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| Improving the stability of microseismic event detection by clustering algorithm |
| GONG Yi1, MENG Qingli1, LAN Jiada1, SHAN Zhongqiang1, HE Pei2, ZHAI Renlei2 |
1. Exploration and Development Research Institute, SINOPEC East China Oil & Gas Company, Nanjing, Jiangsu 210000, China;
2. Huadong Branch, SINOPEC Geophysical Corporation, Nanjing, Jiangsu 210000, China |
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Abstract A key step in microseismic monitoring is the efficient and accurate picking of the first break of the microseismic data. Currently，the commonly used method to pick the first break is the energy ratio algorithm，which is simple and efficient in application. However，the main weakness of this algorithm is the poor results on low signal-to-noise ratio data. In this paper，the algorithm is improved by applying the clustering algorithm. The principle of the improved method is to first pick the first break through the energy ratio algorithm，and optimize the results by clustering algorithm to divide the low error result with false pickings. Then，the false pickings are corrected according to the distribution fitted by the low-error result. Finally，the Akaike information criteria （AIC） algorithm is used in a small window that creates from optimized results to pick the first break accurately. This algorithm combines the benefits of the energy ratio algorithm and the AIC algorithm. Actual data test results show that the improved algorithm has higher pick-up accuracy in low SNR data compared to the conventional algorithm and can effectively identify the first break of multiple seismic phases. In addition，the algorithm is efficient and can be applied to field processing.
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Received: 17 May 2023
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2024, Vol. 59 
