Data-Driven Proxy Models for Assisted History Matching of SAGD Reservoirs

[1]  D. Oliver,et al.  Recent progress on reservoir history matching: a review , 2011 .

[2]  Rolf Johan Lorentzen,et al.  Underbalanced and Low-head Drilling Operations: Real Time Interpretation of Measured Data and Operational Support , 2001 .

[3]  G. Evensen,et al.  Analysis Scheme in the Ensemble Kalman Filter , 1998 .

[4]  L. Dake.  Fundamentals of Reservoir Engineering , 1983 .

[5]  S. Isukapalli.  UNCERTAINTY ANALYSIS OF TRANSPORT-TRANSFORMATION MODELS , 1999 .

[6]  Thomas Graf,et al.  Proxy Modeling in Production Optimization , 2006 .

[7]  Jan Dirk Jansen,et al.  Improved Reservoir Management Through Optimal Control and Continuous Model Updating , 2004 .

[8]  Olivier Gosselin,et al.  Gradient-Based History Matching With a Global Optimization Method , 2001 .

[9]  Michael Andrew Christie,et al.  Multiple history-matched models for Teal South , 2002 .

[10]  Zukui Li,et al.  Reservoir Geological Uncertainty Reduction: an Optimization-Based Method Using Multiple Static Measures , 2015, Mathematical Geosciences.

[11]  Assessment of Optimal Operating Conditions in a SAGD Project by Design of Experiments and Response Surface Methodology , 2008 .

[12]  Cheong Yaw Peng,et al.  Experimental Design and Analysis Methods in Multiple Deterministic Modelling for Quantifying Hydrocarbon In-Place Probability Distribution Curve , 2004 .

[13]  C. D. Gelatt,et al.  Optimization by Simulated Annealing , 1983, Science.

[14]  Ning Liu,et al.  Inverse Theory for Petroleum Reservoir Characterization and History Matching , 2008 .

[15]  Dean S. Oliver,et al.  THE ENSEMBLE KALMAN FILTER IN RESERVOIR ENGINEERING-A REVIEW , 2009 .

[16]  Sirish L. Shah,et al.  Application of the Ensemble Kalman Filter for Characterization and History Matching of Unconventional Oil Reservoirs , 2010 .

[17]  Baoyan Li,et al.  Semiautomatic Multiple Resolution Design for History Matching , 2007 .

[18]  M. Marietta,et al.  Pilot Point Methodology for Automated Calibration of an Ensemble of conditionally Simulated Transmissivity Fields: 1. Theory and Computational Experiments , 1995 .

[19]  siavash nejadi,et al.  Re-Sampling the Ensemble Kalman Filter for Improved History Matching and Characterizations of Non-Gaussian and Non-Linear Reservoir Models , 2015 .

[20]  Baosheng Liang,et al.  An ensemble Kalman filter module for automatic history matching , 2007 .

[21]  Denis José Schiozer,et al.  Application of artificial neural networks in a history matching process , 2014 .

[22]  R. Ghanem,et al.  Stochastic Finite Elements: A Spectral Approach , 1990 .

[23]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[24]  Ehsan Amirian,et al.  An Integrated Application of Cluster Analysis and Artificial Neural Networks for SAGD Recovery Performance Prediction in Heterogeneous Reservoirs , 2014 .

[25]  I. Pan,et al.  Robust optimization of subsurface flow using polynomial chaos and response surface surrogates , 2015, Computational Geosciences.

[26]  P. Houtekamer,et al.  An Adaptive Ensemble Kalman Filter , 2000 .

[27]  Genbao Shi,et al.  Improved and More Rapid History Matching With a Nonlinear Proxy and Global Optimization , 2006 .

[28]  Kok-Kwang Phoon,et al.  Convergence study of the truncated Karhunen–Loeve expansion for simulation of stochastic processes , 2001 .

[29]  Alberto Guadagnini,et al.  Use of global sensitivity analysis and polynomial chaos expansion for interpretation of nonreactive transport experiments in laboratory‐scale porous media , 2011 .

[30]  Geir Nævdal,et al.  Reservoir Monitoring and Continuous Model Updating Using Ensemble Kalman Filter , 2005 .

[31]  B. Li,et al.  Novel Multiple Resolutions Design of Experiment/Response Surface Methodology for Uncertainty Analysis of Reservoir Simulation Forecasts , 2005 .

[32]  Adam James H. Little,et al.  Modern Approach to Estimation of Uncertainty of Predictions With Dynamic Reservoir Simulation - A Case Study of a German Rotliegend Gasfield , 2006 .

[33]  Sergey Oladyshkin,et al.  Polynomial Response Surfaces for Probabilistic Risk Assessment and Risk Control via Robust Design , 2012 .

[34]  David S. Broomhead,et al.  Multivariable Functional Interpolation and Adaptive Networks , 1988, Complex Syst..

[35]  B. Jafarpour,et al.  History matching with an ensemble Kalman filter and discrete cosine parameterization , 2008 .

[36]  Geir Evensen,et al.  History Matching Using the Ensemble Kalman Filter on a North Sea Field Case , 2008 .

[37]  Salvador Pintos,et al.  Surrogate modeling-based optimization of SAGD processes , 2002 .

[38]  P. A. Slotte,et al.  Response Surface Methodology Approach for History Matching and Uncertainty Assessment of Reservoir Simulation Models , 2008 .

[39]  G. Evensen.  Sequential data assimilation with a nonlinear quasi‐geostrophic model using Monte Carlo methods to forecast error statistics , 1994 .

[40]  Dean S. Oliver,et al.  Reparameterization Techniques for Generating Reservoir Descriptions Conditioned to Variograms and Well-Test Pressure Data , 1996 .

[41]  H. Bazargan.  An efficient polynomial chaos-based proxy model for history matching and uncertainty quantification of complex geological structures , 2014 .

[42]  Zukui Li,et al.  Initial Sampling of Ensemble for Steam-Assisted-Gravity-Drainage-Reservoir History Matching , 2015 .