Mitigation and Optimization of Induced Seismicity Using Physics-Based Forecasting

Abstract

Fluid injection can induce seismicity by altering stresses on pre-existing faults. Here, we investigate minimizing induced earthquake potential by optimizing injection operations in a physics-based forecasting framework. We built a 3D finite element model of the poroelastic crust for the Raton Basin, Central US, and used it to estimate time dependent Coulomb stress changes due to $\sim$25 years of wastewater injection in the region. Our finite element model is complemented by a statistical analysis of the seismogenic index (SI), a proxy for critically stressed faults affected by variations in the pore pressure. Forecasts of seismicity rate from our hybrid physics-based statistical model suggest that induced seismicity in the Raton Basin, from 2001 to 2022, is still driven by wastewater injection despite declining injection rates since 2011. Our model suggests that pore pressure diffusion is the dominant cause of Coulomb stress changes at seismogenic depth, with poroelastic stress changes contributing about 5% to the driving force. Linear programming optimization for the Raton Basin reveals that it is feasible to reduce earthquake potential for a given amount of injected fluid (safety objective) or maximize fluid injection for a prescribed earthquake potential (economic objective). The optimization tends to spread out high-rate injectors and shift them to regions of lower SI. The framework has practical importance as a tool to manage injection rate per unit field area to reduce induced earthquake potential. Our optimization framework is both flexible and adaptable to mitigate induced earthquake potential in other regions and for other types of subsurface fluid injection.