Summary
Fault-controlled damage zones have important implications for fluid flow in fractured reservoirs. We present here a methodology for identification of fault-controlled damage zones in microseismic data using a dataset from the Haynesville shale. We first develop a discrete fracture network (DFN) model of the pre-existing faults shear activated during hydraulic fracturing stimulation. We utilize the DFN to reveal fracture concentrations, diagnostic of fault damage zones. The DFN also reveals a planar zone of diminished microseismic events which we hypothesize are correlative with the fault itself. In support of this interpretation, we show that fault density in the damage zones drops off with distance from the fault according to a power law F=F0r-n which has been observed in faultcontrolled damage zones at other locations
Introduction
Microseismic events induced during hydraulic fracturing stimulation provide a valuable opportunity to constrain information of subsurface faults (e.g., Deichmann et al., 2014; Stabile et al., 2014; Block et al., 2015). In this study, we present a method for fault identification based on detection of fault-controlled damage zones in microseismic data recorded during multi-stage hydraulic fracturing. We illustrate this method using a data set recorded in the Haynesville shale.
For this study, we choose a microseismic event catalog containing 3159 events that were recorded by a down-hole seismic array during stimulation of a horizontal well located in Haynesville shale (figure 1). We assume each microseismic event was generated from shear slip on a preexisting fracture due to the pore pressure increase during hydraulic fracturing stimulation. We also assume each event location denotes the center of an activated fracture. However, for the very small source dimensions of these events (see below) this is not an important assumption. The shear fracture size can be constrained through event moment magnitude using well-established scaling laws among seismic source parameters.
