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  • 标题:Fracture Modeling and Productivity Prediction Technology of Shale Reservoir Based on Multivariate Data
  • 本地全文:下载
  • 作者:Yong Jie ; Qin Li ; Li Yiwe
  • 期刊名称:IOP Conference Series: Earth and Environmental Science
  • 印刷版ISSN:1755-1307
  • 电子版ISSN:1755-1315
  • 出版年度:2020
  • 卷号:474
  • 期号:5
  • 页码:1-7
  • DOI:10.1088/1755-1315/474/5/052085
  • 语种:English
  • 出版社:IOP Publishing
  • 摘要:The practice of fracture network fracturing in shale gas layers indicates that the formation of complex fracture networks is directly related to the probability of obtaining a sufficiently large reservoir to effectively rebuild the volume and the ability to obtain high economic benefits. With the continuous deepening of shale gas exploration and development, it is found that the current artificial fractures have slopes, branches and asymmetric distribution. As a result, the production difference between different horizontal wells in the same platform and different fracturing sections of the same horizontal well is obvious. How to optimize the exploration and development plan and promote the economical and effective development of shale gas resources is the most important problem currently facing. The post-evaluation technology of reservoir reconstruction effect has become a key technology. Therefore, it is of great production significance to carry out post-evaluation work by integrating multivariate data. This article takes the SiChuan WeiYuan Shale Gas Demonstration Area as an example, and uses microseismic results and surface seismic data, geology, logging, fracturing and production dynamics data to carry out fracturing fracture modeling and productivity prediction. Provided guidance for fracturing design optimization, development well location, well spacing deployment, and development effectiveness, with good application results.
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