赵建国^1,,
潘建国²,
胡洋铭¹,
李劲松³,
刘欣泽¹,
李闯²,
闫博鸿¹
1. 中国石油大学(北京)油气资源与探测国家重点实验室, 北京 102249
2. 中国石油勘探开发研究院西北分院, 兰州 730020
3. 中国石油勘探开发研究院, 北京 102258

基金项目: 国家自然科学基金面上项目"针对碳酸盐岩储层的跨频段（从地震频率-超声频率）岩石物理实验与建模研究"（41574103），"跨频段岩石物理实验与理论驱动的地震速度频散成像研究"（41974120），"基于储层岩石微观结构单元的数字岩石物理建模及弹性模拟研究"（41774130）；国家自然科学基金联合基金重点项目"莺琼盆地超高温压跨频段地震岩石物理响应机理研究"（U20B2015）；国家重大专项课题"下古生界-前寒武系地球物理勘探关键技术研究"（2016ZX05004-003）联合资助


详细信息

作者简介: 赵建国, 男, 1976年12月生, 现为中国石油大学(北京)地球物理学院教授, 主要从事地震波传播、数字岩心、跨频段地震岩石物理实验技术与理论研究.E-mail:zhaojg@cup.edu.cn; jgzhao761215@aliyun.com

中图分类号: P631

收稿日期:2020-08-29
修回日期:2021-01-02
上线日期:2021-02-10

Digital rock physics-based studies on effect of pore types on elastic properties of carbonate reservoir Part 2: Pore structure factor characterization and inversion of reservoir

ZHAO JianGuo^1,,
PAN JianGuo²,
HU YangMing¹,
LI JinSong³,
LIU XinZe¹,
LI Chuang²,
YAN BoHong¹
1. State Key Laboratory of Petroleum Resource and Prospecting, China University of Petroleum(Beijing), Beijing 102249, China
2. Northwest Branch of China Petroleum Exploration and Development Institute, Lanzhou 730020, China
3. China Petroleum Exploration and Development Institute, Beijing 102258, China


MSC: P631

--> Received Date: 29 August 2020
Revised Date: 02 January 2021
Available Online: 10 February 2021


摘要
摘要:碳酸盐岩复杂的孔隙结构如何影响其弹性性质一直是地球物理研究的难点问题，在此基础上如何半定量甚至是定量地对碳酸盐岩储层预测，特别是如何有效地获取孔隙结构参数相关的地震属性体一直是油气工业界追求的目标，本研究从数字岩心角度入手，联合测井以及地震数据尝试探究这一问题的解决方案.首先针对代表不同孔隙结构类型的有限数目的碳酸盐岩样品获得其对应的高精度数字岩心数据体，为了获得更加可靠的具有地球物理含义的弹性性质随孔隙度变化的统计规律，我们通过子网格的技术，在有限数目的碳酸盐岩数字岩心数据体上获得了大量的数字岩心子网格样本，对于每个子网格样本可以分别获得其对应的数字岩心图像孔隙度、表征孔隙软硬程度的孔隙结构参数（γ）、以及基于有限元法模拟的弹性性质，由此基于数字岩心的研究思路，我们最终获得了基于孔隙结构因子表征与分类下的弹性性质与孔隙度的定量化解释量版.与此同时，在地震尺度上通过叠前地震资料获取的纵横波及密度属性体后，基于如上获得的定量化解释量版，我们最终获得了针对碳酸盐岩储层的新的属性体——孔隙结构参数（γ）属性体，这使得在地震尺度上预测碳酸盐岩储层的孔隙结构类型成为可能，也使利用地震数据在孔隙结构参数表征与分类下的碳酸盐岩储层反演精度的提高成为可能.
关键词: 碳酸盐岩/
孔隙结构类型/
弹性性质/
数字岩心/
图像处理/
二值化

Abstract:How the complex pore structure of carbonate rock affects the elastic properties of carbonate rock has always been a difficult problem in the research of geophysics. How to make semi-quantitative or even quantitative predictions of carbonate reservoirs on this basis, and in particular how to effectively obtain pore structure parameters-related seismic property bodies have been pursued by the oil and gas industry. This study attempts to explore the solution to this problem from the perspective of digital cores, combined with well logging and seismic data. To this end, we firstly obtain high-resolution digit core data sets for a limited number of carbonate rock samples with representative pore structures, and then subgridding technique is applied to well-established digital core data sets in order to obtain a large amount of data sets of subgridding digital core, which can meet the need to analyze the relationship of elastic properties vs porosity in a statistical sense. For each subgridding digital core, we can obtain its image porosity, porosity structure factor γ to characterize pore stiffness, and finite element method-based elastic properties respectively. Subsequently, a quantitative interpretation template can be achieved to establish the relationship analysis of elastic properties vs porosity on the basis of pore structure characterization and classification. The quantitative interpretation template is then used to seismic scale V_P, V_S, and density attributes through pre-stack inversion technique, and finally a newly proposed seismic attribute-pore structure factor γ is obtained for carbonate reservoir prediction and characterization.
Key words:Carbonate/
Pore structure type/
Elastic properties/
Digital core/
Image processing/
Binarization



PDF全文下载地址:

http://www.geophy.cn/data/article/export-pdf?id=608009fcc23e67607ae103fd