Assessing leakage detectability at geologic CO2 sequestration sites using the probabilistic collocation method

Advances in Water Resources

Volumn 56, Issue , 2013, Pages 49-60

  Sun, Alexander Y ^a   Zeidouni, Mehdi ^a   Nicot, Jean Philippe ^a   Lu, Zhiming ^b   Zhang, Dongxiao ^c  

^a UNIVERSITY OF TEXAS AT AUSTIN   (United States)

^b LOS ALAMOS NATIONAL LABORATORY   (United States)

^c PEKING UNIVERSITY   (China)

Author keywords

Carbon sequestration and storage; Detectability; Leakage detection; Probabilistic collocation method; Signal to noise ratio; Uncertainty quantification

Indexed keywords

CARBON SEQUESTRATION; DETECTABILITY; LEAKAGE DETECTION; PROBABILISTIC COLLOCATION METHOD; UNCERTAINTY QUANTIFICATIONS;

AQUIFERS; CARBON DIOXIDE; RISK ASSESSMENT; SIGNAL TO NOISE RATIO; STOCHASTIC MODELS; WELLS;

UNCERTAINTY ANALYSIS;

AQUIFER; CARBON DIOXIDE; CARBON SEQUESTRATION; DETECTION METHOD; FORWARD MODELING; HYDRAULIC CONDUCTIVITY; LEAKAGE; PARAMETERIZATION; PROBABILITY; QUANTITATIVE ANALYSIS; REPOSITORY; RISK ASSESSMENT; SIGNAL-TO-NOISE RATIO; STRUCTURAL GEOLOGY; UNCERTAINTY ANALYSIS;

EID: 84876319557     PISSN: 03091708     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.advwatres.2012.11.017     Document Type: Article

References (67)

1. European Union. Directive 2009/31/EC on the geological storage of carbon dioxide and amending Council Directive 85/337/EEC, European Parliament and Council Directives 2000/60/EC, 2001/80/EC, 2004/35/. European Parliament and Council, 2009.
2. US EPA. 40 CFR parts 144 and 146 federal requirements under the underground injection (UIC) program for carbon dioxide (CO2) geologic sequestration (GS) wells; Proposed Rule, 2008. p. 43492-43541.
3. NETL. Best practices for: monitoring, verification, and accounting of CO2 stored in deep geologic formations. Available at Accessed on January 3, 2012. National Energy Technology Laboratory, Pittsburgh, PA, 2009. http://www.netl.doe.gov/technologies/carbon_seq/refshelf/MVA_Document.pdf.
4. NETL. Best practices for: risk analysis and simulation for geologic storage of CO2. Available at Accessed on January 3, National Energy Technology Laboratory, Pittsburgh, PA, 2011. http://www.netl.doe.gov/technologies/carbon_seq/refshelf/BPM-SiteScreening.pdf.
5. Wickens T.D. Elementary signal detection theory 2002, Oxford University Press, Oxford, New York.
6. Taguchi G. Introduction to quality engineering: designing quality into products and processes 1986, Kraus International Publications, White Plains, NY.
7. Taguchi G, Phadke MS. Quality engineering through design optimization. In: IEEE globecom 1984 conference, Institute of Electrical and Electronics Engineers: Atlanta, GA; 1984. p. 1106-1113.
8. Taguchi G, Wu Y. Introduction to off-line quality control, Central Japan Quality Control Association, Nagaya, Japan, 1985.
9. Sun A.Y., Nicot J.P. Inversion of pressure anomaly data for detecting leakage at geologic carbon sequestration sites. Adv Water Resour 2012, 20-29.
10. 2 seepage from geologic carbon sequestration sites. Int J Greenh Gas Con 2008, 2:640-652.
11. Zeidouni M., Pooladi-Darvish M. Leakage characterization through above-zone pressure monitoring: 1 -Inversion approach. J Petrol Sci Eng 2012, 98-99:95-106.
12. Oladyshkin S., Class H., Helmig R., Nowak W. An integrative approach to robust design and probabilistic risk assessment for CO(2) storage in geological formations. Comput Geosci 2011, 15:565-577.
13. 2 storage in geologic formations. Comput Geosci 2009, 13:409-434.
14. 2 leakage through an abandoned well: problem-oriented benchmarks. Comput Geosci 2007, 11:103-115.
15. 2 leakage up through an abandoned well from deep saline aquifer to shallow fresh groundwaters. Transport Porous Med 2011, 90:153-181.
16. 2. Greenhouse Gases: Sci Technol 2011, 1:237-247.
17. 2 plume evolution during injection. Transport Porous Med 2005, 58:339-360.
18. Zhang D. Stochastic methods for flow in porous media: coping with uncertainties. Academic, San Diego, Calif. London, 2002.
19. Ganapathysubramanian B., Zabaras N. Sparse grid collocation schemes for stochastic natural convection problems. J Comput Phys 2007, 225:652-685.
20. Xiu D. Numerical methods for stochastic computations: a spectral method approach 2010, Princeton University Press, Princeton, NJ.
21. Xiu D., Karniadakis G.E. The Wiener-Askey polynomial chaos for stochastic differential equations. SIAM J Sci Comput 2002, 24:619-644.
22. Xiu D., Karniadakis G.E. Modeling uncertainty in flow simulations via generalized polynomial chaos. J Comput Phys 2003, 187:137-167.
23. Eldred M. Recent advances in non-intrusive polynomial chaos and stochastic collocation methods for uncertainty analysis and design. In: 50th AIAA/ASME/ASCE/AHS/ASC structures structural dynamics and materials conference, Palm Springs, California, 2009.
24. Ghanem R., Spanos P.D. Stochastic finite elements: a spectral approach 1991, Springer-Verlag, New York.
25. Wiener N. The homogeneous chaos. Am J Math 1938, 60:897-936.
26. Nobile F., Tempone R., Webster C.G. A sparse grid stochastic collocation method for partial differential equations with random input data. SIAM J Numer Anal 2008, 46:2309-2345.
27. Babuska I., Nobile F., Tempone R. A stochastic collocation method for elliptic partial differential equations with random input data. SIAM J Numer Anal 2007, 45:1005-1034.
28. Tatang M.A., Pan W., Prinn R.G., McRae G.J. An efficient method for parametric uncertainty analysis of numerical geophysical models. J Geophys Res 1997, 102:21925-21932.
29. Li H., Zhang D. Probabilistic collocation method for flow in porous media: comparisons with other stochastic methods. Water Resour Res 2007, 43:W09409.
30. Lin G., Tartakovsky A.M. An efficient, high-order probabilistic collocation method on sparse grids for three-dimensional flow and solute transport in randomly heterogeneous porous media. Adv Water Resour 2009, 32:712-722.
31. Shi L., Yang J., Zhang D., Li H. Probabilistic collocation method for unconfined flow in heterogeneous media. J Hydrol 2009, 365:4-10.
32. Ma X., Zabaras N. A stochastic mixed finite element heterogeneous multiscale method for flow in porous media. J Comput Phys 2011, 230:4696-4722.
33. Zhang D., Shi L., Chang H., Yang J. A comparative study of numerical approaches to risk assessment of contaminant transport. Stoch Environ Res Risk Assess 2010, 24:971-984.
34. Walter L, Binning P, Oladyshkin S, Flemisch B, Class H. Brine migration resulting from CO2 injection into saline aquifers-an approach to risk estimation including various levels of uncertainty. In: International Journal of Greenhouse Gas Control, vol. 9, Elsevier, 2012. p. 495-506.
35. Wang X.-S., Jiang X.-W., Wan L., Ge S., Li H. A new analytical solution of topography-driven flow in a drainage basin with depth-dependent anisotropy of permeability. Water Resour Res 2011, 47:W09603.
36. Szymkiewicz A., Helmig R., Kuhnke H. Two-phase flow in heterogeneous porous media with non-wetting phase trapping. Transport Porous Med 2011, 86:27-47.
37. Doughty C., Pruess K. Modeling supercritical carbon dioxide injection in heterogeneous porous media. Vadose Zone J 2004, 3:837-847.
38. 2 modeling in a deep saline aquifer: a predictive uncertainty analysis using design of experiment. Environ Sci Technol 2011, 45:3504-3510.
39. 2 sequestration. Int J Greenhouse Gas Control 2011, 5:281-293.
40. 2 storage simulation. Water Resour Res 2011, 47:W05534.
41. DOE/NETL. Best management practices for risk analysis and simulation for geologic storage of CO2. National Energy Technology Laboratory, Pittsburgh, PA, 2011.
42. Birkholzer J.T., Nicot J.P., Oldenburg C.M., Zhou Q., Kraemer S., Bandilla K. Brine flow up a well caused by pressure perturbation from geologic carbon sequestration: Static and dynamic evaluations. Int J Greenhouse Gas Control 2011, 5:850-861.
43. Nordbotten J.M., Celia M.A., Bachu S. Analytical solutions for leakage rates through abandoned wells. Water Resour Res 2004, 40.
44. 2 and brine leakage along old wells. Int J Greenhouse Gas Control 2011, 5:257-269.
45. Press W.H. Numerical recipes in C++: the art of scientific computing 2002, Cambridge University Press, Cambridge, UK, New York. 2nd ed.
46. Zhang D.X., Lu Z.M. An efficient, high-order perturbation approach for flow in random porous media via Karhunen-Loeve and polynomial expansions. J Comput Phys 2004, 194:773-794.
47. Oldenburg C.M., Bryant S.L., Nicot J.P. Certification framework based on effective trapping for geologic carbon sequestration. Int J Greenhouse Gas Control 2009, 3:444-457.
48. Li H, Chang H, Zhang D. Stochastic collocation methods for efficient and accurate quantification of uncertainty in multiphase reservoir simulations. In: SPE reservoir simulation symposium, 2-4 February 2009, Society of Petroleum Engineers the Woodlands, Texas, 2009.
49. Zeidouni M., Pooladi-Darvish M., Keith D.W. Analytical models for determining pressure change in an overlying aquifer due to leakage. Energy Proc 2011, 3833-3840.
50. Hovorka SD, Doughty C, Benson SM, Pruess K, Knox PR. The impact of geologic heterogeneity on CO2 storage in brine formations: a case study from the Texas Gulf Coast. In: Baines SJ, Worden RH, editors. Geological storage of carbon dioxide geological society, London, special publications, The Geological Society of London, London, 2004. p. 147-163.
51. Rubin Y. Applied stochastic hydrogeology 2003, Oxford University Press, Oxford, New York.
52. Sun A.Y., Zhang D. A solute flux approach to transport through bounded, unsaturated heterogeneous porous media. Vadose Zone J 2004, 3:513-526.
53. Zhang D., Andricevic R., Sun A.Y., Hu X., He G. Solute flux approach to transport through spatially nonstationary flow in porous media. Water Resour Res 2000, 36:2107-2120.
54. Nowak W., Schwede R.L., Cirpka O.A., Neuweiler I. Probability density functions of hydraulic head and velocity in three-dimensional heterogeneous porous media. Water Resour Res 2008, 44:W08452.
55. Gibbons R.D., Bhaumik D., Aryal S. Statistical methods for groundwater monitoring 2009, Wiley, Hoboken, NJ. 2nd ed.
56. EPA. Statistical analysis of groundwater monitoring data at RCRA facilities: unified guidance. EPA 530/R-09-007. EPA Office of Resource Conservation and Recovery 2009.
57. Tartakovsky D.M., Neuman S.P. Transient flow in bounded randomly heterogeneous domains: 1. Exact conditional moment equations and recursive approximations. Water Resour Res 1998, 34:1-12.
58. Zhang D., Sun A.Y. Stochastic analysis of transient saturated flow through heterogeneous fractured porous media: a double-permeability approach. Water Resour Res 2000, 36:865-874.
59. Hosder S, Perez R, Walters RW. A non-intrusive polynomial chaos method for uncertainty propagation in CFD simulations. In: 44th AIAA Aerospace Sciences Meeting and Exhibit, Reno, Nevada, 2006.
60. Sun A.Y., Morris A.P., Mohanty S. Sequential updating of multimodal hydrogeologic parameter fields using localization and clustering techniques. Water Resour Res 2009, 45.
61. Bellman R. Dynamic programming 2003, Dover Publications, Mineola, N.Y. Dover ed.
62. Mitchell R.L. Permanence of the log-normal distribution. J Opt Soc Am 1968, 58:1267-1272.
63. Tolson B.A., Shoemaker C.A. Efficient prediction uncertainty approximation in the calibration of environmental simulation models. Water Resour Res 2008, 44:W04411. 10.1029/2007WR005869.
64. Lu Z.M., Zhang D.X. Stochastic simulations for flow in nonstationary randomly heterogeneous porous media using a KL-based moment-equation approach. Multiscale Model Simul 2007, 6:228-245.
65. Caers J., Zhang T. Multiple-point geostatistics: a quantitative vehicle for integrating geologic analogs into multiple reservoir models. AAPG Mem 2004, 20:383-394.
66. Sarma P., Durlofsky L., Aziz K. Kernel principal component analysis for efficient, differentiable parameterization of multipoint geostatistics. Math Geosci 2008, 40:3-32.
67. Scheidt C., Caers J., Chen Y., Durlofsky L. A multi-resolution workflow to generate high-resolution models constrained to dynamic data. Comput Geosci 2011, 15:545-563.