Quantitative prediction of shale gas sweet spots based on seismic data in Lower Silurian Longmaxi Formation, Weiyuan area, Sichuan Basin, SW China

被引:20
作者
Zeng Qingcai [1 ]
Chen Sheng [1 ,2 ]
He Pei [1 ]
Yang Qing [1 ]
Guo Xiaolong [1 ]
Chen Peng [1 ]
Dai Chunmeng [1 ]
Li Xuan [1 ]
Gai Shaohua [1 ]
Deng Yu [1 ]
Hou Huaxing [1 ]
机构
[1] PetroChina, Res Inst Petr Explorat & Dev, Beijing 100083, Peoples R China
[2] China Univ Petr, Beijing 102249, Peoples R China
关键词
Sichuan Basin; Lower Silurian Longmaxi Formation; shale gas; sweet spots; quantitative prediction; fuzzy optimization;
D O I
10.1016/S1876-3804(18)30047-8
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Sweet spots in the shale reservoirs of the Lower Silurian Longmaxi Formation in Weiyuan 201 Block of Sichuan Basin were predicted quantitatively using seismic data and fuzzy optimization method. First, based on seismic and rock physics analysis, the rock physics characteristics of the reservoirs were determined, and elastic parameters sensitive to shale reservoirs with high gas content were selected. Second, data volumes with high precision of the elastic parameters were obtained from pre-stack simultaneous inversion. The horizontal distribution of key parameters for shale gas evaluation were calculated based on the results of rock physics analysis. Then, the fuzzy evaluation equation was established by fuzzy optimization method with test and logging data of horizontal wells with similar operation conditions. key parameters affecting the productivity of horizontal wells were sorted out and the weights of them in the sweet spots quantitative prediction were worked out by fuzzy optimization to set up a sweet spots evaluation system. Three classes of shale gas reservoirs which including two kinds of sweet spots were predicted with the above procedure, and the sweet spots have been predicted quantitatively by combining the above prediction results with the testing production. The testing results of 7 verification wells proved the reliability of the prediction results.
引用
收藏
页码:422 / 430
页数:9
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