Validating induced seismicity forecast models - Induced Seismicity Test Bench

TL;DR

This paper introduces an Induced Seismicity Test Bench to evaluate and compare models predicting earthquake hazards from fluid injection, applying it to geothermal data and assessing two models' performance in different phases.

Contribution

It presents a new test bench framework for evaluating probabilistic seismicity forecast models, facilitating model development, selection, and ensemble creation.

Findings

HySei forecasts seismicity rate better after shut-in

SaSS predicts spatial distribution more accurately

Both models underpredict seismicity around shut-in

Abstract

Induced earthquakes often accompany fluid injection, and the seismic hazard they pose threatens various underground engineering projects. Models to monitor and control induced seismic hazard with traffic light systems should be probabilistic, forward-looking, and updated as new data arrive. In this study, we propose an Induced Seismicity Test Bench to test and rank such models; this test bench can be used for model development, model selection, and ensemble model building. We apply the test bench to data from the Basel 2006 and Soultz-sous-For\^ets 2004 geothermal stimulation projects, and we assess forecasts from two models: Shapiro and Smoothed Seismicity (SaSS) and Hydraulics and Seismics (HySei). These models incorporate a different mix of physics-based elements and stochastic representation of the induced sequences. Our results show that neither model is fully superior to the other. Generally, HySei forecasts the seismicity rate better after shut-in, but is only mediocre at forecasting the spatial distribution. On the other hand, SaSS forecasts the spatial distribution better and gives better seismicity rate estimates before shut-in. The shut-in phase is a difficult moment for both models in both reservoirs: the models tend to underpredict the seismicity rate around, and shortly after, shut-in.