Weak signal identification in microseismic monitoring with multi-scale morphology
Li Huijian1,2, Wang Runqiu1,2, Cao Siyuan1,2, Yao Xinrui1,2, Wang Fanglin3, Sun Lipeng1,2
1. State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum(Beijing), Beijing 102249, China;
2. CNPC Key Laboratory of Geophysical Exploration, China University of Petroleum(Beijing), Beijing 102249, China;
3. Geophysics Research Institute of Jiangsu Oilfield Branch Co., SINOPEC, Nanjing, Jiangsu 210046, China
Abstract：Data acquired by borehole microseismic monitoring is characterized by low signal-to-noise ratio and weak energy. So it is very difficult to identify signals. We propose in this paper a multi-scale morphological approach for weak signal identification. There are some small difference in amplitude and duration between noise and signal, Therefore it can be carried out in digital analysis based on morphology. This approach decomposes data morphological characteristics, and analyzes waveform shape variance details. With different-scale structural elements, the original data can be decomposed into different scales. Then characteristics of weak signals and noise in different scales are identified and noise would be eliminated. Examples of both synthetic and real data show that the proposed approach can identify weak signals and suppress noise, which proves the effectiveness and practicability of the proposed approach.
李会俭, 王润秋, 曹思远, 药鑫蕊, 王芳琳, 孙立鹏. 利用多尺度形态学识别微地震监测中的弱信号[J]. 石油地球物理勘探, 2015, 50(6): 1105-1111.
Li Huijian, Wang Runqiu, Cao Siyuan, Yao Xinrui, Wang Fanglin, Sun Lipeng. Weak signal identification in microseismic monitoring with multi-scale morphology. OGP, 2015, 50(6): 1105-1111.
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