Induced seismicity after termination of rock stimulations: Possibilities for reservoir characterization
Cornelius Langenbruch, S. A. Shapiro
Abstract
Cornelius Langenbruch, S. A. Shapiro
Abstract
In this paper we analyze the temporal distribution of fluid induced microseismicity and show which information about reservoir and source can be extracted from the seismicity rate. We assume that microseismic events induced through fluid injections are triggered by a pure diffusive process of pore pressure relaxation. We improve an existing formulation for the seismicity rate of fluid induced microseismicity, which is developed based on this assumption. In this way we derive to a formulation, which describes the temporal distribution of microseismic activity in dependency on the parameters of source and reservoir. In the next step we show that the well known Omori law, which describes the frequency of aftershock occurrence, can be transferred to the case of fluid induced microseismicity to describe the temporal distribution of events induced after injection stop. Even in seismology the controlling parameters of the characteristic p‐value of the Omori law are still under discussion. Here we identify the controlling parameters of the p‐value for fluid induced seismicity and show, which parameters of source and reservoir can be reconstructed by a p‐value analysis. Finally we apply the developed theory to synthetic data sets and to the Fenton Hill (1983) real data example.
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In this paper we analyze the temporal distribution of fluid induced microseismicity and show which information about reservoir and source can be extracted from the seismicity rate. We assume that microseismic events induced through fluid injections are triggered by a pure diffusive process of pore pressure relaxation. We improve an existing formulation for the seismicity rate of fluid induced microseismicity, which is developed based on this assumption. In this way we derive to a formulation, which describes the temporal distribution of microseismic activity in dependency on the parameters of source and reservoir. In the next step we show that the well known Omori law, which describes the frequency of aftershock occurrence, can be transferred to the case of fluid induced microseismicity to describe the temporal distribution of events induced after injection stop. Even in seismology the controlling parameters of the characteristic p‐value of the Omori law are still under discussion. Here we identify the controlling parameters of the p‐value for fluid induced seismicity and show, which parameters of source and reservoir can be reconstructed by a p‐value analysis. Finally we apply the developed theory to synthetic data sets and to the Fenton Hill (1983) real data example.
Key concepts: Induced seismicity, Geology, Reservoir modeling, Seismology, Characterization (materials science), Petroleum engineering, Materials science, Nanotechnology