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Investigation of induced seismicity mechanisms and magnitude distributions under different stress regimes, geomechanical factors, and fluid injection parameters Amini, Afshin

Abstract

Hydraulic fracturing is the primary means of developing and completing production wells targeting unconventional gas reservoirs. However, these operations have been subject to public concern and regulatory oversight over their rapid growth in use, environmental footprint and potential hazards. This thesis is motivated by one of these potential hazards, induced seismicity, and the need to better understand the level of hazard present with respect to the event magnitudes possible, recognizing that these are not equal across different shale gas plays due to regional differences in the geological conditions or even within the same play due to local differences. The research presented focuses on three objectives: 1) to investigate the effect of different tectonic stress regimes on the magnitude distribution of induced seismicity events; 2) to analyze the influence of fluid injection rate and volume on induced seismicity; and 3) to compare the influence of different geological and operational parameters on induced seismicity in the Montney play in northeastern British Columbia. The methodology integrates statistical and machine learning analysis techniques with advanced 3-D numerical modelling. The empirical analyses are applied to compiled databases of recorded seismicity, hydraulic fracturing well data, and available geology and in situ stress data. Focus is placed on the Montney, but comparisons are also made to other shale gas basins. These analyses are complemented by 3-D numerical modelling used to provide mechanistic understanding to the trends observed in the empirical analyses. The main findings of this thesis are as follows. 1) Thrust faulting stress regimes have lower b-values than strike-slip stress regimes and therefore are more susceptible to larger induced seismicity events. 2) Specific to Montney, injection volume influences susceptibility to induced seismicity for wells that target naturally fractured formations, such as Middle Montney formation, whereas injection rate was seen to be an influencing factor for wells targeting the Upper Montney formation. 3) Machine learning provides a valuable means to assess the importance of different geological and operational parameters on induced seismicity for individual shale gas plays, allowing for susceptibility maps and mitigation options to be determined in advance.

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Attribution-NonCommercial-NoDerivatives 4.0 International