Recent advances in earthquake monitoring Ⅱ: Emergen-ce of next-generation intelligent systems

• 作者: Zefeng Li
• 来源期刊: 地震学报（英文版）
• 年，卷（期）: 2021,（6）
• 所属期刊栏目: Review
• 页码范围: 531-540
• 页数: 10页
• 语种: 英文
• DOI: 10.29382/eqs-2021-0054

摘要

Seismic data processing techniques, together with seismic instrumentation, determine our earth-quake monitoring capability and the quality of resulting earthquake catalogs. This paper is intended to review the improvement of earthquake monitoring capability from the perspective of data processing. Over the past two decades, seismologists have made considerable advancements in seismic data processing, partly thanks to the significant develop-ment of computational power, signal processing, and machine learning techniques. In particular, wide application of temp-late matching and increasing use of deep learning signifi-cantly enhance our capability to extract signals of small earthquakes from noisy data. Relative location techniques provide a critical tool to elucidate fault geometries and seismicity migration patterns at unprecedented resolution. These techniques are becoming standard, leading to emerging intelligent software systems for next-generation earthquake monitoring. Prospective improvements in future research must consider the urgent needs in highly generalizable detection algorithms (for both permanent and temporary deployments) and in emergency real-time monitoring of ongoing sequences (e.g., aftershock and induced seismicity sequences). We believe that the maturing of intelligent and high-resolution processing systems could transform traditi-onal earthquake monitoring workflows and eventually liberate seismologists from laborious catalog construction tasks.