Invention Grant
- Patent Title: Reservoir characterization using machine-learning techniques
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Application No.: US17136838Application Date: 2020-12-29
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Publication No.: US11703608B2Publication Date: 2023-07-18
- Inventor: Kalyan Saikia , Samiran Roy
- Applicant: Landmark Graphics Corporation
- Applicant Address: US TX Houston
- Assignee: Landmark Graphics Corporation
- Current Assignee: Landmark Graphics Corporation
- Current Assignee Address: US TX Houston
- Agency: Kilpatrick Townsend & Stockton LLP
- Main IPC: G01V1/30
- IPC: G01V1/30 ; G06N5/04 ; G06N20/00
Abstract:
A system can determine a location for future wells using machine-learning techniques. The system can receive seismic data about a subterranean formation and may determine a set of seismic attributes from the seismic data. The system can block the set of seismic attributes into a set of blocked seismic attributes by distributing the set of seismic attributes onto a geo-cellular grid representative of the subterranean formation. The system can apply a trained machine-learning model to the set of blocked seismic attributes to generate a composite seismic parameter. The system can distribute the composite seismic parameter in the subterranean formation to characterize formation locations based on a predicted presence of hydrocarbons.
Public/Granted literature
- US20220206177A1 RESERVOIR CHARACTERIZATION USING MACHINE-LEARNING TECHNIQUES Public/Granted day:2022-06-30
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