基于水平集的两步MCMC方法对河道形态的识别

doi:10.19596/j.cnki.1001-246x.7650

计算物理 ›› 2018, Vol. 35 ›› Issue (3): 321-329.DOI: 10.19596/j.cnki.1001-246x.7650

基于水平集的两步MCMC方法对河道形态的识别

马先林^1,2, 周德胜^1,2

1. 西安石油大学石油工程学院, 陕西西安 710065;
2. 西部低渗-特低渗油藏开发与治理教育部工程研究中心, 陕西西安 710065

收稿日期:2017-03-02 修回日期:2017-06-01 出版日期:2018-05-25 发布日期:2018-05-25
作者简介:马先林(1966-),男,博士,教授,主要从事油气田开发研究与教学工作,E-mail:Xianlinm@126.com
基金资助:
国家科技重大专项项目（2016ZX0505-0009）及陕西省自然科学基金项目（2017JM5109）资助

Identification of Channel Geometry with Level Set Based Two-stage MCMC Method

MA Xianlin^1,2, ZHOU Desheng^1,2

1. School of Petroleum Engineering, Xi'an Shiyou University, Xi'an 710065, China;
2. Engineering Research Center of Development and Management for Low to Ultra-Low Permeability Oil & Gas Reservoirs in West China, MOE, Xi'an 710065, China

Received:2017-03-02 Revised:2017-06-01 Online:2018-05-25 Published:2018-05-25

摘要/Abstract

摘要： 首先运用符号距离函数刻画河道的复杂几何形态，然后通过求解水平集演化方程和两步马尔科夫链蒙特卡罗（MCMC）算法拟合生产历史数据，逐步更新河道的边界.在两步MCMC方法的第一步，应用流线模拟计算的敏感性矩阵获取近似的似然函数，修改MCMC的推荐概率分布；第二步，为确保MCMC算法的严密性，对通过第一步的油藏模型进行完整的数值模拟以获取精准的似然函数，并用更改的接受概率作为模型接受的判断准则.最后通过二维计算实例验证该方法的有效性.

关键词: 河道几何形态, 历史拟合, 马尔科夫链蒙特卡罗, 水平集

Abstract: Channel geometry is represented by a signed distance function, and boundaries are then updated gradually by solving level set equation and matching of production historical data using two-stage Markov chain Monte Carlo (MCMC) method. In the first stage, streamline-derived sensitivities are employed to approximate a likelihood function, and instrumental proposal distribution of MCMC is modified by the approximation. In the second stage, proposals that pass the first stage are further assessed by running full numerical simulations, and a precise likelihood function is acquired. The models are checked for acceptance with modified acceptance probability. Finally, a 2D example demonstrates effectiveness of the method.

Key words: channel geometry, history matching, Markov chain Monte Carlo, level set

中图分类号:

TE319

马先林, 周德胜. 基于水平集的两步MCMC方法对河道形态的识别[J]. 计算物理, 2018, 35(3): 321-329.

MA Xianlin, ZHOU Desheng. Identification of Channel Geometry with Level Set Based Two-stage MCMC Method[J]. CHINESE JOURNAL OF COMPUTATIONAL PHYSICS, 2018, 35(3): 321-329.

参考文献

[1] QIU Y N, XUE S H, YING F X. Terrestrial oil & gas reservoir in China[M]. Beijing:Petroleum Industry Press, 1997:223-225.
[2] DEUTSCH C V, TRAN T T. Fluvsim:A program for object-based stochastic modeling of fluvial depositional systems[J]. Computers & Geosciences, 2002, 28(4):525-535.
[3] MARIETHOZ G, CAERS J. Multiple-point geostatistics:Stochastic modeling with training images[M]. Wiley-Blackwell, 2014.
[4] GILMAN J, OZGEN C. Reservoir simulation:History matching and forecasting[M]. Society of Petroleum Engineering, 2013, 1-120.
[5] HUANG T, HUANG Z Q, ZHANG J G, et al. Non-Darcy flow simulation of oil-water phase in low permeability reservoirs based on mimetic finite difference method[J]. Chinese Journal of Computational Physics, 2016, 33(6):707-716
[6] PING J, ZHANG D. History matching of channelized reservoirs with vector-based level-set parameterization[J]. SPE Journal, 2014, 19(3):1-16
[7] MORENO D, ANONSEN, S. Conditioning geological facies to production and well data using the ensemble Kalman filter and the level set method[C]. IAMG, 2015.
[8] MA X, ALHARBI M, DATTA-GUPTA A., et al. An efficient two-stage sampling method for uncertainty quantification in history matching geological models[J]. SPE Journal, 2008, 13(1):77-87.
[9] MAUCEC M, et al. Engineering workflow for probabilistic assisted history matching and production forecasting:Application to a Middle East carbonate reservoir[C]. SPE Reservoir Characterization and Simulation Conference and Exhibition,16-18 September, 2013, Abu Dhabi, UAE.
[10] OSHER S, SETHIAN J A. Fronts propagation with curvature-dependent speed:Algorithms based on Hamilton-Jacobi formulations[J]. Journal of Computational Physics, 1988, 79(1):12-49.
[11] VASCO D W, YOON S, DATTA-GUPTA A. Integrating dynamic data into high-resolution reservoir models using streamline-based analytic sensitivity coefficients[J]. SPE Journal, 1999, 4(4):389-399.
[12] DATTA-GUPTA A, KING M J. Streamline simulation:Theory and practice[M]. SPE Textbook Series, Vol. 11. Richardson, Texas, USA:Society of Petroleum Engineers, 2007.
[13] EFENDIEV Y, DATTA-GUPTA A, MA X, et al. 2008. Modified MCMC for dynamic data integration using streamline models[J]. Mathematical Geosciences, 2008, 40(2):213-232.
[14] REMY N, BOUCHER A, WU J. Applied geostatistics with SGeMS[M]. New York City:Cambridge University Press, 2009.

基于水平集的两步MCMC方法对河道形态的识别

Identification of Channel Geometry with Level Set Based Two-stage MCMC Method

RichHTML

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 9

编辑推荐

Metrics

作者中心

审稿中心

期刊浏览

期刊介绍

[1]	高普阳. 聚合物充填过程中裹气现象的数值模拟[J]. 计算物理, 2021, 38(6): 693-706.
[2]	赵玉龙, 周厚杰, 李洪玺, 文涛, 张芮菡, 张烈辉. 基于水平集方法的低渗砂岩数字岩心气水两相渗流模拟[J]. 计算物理, 2021, 38(5): 585-594.
[3]	徐建军, 史卫东, 李兴伟, 舒适. 块结构自适应网格上任意区域和任意界面的数值积分[J]. 计算物理, 2017, 34(1): 10-18.
[4]	田辉, 李国君. 改进粒子水平集法及其应用[J]. 计算物理, 2013, 30(6): 833-842.
[5]	张彬, 刘小民. 一种保持界面位置不动的水平集函数隐式重新初始化方法[J]. 计算物理, 2011, 28(5): 667-676.
[6]	程俊霞. 曲率相关的爆轰波在非结构四边形网格上的数值方法[J]. 计算物理, 2011, 28(2): 199-206.
[7]	王景焘, 张德良, 刘凯欣. 基于CE/SE方法的二维Euler型多物质流体弹塑性问题计算[J]. 计算物理, 2007, 24(4): 395-401.
[8]	葛全文. 惯性约束聚变激光烧蚀驱动内界面不稳定性数值模拟[J]. 计算物理, 2004, 21(3): 294-304.
[9]	徐军. 小尺度不可压粘性气液两相流中分界面拓扑改变的水平集方法数值模拟[J]. 计算物理, 1998, 15(3): 349-356.