Increased Detections Through Array Design and Processing

Date: 4/26/2019

Time: 09:15 AM

Room: Cascade I

Induced and microseismic monitoring is often hindered by the low signal-to-noise ratio (SNR) of the arrivals. This is due to both the often weak source and strong surface noise. Within the oil and gas industry it has become common practice to deploy very large numbers of geophones to allow for the detection of the weak seismic events, primarily through stacking techniques. The cost of acquiring and processing such large datasets can be prohibitive, particularly for academic and government institutions. Therefore, this may not be a practical design for all applications. While more sensors will theoretically improve the signal-to-noise ratio by √N, where, N is the number of measurements, this assumes prior removal of coherent noise sources. Large densely sampled patches remove coherent surface wave noise through application of an F-K, or similar, filter. This approach is only valid when the wavefield is well sampled, often requiring a prohibitive number of instruments. We demonstrate that using a small array and semblance-weighted stacking we can achieve similar results to the large dense patch design.

Our data set consists of two arrays that recorded a hydraulic fracture treatment in western Canada. The first consists of 25 dense patches with 96 recorded channels in a grid. Each channel is comprised of a string of 12 1C geophones. The second array has eight hexagonal subarrays of 3C geophones. Using subsets of the large patch data, we show that semblance-weighted stacking can achieve a √N increase in SNR. This suggests that the coherent noise within the data has been successfully attenuated. We also show that applying semblance-weighted stacking on the hexagonal subarrays falls on the √N from the patch data. We conclude that we can attenuate the coherent noise using only a six-station hexagonal array and semblance-weighted stacking. Thus, a limited number of sensors in an easily acquired array design and intelligent processing can increase detections to provide a more complete catalog.

Presenting Author: Sepideh Karimi

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