Patent · US Active

Subsurface fluid-type likelihood using explainable machine learning

US11630224B2 · kind B2 · utility

0Cited by

1References

20Claims

0Family size

Assignee

Landmark Graphics Corporation · US

Inventors

Samiran Roy · Sherghati, IN
Shashwat Verma · Kanchinakote, IN

Key dates

Filing date	Dec 11, 2020
Grant date	Apr 18, 2023
Priority date	—
Expiry date	Aug 19, 2041

Classification

Technology area (CPC G)Physics
CPC primaryG01V2210/645
WIPO fieldMeasurement
WIPO sectorInstruments

Abstract

A system is described for determining a likelihood of a type of fluid in a subterranean reservoir. The system may include a processor and a non-transitory computer-readable medium that includes instructions executable by the processor to cause the processor to perform various operations. The processor may receive pre-stack seismic data having seismically-acquired data elements for geometric locations in a subterranean reservoir. The processor may determine, using the pre-stack seismic data, input features for each geometric location and may execute a trained model on the input features for determining a likelihood of a type of fluid in the subterranean reservoir and for determining a list of features affecting the likelihood. The processor may subsequently output the likelihood and the list of features.

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