Analysis of passive surface-wave noise in surface microseismic data and its implications

Tight gas reservoirs are projected to be a major portion of future energy resources. Because of their low permeability, hydraulic fracturing of these reservoirs is required to improve the permeability and reservoir productivity. Passive seismic monitoring is one of the few tools that can be used to characterize the changes in the reservoir due to hydraulic fracturing. Although the majority of the studies monitoring hydraulic fracturing exploit down hole microseismic data, surface microseismic monitoring is receiving increased attention because it is potentially much less expensive to acquire. Due to a broader receiver aperture and spatial coverage, surface microseismic data may be more advantageous than down hole microseismic data. The effectiveness of this monitoring technique, however, is strongly dependent on the signal-to-noise ratio of the data. Cultural and ambient noise can mask parts of the waveform that carry information about the subsurface, thereby decreasing the effectiveness of surface microseismic analysis in identifying and locating the microseismic events. Hence, time and spatially varying suppression of the surface-wave noise ground roll is a critical step in surface microseismic monitoring. Here, we study a surface passive dataset that was acquired over a Barnett Shale Formation reservoir during two weeks of hydraulic fracturing, in order to characterize and suppress the surface noise in this data. We apply techniques to identify the characteristics of the passive ground roll. Exploiting those characteristics, we can apply effective noise suppression techniques to the passive data.