The most accessible product of microseismic monitoring during hydraulic fracturing is the 3-dimensional seismic cloud around the wellbore. To realize the benefit of microseismic monitoring, we must quantify the data seismologically, spatially, and spatio-temporally, and compare this with pumping data and energy input/output to/from the system. Our goal is to quantify meaningful correlations between the fractal dimensions b (frequency-magnitude; <1 = compression, 1 = shear, >1 = tension) and D (spatial clustering; 0 = point, 1 = line, 2 = plane, 3 = cloud), calculated from microseismic data collected in the Marcellus Shale of Southwestern Pennsylvania. Limitations are related to the sensitivity and geometry of the acquisition system which affects microseism coordinates (and any calculated distances), magnitudes, signal/noise ratios, and energy arrivals.

We illustrate the evolution of b and D as a function of time through four stages, with between 328 and 1048 events per stage. In addition we compute the hydraulic diffusivity triggering front for each stage using time-distance plots and diffusivity contouring, the cumulative seismic energy and the s and p-wave energy components for each of the five stages. Plotting b, D, and diffusivity values as well as pumping pressure, slurry rate, proppant concentration, and seismic energy release against time will shed light on the complex down-hole interactions between fluid and rock that create and propagate fractures. In all stages, we see correlation between the b and D-values, but it is not consistently positive or negative throughout any stage. Changes in the correlation are accompanied by a change in pumping pressure, rate, and the frequency of microseismic events. An intriguing observation is a correlation between abrupt increases in total s-wave energy and decreasing b-value.

In addition, we introduce the concept of slow slip seismicity during hydraulic fracturing in the Marcellus Shale and its importance to the reservoir stimulation process. A preliminary analysis of data collected by a 2 Hz, three-component seismometer at the surface indicates the presence of this phenomenon and creates an opportunity to extend this research into the Appalachian Basin.

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