郑颖,
宗兆云,
林利明
中国石油大学(华东)地球科学与技术学院, 山东青岛 266580
基金项目: 国家自然科学基金（U1562215，41604101），国家油气重大专项课题（2017ZX05032003，2016ZX05024004，2017ZX05009001，2017ZX05036005）联合资助
详细信息
作者简介: 印兴耀, 男, 中国石油大学(华东)教授.主要从事地球物理理论与方法方面的研究.E-mail:xyyin@upc.edu.cn
中图分类号: P631 收稿日期:2017-09-12
修回日期:2019-01-03
上线日期:2019-02-15
Estimation of reservoir properties with inverse digital rock physics modeling approach
YIN XingYao,ZHENG Ying,
ZONG ZhaoYun,
LIN LiMing
School of Geosciences, China University of Petroleum, Qingdao Shandong 266580, China
MSC: P631
--> Received Date: 12 September 2017
Revised Date: 03 January 2019
Available Online: 15 February 2019
摘要
摘要:数字岩心微观孔隙结构十分复杂，有限元模拟物性参数与弹性参数之间关系是非线性的，直接反演其物性参数准确度低、稳定性差.本文发展了一种数字岩石物理逆建模方法，实现了基于数字岩心的储层参数有效预测.从数字岩心基函数的构建出发，基于有限元方法，计算了一系列具有等间距物性参数值（孔隙度、泥质含量和含水饱和度）的数字岩心弹性参数（体积模量、剪切模量和密度），通过插值算法建立了数字岩心弹性参数三维数据集，从而实现了弹性模量的有限元数值解的快速构建；然后搜索弹性参数的单值等值面，通过等值面的空间交会得到交点，完成储层参数预测.测试结果表明：基于数字岩心逆建模理论的储层参数预测结果与实际模型一致，具有可行性，并且可以通过增加插值点数目提高预测的准确性；孔隙度和泥质含量预测结果稳定性很好，而含水饱和度对噪声的加入较为敏感.
关键词: 数字岩心/
有限元法/
弹性模量/
逆建模/
储层参数
Abstract:The microstructure of the digital core is complex and the relationship between reservoir parameters and elastic parameters is nonlinear. Therefore, it is difficult to calculate the reservoir parameters directly. This paper apply the inverse rock physics modeling method to the digital core to estimate the reservoir properties. The elastic parameters of digital core with equal spacing reservoir parameters are calculated by finite element method. Then, an improved Lagrange interpolation algorithm is used to fit the calculation formula of the elastic parameters of digital cores. Based on the digital core basis function, we establish the digital core dataset in 3-D spatial domain to determine the link between the geophysical parameters and reservoir parameters, which constructs the finite element numerical solution of elastic modulus quickly. The digital core inverse modeling is to search the single value isosurface of the elastic parameters (K, μ, ρ) in 3-D database, intersect the isosurface and get the coordinates of the intersection point, which are the values of the reservoir parameters. Tests show that, the inverse digital rock physics modeling method for reservoir parameter prediction of digital cores is feasible, and the accuracy of the prediction can be improved by increasing the number of interpolation points. The prediction results of porosity and shale content are very stable, while water saturation is more sensitive to noise.
Key words:Digital core/
Finite element method/
Elastic modulus/
Inverse modeling method/
Reservoir parameters
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