Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1029/2020GL089651 |
Machine learning‐based analysis of geological susceptibility to induced seismicity in the Montney Formation, Canada | |
P. Wozniakowska; D. W. Eaton | |
2020-11-09 | |
发表期刊 | Geophysical Research Letters
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出版年 | 2020 |
英文摘要 | We analyze data from 6,466 multistage horizontal hydraulic fracturing wells drilled into the Montney Formation over a large region in western Canada to evaluate the impact of geological, geomechanical and tectonic characteristics on the distribution of hydraulic fracturing induced seismicity. Logistic Regression was used to obtain a machine learning estimate of the seismogenic activation potential of each well. Our results fit the observed spatial variability, including an enigmatic change in seismicity at 120oW that does not correlate with any change in industrial activity. Feature importance analysis provides insight into data types that have the greatest impact on the results. Based on current data, seismogenic activation potential is most strongly influenced by depth of injection and distance of the well to the Cordilleran thrust belt. |
领域 | 气候变化 |
URL | 查看原文 |
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文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/303941 |
专题 | 气候变化 |
推荐引用方式 GB/T 7714 | P. Wozniakowska,D. W. Eaton. Machine learning‐based analysis of geological susceptibility to induced seismicity in the Montney Formation, Canada[J]. Geophysical Research Letters,2020. |
APA | P. Wozniakowska,&D. W. Eaton.(2020).Machine learning‐based analysis of geological susceptibility to induced seismicity in the Montney Formation, Canada.Geophysical Research Letters. |
MLA | P. Wozniakowska,et al."Machine learning‐based analysis of geological susceptibility to induced seismicity in the Montney Formation, Canada".Geophysical Research Letters (2020). |
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