A History Matching Framework to Characterize Fracture Network and Reservoir Properties in Tight Oil

被引:11
作者
Xu Shiqian [1 ,2 ,3 ]
Li Yuyao [1 ,2 ]
Zhao Yu [3 ]
Wang Sen [1 ,2 ]
Feng Qihong [1 ,2 ]
机构
[1] China Univ Petr East China, Sch Petr Engn, Qingdao 266580, Peoples R China
[2] China Univ Petr East China, Key Lab Unconvent Oil & Gas Dev, Minist Educ, Qingdao 266580, Peoples R China
[3] Univ Tulsa, McDougall Sch Petr Engn, Tulsa, OK 74104 USA
来源
JOURNAL OF ENERGY RESOURCES TECHNOLOGY-TRANSACTIONS OF THE ASME | 2020年 / 142卷 / 04期
基金
中国国家自然科学基金; 中国博士后科学基金;
关键词
oil/gas reservoirs; petroleum engineering; unconventional petroleum; NUMERICAL-SIMULATION; MULTIPHASE FLOW; INTEGRATED WORKFLOW; HYDRAULIC FRACTURE; MICROSEISMIC DATA; HOUGH-TRANSFORM; OPTIMIZATION; MODEL; SHALE; WELL;
D O I
10.1115/1.4044767
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
Accurately characterizing hydraulic fracture network and tight oil reservoir properties can lay the foundation for the production forecast and development design. In this work, we proposed a history matching framework for tight oil. We first use the Hough transform method to characterize complex fracture network from microseismic data. Then, we put the fracture network into an embedded discrete fracture model (EDFM) to build a tight oil reservoir simulation model. After that, we further couple whale optimization algorithm (WOA) and EDFM to match the field production data. In this way, we can accurately estimate reservoir properties, including matrix permeability and porosity, as well as fracture permeability. We apply the framework to two-field applications in China. One is fractured vertical well in the Songliao Basin of Daqing oilfield. The other one is multi-stage fractured horizontal well in the Jimsar Sag of the Xinjiang oilfield. Results show that if we do not consider tight oil characteristics, the estimated fracture permeability, matrix permeability, and matrix porosity will underestimate 73%, 20%, and 47%, respectively. Because we apply WOA to history matching for the first time, we compare the performance of WOA with ensemble-smoother with multiple data-assimilation (ES-MDA). When we fit six parameters, ES-MDA performs better than WOA. However, when we fit three parameters, WOA performs better than ES-MDA. In addition, for engineering problem, WOA performs well on both convergence speed and stability. Therefore, WOA is recommended in the future application of history matching.
引用
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页数:13
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