桂俊川^1,2,,
马天寿^1,,,
陈平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. 中国石油西南油气田公司页岩气研究院, 成都 610051

基金项目: 国家自然科学基金项目（51604230，41874216）和四川省科技计划项目（20JCQN0158）资助


详细信息

作者简介: 桂俊川, 男, 1989年生, 博士后, 主要从事地球物理测井在油气井工程的应用研究.E-mail:guijunchuan@163.com

通讯作者: 马天寿, 男, 1987年生, 副研究员, 主要从事油气井工程教学与科研工作.E-mail:matianshou@126.com

中图分类号: P631

收稿日期:2019-07-04
修回日期:2020-08-09
上线日期:2020-11-05

Rock physics modeling of transversely isotropic shale: an example of the Longmaxi formation in the Sichuan basin

GUI JunChuan^1,2,,
MA TianShou^1,,,
CHEN Ping¹
1. State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Southwest Petroleum University, Chengdu 610500, China
2. Research Institute of Shale Gas, PetroChina Southwest Oil and Gasfield Company, Chengdu 610051, China


More Information

Corresponding author: MA TianShou,E-mail:matianshou@126.com

MSC: P631

--> Received Date: 04 July 2019
Revised Date: 09 August 2020
Available Online: 05 November 2020


摘要
摘要:在龙马溪页岩微观物性特征分析的基础上，综合利用测井解释、微观测试分析资料，建立了一种适用于龙马溪页岩的横观各向同性岩石物理模型，该模型建模过程：将各向异性SCA和DEM模型联合模拟得到的黏土和干酪根混合物作为背景介质；采用SCA模型对脆性矿物混合物进行模拟，利用各向异性DEM将脆性矿物混合物添加到背景介质；进一步将空孔隙添加到页岩基质，并利用Brown-Korringa模型进行各向异性条件下的流体替换，从而得到横观各向同性页岩岩石物理模型.通过对四川盆地A井龙马溪页岩进行岩石物理建模分析，计算了孔隙纵横比、纵横波速、各向异性系数和弹性参数，检验了模型的准确性.研究结果表明：矿物颗粒和孔隙纵横比是影响模型精度的关键参数，黏土和干酪根颗粒纵横比为0.05，图像识别获得的脆性矿物颗粒纵横比主要分布于0.45~1.0（集中分布于0.5~0.85），横波波速反演获得的孔隙纵横比主要分布于0.1~0.3（平均值约为0.22）；模型预测和实测纵波波速之间误差为-2.40%~2.21%（平均绝对误差仅1.20%），预测和实测横波波速之间误差为-1.93%~1.42%（平均绝对误差仅0.64%），证实了本文模型的准确性和精度.本文模型能够准确计算页岩5个独立的刚度系数，为页岩弹性参数、声波波速、各向异性和脆性分析提供了有效手段，也为后续地球物理和工程地质参数分析提供了重要依据.
关键词: 岩石物理建模/
各向异性/
横观各向同性/
SCA模型/
DEM模型/
页岩

Abstract:Based on the microscopic characteristics of the rock, a transversely isotropic rock physical model was proposed for shale in the Longmaxi formation, Sichuan Basin in terms of logging interpretation and microscopic testing data. The process of modeling is as follows: The mixture of clay and kerogen was jointly simulated by the anisotropic SCA (Self-Consistent Approximation) and DEM (Differential Effective Medium) models, which was regarded as the background medium. The SCA model was used to simulate the mixture of brittle minerals, and the mixture of brittle minerals was added into the background medium using the anisotropic DEM model. Adding the empty pores into the shale matrix to form a dry shale model, and the Brown-Korringa model was adopted to replace the fluid under anisotropic conditions. Finally a transversely isotropic rock physical model with saturated fluid was constructed. Via rock physical modeling and analysis for Longmaxi shale in well A in the Sichuan basin, this work calculated the pore aspect ratio, P- and S-wave velocity, anisotropic coefficients, and elastic parameters to verify the accuracy of the model established. The results show that the mineral particle and pore aspect ratios are the key parameters that affect the accuracy of the model. The aspect ratio of clay and kerogen particles is 0.05, that of brittle mineral particle obtained by image recognition ranges 0.45~1.0 (concentrated in 0.5~0.85), and that by S-wave velocity inversion is mainly distributed in 0.1~0.3 (with average approximately 0.22). The error between the predicted and measured P-wave velocities is between -2.40%~2.21% (with average absolute error only 1.20%), and the error between the predicted and measured S-wave velocities is between -1.93%~1.42% (only 0.64% on average), which confirms the accuracy of the model. This model can accurately calculate the five independent stiffness coefficients of shale, providing an effective measure for the analysis of elastic parameters, acoustic velocity, anisotropy and brittleness characteristics of shale formation, and important basic data for the subsequent calculation and analysis of geophysical and geotechnical parameters.
Key words:Rock physics modelling/
Anisotropy/
Transverse isotropy/
SCA model/
DEM model/
Shale



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