Characterization of Moment tensor Derived Discrete Fracture Networks Utilizing Scanlines and Topological Approaches

Hydraulic fracturing is the primary method used to stimulate production from new and existing unconventional oil and gas wells by creating fractures in the target formations. The generated discrete fracture network has a key role in increasing the effective rock permeability surrounding the production wells. Therefore better understanding of the fracture (individually and as a group) properties are extremely vital to increase the completion efficiency. One approach for fracture network characterization is through higher-order microseismic data analyses such as SeismicMoment Tensor Inversion and source parameter examination. Microseismic monitoring is a common deployment in the hydraulic fracture treatments, and if high quality data are sufficiently sampled from a large azimuthal range (thorough multi-array downhole deployments), the generated discrete fracture network properties can be characterized. These properties consist ofquantitative measures such as the type of failure (tensile, shear, or shear-tensile), fracture orientation (azimuth, dip, and rake), the relative dimensions (length, slip, and aperture), and qualitative observations such as the fracture state interaction with planes of the weakness (i.e.,bedding planes and stratigraphic boundaries). In this paper we characterize the discrete fracture network from a range of hydraulic fracturing monitoring projects in shale plays throughout North America. In the process of this investigation, we utilize scanline and topological approaches to facilitate the visualization and interpretation of the inferred fracture characteristics.