A seismological model for earthquakes induced by fluid extraction from a subsurface reservoir

Abstract

A seismological model is developed for earthquakes induced by subsurface reservoir volume changes. The approach is based on the work of Kostrov () and McGarr () linking total strain to the summed seismic moment in an earthquake catalog. We refer to the fraction of the total strain expressed as seismic moment as the strain partitioning function, α. A probability distribution for total seismic moment as a function of time is derived from an evolving earthquake catalog. The moment distribution is taken to be a Pareto Sum Distribution with confidence bounds estimated using approximations given by Zaliapin et al. (). In this way available seismic moment is expressed in terms of reservoir volume change and hence compaction in the case of a depleting reservoir. The Pareto Sum Distribution for moment and the Pareto Distribution underpinning the Gutenberg‐Richter Law are sampled using Monte Carlo methods to simulate synthetic earthquake catalogs for subsequent estimation of seismic ground motion hazard. We demonstrate the method by applying it to the Groningen gas field. A compaction model for the field calibrated using various geodetic data allows reservoir strain due to gas extraction to be expressed as a function of both spatial position and time since the start of production. Fitting with a generalized logistic function gives an empirical expression for the dependence of α on reservoir compaction. Probability density maps for earthquake event locations can then be calculated from the compaction maps. Predicted seismic moment is shown to be strongly dependent on planned gas production.

Geomechanical models for induced seismicity in the Netherlands: inferences from simplified analytical, finite element and rupture model approaches

“…We show that mechanical models tend to predict growth of moment strongly bounded by the structural extent of stress perturbations. Consequently, the inferences from the geomechanical models pose a natural limit on predictions of future seismicity, which are low compared to the 10-to 1000-fold increase in cumulative seismic moment inferred by, for example, Bourne et al (2014). However, it should be noted that our model has limited quantitative predictive power for the Groningen field, as it is based on a single fault with simplified geometry, and limited parameter variations.…”

“…14) and seems to underestimate the observed increasing growth marked by more-or-less linear growth of log moment as a function of pressure depletion (Fig. 3) coefficient in Bourne et al, 2014). Various mechanisms can be considered which can explain this discrepancy, including:…”

“…Van Wees et al, 2014;Sanz et al, 2015) allow us to place the delay of onset and observed increasing growth of seismic moment ( Fig. 3; Bourne et al, 2014) in a physical context. Here, we aim to show that mechanical rupture models (Baisch et al, 2010) can be used to predict seismic catalogues whose moment evolution appear to be consistent with findings from other mechanical analysis approaches which do not include rupture.…”

“…5; Table 1), which can be considered representative for major fault zones in the central area of the Groningen field, in the vicinity of which most seismic events have occurred ( Fig. 4; Bourne et al, 2014). The plane-strain finite element mesh models a 2D section 6 km wide and 6 km deep.…”

“…Furthermore, the moment density has been constructed in accordance with the correlation of compaction strain and the logarithm of seismic moment increase (Bourne et al, 2014, median in their fig. 18a).…”