predictinG EaRthquakES induced by fluid injecTion
Fluid injection related to underground resources has become widespread, causing numerous cases of induced seismicity. If felt, induced seismicity has a negative effect on public perception and may jeopardise wellbore stability, which has led to the cancellation of several projects. Forecasting injection-induced earthquakes is a big challenge that must be overcome to deploy geo-energies to significantly reduce CO2 emissions and thus mitigate climate change and reduce related health issues. The basic conjecture is that, while initial (micro)seisms are caused by well-known mechanisms that could be predicted, subsequent activity is caused by harder to understand and, at present, unpredictable coupled thermo-hydro-mechanical-seismic (THMS) processes, which is the reason why available models fail to forecast induced seismicity. The objective of this project is to develop a novel methodology to predict and mitigate induced seismicity. We propose an interdisciplinary approach that integrates the THMS processes that occur in the subsurface as a result of fluid injection. The methodology, based on new analytical and numerical solutions, will concentrate on (1) understanding the processes that lead to induced seismicity by model testing of specific conjectures, (2) improving and extending subsurface characterization by using industrial fluid injection operations as a long-term continuous characterization methodology, so as to reduce prediction uncertainty, and (3) using the resulting understanding and site specific knowledge to predict and mitigate induced seismicity. Project developments will be tested and verified against fluid-induced seismicity at field sites that present diverse characteristics. Arguably, the successful development of this project will provide operators with concepts and tools to perform pressure management to reduce the risk of inducing seismicity to acceptable levels and thus, improve safety and reverse public perception on fluid injection activities.
ERC-2018-STG