Invention Application
- Patent Title: USING NEURAL NETWORKS FOR INTERPOLATING SEISMIC DATA
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Application No.: US17497312Application Date: 2021-10-08
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Publication No.: US20230114602A1Publication Date: 2023-04-13
- Inventor: Song HOU , Peng ZHAO
- Applicant: CGG SERVICES SAS
- Applicant Address: FR Massy Cedex
- Assignee: CGG SERVICES SAS
- Current Assignee: CGG SERVICES SAS
- Current Assignee Address: FR Massy Cedex
- Main IPC: G01V1/36
- IPC: G01V1/36

Abstract:
One method interpolates simulated seismic data of a coarse spatial sampling to a finer spatial sampling using a neural network. The neural network is previously trained using a set of simulated seismic data with the finer spatial sampling and a subset thereof with the coarse spatial sampling. The data is simulated using an image of the explored underground formation generated using real seismic data. The seismic dataset resulting from simulation and interpolation is used for denoising the seismic data acquired over the underground formation. Another method demigrates seismic data at a sparse density and then increases density by interpolating traces using a neural network.
Public/Granted literature
- US11796700B2 Using neural networks for interpolating seismic data Public/Granted day:2023-10-24
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