Optimization Algorithms Used in Reservoir History Matching-Reference-Cited by-同舟云学术

Optimization Algorithms Used in Reservoir History Matching

Published:2013-08 Issue: Volume:748 Page:614-618
ISSN:1662-8985
Container-title:Advanced Materials Research
language:
Short-container-title:AMR

Author:

Jiang Bao Yi¹,Li Zhi Ping¹,Zhang Cheng Wen²,Wang Xi Gang³

Affiliation:

1. China University of Geosciences(BeiJing)

2. Shengli Oilfield Geophysical Corporation

3. Shengli Oilfield Logging Corporation

Abstract

Numerical reservoir models are constructed from limited available static and dynamic data, and history matching is a process of changing model parameters to find a set of values that will yield a reservoir simulation prediction of data that matches the observed historical production data. To minimize the objective function involved in the history matching procedure, we need to apply the optimization algorithms. This paper is based on the optimization algorithms used in automatic history matching. Several optimization algorithms will be compared in this paper.

Publisher

Trans Tech Publications, Ltd.

Subject

General Engineering

Link

https://www.scientific.net/AMR.748.614.pdf

Reference12 articles.

1. Baosheng Liang, A Singular Evolutive Interpolated Kalman Filter for Rapid Uncertainty Quantification, SPE Reservoir Simulation Symposium, 26-28 February (2007).

2. Roger Fletcher. Practical Methods of Optimization, John Wiley& Sons. New York, second editon. (1987).

3. Y. Abacioglu, D. S. Oliver. And A.C. Reynolds. Efficient history-matching using subspace vectors, In TUPREP Research Report 17 (May 22, 2000). Pages 69-90.

4. Fengjun Zhang, Jan Arild Skjervheim, D.S. Oliver, Automatic History Matching in a Bayesian Framework, Example Applications, SPE Reservoir Evaluation & Engineering. June 2005, pp.214-223.

5. Owe Axelsson. Iterative Solution Methods, Cambridge University Press. 40 West 20th Street. New York. NY 10011-4211, USA, (1996).