Hydraulic Fracture Monitoring: Integrating Multi-Scale Borehole-Based Geophysical Measurement to Improve Formation Understanding
Le Calvez, Joel; Puckett, Mark
Rigorous and proper processing of microseismic data is a sine qua non condition to derive confident mapped hypocentral locations and associated source parameters associated to hydraulically-induced fracture networks when using surface- and borehole-based microseismic monitoring surveys; thus, to help understand formation behavior. In this study, we present the results of a microseismic monitoring campaign performed on multi-stage hydraulic fracturing treatments using two nearby pseud-vertical monitoring arrays composed of eight 3C geophones each. We benefit from several borehole-based geophysical measurements such as sonic logs, cross well tomographic and attenuation profiles as well as multi-calibration perforation points. Though, all these measurements take place in different frequency domains they allow to document very efficiently the variations in space and time of the velocities, anisotropies, attenuations, and rock physics in the zones of interest and surrounding formations. Initial results show that the hydraulic treatments performed in the sandstone formation are not fully contained by the surrounding coal layers. Microseismic activity monitoring seems to correlate with rock fabric despite slight seismic signal attenuation likely associated to coal. Apparent asymmetry of the mapped hydraulically fracture network seems to relate to the monitoring geometry. Simple fault plane solution seems to indicate rock failure consistent with regional observations. Velocity of the formation seems to change in relation to pressure and effective porosity and/or shear-wave attenuation. In addition, early interpretations relied on filtering events with low signal-to-noise ratio and high location uncertainty in association to various source parameters. This approach may significantly reduce the number of events available for interpretation since most microseismic events are by definition weak rather than strong. Using a series of quality control attributes based on various characteristics to increase confidence in interpretation using examples to ascertain usefulness. Quality control attributes quantify for both P- and S-waves signal-to-noise ratio, time and azimuthal residuals, orthogonality and confidence factor. These quality control attributes can be used to systematically compare data quality between various events within one stage, between various stages within a single well, between various treatments among many wells in one or more fields or basins.
AAPG Search and Discovery Article #90163©2013AAPG 2013 Annual Convention and Exhibition, Pittsburgh, Pennsylvania, May 19-22, 2013