Probabilistic Forecasting of Hydraulic Fracturing Induced Seismicity Using an Injection-Rate Driven ETAS Model

Simone Mancini*, Max Werner, Margarita Segou, Brian J. Baptie

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

10 Citations (Scopus)
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The development of robust forecasts of human-induced seismicity is highly desirable to mitigate the effects of disturbing or damaging earthquakes. We assess the performance of a well-established statistical model, the Epidemic-Type Aftershock Sequence (ETAS) model, with a catalog of ~93,000 microearthquakes observed at the Preston New Road (UK) unconventional shale gas site during and after hydraulic fracturing of the PNR-1z and PNR-2 wells. Because ETAS was developed for slower loading rate tectonic seismicity, in order to account for seismicity generated by pressurized fluid we also generate three modified ETAS with background rates proportional to injection rates. We find that (1) the standard ETAS captures low seismicity between and after injections but is outperformed by the modified model during high seismicity periods, and (2) the injection-rate driven ETAS substantially improves when the forecast is calibrated on sleeve-specific pumping data. We finally forecast out-of-sample the PNR-2 seismicity using the average response to injection observed at PNR-1z, achieving better predictive skills than the in-sample standard ETAS. The insights from this study contribute towards producing informative seismicity forecasts for real-time decision making and risk mitigation techniques during unconventional shale gas development.
Original languageEnglish
Pages (from-to)3471-3481
Number of pages11
JournalSeismological Research Letters
Issue number6
Early online date19 May 2021
Publication statusPublished - Nov 2021

Bibliographical note

Funding Information:
The authors thank the editor and two anonymous reviewers for their constructive comments. The authors would also like to thank the UK Oil and Gas Authority (OGA) for providing the datasets. Simone Mancini was supported by a Great Western Four+ Doctoral Training Partnership (GW4+ DTP) studentship from the Natural Environment Research Council (NERC) (NE/L002434/1) and by a studentship from the British Geological Survey (BGS) University Funding Initiative (BUFI) (S350). Maximilian Jonas Werner and

Funding Information:
Brian Baptie were supported by NERC (NE/R017956/1, “EQUIPT4RISK”). Maximilian Jonas Werner and Margarita Segou were supported by the European Union H2020 program (number 821115, “RISE”). Brian Baptie was also supported by the NERC Grant Number NE/R01809X/1. This work was also supported by the Bristol University Microseismic ProjectS (“BUMPS”) and by the Southern California Earthquake Center (SCEC) (Contribution Number 10149). SCEC is funded by the National Science Foundation (NSF) Cooperative Agreement EAR-1600087 and U.S. Geological Survey (USGS) Cooperative Agreement G17AC00047.

Publisher Copyright:
© 2021 Seismological Society of America. All rights reserved.


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