基于岩石物理模型的页岩储层裂缝属性及各向异性参数反演

doi:10.13278/j.cnki.jjuese.20170285

吉林大学学报(地球科学版) ›› 2018, Vol. 48 ›› Issue (4): 1244-1252.doi: 10.13278/j.cnki.jjuese.20170285

基于岩石物理模型的页岩储层裂缝属性及各向异性参数反演

张冰¹, 郭智奇¹, 徐聪², 刘财¹, 刘喜武^3,4,5, 刘宇巍^3,4,5

1. 吉林大学地球探测科学与技术学院, 长春 130026;
2. 中国电力工程顾问集团东北电力设计院有限公司, 长春 130021;
3. 页岩油气富集机理与有效开发国家重点实验室, 北京 100083;
4. 中国石化页岩油气勘探开发重点实验室, 北京 100083;
5. 中国石化石油勘探开发研究院, 北京 100083

收稿日期:2017-10-26 出版日期:2018-07-26 发布日期:2018-07-26
通讯作者: 郭智奇(1980-),男,教授,博士生导师,主要从事储层地球物理、岩石物理、各向异性地震波场正反演等方面的研究,E-mail:guozhiqi@jlu.edu.cn E-mail:guozhiqi@jlu.edu.cn
作者简介:张冰(1990-),男,博士研究生,主要从事统计岩石物理和地震反演研究,E-mail:usrzhb@hotmail.com
基金资助:
国家自然科学基金项目（41430322，41404090）；国家自然科学基金石油化工联合基金（U1663207）；“十三五”国家重大专项（2017ZX05049-002）

Fracture Properties and Anisotropic Parameters Inversion of Shales Based on Rock Physics Model

Zhang Bing¹, Guo Zhiqi¹, Xu Cong², Liu Cai¹, Liu Xiwu^3,4,5, Liu Yuwei^3,4,5

1. College of GeoExploration Science and Technology, Jilin University, Changchun 130026, China;
2. Northeast Electric Power Design Institute Co., Ltd. of China Power Engineering Consulting Group, Changchun 130021, China;
3. State Key Laboratory of Shale Oil and Gas Enrichment Mechanisms and Effective Development, Beijing 100083, China;
4. SinoPEC Key Laboratory of Shale Oil/Gas Exploration and Production Technology, Beijing 100083, China;
5. SinoPEC Petroleum Exploration and Production Research Institute, Beijing 100083, China

Received:2017-10-26 Online:2018-07-26 Published:2018-07-26
Supported by:
Supported by National Natural Science Foundation of China (41430322, 41404090), the NSFC and SinoPEC Joict key Project (U1663207) and National Key S & T Special Project of China (2017ZX05049-002)

摘要/Abstract

摘要： 针对富有机质页岩储层复杂的矿物组分与微观孔缝结构，本文提出基于岩石物理模型和改进粒子群算法的页岩储层裂缝属性及各向异性参数反演方法。应用自相容等效介质理论与Chapman多尺度孔隙理论建立裂缝型页岩双孔隙系统岩石物理模型。开发基于岩石物理模型的反演流程，引入模拟退火优化粒子群算法解决多参数同时反演问题，反演算法能够避免陷入局部极值且收敛速度快。将本文方法应用于四川盆地龙马溪组页岩气储层，反演得到的孔隙纵横比、裂缝密度等物性参数和各向异性参数与已有研究结果一致，能为页岩储层的评价提供多元化信息。

关键词: 页岩储层, 裂缝属性, 各向异性, Chapman模型, 粒子群算法, 四川盆地

Abstract: Organic-rich shale reservoirs usually have complex mineral compositions and pore system in a small scale. This study presents a workflow of the fracture properties and anisotropy parameter inversion of shales based on the rock physics model and improved particle swarm optimization algorithm. A two-pore system for fractured shales was built through applying the self-consistent equivalent medium theory and Chapman's multi-scale porosity model. This inversion workflow can be used to estimate multi-parameter simultaneously by utilizing the simulated annealing-based particle swarm optimization algorithm. The intelligence algorithm has the ability to find global optimization and fast convergence. The workflow was applied in the Longmaxi shale-gas reservoir in the Sichuan basin to estimate the aspect ratio of pores, fracture density, and anisotropy parameters. The result is consistent with the existing research and provides diversified information for the shale reservoir evaluation.

Key words: shale reservoir, fracture properties, anisotropy, Chapman's model, particle swarm optimization algorithm, Sichuan basin

中图分类号:

P631.4

张冰, 郭智奇, 徐聪, 刘财, 刘喜武, 刘宇巍. 基于岩石物理模型的页岩储层裂缝属性及各向异性参数反演[J]. 吉林大学学报(地球科学版), 2018, 48(4): 1244-1252.

Zhang Bing, Guo Zhiqi, Xu Cong, Liu Cai, Liu Xiwu, Liu Yuwei. Fracture Properties and Anisotropic Parameters Inversion of Shales Based on Rock Physics Model[J]. Journal of Jilin University(Earth Science Edition), 2018, 48(4): 1244-1252.

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基于岩石物理模型的页岩储层裂缝属性及各向异性参数反演

Fracture Properties and Anisotropic Parameters Inversion of Shales Based on Rock Physics Model

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