Microseismic monitoring has become a standard industry technique to monitor stimulation effectiveness as it provides information as to the length, height and orientation of the mapped hydrauli-cally-stimulated fracture network and surrounding formations. In some cases, focal mechanisms may be extracted as well, providing additional insight into the geomechanical behavior of the reacting formation in relation to the spatial and temporal evolution of the hydraulically-stimulated fracture network. Though there is much to learn from the interaction between sensor selection, survey design, operation, etc., in this work, we focus on the surface processing of a microseismic monitoring campaign performed in the Sultanate of Oman in 2015 ultimately comparing surface-derived results with downhole-derived results and the impact of joint inversion combining both surface and downhole data. Given the operation parameters (e.g., wells to be monitored, formation velocities, spread limitations, completion schedule, and monitoring objectives) a pre-job modeling exercise took place to design the most effective surface and downhole monitoring array configuration. On site surveying was carried-out to ensure all health, safety and environment-related aspects were covered prior to and during the acquisition over a 67-day-long period. At the end of each stimulation, datasets acquired were processed in the office prior to results interpretation and integration with multi-domain data. For the data acquired with the surface array, processing steps start with pre-processing including noise conditioning (e.g., filtering and spectral whitening) and grouping (i.e., stacking and beamforming). An iterative velocity model building and calibration exercise is performed using an initial model derived from well logs, surface surveys, check-shot data and, picking of accurate perforation shot timing (and large magnitude events). Events are detected and located using a source scanning approach prior to be manually inspected and relocated as needed during a quality check and editing phase. Additional refinement of the hypocenters takes place during the moment tensor inversion exercise prior to a final quality check and editing. Both a linear (detection) and an iterative (inversion) workflows are used to ensure optimal event location accuracy and moment tensor inversion.
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