Seismic interpretation using flow fields
AssigneeSchlumberger Technology Corporation
InventorsZhun Li, Aria Abubakar
Life of this patent
Estimating the term…
Abstract
A method for modeling a subsurface volume includes receiving a plurality of ordered seismic images including representations of objects in the subsurface volume, generating flow fields based on a difference between individual images of the plurality of ordered seismic images, and identifying the objects in the seismic images based on the flow fields and the plurality of ordered seismic images.
Claims22
A method for modeling a subsurface volume, comprising:
- training a machine learning model to generate flow fields based at least partially upon a first training seismic image and a second training seismic image;
- receiving a plurality of ordered seismic images comprising representations of objects in the subsurface volume;
- generating the flow fields using the trained machine learning model based on a difference between individual images of the plurality of ordered seismic images;
- and
- identifying the objects in the seismic images based on the flow fields and the plurality of ordered seismic images.
A non-transitory computer-readable medium storing instructions that, when executed by at least one processor of a computing system, cause the computing system to perform operations, the operations comprising:
- training a machine learning model to generate flow fields based at least partially upon a first training seismic image and a second training seismic image;
- receiving a plurality of ordered seismic images comprising representations of objects in a subsurface volume;
- generating the flow fields using the trained machine learning model based on a difference between individual images of the plurality of ordered seismic images;
- and
- identifying the objects in the seismic images based on the flow fields and the plurality of ordered seismic images.
A computing system, comprising:
- at least one processor;
- and
- a memory system comprising one or more non-transitory computer-readable media storing instructions that, when executed by at least one of the one or more processors, cause the computing system to perform operations, the operations comprising:
- training a machine learning model to generate flow fields based at least partially upon a first training seismic image and a second training seismic image;
- receiving a plurality of ordered seismic images comprising representations of objects in a subsurface volume;
- generating the flow fields using the trained machine learning model based on a difference between individual images of the plurality of ordered seismic images;
- and
- identifying the objects in the seismic images based on the flow fields and the plurality of ordered seismic images.
Dependencies are inferred from the claim text.