Invention Application
- Patent Title: GEOLOGICAL PROPERTY MODELING WITH NEURAL NETWORK REPRESENTATIONS
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Application No.: US17130708Application Date: 2020-12-22
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Publication No.: US20220198587A1Publication Date: 2022-06-23
- Inventor: Genbao Shi , Mehran Hassanpour , Steven Bryan Ward
- Applicant: Landmark Graphics Corporation
- Applicant Address: US TX Houston
- Assignee: Landmark Graphics Corporation
- Current Assignee: Landmark Graphics Corporation
- Current Assignee Address: US TX Houston
- Main IPC: G06Q50/16
- IPC: G06Q50/16 ; G06N3/08

Abstract:
A neural network trainer trains neural networks to estimate secondary data at locations throughout a geological formation where secondary data is unknown. The neural networks are trained to estimate secondary data using locations in the geological formation as input. Subsequently, the secondary data is deleted from memory using the trained neural network as a proxy representation to reduce memory footprint and allow for estimation of secondary data at locations where it is unknown.
Public/Granted literature
- US12056780B2 Geological property modeling with neural network representations Public/Granted day:2024-08-06
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