Optimization of local scale seismic networks applied to geothermal fields. The case of the Acoculco caldera, Mexico

Abstract

The exploitation of a geothermal field can be accompanied by both natural and induced seismicity. Hence the installation of a seismic network suitable for also locating low-magnitude earthquakes, is of great interest for geothermal development, especially for monitoring the activity related to the injection or production.Most of the aspects that affect the location of earthquakes are data quality and phase picking, the inverse method chosen to solve the problem, the velocity model, and the seismic network configuration. We focus on the optimization of network configuration and the reduction of the location error is one of the alternatives to finding optimal station positions. Here we propose an improvement of the D-OPTIMAL algorithm (Tramelli et al., 2013) that tries and find optimal station positions minimizing the amount of the error ellipsoid of the event location using the D-criterion. This algorithm is computationally efficient and easy to be implemented. In this version, we also introduced the possibility to account for several prior information that is generally available when implementing a monitoring site permanently or temporarily. These a priori parameters introduced are: i) three-dimensional seismic velocity models, ii) seismic noise levels, iii) topographic gradient, and iv) H/V ratio values. The last three parameters are introduced in the station position selection using a weighted system scheme.We applied this methodology to the Acoculco geothermal field (Mexico) where an injection test was planned and executed in 2021. The comparison between the network defined using the standard approach, which considers a 1D velocity model and the installation costs, and this improved version shows the importance of introducing a priori information during the selection of the network. Installation sites showed better distribution in the region, resulting in an overall increase in the sensitivity and a decreasing of the error location estimation in the target region.The methodology presented here is easy to apply to other study cases such as active volcanoes, anthropogenic activities, or other kinds of location studies at local scale.