Precise microseismic event location is necessary to correctly assess the hydraulic stimulation effectiveness. In order to obtain proper event locations reliable location uncertainty analysis have to be performed. Location uncertainty computed with use of the Bayesian inversion is efficiently characterised by probability density function (pdf). We present the Bayesian approach for location of microseismic events recorded by a single vertical receiver array during hydraulic fracturing in northern Poland. We compare a cumulative probability density function for the location of all events with a standard representation of events as maximum likelihood points (‘dots in the box’). The discussion is extended by considering seismic moment and moment magnitude as the weighting parameters for pdf visualization. Bayesian approach is more intuitive and easier to directly transfer into reservoir engineering parameters, like the Stimulated Reservoir Volume, or to be used in Discrete Fracture Network modelling. The obtained cumulative location pdf clearly points out highly fractured zones and shows directly the scale and the distribution of the location uncertainty. Particularly in case of the studied acquisition geometry the shape of the pdf distribution cannot be explained in standard way in terms of horizontal and vertical errors.


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