Schlumberger Technology Corporation

Anatoly Aseev

Andrey Sergeevich Konchenko

Suhas Suresha

Prasham Sheth

Indranil Roychoudhury

Alfredo De La Fuente

A method implements property modeling using attentive neural processes. The method includes receiving sparse context input comprising a plurality of context locations corresponding to a plurality of geological property values for a geological property and selecting a plurality of target locations in a space of the plurality of context locations. The method further includes generating a predicted mean image for the geological property by an attentive neural process model using the plurality of target locations and the sparse context input and presenting the predicted mean image.

Property modeling using attentive neural processes

A method may include receiving, via one or more processors, a set of image data representative of equipment configured to distribute a gas. The method may then involve determining a type of equipment depicted in the first set of image data, retrieving a leak detection model corresponding to the type of equipment depicted in the first set of image data, and determining that a gas leak is present on the equipment based on the set of image data and the leak detection model. After determining that the gas leak is present, the method may include sending a notification to a computing device in response to detecting the gas leak.

Growing community of inventors

Menlo Park, CA, United States of America

Anatoly Aseev