中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
首页 机构 成果 学者
  
  1. CAS IR Grid
  2. 地质与地球物理研究所
  3. 中国科学院地质与地球物理研究所
  4. 中国科学院油气资源研究重点实验室
Petrofacies prediction and 3-D geological model in tight gas sandstone reservoirs by integration of well logs and geostatistical modeling

文献类型：期刊论文

作者Cao, Binfeng1,2,4; Luo, Xiaorong1,2,4; Zhang, Likuan1,2,4; Lei, Yuhong1,2,4; Zhou, Jinsong3
刊名MARINE AND PETROLEUM GEOLOGY
出版日期2020-04-01
卷号114页码:25
关键词Reservoir heterogeneity Petrofacies Well log 3-D modeling Tight gas sand
ISSN号0264-8172
DOI10.1016/j.marpetgeo.2019.104202
英文摘要These effective reservoir rocks that can have sufficient porosity and permeability and hydrocarbon accumulations determine economic reserves and high yield of tight oil and gas. Understanding the origin and distribution of these effective reservoir rocks is important for sorting out "sweet spots" in tight reservoirs. Multiple-scale analyses from the microscopic, via drill core to single wellbore have been conducted to examine reservoir heterogeneity of the Upper Paleozoic Shanxi Formation in the southeastern Ordos Basin. Five sandstone petrofacies have been defined in terms of texture and framework composition, detrital matrix, diagenesis and pore types: quartz arenite, tuffaceous quartz arenite, ductile lithic-lean sub-litharenite, ductile lithic-rich sandstone and tightly carbonate-cemented sandstone. The various petrofacies show fundamentally different pathways of diagenetic and reservoir-quality evolutions, due to the complexity of texture and detrital composition in the Shanxi Formation, directly related to the provenance and depositional environment. Quartz arenites and ductile grain-lean sub-litharenites both form effective reservoir rocks. By translating petrofacies to well-log signatures corrected from petrographic and core analysis data, a model based on factor analysis has been built to predict petrofacies at the well scale. For investigating the distribution of each petrofacies at the field scale, sequential indicator simulation method has been used to construct a 3-D petrofacies model with facies conditioning. The isopach maps of quartz arenites and ductile lithic-lean sub-litharenites have been made from the 3-D petrofacies model to quantify their areal distributions, and to define the "sweet spots" by combining isopach maps of these effective reservoir rocks and gas production data from well tests. The concept of reservoir petrofacies is an important tool for the characterization of tight sandstone reservoirs.
WOS关键词ORDOS BASIN ; SECONDARY MIGRATION ; QUALITY PREDICTION ; YANCHANG FORMATION ; DIAGENETIC FACIES ; PICEANCE BASIN ; JUNGGAR BASIN ; OUTCROP ; FIELD ; HETEROGENEITY
资助项目National Science and Technology Major Project[2017ZX05008-004] ; Strategic Priority Research Program of the Chinese Academy of Sciences[XDA14010202] ; National Natural Science Foundation of China[41902135] ; China Postdoctoral Science Foundation[2018M641465]
WOS研究方向Geology
语种英语
WOS记录号WOS:000514747800011
出版者ELSEVIER SCI LTD
资助机构National Science and Technology Major Project ; National Science and Technology Major Project ; National Science and Technology Major Project ; National Science and Technology Major Project ; Strategic Priority Research Program of the Chinese Academy of Sciences ; Strategic Priority Research Program of the Chinese Academy of Sciences ; Strategic Priority Research Program of the Chinese Academy of Sciences ; Strategic Priority Research Program of the Chinese Academy of Sciences ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; China Postdoctoral Science Foundation ; China Postdoctoral Science Foundation ; China Postdoctoral Science Foundation ; China Postdoctoral Science Foundation ; National Science and Technology Major Project ; National Science and Technology Major Project ; National Science and Technology Major Project ; National Science and Technology Major Project ; Strategic Priority Research Program of the Chinese Academy of Sciences ; Strategic Priority Research Program of the Chinese Academy of Sciences ; Strategic Priority Research Program of the Chinese Academy of Sciences ; Strategic Priority Research Program of the Chinese Academy of Sciences ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; China Postdoctoral Science Foundation ; China Postdoctoral Science Foundation ; China Postdoctoral Science Foundation ; China Postdoctoral Science Foundation ; National Science and Technology Major Project ; National Science and Technology Major Project ; National Science and Technology Major Project ; National Science and Technology Major Project ; Strategic Priority Research Program of the Chinese Academy of Sciences ; Strategic Priority Research Program of the Chinese Academy of Sciences ; Strategic Priority Research Program of the Chinese Academy of Sciences ; Strategic Priority Research Program of the Chinese Academy of Sciences ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; China Postdoctoral Science Foundation ; China Postdoctoral Science Foundation ; China Postdoctoral Science Foundation ; China Postdoctoral Science Foundation ; National Science and Technology Major Project ; National Science and Technology Major Project ; National Science and Technology Major Project ; National Science and Technology Major Project ; Strategic Priority Research Program of the Chinese Academy of Sciences ; Strategic Priority Research Program of the Chinese Academy of Sciences ; Strategic Priority Research Program of the Chinese Academy of Sciences ; Strategic Priority Research Program of the Chinese Academy of Sciences ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; China Postdoctoral Science Foundation ; China Postdoctoral Science Foundation ; China Postdoctoral Science Foundation ; China Postdoctoral Science Foundation
源URL[http://ir.iggcas.ac.cn/handle/132A11/96239]  
专题地质与地球物理研究所_中国科学院油气资源研究重点实验室
通讯作者Cao, Binfeng; Luo, Xiaorong
作者单位1.Chinese Acad Sci, Inst Geol & Geophys, Beijing 100029, Peoples R China
2.Chinese Acad Sci, Innovat Acad Earth Sci, Beijing 100029, Peoples R China
3.Res Inst Shaanxi Yanchang Petr Grp Co Ltd, Xian 710075, Peoples R China
4.Chinese Acad Sci, Key Lab Petr Resources Res, Beijing 100029, Peoples R China
推荐引用方式
GB/T 7714		 Cao, Binfeng,Luo, Xiaorong,Zhang, Likuan,et al. Petrofacies prediction and 3-D geological model in tight gas sandstone reservoirs by integration of well logs and geostatistical modeling[J]. MARINE AND PETROLEUM GEOLOGY,2020,114:25.
APA Cao, Binfeng,Luo, Xiaorong,Zhang, Likuan,Lei, Yuhong,&Zhou, Jinsong.(2020).Petrofacies prediction and 3-D geological model in tight gas sandstone reservoirs by integration of well logs and geostatistical modeling.MARINE AND PETROLEUM GEOLOGY,114,25.
MLA Cao, Binfeng,et al."Petrofacies prediction and 3-D geological model in tight gas sandstone reservoirs by integration of well logs and geostatistical modeling".MARINE AND PETROLEUM GEOLOGY 114(2020):25.

入库方式： OAI收割

来源：地质与地球物理研究所

浏览0
下载0
收藏0
其他版本

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。