A comparative study of the probabilistic-collocation and experimental-design methods for petroleum-reservoir uncertainty quantification

SPE Journal

Volumn 16, Issue 2, 2011, Pages 429-439

  Li, Heng ^a   Sarma, Pallav ^b   Zhang, Dongxiao ^a  

^a UNIVERSITY OF SOUTHERN CALIFORNIA   (United States)

^b CHEVRON ENERGY TECHNOLOGY COMPANY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

GASOLINE; MONTE CARLO METHODS; PETROLEUM INDUSTRY; PETROLEUM RESERVOIR ENGINEERING; PROBABILITY DENSITY FUNCTION; PROBABILITY DISTRIBUTIONS; RESERVOIR MANAGEMENT; STATISTICS;

ARBITRARY DISTRIBUTION; EXPERIMENTAL DESIGN METHOD; LARGE SCALE SIMULATIONS; PROBABILISTIC COLLOCATIONS; PROBABILITY DENSITY FUNCTIONS (PDFS); RESERVOIR PERFORMANCE; UNCERTAINTY PROPAGATION; UNCERTAINTY QUANTIFICATIONS;

UNCERTAINTY ANALYSIS;

EID: 79959543322     PISSN: 1086055X     EISSN: None     Source Type: Journal    
DOI: 10.2118/140738-PA     Document Type: Article

References (18)

1. Amudo, C., Graf, T., Harris, N.R., Dandekar, R., Ben Amor, F., and May, R.S. 2008. Experimental Design and Response Surface Models as a Basis for Stochastic History Match-A Niger Delta Experience. Paper SPE 23665 presented at the International Petroleum Technology Conference, Kuala Lumpur, 3-5 December. doi: 10.2523/12665-MS.
2. Friedmann, F., Chawathe, A., and Larue, D.K. 2003. Assessing Uncertainty in Channelized Reservoirs Using Experimental Designs. SPE Res Eval & Eng 6 (4): 264-274. SPE-85117-PA. doi: 10.2118/85117-PA. (Pubitemid 37172180)
3. Gautschi, W. 1994. Algorithm 726: ORTHPOL-A Package of Routines for Generating Orthogonal Polynomials and Gauss-Type Quadrature Rules. ACM Transactions on Mathematical Software 20 (1): 21-62. doi: 10.1145/174603.174605.
4. Ghanem, R. and Spanos, P. 1991. Stochastic Finite Element: A Spectral Approach. New York: Springer-Verlag.
5. Kalla, S. and White, C.D. 2007. Efficient Design of Reservoir Simulation Studies for Development and Optimization. SPE Res Eval & Eng 10 (6): 629-637. SPE-95456-PA. doi: 10.2118/95456-PA. (Pubitemid 351188448)
6. Lawal, K.A. 2009. Modeling Subsurface Uncertainties with Experimental Design: Some Arguments of Non-Conformists. Paper SPE 128350 presented at the Nigeria International Conference and Exhibition, Abuja, Nigeria, 3-5 August. doi: 10.2118/128350-MS.
7. Li, H. and Zhang, D. 2007. Probabilistic Collocation Method for Flow in Porous Media: Comparisons With Other Stochastic Methods. Water Resources Research 43: W09409. doi: 10.1029/2006WR005673. (Pubitemid 350064084)
8. Li, H. and Zhang, D. 2009. Efficient and Accurate Quantification of Uncertainty for Multiphase Flow With Probabilistic Collocation Method. SPE J. 14 (4): 665-679. SPE-114802-PA. doi: 10.2118/114802-PA.
9. Sarma, P., Durlofsky, L.J., and Aziz, K. 2005. Efficient Closed-Loop Production Optimization Under Uncertainty. Paper SPE 94241 presented at the SPE Europec/EAGE Annual Conference, Madrid, Spain, 13-16 June. doi: 10.2118/94241-MS.
10. Schaaf, T., Coureaud, B., and Labat, N. 2008. Using Experimental Designs, Assisted History Matching Tools and Bayesian Framework to get Probabilistic Production Forecasts. Paper SPE 113498 presented at the Europec/EAGE Conference and Exhibition, Rome, 9-12 June. doi: 10.2118/113498-MS.
11. Tatang, M.A., Pan, W., Prinn, R.G., and McRae, G.J. 1997. An Efficient Method for Parametric Uncertainty Analysis of Numerical Geophysical Models. J. Geophys. Res. 102 (D18): 21925-21932. doi: 10.1029/97JD01654.
12. Tipping, D.E., Deimbacher F.X., Kovyazin, D., Medvedev, A., and Valencia, R. 2008. Experimental Design Reduces Risks of a Siberian Development With Subsurface and Financial Uncertainties. Paper SPE 115575 presented at the SPE Russian Oil and Gas Technical Conference and Exhibition, Moscow, 28-30 October. doi: 10.2118/115575-RU.
13. van Elk, J.F., Guerrera, L., Vijayan, K., and Gupta, R. 2000. Improved Uncertainty Management in Field Development Studies Through the Application of the Experimental Design Method to the Multiple Realizations Approach. Paper SPE 64462 presented at the SPE Asia Pacific Oil and Gas Conference and Exhibition, Brisbane, Australia, 16-18 October. doi: 10.2118/64462-MS.
14. Venkataraman, R. 2000. Application of the Method of Experimental Design to Quantify Uncertainty in Production Profiles. Paper SPE 59422 presented at the SPE Asia Pacific Conference on Integrated Modelling for Asset Management, Yokohoma, Japan, 25-26 April. doi: 10.2118/59422-MS.
15. Wiener, N. 1938. The Homogeneous Chaos. American Journal of Mathematics 60 (4): 897-936. doi: 10.2307/2371268.
16. Xiu, D. and Karniadakis, G.E. 2002. Modeling Uncertainty in Steady State Diffusion Problems Via Generalized Polynomial Chaos. Comput. Methods Appl. Mech. Eng. 191 (43): 4927-4948. doi: 10.1016/S0045-7825(02)00421-8. (Pubitemid 35212677)
17. Yeten, B., Castellini, A., Güyagüler, B.A., and Chen, W.H. 2005. A Comparison Study on Experimental Design and Response Surface Methodologies. Paper SPE 93347 presented at the SPE Reservoir Simulation Symposium, The Woodlands, Texas, USA, 31 January-2 February. doi: 10.2118/93347-MS.
18. Zhang, D. 2002. Stochastic Methods for Flow in Porous Media: Coping With Uncertainties. San Diego, California: Academic Press.