Abstract

The engineering evaluation of microseismic events data acquired during hydraulic fracturing treatments can be influenced by factors that affect both the number of events detected and the quality of the waveforms used to locate the microseismic events. Variations in microseismic response that are observed during multistage stimulation treatments might be related to changes in rock properties or the stimulation treatment design or might be caused by detectability limitations related to distance, monitoring tool performance, and signal quality.

Magnitude-versus-distance plots are routinely used to determine detectability limits. Data filters based on a combination of measurement parameters of the detected waveforms can be used to reduce location uncertainty. The selections of filters to be used and the thresholds for filtering need to undertaken with care. Inadequate filtering can allow monitor well bias and microseismic events with low location confidence to adversely affect the evaluation. Aggressive filtering can introduce additional detection biases and might limit full characterization of the hydraulic fracture.

Frequency-versus-magnitude data from multiple treatments can be used to make comparative evaluations of microseismic data that have been acquired over a large range of monitoring distances during multiple stimulation treatments. The events from each treatment can be evaluated to determine a minimum event magnitude that can be used to minimize monitor well bias.

The use of cumulative-frequency-versus-magnitude data can be used to improve the engineering evaluation of microseismic events. This approach to evaluation is quantitative rather than qualitative and increases confidence that observations and analyses based on microseismic events are directly related to the stimulation procedure and properties of the reservoir.

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