Patent · US Active

Geophysical deep learning

US11313994B2 · kind B2 · utility

8Cited by

3References

20Claims

0Family size

Assignee

SCHLUMBERGER TECHNOLOGY CORPORATION · US

Inventors

Nader Salman · Tomball, US
Victor Aarre · Stavanger, NO
Hilde Grude Borgos · Stavanger, NO
Michael Nickel · Stavanger, NO

Key dates

Filing date	Feb 9, 2018
Grant date	Apr 26, 2022
Priority date	—
Expiry date	Aug 2, 2038

Classification

Technology area (CPC G)Physics
CPC primaryG01V2210/64
WIPO fieldMeasurement
WIPO sectorInstruments

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.

Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.