Fracture identification based on information fusion of conventional logging and electrical imaging logging
Xiao Xiaoling1, Jin Xiuju2, Zhang Xiang1, Liu Honglei2, Jiang Yiwei2
1. Key Laboratory of Exploration Technologies for Oil and Gas Resources, Ministry of Education, Yangtze University, Wuhan, Hubei 430100, China;
2. Research Institute of Exploration & Development, Zhongyuan Oilfield Branch Co., SINOPEC, Puyang, Henan 636156, China
Abstract：Fractures cannot be well identified with conventional logging curves due to dissolved pores development and low fracture opening degree in carbonate reservoir in Sichuan Basin. We propose in this paper an approach for fracture identification based on information fusion of conventional logging and imaging logging. We first reconstruct conventional logging curves to fully amplify fracture response. And then we analyzed porosity spectrum of the electric imaging logging, and extract spectrum characteristics such as entropy and energy from the spectrum of porosity. Finally we construct a probabilistic model based on multi-information fusion for reservoir fracture identification. Comparisons with core fracture observation and imaging logging verify the effectiveness of the proposed approach.
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