3D computational models for subsurface reservoir flow (simulation, data assimilation, and optimization)

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Abstract/Contents

Abstract

The data set corresponds to the two examples of the paper "History matching production data and uncertainty assessment with an efficient TSVD parameterization algorithm".
Files in Example 1 contain 200 realizations of a subsurface reservoir of dimension 30x30x3 where each layer has a different covariance matrix. Each realizations include isotropic horizontal log-permeability field, vertical log-permeability field, and porosity field. The true permeability and porosity fields and simulation parameters (e.g., well locations and controls) are also included. The goal is to generate synthetic observed data from the true model, and then apply the algorithm to update/calibrate each of the realizations such that they match production data to within some tolerance.
Example 2 contains 1500 realizations of a 28x30x3 model. This example applies ensemble-based regularization to estimate the covariance matrix within the model calibration/estimation framework.

Description

Type of resource software, multimedia
Date created 2014

Creators/Contributors

Author Shirangi, Mehrdad G.

Subjects

Subject Reservoir simulation
Subject Inverse problem
Subject History matching
Subject Levenberg–Marquardt
Subject Gauss–Newton
Subject Singular value decomposition
Subject Uncertainty quantification
Subject Data assimilation
Subject Model calibration
Subject Inference
Subject MAP estimate. Department of Energy Resources Engineering
Subject School of Earth Sciences
Subject Stanford University.
Genre Dataset

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This work is licensed under a Creative Commons Attribution 3.0 Unported license (CC BY).

Preferred citation

Preferred Citation
Shirangi, M. G. (2014). History matching production data and uncertainty assessment with an efficient TSVD parameterization algorithm. Journal of Petroleum Science and Engineering, 113, 54-71.

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