Over the last decade, partly in relation to brown fields and unconventional reservoir development, microseismic monitoring of hydraulic fracture stimulations has increased dramatically. Geoscientists, engineers and decision makers realize the value this measurement brings in terms of reservoir understanding (e.g., geophysics, geology, geomechanics, reservoir quality, well placement, completion strategy, etc.). With proper integration of additional multiscale, multidomain measurements and observations, this value can increase even further.

It is not uncommon for mapped event locations, associated source parameters, and attributes derived from surface, shallow wellbore and/or deep wellbore (vertical, deviated, or horizontal) to be taken at face value without proper understanding as to how they have been obtained. This can lead to misunderstandings, misconstructions of measurement limitations, and more importantly, misinterpretations. Using various treatment and monitoring configurations, we demonstrate that ignoring the geology (e.g., lithology, stress contrast, natural fracturing, structural or depositional dip, faulting) and the associated rock properties (e.g., noise, slowness, anisotropy, attenuation) can potentially lead to poor stimulation and well placement, inadequate monitoring configurations, inconsistent processing approaches, and misleading interpretations.

Geology matters for validation of the exploration and production effort. For example, a producer well landed relative to lithology, but not oriented according to the local stress field, will likely not be stimulated as effectively as a properly oriented one. Moreover, if a well is oriented adequately in terms of local stress regime, but lateral variations in stress contrasts are ignored, perforation placement and stimulation will likely be ineffective. If a lateral is landed in a dipping formation, but recorded acoustic emissions are processed assuming a flat velocity model, mapped events will be erroneously located. If a formation is naturally quiet but monitoring geophones are positioned in surrounding noisy rocks, quality of the monitored signals and resulting processing is not optimum. If the velocity model used to process the recorded acoustic emissions is inappropriately blocked, the geological reality is not properly represented, resulting in a biased interpretation.

Often ignored, geology and rock properties play a critical role in understanding and optimizing stimulation treatments.

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