基于随机孔隙网络模拟的渗透率应力敏感机理

doi:10.13278/j.cnki.jjuese.201702306

吉林大学学报(地球科学版) ›› 2017, Vol. 47 ›› Issue (2): 626-632.doi: 10.13278/j.cnki.jjuese.201702306

基于随机孔隙网络模拟的渗透率应力敏感机理

阳建平^1,2, 刘志斌¹, 喻晓琳³, 陶正武², 徐鹏⁴, 李志强¹

1. 西南石油大学油气藏地质及开发工程国家重点实验室, 成都 610500;
2. 中国石油塔里木油田分公司勘探开发研究院, 新疆库尔勒 841000;
3. 中国石油长庆油田分公司勘探开发研究院, 西安 710018;
4. 长江大学石油工程学院, 武汉 430100

收稿日期:2016-06-07 出版日期:2017-03-26 发布日期:2017-03-26
作者简介:阳建平(1974),男,高级工程师,博士,主要从事油气田开发方面的研究,E-mail:shuxingyun@163.com
基金资助:
国家重点基础研究发展计划（"973"计划）项目（2015CB250902）；油气藏地质及开发工程国家重点实验室开放式基金项目（PLN1129）

Mechanism of Permeability Stress Sensitivity Based on Random Pore Network Simulation

Yang Jianping^1,2, Liu Zhibin¹, Yu Xiaolin³, Tao Zhengwu², Xu Peng⁴, Li Zhiqiang¹

1. State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Southwest Petroleum University, Chengdu 610500, China;
2. Research Institute of Exploration and Development, Tarim Oilfield Company, PetroChina, Korla 841000, Xinjiang, China;
3. Exploration & Development Research Institute, Changqing Oilfield Company, Petrochina, Xi'an 710018, China;
4. College of Petroleum Engineering, Yangtze University, Wuhan 430100, China

Received:2016-06-07 Online:2017-03-26 Published:2017-03-26
Supported by:
Supported by the National Key Basic Research Program ("973" Program) of China (2015CB250902) and the Open Fund Projects of State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation (PLN1129)

摘要/Abstract

摘要： 储层岩石物性应力敏感研究主要停留在实验测试与数据处理方法上，无法通过单一形状孔隙的理论模型从机理上得到解释；因此，本研究基于随机孔隙网络模型实现渗透率应力敏感感机理解释。以逾渗理论、水电相似原理、Kirchoff定律为理论基础，采用迭代法，基于QT Creator平台编程生成了三维随机孔隙网络模型，并对无因次半径与有效应力的关系进行了模拟。模拟结果表明：纵横比越小，无因次半径受到有效应力的影响越明显。因此，通过网络模型建立渗透率与有效应力关系，能够实现渗透率应力敏感的机理解释。

关键词: 网络模型, 有效应力, 应力敏感

Abstract: Since the study of the reservoir rock physical property stress sensitivity mainly focus on the test and data processing method, and can't be explained on mechanism via the single shape pore theory model so far, the random pore network simulations are proposed for the rock physical property stress sensitivity mechanism explanation in the paper. Based on percolation theory, similarity principle of water and electricity, Kirchoff law, three dimensional random pore network model using iteration method is generated programmatically based on the QT Creator platform. The relationship of experiment dimensionless radius and the effective stress is simulated, and the simulation results show that smaller the aspect ratio is, the more obvious the dimensionless radius responds to the stress effect. Thus permeability stress sensitivity mechanism explanation is realized based on the relation of permeability and effective stress established using the network simulation method.

Key words: network model, effective stress, stress sensitivity

中图分类号:

TE311

阳建平, 刘志斌, 喻晓琳, 陶正武, 徐鹏, 李志强. 基于随机孔隙网络模拟的渗透率应力敏感机理[J]. 吉林大学学报(地球科学版), 2017, 47(2): 626-632.

Yang Jianping, Liu Zhibin, Yu Xiaolin, Tao Zhengwu, Xu Peng, Li Zhiqiang. Mechanism of Permeability Stress Sensitivity Based on Random Pore Network Simulation[J]. Journal of Jilin University(Earth Science Edition), 2017, 47(2): 626-632.

参考文献

[1] Tiab D,Donaldson E C. Petrophysics[M]. New York:Elsevier,2012.
[2] Li M,Bernabe Y,Xiao W L,et al. Effective Pressure Law for Permeability of E-Bei Sandstones[J].Journal of Geophysical Research:Solid Earth,2009,114(B7):223-223.
[3] Jaeger J C,Cook N G W,Zimmerman R W.Funda-mentals of Rock Mechanics[M].London:Blackwell Publishing,2007.
[4] Seeburger D A,Nur A.A Pore Space Model for Rock Permeability and Bulk Modulus[J].Journal of Geophysical Research,1984,89(B1):527-536.
[5] Yale D P.Network Modeling of Flow,Storage,and De-formation in Porous Rock[D].Stanford Calif:Stanford University,1984.
[6] Sigal R F.The Pressure Dependence of Permeability[J].Petrophysics,2002,43(2):92-102.
[7] Fredrich J T. 3D Imaging of Porous Media Using Laser Scanning Confocal Microscopy with Application to Microscale Transport Processes[J].International Journal of Rock Mechanics Sciences & Geomechanics Abstracts,1993,24(99):551-561.
[8] 陶正武.毛管压力曲线数值实验研究[D].成都:西南石油大学,2013. Tao Zhengwu.Numerical Experiments of Capillary Pressure Curve[D].Chengdu:Southwest Petroleum University,2013.
[9] 张婷,徐守余,王子敏.储层微观孔喉网络图形识别方法[J].吉林大学学报(地球科学版),2011,41(5):1646-1650. Zhang Ting,Xu Shouyu,Wang Zimin.Identificaiton Method of Reservoir Microscopic Pore-Thort Network[J].Journal of Jilin University(English Science Edition),2011,41(5):1646-1650.
[10] Tsakiroglou C D, Fleury M.Pore Network Analysis of Resistivity Index for Water-Wet Porous Media[J].Transport in Porous Media,1999,35(35):89-128.
[11] Bishop A W.The Principle of Effective Strength[J].Teknisk Ukeblad,1959,106(39):859-863.
[12] Gray W G, Schrefler B A. Thermodynamic Approach to Effective Stress in Partially Saturated Porous Media[J]. European Journal of Mechanics:A:Solids, 2001,20(4):521-538.
[13] Nuth M, Laloui L. Effective Stress Concept in Unsa-turated Soils:Clarification and Validation of a Unified Framework[J].International Journal for Numerical and Analytical Methods in Geomechanics,2008,32(7):771-801.
[14] Noble B.Applied Linear Algebra[M].New Jersey:Englewood Cliffs,1969.

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基于随机孔隙网络模拟的渗透率应力敏感机理

Mechanism of Permeability Stress Sensitivity Based on Random Pore Network Simulation

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