Automated Monitoring of a Hydraulic Fracture by Coalescence Microseismic Mapping

Woerpel, Craig; Maxwell, Shawn; Underhill, Bill; Wolfe, James E.

doi:10.2118/139043-ms

Cited by 1 publication

(1 citation statement)

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“…This means a simplified velocity model with only two or three layers must be used to reduce the calculation time. In contrast, we determined event locations following the Coalescent Microseismic Mapping technique described by Woerpel et al (2010). Implementing a look-up-table becomes very practical in that all ray-tracing is done before the treatment starts, allowing for an anisotropic velocity model with more than 100 layers, without reduction in processing speed as the job is being executed.…”

Section: Event Locationmentioning

confidence: 99%

The Impact of Dipping Velocity Models on Microseismic Event Locations

et al. 2012

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Once a microseism is detected, its source location can relatively easily be identified if the velocity characteristic of the medium traversed by the recorded waveforms is known. Unfortunately, this is rarely the case. Velocity models are used to estimate, with some degree of confidence, microseismic event locations. This work shows how a simple modification to the velocity model, accounting for a 4.5-degree dip supported by geological data, significantly impacts the event final locations during a borehole-based hydraulic fracturing monitoring job. Overall geometry of the hydraulically-induced fracture system interpreted (e.g. height) is the most affected. For instance, when a preliminary event location is selected without introducing the observed structural component of the beds, these measurements could change by as much as fifty percent. For the reservoir engineer, sometimes unaware of the assumptions made at the microseismic processing level, these differences could imply major changes to the field development plans. These results underscore the importance of integrating all available data and implementing well known quality controls before using microseismic monitoring data for reservoir analysis.

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Section: Event Locationmentioning

confidence: 99%