The aim of this article is to understand and improve the predictive power of our previously developed empirical model (Hettema et al., 2017) to be able to better predict the seismicity of the Groningen gas reservoir. A specific characteristic of the gas production from the Groningen field has been the large seasonal variations in production. Four issues are addressed, namely the effects of delay time and production fluctuations, the application to regions in the field and understanding the causality between the production and seismicity. The model predicts inter-event volumes, which is the product of inter-event time and production rate, which decreases with increasing production. The analysis of four classes of minimum magnitudes with different data densities, requires a proper choice of the analysis window, sometimes requiring single event analysis. The causality of the model is understood and allows determination of inter-event times. Furthermore we come to the conclusion that the delay time is currently limited to days. Applying the model to different regions of the field gave reasonable descriptive results, but the applicability is still not proven.With a P of 2900 billion normal cubic meters, the Groningen field in The Netherlands is the largest onshore gas field in Europe. Continuous production since 1963 has led to induced seismicity starting in the early 90's. Production measures aimed at lowering the level of seismicity have been implemented since 2014. Based on an empirical relationship between the cumulative number of seismic events and cumulative gas production, a basic empirical predictive model has been developed
. The two empirical parameters and the confidence interval of the prediction have been determined by analyzing the yearly ratio of seismic activity over production versus the cumulative production. Predictions have only been made one year ahead. The present article aims to further develop the model with better predictive power and its control possibilities by increasing the confidence of the model. This requires incorporation of four refinements/extensions: the effects of delay time and production fluctuations, application to regions of the field and understanding the causality between the production and the seismicity. The effect of delay times between production and seismicity has been included by analyzing the pressure transient effects based on semi-steady-state diffusion times.
have shown that this delay-time increases with increasing reservoir pressure depletion. A specific characteristic of the gas production from the Groningen field has been the large seasonal variation in production. With the demand being high in winter and low in summer, the field played the role of ‘swing producer’ for the Dutch gas market. Since the previous model relates the seismic activity rate to the volume produced, the production rates are averaged within the analyzed window. Consequently, the rate fluctuations and time delays are suppressed. The present model performs better than the basic empirical model in that the goodness-of-fit shows a better confidence interval. It is desirable to be able to apply a model to different parts of the field as to optimize the production control based on localized risk. Finally, we aim to understand the physical causality of the model by considering the material balance and the well production profiles of the depleting gas reservoir. With this new model we gain confidence that better seismicity rate and inter-event time predictions can be made, with the goal to enable the decision makers to make science-based decisions to optimize the safety of the people that live in the province of Groningen.
