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Picking Automatization by Pattern Matching: A New Methodology Using EAT Events
- Publisher: European Association of Geoscientists & Engineers
- Source: Conference Proceedings, EAGE GeoTech 2021 First EAGE Workshop on Induced Seismicity, Mar 2021, Volume 2021, p.1 - 5
Abstract
Summary
The drastic increase of the observed seismicity at fluid injection sites has led to the need for further development of automatic picking methods for seismic events. Here, we focused on a pattern matching technique, which has traditionally relied on a representative Master event. However, this method strongly depends on the selection of the Master Event, which can be challenging with low Signal to Noise Ratios (SNR) or data gaps. In this study, we developed the Empirically Aggregated Template (EAT) concept. An EAT is a type of Master Event built using the seismic traces with the best SNR at each sensor, based on a set of events that exhibit high waveform similarity, and which are spatially close to one another. Thus, an EAT event will present the highest possible SNR of the database, and is not affected by data gaps. The efficiency and quality of this methodology has been tested by comparing with a set of manually picked events. The picking accuracy, location error, and travel-time residuals demonstrate similarities between manually and EAT picked events and allow us to validate this method. Finally, we have highlighted the advantages and improved results obtained using an EAT compared to a standard Master Event.
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