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US Patent 11481677 Machine learning based signal recovery

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Contents

Is a
Patent
Patent

Patent attributes

Patent Applicant
‌
SHEARWATER GEOSERVICES SOFTWARE, INC.
Current Assignee
‌
SHEARWATER GEOSERVICES SOFTWARE, INC.
Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
Patent Number
11481677
Date of Patent
October 25, 2022
Patent Application Number
16583528
Date Filed
September 26, 2019
Patent Citations
‌
US Patent 10823867 Seismic data acquisition using designed non-uniform receiver spacing
‌
US Patent 11035968 Use nuos technology to acquire optimized 2D data
‌
US Patent 10989826 Seismic data acquisition using designed non-uniform receiver spacing
‌
US Patent 10267939 3D seismic acquisition
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US Patent 10267940 Noise template adaptation
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US Patent 10514474 Method for synchronizing continuous seismic survey
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US Patent 10605941 Methods for simultaneous source separation
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US Patent 10809402 Non-uniform optimal survey design principles
Patent Primary Examiner
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Ojiako K Nwugo
CPC Code
‌
G01V 2210/324
‌
G06N 20/00
‌
G01V 2210/3248
‌
G01V 2210/3246
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G01V 1/364

Various aspects described herein relate to a machine learning based signal recovery. In one example, a computer-implemented method of noise contaminated signal recovery includes receiving, at a server, a first signal including a first portion and a second portion, the first portion indicative of data collected by a plurality of sensors, the second portion representing noise; performing a first denoising process on the first signal to filter out the noise to yield a first denoised signal; applying a machine learning model to determine a residual signal indicative of a difference between the first signal and the first denoised signal; and determining a second signal by adding the residual signal to the first denoised signal, the second signal comprising (i) signals of the first portion with higher magnitudes than the noise in the second portion, and (ii) signals of the first portion having lower magnitudes than the noise in the second portion.

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