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Improving Geological and Engineering Interpretation of Hydraulic Treatment-Induced Fracture Systems Using Quality Control Attributes Applied to Microseismic Monitoring Results

Joel H. Le Calvez¹, Shawn Maxwell², and Les Bennett¹
¹Schlumberger, Houston, TX, [email protected], [email protected]
²Schlumberger, Calgary, Canada, [email protected]

Rigorous and proper processing of microseismic data is a sine qua non condition to derive confident interpretation of mapped hydraulically-induced fracture networks when using surface- and borehole-based microseismic monitoring surveys. During most hydraulic fracture treatments, thousands of microseismic events may be mapped. However, signal strength varying from event to event, time-picks accuracy varies and ultimately location accuracy is impacted. Thus, it may be relatively challenging to propose a reliable interpretation of mapped hypocentral locations associated to the monitoring of a hydraulic treatment.

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. We present 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.

Using examples from tight sand and shale formations whose treatments are monitored using one or more monitoring wells, we illustrate how the use of quality control attributes may help define a fault complex which could have otherwise remained hidden. Similarly, we document that what may appear to be a complex hydraulic fracture network is a series of well-defined hydraulically-induced fractures as suggested by wellbore resistivity imaging and sonic log.


AAPG Search and Discovery Article #90154©2012 AAPG Eastern Section Meeting, Cleveland, Ohio, 22-26 September 2012