An Overview of Center for Frontiers of An Overview of Center for Frontiers of Subsurface Energy Security (CFSES)Subsurface Energy Security (CFSES)

Gary A. PopeUniversity of Texas

SciDAC-e July 14, 2010

University of Texas

July 14, 2010

Frontiers of Subsurface Energy Security

Center for Frontiers of Subsurface Energy SecurityGary. A. Pope, Director, The University of Texas

http://www utcfses org/Summary statement: Our goal is scientific understanding of subsurface physical, chemical and biological processes from the very small scale to the

http://www.utcfses.org/

g p yvery large scale so that we can predict the behavior of CO2 and other byproducts of energy production that may need to be stored in the subsurface.

RESEARCH PLAN AND DIRECTIONSRESEARCH PLAN AND DIRECTIONS• Challenges and approaches: Integrate and expand our knowledge of subsurface

phenomena across scientific disciplines using both experimental and modeling approaches to better understand and quantify behavior far from equilibrium. q y q

• Unique aspects: The uncertainty and complexity of fluids in geologic media from the molecular scale to the basin scale.

• Outcome: Predict long term behavior of subsurface storage.

U.S. Department of ENERGY-BES

CO2 Sequestration

Potential Sinks for CO2 Storage: Deep Saline Aquifers Mature Oil and Gas Fields Mature Oil and Gas Fields Deep Coal Seems

CFSES Management Structure

Highly Integrated Multidisciplinary, Multiscale, Multiprocess

GeologicalEng

PhysicsMathematics GeophysicsExploration

Characterization

ExplorationCharacterizationDiagnostics

Eng. Geology

GeomechanicsFluid Flow Waste

Earth StressesMechanicalRock/Soil Behavior

Geomechanics

Petroleum E i i

GeoHydrologyWaste isolation

HydrocarbonRecovery

Construction EngineeringCivil

Engineering

SimulationConstructionSoil Mech.

Rock Mech.Struct. Anal.

Mining Engineering

Mechanical Computer

GeochemistryMining Design/Stab, Waste,

Land Reclamation

Waste isolation

MechanicalEngineering Sciences

Drilling & Excav.,Support, Instruments

Code Development, Software Engineering

Center for Frontiers of Subsurface Energy Security (CFSES)

Multidisciplinary research goals to bridge the physical, biogeochemical and geomechanical phenomenabiogeochemical, and geomechanical phenomena across multiple scales from subpore to field scale

Interdisciplinary team of biologists, chemists, p y gcomputational scientists, engineers, geologists, and mathematicians

Integrate theory and computational methods directly Integrate theory and computational methods directly into laboratory and field studies

Address grand-challenge carbon sequestration g g qproblem

Coupled Physical and Biogeochemical Complexity at the Subpore Scale

Vision and GoalsUnderstand CO2/brine/geo/bio pore scale behavior

Research Focus Area 1

fully flexible CO2 molecular dynamics simulations; CO2 and H2O interfacial processes through MD modeling

and high PT experiments; pore scale CO2+brine fluid flow

Molecular dynamic simulation 512 CO2

molecules

CO2 – Mineral microbe reactions and transportChallenges and OpportunitiesDeveloping CT scanned column flow apparatusDeep CO2 injection test - SECARB phase 3 Deep CO2 injection test SECARB phase 3,

180 gas samples analyzed & interpreted to characterize CO2-water-rock interactions.

Accomplishment and HighlightsCharacterized microbial survival at high CO pressures

Confocal laser

Characterized microbial survival at high CO2 pressures Tested brine/CO2/Microbe reactor design.Path ForwardExperimental determination of Ca-brine/CO2/CH4 EOS

scanning image of pore-space

Measurements of metal mobilityMeasurements of microbial survival on minerals

Collaborations: Framework

CFSES is organized around 4 scales of observations coordinated to achieve integration observations, coordinated to achieve integration and synergy across these scales.

Each of the focus areas work within their scope of interest while passing out critical results to of interest, while passing out critical results to other focus areas, incorporating results, interpretations, and opportunities from others.

This concatenation of results ensures that data This concatenation of results ensures that data from one area can be upscaled (or downscaled), and that results are validated by information or investigations at other spatial and temporal g p pscales.

The organizational design compels the research focus areas to interact extensively and to ycoordinate their activities

Collaborations: X-ray CT lab

The High Resolution X-Ray CT facility at the university of Texas is a NSF multi-user laboratory f ilit th t ill b f f ti it facility that will be a focus of activity across scales.

This facility, housed in the Jackson Geosciences B ilding offe s ead access to cond ct Building, offers ready access to conduct experiments with resolutions <5m, or object sizes >30cm

Gas, water, and quartz sand in high pressure column capable of flowing sc CO2.

Paired labs using model materials and organisms with shared experimental goals allow collaboration goals allow collaboration while still taking advantage of institutional strengths.

SNL Confocal imaging lab for Biofilm on mineral surface from the UT ESEM imaging lab

SNL Confocal imaging lab for biofilms

UT-CT Facility

• Will be used for imaging scCO2/water/minerals/biofilm in static and column dynamic experimentsdynamic experiments

• XRadia MicroXCT– 150 kV Hamamatsu closed source; spot size to 4-7 µm

Cone beam data collection (up to 2048 slices)– Cone beam data collection (up to 2048 slices)– Voxel size down to 0.2 µm, line pair detection to 1.5 µm– Successfully tested with high pressure multi-phase fluids in PEEK column

In situ observations in diamond cellJung-Fu Lin

• Optical Raman/IR• X-ray Diffraction• Inelastic X ray and Brillouin spectroscopies

• Phase identification/transitions• Crystal/Local structures

S d l iti

High P-T TechniquesMineral Physics

• Inelastic X-ray and Brillouin spectroscopies• Time-resolved laser spectroscopy• X-ray Raman spectroscopy• Dynamic diamond cell with fast detectors

• Sound velocities • Transport properties (i.e., thermal)• Local electronic structures• Dynamic, kinetics of reactionsHydrothermal Diamond Cell Raman System at Jackson School Advanced Synchrotron Spectroscopies

(X-ray Raman spectra of liquid H2O)

Mechanics and Flow at the Pore-to-Continuum Scale

Vision and Goals Ch t i i t b d t l t

Research Focus Area 2

Characterizing perturbed natural systemsModeling across time and length scales Imaging flow and deformation Engineering of perturbed multiphase systems

Sandstone pores unaltered (a) and altered (b) by exposure to CO2

g gChallenges and OpportunitiesUpscaling and downscaling between pore and

continuum multiphysics Capturing nonlinear coupling, resulting feedbacks Capturing nonlinear coupling, resulting feedbacks

and emergent phenomenaAccomplishments and HighlightsNew imaging and flow labs Proof of concept of in situ CO2 foam generation

Using FEM mortars to link pore-level descriptions Proof of concept of in situ CO2 foam generation

Field investigation at Crystal Geyser, UtahMortar method for pore-to-FEM modelsPath Forward T ti h th d ti b t

p

Testing hypotheses and assumptions about multiphase flow

Integrating field, lab, and modelPore-to continuum upscaling

Coupled mechanics, reactions, flow & transport at the continuum to field scales

Vision and GoalsDevelop scientific understanding of reactivation and seepage of fluids along faults/fractures through

Research Focus Area 3

experimental and field scale characterization, modeling and monitoring

Challenges and Opportunities Characterization, modeling and monitoring of reactivation

and seepage of fluids along faultsp g g Understanding and analyzing scale up characteristics of

subsurface processes Seismic monitoring of a sequestration field site, prior,

during and post injectionAccomplishment and Highlights Di k it KS US DOEp g g Determined CO2 reservoir escape paths at Crystal Geyser

natural analog using mineralogical analysis Improved reservoir characterization using seismic for the

CO2 sequestration project at Dickman, Kansas Mathematical/statistical scale up analysis of flow processes

Dickman site, KS – US DOE funded CO2 sequestration

project

Mathematical/statistical scale-up analysis of flow processes Path Forward Analyze pressure and injection data at Cranfield site to

determine signature of faults on the data collected Develop faster cellular automata model to describe episodic

behavior of faults subject to high pressure fluid source behavior of faults subject to high-pressure fluid source.

Simulation of Multiscale, Multiphysics, Heterogeneous Systems

Vision and Goals

Research Focus Area 4

Synthesize and build upon first 3 Focus Areas Develop cutting-edge couplings across scales Model and simulate the subsurface to make long-

term, reservoir scale predictions

Challenges and Opportunities What models are needed to assess CO2 fate? How do fluids flow in damaged cap rocks? How can we be computationally efficient?

Modeling fluid flow and geomechanics

with fracturesp y

Accomplishment and Highlights Preliminary simulations of field pilot test data Multiscale and general gridding methods Simulation of flow in pervasive fractures Simulation of flow in pervasive fractures

Path Forward Work with other Tasks for needed models Create novel physics-based simulation tools

CO leakageCO2 leakage through an

abandoned well

Some Specific Objectives of Focus Area 4

Models and NumericsModeling multiphase compositional flow in realistic geometries.Modeling multiphase compositional flow in realistic geometries.Assessment of numerical accuracy via adaptive error estimators. Enhance phase behavior and physical property models.Multiscale modeling of medium heterogeneities.Modeling geomechanical effects on the medium, including

fractures.Couplings and SolversCoupling of geochemical geomechanical and geobiologicalCoupling of geochemical, geomechanical, and geobiological

multiscale processes with flow and transport. Implementation of efficient and accurate parallel multiscale and

multiphysics solvers and time-stepping.

Field studies of CO2 demonstration sites that include parameter estimation (V&V) and uncertainty quantification.

Assumptions and Governing Equations for a Gas Flooding Process

Applying Inspectional AnalysisApplying Inspectional Analysis

Assumptions:2 dimensional vertical cross section

0p p pn n n

ijjij j j ij j j ijx S x u K xt

Conservation Equations

-2 dimensional vertical cross section-3 three components (Solvent, light-oil component, heavy-oil component)-3 phases (Oil, Gas, water)-No chemical reactionsN d ti

1 1 1j j jt

( )rjj

kku P g

Darcy’s Law Equations

-No adsorption

Total number of unknowns: 21-9 compositions NpNc-3 saturations Np3 h N

( )j j jj

u P g

( )P P P j S

Capillary Pressure Equations

-3 phase pressures Np-6 Darcy velocities NpND

Total number of Equations: 21-3 conservation equations Nc6 h ilib i ti N (N 1)

( )j k ckj kjP P P j Sk

Phase Equilibrium Equations

( )RT a T-6 phase equilibrium equations Nc(Np-1)-2 capillary pressure equations Np-1-6 Darcy's law equations NpND-1 saturations sum to 1 1 -3 mole fractions sum to 1 Np n

Saturations and Mole Fractions Sum to 1

( )( )( 2 ) ( )( )

RT a TPV b V c V c b b c V b

1

1 1,cn

ij pi

x j n

1

1pn

jj

S

41 Parameters and 27 Dependent Variables41 Parameters and 27 Dependent Variables

Peng-Robinson Equation of State

RT aP ( ) ( )

Pv b v v b b v b

2 2

0.45724 ( )c

c

R Ta TP

0.07780 c

c

RTbP

1 1wTfT

w

c

fT

20.37464 1.54226 0.26992 0.49

f 2 3 0.379640 + 1.485030 - 0.164423 + 0.016666 0.49wf

Peng-Robinson Equation of State

2 220.45724

[1 (1 )]icR Ta f T 0 07780 ciRTb [1 (1 )]

i i

i

i w rc

a f TP

0.07780ici

bP

c cn n

,1 1

( )(1 )c cn n

m j ij kj i k iki k

a x x a a

,1

cn

m j ij ii

b x b

jj

P vZ

RT ,

2( )m j

j

a PA

RT ,m j

j

b PB

3 2 2 2 3( 1) ( 3 2 ) ( ) 0Z B Z A B B Z A B B B

RT 2( )j RT j RT

3 2 2 2 3( 1) ( 3 2 ) ( ) 0j j j jjj j j j j jZ B Z A B B Z A B B B

Fugacity Coefficients for Peng-Robinson EOSg y g

1

1 2212 2 1 2

cnj jji i

ij j j j mj immm j mj j j

Z BAb bLn Z Ln Z B x a Lnb a bB Z B

m j mj j j

ij ij ijf x Pij ij ijf

cNj

j ij ij

Gg n Lnf

PN

jg g1

j ij iji

g n LnfRT

1

t jj

g g

Phase Diagram for H2O-CO2 Mixture

5000

1000

2000

sia IC A 290m

H-CO2 ()

H2O ()-CO2 () Idealized Fault

500

1000

essu

re, p

s

QA

A 290m

Simulated

200

Pre PathH-CO2 (g) H2O ()-

CO2 (g)

50

100

0 20 40 60 80 100 12032 50 90

98I 710mH2O (s)-

CO2 (g)CO20 20 40 60 80 100 120

Temperature, °F

Key Issues in Storage

What is the likelihood and magnitude of CO2leakage and what are the environmental impacts?impacts?

How effective are different CO2 trapping mechanisms?

What physical geochemical and geomechanical What physical, geochemical, and geomechanical processes are important for the next few centuries and how these processes impact the storage efficacy and security?

h h d l d

drinking-water

What are the necessary models and modeling capabilities to assess the fate of injected CO2?

What are the computational needs and groundwater flow

CO2 leakage

aquiferWhat are the computational needs and capabilities to address these issues?

How these tools can be made useful and accessible to regulators and industry? 2 g

deep brine aquifer

and accessible to regulators and industry?

CO2 Sequestration Modeling Approach

Numerical simulationNumerical simulation Characterization (fault, fractures)Characterization (fault, fractures)

Appropriate griddingAppropriate gridding

Compositional EOSCompositional EOSpp

Parallel computing capabilityParallel computing capability

Key processesKey processes COCO22/brine mass transfer/brine mass transfer

Multiphase flowMultiphase flow

During injection During injection (pressure driven)(pressure driven)g jg j (p )(p )

After injection After injection (gravity driven)(gravity driven)

Geochemical reactionsGeochemical reactions Geomechanical modelingGeomechanical modeling Geomechanical modelingGeomechanical modeling

Frio CO2 Sequestration Pilot South East of USASouth East of USA

HoustonHoustonHoustonHoustonHoustonHoustonHoustonHouston

Pilot Area

High sand trend

in the Frio

Pilot Area

High sand trend

in the Frio

Large Vol. CO2 SourceSmall Vol CO2 Source

Pilot Area

High sand trend

in the Frio

Pilot Area

High sand trend

in the Frio

Large Vol. CO2 SourceSmall Vol CO2 Source

Pilot Area

High sand trend

in the Frio

Pilot Area

High sand trend

in the Frio

Large Vol. CO2 SourceSmall Vol CO2 Source

Pilot Area

High sand trend

in the Frio

Pilot Area

High sand trend

in the Frio

Large Vol. CO2 SourceSmall Vol CO2 Source

20 miles20 miles20 miles

Small Vol. CO2 Source20 miles20 miles20 miles

Small Vol. CO2 Source20 miles20 miles20 miles

Small Vol. CO2 Source20 miles20 miles20 miles

Small Vol. CO2 Source

CO2 Injection Interval

Corner Point Grid for Frio Pilot TestCorner Point Grid for Frio Pilot Test

P biliPermeability

Hysteresis Model

Modified Land’s Equation:Correlation between maximum

residual gas saturation, , and porositymaxgrS

max max1 1 1 1

grh ghgr g S SS S

1

1.2

Fontainebleau

Holtz (2002)

0 3

0.35

0.4

n

maxgrS

0.8

as s

atur

atio

n

0 15

0.2

0.25

0.3

ual g

as s

atur

atio

n grS

0.4

0.6

xim

um re

sidu

al g

a

0

0.05

0.1

0.15

Res

idu

Modified land's equationJerauld's experimentSimulated values

0.2

Max

00 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Gas saturation

5

00 0.1 0.2 0.3 0.4 0.5

Porosity, frac.

Hysteresis in Gas Relative Permeability

J ld' (1996) G R l ti P bilit M d l

Cg1g grS (shifted) S

Jerauld's (1996) Gas Relative Permeability Model

g1 g2

g grg2 gr

rg C (1 1/C )g gr

g2

S (shifted) S(1 C ) 1 S

kS (shifted) S

1 C 1 S

g grgrh gh(S S )(S S )

g gr1 S

g grgrh ghg gr

gh grh

(S S )(S S )S (shifted) S (S S )

6

Physics Based SolversPhysics Based Solvers

Heterogeneity

K Tensor

Flow Regimes

Fractures

ReinforcedReinforced

PhysicsPhysics

Heterogeneity

Multiple Physics

Flow Regimes

Well OperationsRandom GraphRandom Graph

TheoryTheory

ReinforcedReinforcedLearning

Numerical representation Insights

RandomizedRandomizedAlgorithms

MultiresolutionMultiresolutionAnalysis

MFE

CVM

MFD AMG

AML

DD

DiscretizationDiscretization

CVM

DG

MFMFE

HPCHPCSolversSolvers

DD

KrylovNumerical Solution

PhysicsPhysics--basedbasedSolversSolvers

Multimedia Dino Golgoon

MFMFE

Mortar

y

LU/ILU

Solution

Convergence Test for MFMFE on General Hexahedra

Mimetic Finite Difference Method on Polygons

Numerical Simulations of Geological Storage of Supercritical CO2 in Deep Saline Aquifers

CO2 sequestration simulation with IPARS Injection strategy on sequestration performance.Geological trapping mechanisms, permanent trapping. Solver and grid efficiency for IPARS.

CO2 phase behavoir and petrophysical process Equation of State plays a role in modeling the CO2 Equation of State plays a role in modeling the CO2.Comparison of CO2/water phase behavior model with measured data.Model CO2 solubility in water as a function of salinity. The effect of CO2 phase transition on petrophysical properties.p p p y p pCO2 dissolution into the formation brine is affected by both P and T, as

well as salinity.

Relative permeability hysteresis and interfacial tensionRelative permeability hysteresis and interfacial tension The impact of interfacial tension and pressure gradient under typical CO2

injection conditions on relative permeability and capillary pressure.Critical review of existing hysteresis models of relative permeability and

ill d i ith bli h d l b t d tcapillary pressure and comparison with published laboratory data. Implementation of a hysteretic relative permeability model in IPARS.

Enhanced Velocity Method on Locally Refined Grids for CO2 leakage Problem Grid: 5 blocks 40K elements.

11x35x12, 11x37x12, 11x9x24,11x7x24,20x40x3111x9x24,11x7x24,20x40x31

Non-matching grid Constant pressure Dirichlet BC EOS, CO2 immiscible in brine

5-block non-matching grid (fine around wells) Processor distribution (dense near wells)

EOS, CO2 immiscible in brine 24 processors

Simulation of CO2 Benchmark ProblemsSimulation of CO2 Benchmark Problems

CO2 Leakage Benchmark Problem

K = 20 mdObjectiveObjectiveQuantificationQuantification of of leakageleakage raterate in in deepdeep aquiferaquifer@2840@2840--3000 m3000 m

Leakage rate pointOutputOutput11-- LeakageLeakage raterate = %CO= %CO22 massmass flux/flux/injectioninjectionraterate22-- CO2 CO2 saturationsaturation at 1000 at 1000 daysdays

Leakage point

Mesh =0.15

P = 3.08x104 KPa

Grid: several configurationsGrid: several configurations Grid: several configurationsGrid: several configurations Fine grid near wells Fine grid near wells Constant pressure Boundary conditionConstant pressure Boundary condition Compositional modelCompositional model Parallel simulation (up to 256 processors)Parallel simulation (up to 256 processors) Parallel simulation (up to 256 processors)Parallel simulation (up to 256 processors)

Simulation results with IPARS for two cases

CO2 leakagethrough abandoned wellthrough abandoned well

CO2 saturation profile for leaky well

Fig. 3 CO2 distribution over time

Benchmark Problem 3: Permeability

Stair stepped approximation on a 50x100x100 grid (~75,000 active elements) used to derive approximate geometry and suitably interpolate properties.interpolate properties.

Permeability PERMEABILITY

True permeability field Approx. permeability field

X

Y ZPermeability

360.00340.00320.00300.00280.00260.00240.00220.00 X

Y ZPERMEABILITY

360.00340.00320.00300.00280.00260.00240.00220.00220.00

200.00180.00160.00140.00120.00100.00

80.0060.0040.00

X220.00200.00180.00160.00140.00120.00100.00

80.0060.0040.0040.00

Benchmark Problem 3: Porosity

Left: Porosity from true geometry given in a prescribed format. Right: Approximated porosity after interpolation onto a stair-step grid. Arrow

indicated injection well locationindicated injection well location.

Y ZPorosity Y ZPOROSITY

0.245

True porosity Approx. porosity

X

Y ZPorosity

0.2450.2400.2350.2300.2250.2200.2150.2100.2050.2000.195

X

Y0.2450.2400.2350.2300.2250.2200.2150.2100.2050.2000.1950.1900.195

0.1900.1850.1800.1750.1700.165

0.1900.1850.1800.1750.1700.165

Benchmark Problem 3 Results @ 50 yrs

TemperatureTemperature Gas SaturationGas Saturation

Coupled Flow and Fracture

Implemented a self-adaptive quasi-static algorithm into transient dynamic pervasive fracture codefracture code

• added velocity and frequency dependent critical damping termadapti e Ra leigh q otient to get• adaptive Rayleigh quotient to get participating natural frequency

• mesh homogenization (uniform CFL) to transmit information uniformly throughout

Mechanical fracturing results in CO2containment breach

y gthe mesh

Initial assumptions made regarding fracture models

• Assume that fractures are present and initially impermeable• Consider only fractures that run completely through the caprock• Fractures are only allowed to reactivate along specific orientations• Caprock material is modeled as a hyper-elastic material with a cohesive zone traction model for separation

Coupled Flow and Fracture

Analyses considered to date•solved single crack, variable orientation problems•angles 0 (vertical) to 45 degrees•pressure and/or displacement loading•elastic material response with cohesive zone model for fractures

Developed analytic porous flow solution for flow in fracture•quasi-steady flow initially, moving to transient (under evaluation)•network model based on lubrication theory•allows for variable aperture fractures

f•acts as pressure loading on crack faces

Leveraged development to handle multi-sided elements into EXODUS database

L d d l l h l f d V i hLeveraged development to get a general mesh tool for random Voronoi meshes

Ph 3

Cranfield Stacked Storage Field TestPhase 3:

2 observation wells, multiple injectors, 1 Mt/yrVarious monitoring toolsg

MS River

N t h MSNatchez, MS

Tuscaloosa Formation:Cranfield, MS

Cranfield Stacked Storage Field Test

New Approach

Dissolved CH4 is typically about 30 SCF/Bbl of brine Estimates of dissolved CH4 in aquifers along the Gulf Coast Estimates of dissolved CH4 in aquifers along the Gulf Coast

range from 3000 to 46,000 TCF (Griggs, 2005) compared to 238 TCF (US proven reserves) to 1,700 TCF (US total including unconventional resources)

In the 70s and 80s, researchers investigated geopressured aquifers saturated with methane (CH4)

Wells were drilled and tested The Pleasant Bayou No. 2 well produced 330 MMSCF of natural

gas from 1979 to 1983 Gladys-McCall No. 1 well produced 675 MMSCF and 27 MMbbls of

t f 1983 t 1987water from 1983 to 1987 When CO2 dissolves in brine almost all of the CH4 forms a

separate gas phase

Location of Geopressured Aquifers Along the Gulf Coast

Key Limitation to Geologic CO2 Storage: Controlling Pressure Increase During Injection

Pressure increase in aquifer is main limitation on CO2 injection rate if there is no production and if the CO2 injection rate if there is no production and if the aquifer acts like a closed system

i j t

closed storage aquiferinfinite-acting storage aq ifer

storage aquifer

injectors

constant pressure boundary

storage aquifer

pressure of

aquifer

time

constant pressure boundarypressure of

brine at boundary of

storage aquifer

boundary

closed storage

infinite-acting storage aquifer

q

time

closed storage aquifer

Applying the “Surface Dissolution*” Concept Provides Constant Pressure Boundary AND Reduces Injection, Compression Costs

Coal-fired Power Plant

CO2

Pressurized Mixing

SURFACE DISSOLUTION

CH4

BrineDense CO2B i / 2

Saturated Brine2000-6000ft12000-18000 ft

Brine w/ dissolved

CH4

Brine Geopressured Aquifer

pBrine Formation

*Modified from Burton and Bryant, SPEJ 2009

Questions

What fraction of the methane can be produced and at what ratesproduced and at what rates

What is the total volume of CH4 that can be produced and the total volume CO2 that can produced and the total volume CO2 that can be stored in geopressured aquifers

What is the best strategy for injecting CO2gy j g 2and producing CH4

What is the economic benefit of producing CH4 and/or geothermal brine saturated with CH4

What are the most important problems

Methane bank after 730 Days

Partial List of Complications and Uncertainties

Produced CH4 mixed with CO2

Aquifer heterogeneities faults barriers Aquifer heterogeneities, faults, barriers, ...

Relative permeability hysteresis/gas trapping

Impurities in injected CO2

Uncertainties in aquifer size and properties

Pipe scaling and plugging by reservoir brine

Uncertainties in how to operate wellsp

Uncertainties in cost to operate

Uncertainties in government regulations and Uncertainties in government regulations and incentives

CFSES External Activities

A Teacher Workshop on “The Role of pComputation in Protecting the Environment: A Workshop on Carbon Sequestration Simulation for High School Mathematics and Science for High School Mathematics and Science Teachers.”

June 15-16, 2010 hosted by

M. Wheeler, M. Delshad, T. Arbogast, and I. Duncan

Funded by NSF and DOE

Outreach Program

SciDAC-e Projects

Patrick Knupp : “Mesh generation for modeling andPatrick Knupp : “Mesh generation for modeling and simulations of carbon sequestration processes”

Michael Heroux: “Algebraic multi-grid methods for modeling, simulation and uncertainty quantification ofmodeling, simulation and uncertainty quantification of carbon sequestration processes on multi-core architectures”