs.



## Acknowledgments

The authors thank USGS authors from previous versions of this methodology; Mark F. Becker, William N. Herkelrath, Yousif K. Kharaka, Christopher E. Neuzil, Sharon M. Swanson, Troy A. Cook, Timothy R. Klett, Philip H. Nelson, and Christopher J. Schenk. Thank s to Ronald R. Charpentier (USGS) for expert gui dance and advice on developing probabilistic models and calculations. Substantial improvements and modifications to earlier versions could not have occurred without the assistance of reviews and meetings with the members of an external review panel ( Ste f an Bachu (Alberta Innovates-Technology Futures, Edmonton, Alberta, Canada), Charles Gorecki (Energy &19 Environmental Research Center, University of North Dakota, Grand Forks, N. Dak.), Kenneth Hood (ExxonMobil Exploration Company, Houston T ex. ), William Maze (ExxonMobil Upstream Research Company, Houston, T ex. – Chairman of the review committee), George Peridas (Natural Resource Defense Council, San Francisco, C alif. ), Rusty Riese (BP Alternative Energy, Houston, T ex. ), John Rupp (Indiana Geological Survey, Bloomington, Ind.), and Gary Teletzke (ExxonMobil Upstream Research Company, Houston, T ex )) 1 . The content and presentation of this report benefited greatly from the technical reviews of Ronald R. Charpentier, Christopher J. Schenk, Laurie Burke, Phil Nelson, Troy Cook, and Lynn Tennyson. In the methodology development process, extensive collaboration was provided by the USGS Tertiary assessment team, especially Alex Karlsen, and the USGS Wind River Basin Province assessment team, in particular Mark Kirschbaum and Laura Roberts. Susan D. Hovorka

an d the Gulf Coast Carbon Center team at the Texas Bureau of Economic Geology provided data and helpful discussions on the potential for CO 2 storage in the sediments of the Texas Gulf Coast. Eric Morrissey (USGS) was he lpful in the redesign of several illustrations within the report. The authors thank Desiree Polyak (USGS) for her contributions to the project . The authors also wish to acknowledge the support of the USGS Enterprise Publishing Network.



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Basin

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Bennion, D.B., and Bachu, Stefan, 2008, Draina ge and imbibition relative permeability relationships for supercritical CO 2 /brine and H 2 S/brine systems in intergranular sandstone, carbonate, shale, and anhydrite rocks: Society of Petroleum Engineers Reservoir Evaluation and Engineering, v. 11, no. 3, p. 487–496, doi:10.2118/99326– PA [may require subscription to access].

_______________

1 Public Law 110

– 140, Section 711(d)(2), mandated the establishment of "a panel of individuals with expertise in the matters described. . .composed of representatives of Federal agencies, institutions of higher education, nongove rnmental organizations, State organizations, industry, and international geoscience organizations to review the methodology and comments received" on the carbon dioxide sequestration capacity assessment. The reviews provided by members of that panel were f or technical purposes only and do not constitute an endorsement of the methodology presented herein by either

the reviewers or their institutions.20 Benson, Sally, and Cook, Peter, 2005, Underground geological storage, chap. 5 of Intergovernmental

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.24 

## Glossary

barrels of oil equivalent (BOE) A unit of petroleum volume in which the gas part is expressed in terms of its energy equivalent in barrels of oil. For this assessment, the energy equivalent (not the volume equivalent) of 6,000 cubic feet of natural gas equals 1 barrel of oil equivalent (Klett and others, 2005).

brine Water having a salinity higher than that of average seawater, that is, more than 35,000 parts per million (milligram s per liter) total dissolved solids.

buoyancy Upward force on one phase (for example, a fluid) produced by the surrounding fluid (for example, a liquid or a gas) in which it is fully or partially immersed, caused by differences in density.

buoyant trapping CO 2 in communication across pore space creating a column that is held in place by a top and lateral seal, either a seal formation or a sealing fault.

buoyant trapping pore volume (B PV ) A geologically determined, probabilistic -distribution of the volume fraction of the storage formation that can store CO 2 by buoyant trapping. This distribution minimum is typically defined by existing plus forecast undiscovered oil and gas production volumes. The maximum is probabi listically calculated from distributions of geologic parameters describing the known trapping structures within the storage formation

. buoyant trapping storage e fficiency (B SE ) A distribution of efficiency values that describes the fraction of buoyant trapping that can occur within a volume of porous media.

buoyant trapping storage resource (B SR ) Mass of CO 2 retained in the storage formation by buoyant trapping.

buoyant trapping storage volume (B SV ) Volume of CO 2 retained in the storage formation by buoyant trapping.

capillary entrance pressure The pressure necessary to displace a wetting fluid from a porous medium by a nonwetting phase (for example , displacing water with gas o r mercury). The surface tension between the phases is a function of the radius of curvature of the interface between the phases, causing capillary entrance pressures to increase as the diameter of the pores and pore throats decreases. V ery fine grained rocks, like mudstones, have very high capillary entrance pressures allowing them to be barriers to flow (seals) for nonwetting fluids , such as oil, gas, and supercritical CO 2

. capillary force Capillary forces in a petroleum reservoir are the result of the combined effect of surface and interfacial tensions, pore size, geometry, and wetting characteristics of a given system (Dandekar, 2006, p. 145).

carbon dioxide plume The subsurface extent, i n three dimensions, of an injected carbon dioxide

stream.

c olumn height The thickness defined by the highest and lowest levels within the strata where the CO 2 phase is continuously connected. This column is held in place by top and lateral seals, and its thickness is controlled by the geometry of the closure and (or) the seal adequacy.

enhanced oil recovery Any process of tertiary oil recovery that follows recovery using natural reservoir pressure (primary recovery) and water flooding (secondary recovery). Common methods

include steam -flooding for heavy oil, polymer and surfactant flooding, and CO 2 miscible gas flooding.

gas:oil ratio (GOR) Ratio of gas to oil (in cubic feet per barrel) in a hydrocarbon accumulation. This ratio is calculated by using volume s of gas and oil at surface conditions.25 gas reservoir A hydrocarbon accumulation composed primarily of gas, defined by the USGS as an accumulation having a gas:oil ratio of 20,000 cubic feet per barrel or greater.

geologic storage of CO 2 The long- term rete ntion of carbon dioxide in subsurface geologic formations.

i njectivity T he rate and pressure at which fluids can be pumped into the rock without fracturing the

formation

. Alt hough injectivity is typically reported as a rate, this methodology addresses this requirement by using permeability values to divide the residual storage component of the stora ge formation into three classes.

known recovery production volumes (KR) The cumulative petroleum production and proved reserves for a given reservoir.

known recovery replacement storage resource (KRR SR ) The storage resource calculated from known recovery production volumes.

minimum size The lower limit for inclusion of oil an d gas field information in assessment calculations. Volumetric data from accumulations with less than 0.5 million barrels of oil equivalent total production are not included in any of the calculations in this methodology

. National Oil and Gas Assessment ( NOGA) U.S. Geological Survey National Oil and Gas Assessment,

described at http://energy.cr.usgs.gov/oilgas/noga/

. net porous thickness (T PI ) Defined in this methodology as the stratigraphic thickness of t he storage formation with a porosity of 8 percent or higher.

oil reservoir A hydrocarbon accumulation composed primarily of oil, defined by the USGS as an accumulation having a gas:oil ratio of less than 20,000 cubic feet per barrel.

original oil in place The total in -place volume of oil within a hydrocarbon reservoir or field, or within a larger region such as a basin or country, prior to the onset of production. The volume of the oil is reported at surface conditions, not reservoir conditions.

p ermeabilit y (k) A measure of the ability of a rock to transmit fluids, controlled by pore size and pore throat geometry. Typically reported in Darcy units.

porosity ( **φ** ) The part of a rock that is occupied by voids or pores . Pores can be connected by passages called pore throats, which allow for fluid flow, or pores can be isolated and inaccessible to fluid flow. Porosity is typically reported as a volume, fraction, or percentage.
pressure gradient The change in pore pressure per unit depth, typically in units of pound- for ce per square inch per foot or kilopascals per meter.

residual t rapping Discrete droplets, blobs, or ganglia of CO 2 as a nonwetting phase, essentially immiscible with the wetting fluid, trapped within individual pores where the capillary forces overcome

th e buoyant forces.

residual trapping class 1 (R 1) Residually trapped storage formation rock having a permeabilit y of greater than 1 D arcy

. residual trapping class 2 (R 2) Residually trapped storage formation rock having a permeability of greater than 1 m illi darcy and less than than 1 D arcy

. residual trapping class 3 (R 3) Residually trapped storage formation rock having a permeability of less

than 1 m illidarcy

. residual trapping pore volume (R PV ) A calculated value equal to the storage formation pore volume (SF PV ) minus the buoyant trapping pore volume (B PV ). The value represents the pore volume within the26 storage formation that can be used to store CO 2 by residual trapping; it is calculated during iterations of

the Monte Carlo simulator after a value from the buoyant trapping pore volume distribution is chosen.

residual t rapping storage e fficiency (R SE ) A distribution of efficiency values that describes the fraction of residual trapping that can occur within a volume of porous media.

residual trapping storage resource (R SR ) The mass of CO 2 retained in the storage formation by residual trapping.

residua l trapping storage volume (R SV ) The volume of CO 2 retained in the storage formation by residual trapping.

salinity A measurement of the water properties determined by the total dissolved solids, generally reported in parts per million or milligrams per lit er.

seal formation The confining rock unit within the storage assessment unit. The seal formation is a rock unit that sufficiently overlies the storage formation and has a capillary entrance pressure low enough to effectively inhibit the upward buoyant flo w of CO 2

. seal A geologic feature that inhibits the mixing or migration of fluids and gases between adjacent geologic units. Typically a rock unit or a fault; it can be a top seal, inhibiting upward flow of buoyant fluids, or a lateral seal, inhibiting the lateral flow of buoyant fluids.

storage assessment unit (SAU) A mappable volume of rock that includes the storage formation, a

reservoir flow unit for CO 2 storage, and a regional seal formation.

storage formation (SF) The reservoir component of the stora ge assessment unit

. The sedimentary rock layers that are saturated with formation water with total dissolved solids greater than 10,000 parts per
million (m illigrams per liter ). In the CO 2 assessment methodology, the s torage formation resource calculation is the main resource calculation and consists of two parts, a buoyant trapping resource and a residual trapping resource.

storage formation pore volume ( SF PV ) The available pore space in the storage formation calculated from area, thickness of the net porous interval

, and porosity. This value is used in the calculation of residual trapping pore volume (R PV ).

supercritical CO 2 Carbon dioxide is in a supercritical fluid state when both the temperature and pressure exceed the critical temperature of 88°F (31°C) and pressure of 74 bars (7,400 kilopascal) at which liquid and vapor CO 2 can no longer coexist.

t echnically accessible storage resource (TA SR ) The CO 2 stor age resource that may be available for CO 2 injection and storage estimated by using present-day geologic and hydrologic knowledge of the subsurface and engineering practices. Analogous to the term “technically recoverable resource” used in USGS oil and gas assessments.

t echnically accessible storage volume (TA SV ) The CO 2 storage volume that may be available for CO 2 injection and storage estimated by using present-day geologic and hydrologic knowledge of the subsurface and engineering practices.

total dissolved solids (TDS) Synonymous with salinity; see salinity.

trapping The physical and geochemical processes by which injected CO 2 is retained in the subsurface.27 

## Appendix A. Assessment Input Forms

Storage Formation (SF) Assessment Method: Input Data Form

The input sections for the storage formation form are described in section 4.3.28 STORAGE FORMATION (SF) ASSESSMENT MODEL: INPUT DATA FORM

IDENTIFICATION INFORMATION

Assessment Geologist: USGS Date: Region: North America Number: 5

Province: Wind River Basin Number: 5035 Storage Assessment Unit (SAU): Tensleep Sandstone Number: S50350101 SAU Relationship to NOGA AU: NOGA AU Tensleep

- Park City Conventional Oil and Gas

Based on Data as of: Nehring Associates, Inc., 2008, data current through 2006; Fox and others, 1975; Kirschbaum and others, 2007

Notes fro m Assessor:

CHARACTERISTICS OF THE STORAGE ASSESSMENT UNIT (SAU)

1) Storage formation depth (ft): minimum: 3,000 mode: 9,500 maximum: 13,000

2) Area of storage formation at depths between 3,000 ft and 13,000 ft, or another interval (acres): 1,400,000

3) Total Storage Formation

Thickness ( 3,000

- 13,000 ft): minimum: 200 mode: 275 maximum: 600

STORAGE FORMATION PORE VOLUME (SF PV ) PROBABILISTIC CALCULATION INPUTS

4) Mean SAU Area (line 2 ): minimum: 1,300,000 mode: 1,400,000 maxi mum: 1,500,000

5) Mean Thickness, Net Porous Interval (ft): minimum: 80 mode: 100 maximum: 120

6) Mean Porosity (fraction): minimum: 0.1 mode: 0.15 maximum: 0.2

BUOYANT TRAPPING PROBABILISTIC CALCULATION INPUTS

7) Buoyant Trapping Por e Volume (MMbbl): minimum: 190 mode: 205 maximum: 4,100

RESIDUAL TRAPPING PROBABILISTIC CALCULATION INPUTS

8) Injectivity Category Allotment (Sum = 1.0)

a) Fraction with Class 1 Injectivity (k > 1 D) 0.05

b) Fraction with Class 2 Injectivity (1 mD < k < 1 D) 0.9

c) Fraction with Class 3 Injectivity (< 1 mD) 0.05

Does the Class 1 fraction have a direct updip path to outcrop that may be a leakage risk? no29 ALLOCATIONS OF THE SF TO STATES Surface Allocations (uncerta inty of a fixed value)

1 ) Wyoming represents 100 area % of the SAU

Volume % in entity m ode : 100

ALLOCATIONS OF THE SF TO GENERAL LAND OWNERSHIPS Surface Allocations (uncertainty of a fixed value)

1 ) Federal Lands r epresents 35.19 area % of the SAU

Volume % in entity m ode : 45

2 ) Private Lands r epresents 29.36 area % of the SAU

Volume % in entity m ode : 25

3 ) Tribal Lands represents 29.91 area % of the SAU

Volume % in entity m ode : 25

4 ) Other Lands represents 0.45 area % of the SAU

Volume % in entity m ode : 0.5

5 ) WY State Lands represents 5.08 area % of the SAU

Volume % in entity m ode : 4.5

ALLOCATIONS OF THE SF TO CRITICAL LAND AREAS Surface Allocations (uncert ainty of a fixed value, does not total 100%)

1 ) Urban Lands represents 0.02 area % of the SAU

Volume % in entity m inimum : 0.01 m ode : 0.02 m aximum : 0.04

2 ) Offshore Storage represents 0 area % of the SAU

Volume % in entity m ini mum : 0 m ode : 0 m aximum : 030 

## Appendix B . GIS Data Manipulations: Creating the SAU

Creating SAU boundaries can be accomplished by using a number of different spatial calculation techniques and will be dependent on the data available. These instructions are i ntended for those with experience using GIS software and specifically raster calculations.



### B .1. Required Data Rasters

[DepthTop] = Raster of depth from surface to top of formation in feet with negative values. [DepthBase] = Raster of depth from surface to base of formation in feet with negative values. [Isopach] = Raster of the thickness of the reservoir formation in feet with positive values. [WaterTDSLimit] = Raster of the depth from surface to the potable/saline water contact at 10,000 ppm (mg/ L ) TDS in feet with negative values (see section 2.3.1 for discussion). A [DepthTop] map and either an [Isopach] map or a [DepthBase] map is required initially

. With a [DepthTop] and either the [Isopach] or [DepthBase] , the final raster can be calculated. If elevati ons are relative to sea level, rather than the land surface, use a digital elevation model to add the appropriate elevation to the file. Directions below are specific to ESRI ArcGIS software

. Other spatial analysis programs are suitable.



### B .2. Creation of Required Data Rasters

To generate an [Isopach ] map from [DepthTop] and [DepthBase], use ESRI ArcGIS Spatial Analyst

raster calculator. Raster Calculator: [Isopach] = [DepthTop]

- [DepthBase] To generate a [DepthBase] map. Raster Calculator: [ DepthBase] = [DepthTop]-[Isopach]



### B.3. Generating S torage A ssessment U nit Extent and Modification of [DepthTop]

Step 1: Select area of [DepthTop] that is at depths of between 3,000 and 13,000 ft

. Raster Calculator: [ExtentDepthTop3 -13k] = [DepthTop] >= -13000 AND [DepthTop] <= -3000 Step 2: Remove area of [DepthTop] that is not at depths of between 3,000 and 13,000 ft

. Reclassify [ExtentDepthTop3 -13k] so the removed area is “NoData.” Spatial Analyst Options: Set Analysis Mask to reclassified [ExtentDepthTop 3-13k]. Raster Calculator: [DepthTop3 -13k] = [DepthTop] Step 3: Select area of [DepthTop3 -13k] that is within potable water. Raster Calculator: [ExtentDepthTop3 -13kW] = [DepthTop3- 13k] > [WaterTDSLimit] Step 4: Remove area of [DepthTop3- 13k] that is within potable water. Reclassify [ExtentDepthTop3 -13kW] so the removed area (potable water) is “NoData.” Spatial Analyst Options: Set Analysis Mask to reclassified [ExtentDepthTop3 -13kW]. Raster Calculator: [DepthTop3 -13kW] = [DepthTop] [DepthTop3-13kW] is the final product of this part of the calculation and is SAU area.31 

### B.4. Isopach Generation and Modification

Step 5: Spatial Analyst Options: Set Analysis Mask to [DepthTop3-13kW]. Raster Calculator: [Isopach3 -13kW] = [DepthTop3-13kW] – max([DepthBase], -13000) [Isopach3-13kW] is the final product of this part of the calculation and represents the thickness of the storage formation from the top of the formation to whatever is shallower: the depth to base or 13,000

feet.