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CO2-PENS A SYSTEM MODEL FOR GEOLOGIC SEQUESTRATION OF Carbon Dioxide PHILIP H. STAUFFER HARI S. VISWANTHAN RAJESH J. PAWAR GEORGE D. GUTHRIE LA-UR 06-2116.

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Presentation on theme: "CO2-PENS A SYSTEM MODEL FOR GEOLOGIC SEQUESTRATION OF Carbon Dioxide PHILIP H. STAUFFER HARI S. VISWANTHAN RAJESH J. PAWAR GEORGE D. GUTHRIE LA-UR 06-2116."— Presentation transcript:

1 CO2-PENS A SYSTEM MODEL FOR GEOLOGIC SEQUESTRATION OF Carbon Dioxide PHILIP H. STAUFFER HARI S. VISWANTHAN RAJESH J. PAWAR GEORGE D. GUTHRIE LA-UR 06-2116

2 Talk Outline PART I –Overview of Geologic CO 2 Sequestration PART II –Description of CO2-PENS system model Part III –Example problem: Reservoir Injectivity with reduction of complexity

3 Part I Overview of Geologic CO 2 Sequestration

4 Background Warming of the earth is correlated with a rise in atmospheric CO 2 concentrations Models suggest further warming could result in many unpleasant scenarios –Rising sea level –Increased disease –Changes in ocean circulation –Loss of species

5 What can be done ? Nobel Prize winning IPCC suggests limiting further rises in CO 2 through a combination of tactics including sequestration of CO2 Sequestration can be accomplished by: –Terrestrial Sequestration (farming, trees, plankton) –Mineralization (calcium carbonate etc.) –Oceanic Sequestration –Geologic Sequestration

6 Geologic Sequestration injects CO 2 into the ground

7 Geologic Sequestration will require quantitative risk assessment

8 Quantitative risk assessment is a formal process to minimize potential consequences of long-term storage. CO 2 storage reservoir Risk assessment must consider the potential for CO 2 release and subsequent movement from storage reservoir to various receptors.

9 One goal is to minimize the potential impact to subsurface receptors. CO 2 storage reservoir other resources groundwater changes to faults

10 Another goal is to minimize the potential impact to surface receptors. CO 2 storage reservoir terrestrial ecosystems; subaqueous systems atmosphere; anthropogenic systems

11 Potential Release and Transport Mechanisms to Consider Key Features/Events/Processes –wellbore release poor (no) completion corrosion of cement or casing –release through seal fractures/faults; diffusion –lateral migration –fastpath transport (including wellbores) –porous flow (saturated and unsaturated)

12 Potential Receptor Impacts to Consider Key Features/Events/Processes –resource-reservoir impacts CO 2 migrates to another reservoir (oil, gas, pore space, etc.) –groundwater impacts CO 2 accumulation followed by water-rock interactions and transport –atmospheric impacts CO 2 return to the atmosphere mixing in atmosphere affects CO 2 level

13 Key Features/Events/Processes –geologic characteristics porosity/permeability lithologic unit(s) (chemistry; mineralogy) geologic structure heterogeneity existing fluids (brine; oil/gas) –containment characteristics vertical seal(s); horizontal seal(s) storage-unit volume –long-term reactions dissolution into brine (reverses buoyancy) reaction with reservoir rock (mineralizes) Factors to Consider –Injection wells needed; existing injection/water wells –Displacement of reservoir fluids –Change in physical conditions –Insufficient capacity

14 NOT YUCCA MOUNTAIN Will require hundreds of individual sites across the USA Orders of magnitude more CO2 than currently sequestered in Enhanced Oil Recovery –30 Tg EOR vs 5800 Tg total US emissions Limited budget at each site Less site specific data available

15 Part II Description of CO2-PENS system model

16 Performance assessment framework for geologic sequestration –From the power plant –Into the Ground –Back toward the Atmosphere Entire CO 2 sequestration analysis –System analysis yields meaningful site comparisons –Provides consistent output for Quality assurance/Quality control

17 CO2-PENS GoldSim Model Root

18 Big problem: collaborators needed for process modules. –Princeton – analytical well bore leakage –MIT – surface pipeline model –Atmospheric scientists –Economists Modular design using GoldSim=flexibility –CO 2 multiphase reactive transport codes: FEHM, PFLOTRAN, TOUGH2, Eclipse, etc. –Analytical solutions

19 Linking Process-Level Modules to a System Model geochemical reactions fluid flow CO 2 release process-level models system model (probabilistic)

20 DATA Input Current CO 2 -PENS Approach –GIS tool can extract site-specific information from databases (e.g., wellbores, reservoirs, etc.) –Data can be loaded through input boxes in GoldSim –Excel spreadsheets can be used for data input

21 GUI for Data Input

22

23 Potential Release and Transport Mechanisms to Consider Current CO 2 -PENS Approach –Analytical solution for injection OR Eclipse and FEHM reservoir simulators can be coupled –Princeton wellbore model for release/transport OR Numerical well leakage capability –Numerical fault module

24 Potential Receptor Impacts to Consider Current CO 2 -PENS Approach –tracks CO 2 accumulation and migration from wellbore release (Princeton analytical model) into overlying aquifer –couples USGS water-rock mo (PHREEQ) to calculate drinking water chemistry changes –allows boundary-layer mixing in simple analytical solution with local meteorological conditions drawn from database

25 Risk-Based Decisions –Predictions use probabilistic approach –Sampling of multidimensional solution spaces –Reduced complexity: abstraction, lookup tables –Generate distributions from experiment, modeling and expert opinion

26 Use existing knowledge : –Theory, experiment, lessons learned –Industry data (Kinder-Morgan), Weyburn, Sleipner –Performance assessment experience (Yucca Mountain, WIPP, Oil/gas, Los Alamos Environmental) –Economic experts –Risk theory experts

27 Part III Example Problem Reservoir Injectivity

28 Reduced complexity reservoir injection module Analytical single fluid approximation run as a dynamic link library from GoldSim 2-D radial, multiphase finite volume calculations used to ‘tune’ the analytical solution

29 Analytical Approximation of Injection –single fluid –no relative permeability model –uses reservoir PT CO 2 viscosity and density –infinite radius with pressure fixed at P ini –runs very quickly as a dynamic link library –can be coded in FORTRAN, C++ etc. –Reference C.S. Matthews and D.G. Russel, (1967). Pressure Buildup and Flow Tests in Wells, Society of Petroleum Engineers, Monograph Vol 1, New York.

30 FEHM 2-D Radial Simulation of Injection and Plume Growth Control volume finite element method Multiphase heat and mass transfer Relative permeability (H 2 0-CO 2 ) All constitutive relationships are in the code (e.g., density, viscosity, enthalpy)

31 Comparison of FEHM with published semi-analytical results FEHM Nordbotten et. al, (2005) 5 km x 30m deep radial grid

32 Example Assumptions

33 30 m deep fully screened reservoir No flow top and bottom boundaries Far-field at background pressure CO 2 coming from a 1 GW power plant for 50 years (230 kg/s CO 2 = 20 kt/day) Example Problem Description

34 Relative Permeability Function

35 Cold + Shallow 1 kmHot + Deep 3 km Pressure1030 MPa Temperature35155 C Max injection pressure 1545 MPa Water density999929 kg/m3 CO 2 density714479 kg/m3 Water viscosity7.2e-4 1.8e-4 Pa s CO 2 viscosity5.8e-54.0e-5 Pa s Two cases (Nordbotten et. al, 2005)

36 Linear Effective Stress Relationship minimum principle stress = 0.65 lithostatic Two cases Gives 1)maximum injection pressure 2)Reservoir background pressure

37 Tuning the Analytical Model to the Numerical Model

38 Points were simulated in FEHM to span a range of permeability and porosity Porosity Permeability mean + stdv - stdv +stdv- stdv mean 1e-14 m2 5e-15 m2 5e-14 m2 0.17 0.15 0.13

39 FEHM simulations versus analytical solution These plots yield are used to “tune” the injector code to recreate FEHM behavior in GoldSim

40 Computational time Goldsim calling the tuned analytical solution –5000 realizations in 14 minutes. Includes passing all variables through the framework, generating output and storing results. FEHM simulations, 700 nodes –5000 realizations in 4400 minutes Tuned analytical is 300+ times faster !!

41 Example Probability Distributions

42 Example Injection Results Cold-Shallow versus Hot-Deep

43 Engineering/Economic Risk Cold + Shallow 1 km Hot + Deep 3 km

44 Plume Area Cold + Shallow 1 km Hot + Deep 3 km 32 km x 32 km 22 km x 21 km

45 Health/Environmental Risk Cold + Shallow 1 km Hot + Deep 3 km

46 Engineering Risk Leakage from the Reservoir Percent per YearPercent Total Cold + Shallow 1 km

47 Conclusions Tuned analytical solution is much faster than running a reservoir solver reduced complexity will be vital for performing risk analysis Integrated approach shows interactions between different types of data and outcomes

48 THANK YOU


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