Coherent noise suppression in electroseismic data with non-stationary prediction-error filters
نویسندگان
چکیده
Non-stationary prediction-error filters (PEF’s) provide an effective means for separating signal from coherent noise in electroseismic data. The electroseismic signal is much weaker than the noise, so we can not rely on windowing, transforms, or other alterations of the original data to create models for the PEF estimation. Instead, we design signal PEF’s using the physical predictability of the phenomena, and estimate noise PEF’s using portions of the original data. This technique is effective on synthetic and real data.
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