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Volumn 4, Issue , 2008, Pages 2532-2550

A multistage MCMC method with nonparametric error model for efficient uncertainty quantification in history matching

Author keywords

[No Author keywords available]

Indexed keywords

EFFICIENCY; ERRORS; MARKOV PROCESSES; RESERVOIR MANAGEMENT; RESERVOIRS (WATER); SAMPLING; UNCERTAINTY ANALYSIS;

EID: 58849144371     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.2118/115911-ms     Document Type: Conference Paper
Times cited : (17)

References (26)
  • 1
    • 0034588986 scopus 로고    scopus 로고
    • Quantifying Uncertainty in Production Forecasts: Another Look at the PUNQ-S3 Problem
    • Barker, J. W. and Cuypers, M., Quantifying Uncertainty in Production Forecasts: Another Look at the PUNQ-S3 Problem, SPE 62925, 2000.
    • (2000) SPE 62925
    • Barker, J.W.1    Cuypers, M.2
  • 2
    • 84950771789 scopus 로고
    • Estimating Optimal Transformations for Multiple Regression and Correlation
    • Breiman, L. and Friedman, J.H. 1985. Estimating Optimal Transformations for Multiple Regression and Correlation. Journal of the American Statistical Association 80 (391): 580-587.
    • (1985) Journal of the American Statistical Association , vol.80 , Issue.391 , pp. 580-587
    • Breiman, L.1    Friedman, J.H.2
  • 3
    • 0032273615 scopus 로고    scopus 로고
    • General Methods for Monitoring Convergence of Iterative Simulations
    • Brooks, S. and Gelman, A. 1998. General Methods for Monitoring Convergence of Iterative Simulations. Journal of Computational and Graphical Statistics 7 (4): 434-455.
    • (1998) Journal of Computational and Graphical Statistics , vol.7 , Issue.4 , pp. 434-455
    • Brooks, S.1    Gelman, A.2
  • 4
    • 58849145519 scopus 로고
    • Computation of Sensitivity Coefficients for Conditioning the Permeability Field to Well Test Data
    • Chu, L., Reynolds, A. C. and Oliver, D. S., Computation of Sensitivity Coefficients for Conditioning the Permeability Field to Well Test Data. In Situ 18(3): 243-275, 1994.
    • (1994) In Situ , vol.18 , Issue.3 , pp. 243-275
    • Chu, L.1    Reynolds, A.C.2    Oliver, D.S.3
  • 5
    • 0030230013 scopus 로고    scopus 로고
    • Scale Up of Heterogeneous Three Dimensional Reservoir Descriptions
    • Durlofsky, L.J., Behrens, R.A., Jones, R.C., and Bemath, A. 1996. Scale Up of Heterogeneous Three Dimensional Reservoir Descriptions. SPE Journal 1(3): 313-326.
    • (1996) SPE Journal , vol.1 , Issue.3 , pp. 313-326
    • Durlofsky, L.J.1    Behrens, R.A.2    Jones, R.C.3    Bemath, A.4
  • 6
    • 0033866407 scopus 로고    scopus 로고
    • Modeling of Subgrid Effects in Coarse-scale Simulations of Transport in Heterogeneous Porous Media
    • Efendiev, Y., Durlofsky, L.J., and Lee, S.H. 2000. Modeling of Subgrid Effects in Coarse-scale Simulations of Transport in Heterogeneous Porous Media. Water Resources Research 36 (8): 2031-2041.
    • (2000) Water Resources Research , vol.36 , Issue.8 , pp. 2031-2041
    • Efendiev, Y.1    Durlofsky, L.J.2    Lee, S.H.3
  • 7
    • 58849093969 scopus 로고    scopus 로고
    • Modified MCMC for Dynamic Data Integration Using Streamline Models
    • Efendiev, Y., Datta-Gupta, A., Ma, X., and Mallick, B. 2008. Modified MCMC for Dynamic Data Integration Using Streamline Models. Mathematical Geosciences. 40:213-232.
    • (2008) Mathematical Geosciences , vol.40 , pp. 213-232
    • Efendiev, Y.1    Datta-Gupta, A.2    Ma, X.3    Mallick, B.4
  • 9
    • 84972492387 scopus 로고
    • Inference from Iterative Simulation Using Multiple Sequences
    • Gelman, A. and Rubin, D. 1992. Inference from Iterative Simulation Using Multiple Sequences. Statistical Science 7 (4): 457-511.
    • (1992) Statistical Science , vol.7 , Issue.4 , pp. 457-511
    • Gelman, A.1    Rubin, D.2
  • 10
    • 0001032163 scopus 로고
    • Evaluating the Accuracy of Sampling-Based Approaches to the Calculation of Posterior Moments
    • Geweke, J. 1992. Evaluating the Accuracy of Sampling-Based Approaches to the Calculation of Posterior Moments. Bayesian Statistics. 4 (2): 169-193.
    • (1992) Bayesian Statistics , vol.4 , Issue.2 , pp. 169-193
    • Geweke, J.1
  • 11
    • 0029413779 scopus 로고
    • Quasi-Linear Geostatistical Theory for Inversing
    • Kitanidis, P.K. 1995. Quasi-Linear Geostatistical Theory for Inversing. Water Resource Research 31 (10): 2411-2420.
    • (1995) Water Resource Research , vol.31 , Issue.10 , pp. 2411-2420
    • Kitanidis, P.K.1
  • 12
    • 77956890234 scopus 로고
    • Monte Carlo Sampling Methods Using Markov Chains and Their Applications
    • Hastings, W. 1970. Monte Carlo Sampling Methods Using Markov Chains and Their Applications. Biometrika 57 (1): 97-109.
    • (1970) Biometrika , vol.57 , Issue.1 , pp. 97-109
    • Hastings, W.1
  • 13
    • 0034000842 scopus 로고    scopus 로고
    • Gradual Deformation and Iterative Calibration of Gaussian-Related Stochastic Models
    • Hu, L.Y. 2000. Gradual Deformation and Iterative Calibration of Gaussian-Related Stochastic Models. Mathematical Geology 32(1): 87-108.
    • (2000) Mathematical Geology , vol.32 , Issue.1 , pp. 87-108
    • Hu, L.Y.1
  • 14
    • 0003981320 scopus 로고
    • Fourth edition, Berlin: Springer-Verlag
    • Loeve, M. 1977. Probability Theory. Fourth edition, Berlin: Springer-Verlag.
    • (1977) Probability Theory
    • Loeve, M.1
  • 15
    • 42549157976 scopus 로고    scopus 로고
    • An Efficient Two-Stage Sampling Method for Uncertainty Quantification in History Matching Geological Models
    • Ma, X., Al-Harbi, M., Datta-Gupta, A., and Efendiev, Y. 2008. An Efficient Two-Stage Sampling Method for Uncertainty Quantification in History Matching Geological Models. SPE Journal 13 (1): 77-87.
    • (2008) SPE Journal , vol.13 , Issue.1 , pp. 77-87
    • Ma, X.1    Al-Harbi, M.2    Datta-Gupta, A.3    Efendiev, Y.4
  • 16
    • 0018468345 scopus 로고
    • A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code
    • MacKay, M., Beckman, R., and Conover, W. 1979. A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code. Technometrics 21 (2): 239-245.
    • (1979) Technometrics , vol.21 , Issue.2 , pp. 239-245
    • MacKay, M.1    Beckman, R.2    Conover, W.3
  • 17
    • 40349089144 scopus 로고    scopus 로고
    • Streamline-Based History Matching and Uncertainty: Markov-chain Monte Carlo Study of an Offshore Turbidite Oil Field
    • Paper SPE 109943 presented at the, Anaheim, 11-14 November
    • Maucec, M., Douma, S., Hohl, D., Leguijt, J., Jimenez, E., and Datta-Gupta, A. 2007. Streamline-Based History Matching and Uncertainty: Markov-chain Monte Carlo Study of an Offshore Turbidite Oil Field. Paper SPE 109943 presented at the Annual Technical Conference and Exhibition, Anaheim, 11-14 November.
    • (2007) Annual Technical Conference and Exhibition
    • Maucec, M.1    Douma, S.2    Hohl, D.3    Leguijt, J.4    Jimenez, E.5    Datta-Gupta, A.6
  • 20
    • 0030757228 scopus 로고    scopus 로고
    • Markov Chain Monte Carlo Methods for Conditioning a Permeability Field to Pressure Data
    • Oliver, D.S., Cunha, L.B., and Reynolds, A.C. 1997. Markov Chain Monte Carlo Methods for Conditioning a Permeability Field to Pressure Data. Mathematical Geology 29 (1): 61-91.
    • (1997) Mathematical Geology , vol.29 , Issue.1 , pp. 61-91
    • Oliver, D.S.1    Cunha, L.B.2    Reynolds, A.C.3
  • 21
    • 4744376504 scopus 로고    scopus 로고
    • Improved Production Forecasts and History Matching using Approximate Fluid Flow Simulators
    • Omre, H. and Lodoen, O.P. 2004. Improved Production Forecasts and History Matching using Approximate Fluid Flow Simulators. SPE Journal 9 (3): 339-351.
    • (2004) SPE Journal , vol.9 , Issue.3 , pp. 339-351
    • Omre, H.1    Lodoen, O.P.2
  • 22
    • 0000759236 scopus 로고
    • How Many Iterations in the Gibbs Sampler?
    • Raftery, A. and Lewis, S. 1992. How Many Iterations in the Gibbs Sampler? Bayesian Statistics. 4 (2): 763-773.
    • (1992) Bayesian Statistics , vol.4 , Issue.2 , pp. 763-773
    • Raftery, A.1    Lewis, S.2
  • 24
    • 37349019755 scopus 로고    scopus 로고
    • Boa: An R Package for MCMC Output Convergence Assessment and Posterior Interference
    • Smith, J. 2007. Boa: An R Package for MCMC Output Convergence Assessment and Posterior Interference. Journal of Statistics Software 21(11): 1-37
    • (2007) Journal of Statistics Software , vol.21 , Issue.11 , pp. 1-37
    • Smith, J.1
  • 26
    • 0031171701 scopus 로고    scopus 로고
    • Optimal Transformations for Multiple Regression: Application to Permeability Estimation From Well Logs
    • Xue, G., Datta-Gupta, A., Valko, P., and Blasingame, T. 1997. Optimal Transformations for Multiple Regression: Application to Permeability Estimation From Well Logs. SPE Formation Evaluation 12 (2): 85-94.
    • (1997) SPE Formation Evaluation , vol.12 , Issue.2 , pp. 85-94
    • Xue, G.1    Datta-Gupta, A.2    Valko, P.3    Blasingame, T.4


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