Development of an Inverse Model Based on Memory-shared Parallel GA for Characterizing a Relative Permeability Curve

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2009 Vol.46, Issue 4 Preview Page Next Page

Development of an Inverse Model Based on Memory-shared Parallel GA for Characterizing a Relative Permeability Curve 상대투과도 규명을 위한 메모리분산 병렬처리 GA 역산 모델 개발: 권순일, 황상훈, 장영호, 허대기, 이원석
Sunil Kwon, Sanghoon Hwang, Youngho Jang, Daegee Huh and Wonsuk Lee

31 August 2009. pp. 431-439

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Abstract

This paper presents the development of inverse model equipped with the memory-shared parallel genetic algorithm (GA) to characterize permeability, water influx and relative permeability, simultaneously. The optimum relative permeability model is selected by GA automatically among the relative permeability models obtained by core analysis in the developed model. By utilizing that, we have estimated the permeability distribution and water influx, and selected the relative permeability model for 3-layered heterogeneous reservoir system with the observed production data during three years. This work was carried out with PC-cluster. From the results of the inverse calculation, it was found that it was converged at thirty generations, and the fitness of the best individual was 0.000112. The pressure matching results showed that the maximum relative error was 3.1% at the fifth producer, and the developed model has generated the favorable permeability distributions, water influx and relative permeability model. The process of selecting the relative permeability model was as follows; The number of individual in each node was twenty at the first generation, but it was converged into the only relative permeability model at fifth generation.

Keywords

Relative permeability

Water Influx

Reservoir characterization

Inverse calculation

Genetic algorithm

Parallel processing

PC-cluster

본 연구에서는 생산 자료의 역산을 통해 투과도, 상대투과도와 대수층 물 유입량을 규명할 수 있는 메모리분산 병렬처리 GA에 기반한 역산 모델을 개발하였다. 이 모델에서 상대투과도는 코아 분석 등을 통해 선정된 상대투과도 모델 중에서 최적의 모델을 GA가 자동으로 선택하도록 개발되었다. 개발된 모델을 3개 층으로 구성된 불균질 저류층에 적용하여 3년간 관측된 생산 자료의 역산을 통해 투과도, 상대투과도, 물 유입량을 규명하는 작업을 PC-클러스터에서 수행하였다. 역산을 수행한 결과, 30세대만에 수렴되었으며 이 때 적합도 값이 0.000112이였다. 생산 압력 매칭 결과, 생산정 5에서 최대 상대오차가 3.1%로서 산출된 상대투과도, 투과도, 물 유입량은 신뢰할 만한 결과임을 알 수 있다. 상대투과도 모델 수렴양상을 살펴보면, 1세대에서 20개씩 동일했던 개체들은 5세대만에 한 개의 상대투과도 모델로 수렴되었다.

키워드

상대투과도

물 유입량

저류층 특성 규명

역산기법

유전자알고리즘

병렬처리

PC-클러스터

References

권순일, 김현태, 허대기, 김세준, 이원석, 성원모, 2003, “병렬처리 유전자 알고리즘을 적용한 저류층 특성 역산모델 개발 및 응용,” 한국지구시스템공학회지, 제40권 5호, pp. 321-328.
박용찬, 1995, 지역적 격자 세분화 기법이 적용된 HYBOS 모델을 활용한 와다구조의 최적생산방안 도출에 관한 연구, 석사학위논문, 한양대학교, 서울, 한국.
성원모, 권오광, 서정규, 류상수, 1998, “유전자알고리즘이 적용된 상평형 모델의 개발 및 탄화수소 혼합물의 상거동 분석,” 한국자원공학회지, 제35권 6호, pp. 547-553.
유인항, 성원모, 1997, “유전자알고리즘을 이용한 자동표준곡선 중첩법에 의한 유정시험자료의 해석,” 한국자원공학회지, 제34권 2호, pp. 218-225.
한충용, 카미 세퍼누리, 2004, “병렬 프로세스 연산기법을 사용한 완전 음역 다성분 저류층”, 한국지구시스템공학회지, 제41권 3호, pp. 242-252.
Gallo, Y.L and Ravalec-Dupin, M.L., 2000, “History Matching Geostatistical Resrvoir Models with Gradual Deformation Method,” Paper SPE 62922, presented at the SPE Annual Technical Conferences and Exhibition held in Dallas, Texas, October 1-4.
Gomez, S., Gosselin, O. and Barker, J.W., 1999, “Gradient -Based History-Matching with a Global Optimization Method,” Paper SPE 56756, presented at the SPE Annual Technical Conferences and Exhibition held in Houston, Texas, October 3-6.
Guyaguler, B., Horne, R.N. and Tauzin, E., 2003, “Automated Reservoir Model Selection in Well-Test Interpretation,” SPE Reservoir Evaluation & Engineering, Vol. 6, No. 2, pp. 100-107.
Kwon, S.I., Sung, W.M., Huh, D.G. and Lee, W.S., 2007, “Characterization of Reservoir Heterogeneity Using Inverse Model Equipped with Parallel Genetic Algorithm”, Energy Sources, Vol. 29, No. 9, pp. 823-838.
Leitao, H.C. and Schiozer, D.J., 1999, “A New Automated History Matching Algorithm Improved by Parallel Computing,” Paper SPE 53977, presented at the SPE Latin American and Caribbean Petroleum Engineering Conference held in Caracas, Venezuela, April 21-23.
Ouenes, A., Weiss, W., Sultan, A.J. and Anwar, J., 1995, “Parallel Reservoir Automatic History Matching Using a Network of Workstations and PVM,” Paper SPE 29107, presented at the 13th SPE Symposium on Reservoir Simulation held in San Antonio, Texas, February 12-15.
Schiozer, D.J. and Sousa, S.H.G, 1997, “Use of External Parallelization to Improve History Matching,” Paper SPE 39062, presented at the Fifth Latin American and Caribbean Petroleum Engineering Conferences and Exhibition held in Rio de Janeiro, Brazil, August 30 - September 3.
Sung, W.M., Kwon, S.I., Huh, D.G., Kim, H.T., Kim, S.J. and Lee, W.S., 2004, “Development and Application of Inverse Model Using Genetic Algorithm for Reservoir Characterization,” Energy Sources, Vol. 26, No. 6, pp. 595-609.

Information

Publisher :The Korean Society of Mineral and Energy Resources Engineers
Publisher(Ko) :한국자원공학회
Journal Title :Journal of the Korean Society for Geosystem Engineering
Journal Title(Ko) :한국지구시스템공학회지
Volume : 46
No :4
Pages :431-439

[1] 권순일, 김현태, 허대기, 김세준, 이원석, 성원모, 2003, “병렬처리 유전자 알고리즘을 적용한 저류층 특성 역산모델 개발 및 응용,” 한국지구시스템공학회지, 제40권 5호, pp. 321-328.

[2] 박용찬, 1995, 지역적 격자 세분화 기법이 적용된 HYBOS 모델을 활용한 와다구조의 최적생산방안 도출에 관한 연구, 석사학위논문, 한양대학교, 서울, 한국.

[3] 성원모, 권오광, 서정규, 류상수, 1998, “유전자알고리즘이 적용된 상평형 모델의 개발 및 탄화수소 혼합물의 상거동 분석,” 한국자원공학회지, 제35권 6호, pp. 547-553.

[4] 유인항, 성원모, 1997, “유전자알고리즘을 이용한 자동표준곡선 중첩법에 의한 유정시험자료의 해석,” 한국자원공학회지, 제34권 2호, pp. 218-225.

[5] 한충용, 카미 세퍼누리, 2004, “병렬 프로세스 연산기법을 사용한 완전 음역 다성분 저류층”, 한국지구시스템공학회지, 제41권 3호, pp. 242-252.

[6] Gallo, Y.L and Ravalec-Dupin, M.L., 2000, “History Matching Geostatistical Resrvoir Models with Gradual Deformation Method,” Paper SPE 62922, presented at the SPE Annual Technical Conferences and Exhibition held in Dallas, Texas, October 1-4.

[7] Gomez, S., Gosselin, O. and Barker, J.W., 1999, “Gradient -Based History-Matching with a Global Optimization Method,” Paper SPE 56756, presented at the SPE Annual Technical Conferences and Exhibition held in Houston, Texas, October 3-6.

[8] Guyaguler, B., Horne, R.N. and Tauzin, E., 2003, “Automated Reservoir Model Selection in Well-Test Interpretation,” SPE Reservoir Evaluation & Engineering, Vol. 6, No. 2, pp. 100-107.

[9] Kwon, S.I., Sung, W.M., Huh, D.G. and Lee, W.S., 2007, “Characterization of Reservoir Heterogeneity Using Inverse Model Equipped with Parallel Genetic Algorithm”, Energy Sources, Vol. 29, No. 9, pp. 823-838.

[10] Leitao, H.C. and Schiozer, D.J., 1999, “A New Automated History Matching Algorithm Improved by Parallel Computing,” Paper SPE 53977, presented at the SPE Latin American and Caribbean Petroleum Engineering Conference held in Caracas, Venezuela, April 21-23.

[11] Ouenes, A., Weiss, W., Sultan, A.J. and Anwar, J., 1995, “Parallel Reservoir Automatic History Matching Using a Network of Workstations and PVM,” Paper SPE 29107, presented at the 13th SPE Symposium on Reservoir Simulation held in San Antonio, Texas, February 12-15.

[12] Schiozer, D.J. and Sousa, S.H.G, 1997, “Use of External Parallelization to Improve History Matching,” Paper SPE 39062, presented at the Fifth Latin American and Caribbean Petroleum Engineering Conferences and Exhibition held in Rio de Janeiro, Brazil, August 30 - September 3.

[13] Sung, W.M., Kwon, S.I., Huh, D.G., Kim, H.T., Kim, S.J. and Lee, W.S., 2004, “Development and Application of Inverse Model Using Genetic Algorithm for Reservoir Characterization,” Energy Sources, Vol. 26, No. 6, pp. 595-609.

Journal of the Korean Society of Mineral and Energy Resources Engineers ISSN:2288-0291(Print) 2288-2790(Online) 한국자원공학회지

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