Multi-resolution graph-based clustering analysis for lithofacies identifi cation from well log data: Case study of intraplatform bank gas fi elds, Amu Darya Basin

作     者：Tian Yu Xu Hong Zhang Xing-Yang Wang Hong-Jun Guo Tong-Cui Zhang Liang-Jie Gong Xing-Lin 田雨;徐洪;张兴阳;王红军;郭同翠;张良杰;龚幸林

作者机构：College of Geoscience and Surveying Engineering China University of Mining and Technology Beijing 100083 China Research Institute of Petroleum Exploration and Development CNPC Beijing 100083 China China National Oil and Gas Exploration and Development Corporation Beijing 100034 China Amu Darya Gas Company CNPC （Turkmenistan） Ashkhabad 744036 Turkmenistan 

出 版 物：《Applied Geophysics》 (应用地球物理（英文版）)

年 卷 期：2016年第13卷第4期

页      面：598-607,736页

核心收录：

学科分类：081801[工学-矿产普查与勘探] 081802[工学-地球探测与信息技术] 081803[工学-地质工程] 0707[理学-海洋科学] 08[工学] 0708[理学-地球物理学] 0818[工学-地质资源与地质工程] 0825[工学-航空宇航科学与技术] 0704[理学-天文学] 

基　　金：supported by the National Science and Technology Major Project of China(No.2011ZX05029-003) CNPC Science Research and Technology Development Project,China(No.2013D-0904) 

主　　题：Multi-resolution graph-based clustering method electrofacies lithofacies intraplatform bank gas fields Amu Darya Basin 

摘      要：In this study, we used the multi-resolution graph-based clustering （MRGC） method for determining the electrofacies （EF） and lithofacies （LF） from well log data obtained from the intraplatform bank gas fields located in the Amu Darya Basin. The MRGC could automatically determine the optimal number of clusters without prior knowledge about the structure or cluster numbers of the analyzed data set and allowed the users to control the level of detail actually needed to define the EF. Based on the LF identification and successful EF calibration using core data, an MRGC EF partition model including five clusters and a quantitative LF interpretation chart were constructed. The EF clusters 1 to 5 were interpreted as lagoon, anhydrite flat, interbank, low-energy bank, and high-energy bank, and the coincidence rate in the cored interval could reach 85%. We concluded that the MRGC could be accurately applied to predict the LF in non-cored but logged wells. Therefore, continuous EF clusters were partitioned and corresponding LF were characteristics ＆different LF were analyzed interpreted, and the distribution and petrophysical in the framework of sequence stratigraphy.