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Automatic Processing of Microseismic Data: Determination of Hypocenter Position and Estimation of Focal Mechanism

J.. Vicek, Tomáš J. Fischer, Jan Vilhelm

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Abstract

Summary We present an automatic method of processing microseismic monitoring data acquired at the surface with star-like array using the back projection approach that allows simultaneous determination of hypocenter position of events and an estimation of their focal mechanisms. Location coordinates are searched in a grid using two norms for seismogram stacking: STA/LTA for location and stack of real amplitudes corrected by the radiation pattern to estimate the focal mechanisms. From each point of the given grid we compute travel times to all geophones on the surface through the assumed velocity model. Afterwards we do migration of each trace using the computed travel time and stack the STA/LTA ratios of all traces. This process is repeated for each point of the grid. The most probable location corresponds to the maximum of the stack. In the second step a small and fine grid with center in the approximate location is used to refine the hypocenter position. In order to find source mechanisms we use additional grid search in source mechanism angles – strike and dip to find focal mechanism and correct polarity of seismograms according to computed theoretical polarities of the found focal mechanism. We test this method on real dataset of hydraulic fracturing monitoring of a shale gas play. We obtain similar hypocenter positions and focal mechanisms as provided by other methods applied to the same dataset.

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Summary We present an automatic method of processing microseismic monitoring data acquired at the surface with star-like array using the back projection approach that allows simultaneous determination of hypocenter position of events and an estimation of their focal mechanisms. Location coordinates are searched in a grid using two norms for seismogram stacking: STA/LTA for location and stack of real amplitudes corrected by the radiation pattern to estimate the focal mechanisms. From each point of the given grid we compute travel times to all geophones on the surface through the assumed velocity model. Afterwards we do migration of each trace using the computed travel time and stack the STA/LTA ratios of all traces. This process is repeated for each point of the grid. The most probable location corresponds to the maximum of the stack. In the second step a small and fine grid with center in the approximate location is used to refine the hypocenter position. In order to find source mechanisms we use additional grid search in source mechanism angles – strike and dip to find focal mechanism and correct polarity of seismograms according to computed theoretical polarities of the found focal mechanism. We test this method on real dataset of hydraulic fracturing monitoring of a shale gas play. We obtain similar hypocenter positions and focal mechanisms as provided by other methods applied to the same dataset.

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Available abstract

Summary We present an automatic method of processing microseismic monitoring data acquired at the surface with star-like array using the back projection approach that allows simultaneous determination of hypocenter position of events and an estimation of their focal mechanisms. Location coordinates are searched in a grid using two norms for seismogram stacking: STA/LTA for location and stack of real amplitudes corrected by the radiation pattern to estimate the focal mechanisms. From each point of the given grid we compute travel times to all geophones on the surface through the assumed velocity model. Afterwards we do migration of each trace using the computed travel time and stack the STA/LTA ratios of all traces. This process is repeated for each point of the grid. The most probable location corresponds to the maximum of the stack. In the second step a small and fine grid with center in the approximate location is used to refine the hypocenter position. In order to find source mechanisms we use additional grid search in source mechanism angles – strike and dip to find focal mechanism and correct polarity of seismograms according to computed theoretical polarities of the found focal mechanism. We test this method on real dataset of hydraulic fracturing monitoring of a shale gas play. We obtain similar hypocenter positions and focal mechanisms as provided by other methods applied to the same dataset.

Key concepts: Hypocenter, Focal mechanism, Seismogram, Geology, Position (finance), Microseism, Geophone, Grid

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