An intelligent prediction method of fractures in tight carbonate reservoirs  

作　　者：DONG Shaoqun ZENG Lianbo DU Xiangyi BAO Mingyang LYU Wenya JI Chunqiu HAO Jingru 

机构地区：[1]State Key Laboratory of Petroleum Resources and Prospecting,China University of Petroleum,Beijing 102249,China [2]College of Science,China University of Petroleum,Beijing 102249,China [3]College of Geoscience,China University of Petroleum,Beijing 102249,China

出　　处：《Petroleum Exploration and Development》2022年第6期1364-1376,共13页石油勘探与开发（英文版）

基　　金：Supported by the China Youth Program of National Natural Science Foundation(42002134);The 14th Special Support Program of China Postdoctoral Science Foundation(2021T140735).

摘　　要：An intelligent prediction method for fractures in tight carbonate reservoir has been established by upgrading single-well fracture identification and interwell fracture trend prediction with artificial intelligence,modifying construction of interwell fracture density model,and modeling fracture network and making fracture property equivalence.This method deeply mines fracture information in multi-source isomerous data of different scales to reduce uncertainties of fracture prediction.Based on conventional fracture indicating parameter method,a prediction method of single-well fractures has been worked out by using 3 kinds of artificial intelligence methods to improve fracture identification accuracy from 3 aspects,small sample classification,multi-scale nonlinear feature extraction,and decreasing variance of the prediction model.Fracture prediction by artificial intelligence using seismic attributes provides many details of inter-well fractures.It is combined with fault-related fracture information predicted by numerical simulation of reservoir geomechanics to improve inter-well fracture trend prediction.An interwell fracture density model for fracture network modeling is built by coupling single-well fracture identification and interwell fracture trend through co-sequential simulation.By taking the tight carbonate reservoir of Oligocene-Miocene AS Formation of A Oilfield in Zagros Basin of the Middle East as an example,the proposed prediction method was applied and verified.The single-well fracture identification improves over 15%compared with the conventional fracture indication parameter method in accuracy rate,and the inter-well fracture prediction improves over 25%compared with the composite seismic attribute prediction.The established fracture network model is well consistent with the fluid production index.

关 键 词：fracture identification by well logs interwell fracture trend prediction interwell fracture density model fracture network model artificial intelligence tight carbonate reservoir Zagros Basin 

分 类 号：TE34[石油与天然气工程—油气田开发工程]