Invention Application
- Patent Title: Geophysical Deep Learning
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Application No.: US16484879Application Date: 2018-02-09
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Publication No.: US20190383965A1Publication Date: 2019-12-19
- Inventor: Nader Salman , Victor Aarre , Hilde Grude Borgos , Michael Hermann Nickel
- Applicant: Schlumberger Technology Corporation
- International Application: PCT/US2018/017544 WO 20180209
- Main IPC: G01V99/00
- IPC: G01V99/00 ; G01V1/36 ; G01V1/50 ; G01V1/28 ; G01V3/38 ; G01V1/30 ; G01V3/08 ; G01V3/18 ; G06N20/00

Abstract:
A method can include selecting a type of geophysical data; selecting a type of algorithm; generating synthetic geophysical data based at least in part on the algorithm; training a deep learning framework based at least in part on the synthetic geophysical data to generate a trained deep learning framework; receiving acquired geophysical data for a geologic environment; implementing the trained deep learning framework to generate interpretation results for the acquired geophysical data; and outputting the interpretation results.
Public/Granted literature
- US11313994B2 Geophysical deep learning Public/Granted day:2022-04-26
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