Доступ предоставлен для: Guest
Портал Begell Электронная Бибилиотека e-Книги Журналы Справочники и Сборники статей Коллекции
International Journal for Uncertainty Quantification
Импакт фактор: 3.259 5-летний Импакт фактор: 2.547 SJR: 0.417 SNIP: 0.8 CiteScore™: 1.52

ISSN Печать: 2152-5080
ISSN Онлайн: 2152-5099

Свободный доступ

International Journal for Uncertainty Quantification

DOI: 10.1615/Int.J.UncertaintyQuantification.2013005281
pages 499-522


V. Ginting
Department of Mathematics, University of Wyoming, Laramie, WY 82071, USA
Felipe Pereira
Departments of Chemical and Petroleum Engineering and Mathematics, School of Energy Resources, University of Wyoming, Laramie, WY 82071, USA
A. Rahunanthan
Department of Mathematics and Computer Science, Edinboro University, Edinboro, PA 16444, USA

Краткое описание

We are concerned with the development of computationally efficient procedures for subsurface flow prediction that relies on the characterization of subsurface formations given static (measured permeability and porosity at well locations) and dynamic (measured produced fluid properties at well locations) data. We describe a predictive procedure in a Bayesian framework, which uses a single-phase flow model for characterization aiming at making prediction for a two-phase flow model. The quality of the characterization of the underlying formations is accessed through the prediction of future fluid flow production.


  1. Ma, S. and Morrow, N., Relationships between Porosity and Permeability for Porous Rocks.

  2. Sperl, J. and Trckova, J., Permeability and porosity of rocks and their relationship based on laboratory testing.

  3. Jin, M., Delshad, M., Dwarakanath, V., McKinney, D., Pope, G., Sepehrnoori, K., Tilburg, C., and Jackson, R., Partitioning tracer test for detection, estimation, and remediation performance assessment of subsurface non-aqueous phase liquids. DOI: 10.1029/95WR00174

  4. Oliver, D., Cunha, L., and Reynolds, A., Markov chain Monte Carlo methods for conditioning a permeability field to pressure data. DOI: 10.1007/BF02769620

  5. Datta-Gupta, A., Yoon, S., Barman, I., and Vasco, D., Streamline-based production-data integration into high-resolution reservoir models.

  6. Datta-Gupta, A., Streamline simulation: A technology update. DOI: 10.2118/65604-JPT

  7. Wang, Y. and Kovscek, A., Streamline approach for history matching production data. DOI: 10.2118/58350-PA

  8. Abbaszadeh-Dehghani, M. and Brigham, W., Analysis of well-to-well tracer flow to determine reservoir layering. DOI: 10.2118/10760-PA

  9. Lake, L., Enhanced Oil Recovery.

  10. Kass, W., Tracing Technique in Geohydrology.

  11. Agca, C., Pope, G., and Sepehrnoori, K., Modelling and analysis of tracer flow in oil reservoirs. DOI: 10.1016/0920-4105(90)90042-2

  12. Zemel, B., Tracers in the Oil Field.

  13. Shook, G., Ansley, S., and Wyile, A., Tracers and tracer testing: Design, implementation, and interpretation methods. DOI: 10.2172/910642

  14. Rieckermann, J., Borsuk, M., Sydler, D., Gujer, W., and Reichert, P., Bayesian experimental design of tracer studies to monitor wastewater leakage from sewer networks. DOI: 10.1029/2009WR008630

  15. Lee, H., Higdon, D., Bi, Z., Ferreira, M., and West, M., Markov random field models for high-dimensional parameters in simulations of fluid flow in porous media. DOI: 10.1198/004017002188618419

  16. Ma, X., Al-Harbi, M., Datta-Gupta, A., and Efendiev, Y., An efficient two-stage sampling method for uncertainty quantification in history matching geological models. DOI: 10.2118/102476-PA

  17. Efendiev, Y., Datta-Gupta, A., Ginting, V., Ma, X., and Mallick, B., An efficient two-stage Markov chain Monte Carlo method for dynamic data integration. DOI: 10.1029/2004WR003764

  18. Douglas, C., Efendiev, Y., Ewing, R., Ginting, V., and Lazarov, R., Dynamic data driven simulations in stochastic environments. DOI: 10.1007/s00607-006-0165-3

  19. Efendiev, Y., Hou, T., and Luo, W., Preconditioning Markov chain Monte Carlo simulations using coarse-scale models. DOI: 10.1137/050628568

  20. Loève, M., Probability theory. DOI: 10.1007/978-1-4684-9464-8

  21. Higdon, D., Lee, H., and Bi, Z., A Bayesian approach to characterizing uncertainty in inverse problems using coarse and fine-scale information. DOI: 10.1109/78.978393

  22. Fox, C. and Nicholls, G., Mardia, K., Gill, C., and Aykroyd, R. (Eds.), The art and science of Bayesian image analysis.

  23. Christen, J. A. and Fox, C., Markov chain Monte Carlo using an approximation. DOI: 10.1198/106186005X76983

  24. Ginting, V., Pereira, F., and Rahunanthan, A., Multi-stage Markov chain Monte Carlo methods for porous media flows.

  25. Pereira, F. and Rahunanthan, A., Numerical simulation of two-phase flows on a GPU.

  26. Chen, Z., Huan, G., and Ma, Y., Computational Methods for Multiphase Flows in Porous Media. DOI: 10.1137/1.9780898718942

  27. Douglas Jr., J., Furtado, F., and Pereira, F., On the numerical simulation of waterflooding of heterogeneous petroleum reservoirs. DOI: 10.1023/A:1011565228179

  28. Abreu, E., Douglas Jr., J., Furtado, F., and Pereira, F., Operator splitting based on physics for flow in porous media.

  29. Abreu, E., Douglas Jr., J., Furtado, F., and Pereira, F., Operator splitting for three-phase flow in heterogeneous porous media. DOI: 10.4208/cicp.2009.v6.p72

  30. Aquino, A., Pereira, T., Francisco, A., Pereira, F., and Amaral Souto, H., A Lagrangian strategy for the numerical simulation of radionuclide transport problems. DOI: 10.1016/j.pnucene.2009.06.018

  31. Raviart, P. and Thomas, J., A mixed finite element method for 2nd order elliptic problems, Galligani, I. and Magenes, E. (Eds.), Mathematical Aspects of Finite Element Methods. DOI: 10.1007/BFb0064451

  32. Liebmann, M., Efficient PDE solvers on modern hardware with applications in medical and technical sciences.

  33. Kurganov, A. and Tadmor, E., New high-resolution central schemes for nonlinear conservation laws and convection-diffusion equations. DOI: 10.1006/jcph.2000.6459

  34. Pereira, F. and Rahunanthan, A., A semi-discrete central scheme for the approximation of two-phase flows in three space dimensions. DOI: 10.1016/j.matcom.2011.01.012

  35. Wong, E., Stochastic Processes in Information and Dynamical Systems.

  36. Ginting, V., Pereira, F., Presho, M., and Wo, S., Application of the two-stage Markov chain Monte Carlo method for characterization of fractured reservoirs using a surrogate flow model. DOI: 10.1007/s10596-011-9236-4

  37. Dagan, G., Flow and Transport in Porous Formations. DOI: 10.1007/978-3-642-75015-1

  38. Frauenfelder, P., Schwab, C., and Todor, R., Finite elements for elliptic problems with stochastic coefficients. DOI: 10.1016/j.cma.2004.04.008

  39. Durlofsky, L., Numerical calculation of equivalent grid block permeability tensors for heterogeneous porous media. DOI: 10.1029/91WR00107

  40. Gamerman, D. and Lopes, H., Markov Chain Monte Carlo—Stochastic simulation for Bayesian inference.

  41. Vasco, D. and Datta-Gupta, A., Asymptotic solutions for solute transport: A formalism for tracer tomography. DOI: 10.1029/98WR02742

  42. Nessyahu, N. and Tadmor, E., Non-oscillatory central differencing for hyperbolic conservation laws. DOI: 10.1016/0021-9991(90)90260-8

  43. Kurganov, A. and Petrova, G., A third-order semi-discrete genuinely multidimensional central scheme for hyperbolic conservation laws and related problems. DOI: 10.1007/PL00005455

  44. Shu, C.-W. and Osher, S., Efficient implementation of essentially nonoscillatory shock-capturing schemes II. DOI: 10.1016/0021-9991(89)90222-2

Articles with similar content:

Journal of Porous Media, Vol.20, 2017, issue 12
Xiao-Ping Li, Ming-Qing Kui, Xiao-Hua Tan, Jianchao Cai
Micromechanical Analyses of Saturated Granular Soils
International Journal for Multiscale Computational Engineering, Vol.1, 2003, issue 4
R. Dobry, Mark S. Shephard, U. El Shamy, T. Abdoun, Mourad Zeghal, Jacob Fish
Second Thermal and Fluids Engineering Conference, Vol.10, 2017, issue
Bolong Ma, Brian P. Sangeorzan, Aaron S. Demers, Morgan R. Jones, Laila Guessous
Proceedings of an International Conference on Mitigation of Heat Exchanger Fouling and Its Economic and Environmental Implications, Vol.0, 1999, issue
C. B. Panchal
Journal of Porous Media, Vol.21, 2018, issue 8
Vatani Ali, Rasaei Mohammad Reza, Moqtaderi Hamed, Kakouei Aliakbar, Sedaee Sola Behnam