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Increasing SNR for Microseismic Arrivals with a Multichannel Adaptive Noise FilterNormal access

Author: K. Chambers
Event name: 80th EAGE Conference and Exhibition 2018
Session: Poster: From Microseismic Data To Source Classification And Inversion
Publication date: 11 June 2018
DOI: 10.3997/2214-4609.201801576
Organisations: EAGE
Language: English
Info: Extended abstract, PDF ( 604.32Kb )
Price: € 20

Summary:
Here an adaptive subtraction noise attenuation method is applied to enhance microseismic arrivals observed on groups of closely spaced sensors. In contrast to many conventional seismic and microseismic deployments in our study the records from all sensors in the group are stored, thus allowing us to apply noise attenuation processing prior to stacking the records. The adaptive subtraction approach is capable of modelling both stationary and transient noise on seismic traces using the recordings at adjacent sensors. The procedure is based on a multichannel Weiner filter which is trained using a sample of the noise prior to application. One -well known- disadvantage of this technique is that where the noise has a similar moveout properties to the desired signal, the filter can replicate and remove or distort the desired signal. We show that by adding constraints to the formulation of the Weiner filter this undesirable effect can be minimized. The processing methodology is tested using a dataset of arrivals from 71 events recorded on three sensor groups. We find that by applying the multichannel filter a 12% improvement in SNR is obtained compared to stacking the raw arrivals without any pre-processing.


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