Using deep-learning models to automatically identify subsurface reservoir boundaries in real time

Abstract

The disclosure focuses on using a boundary identification system to actively determine borders and boundaries in subsurface geological features, such as reservoirs. In various implementations, the boundary identification system uses an ensemble image model leveraging multiple image-to-image machine-learning models to efficiently and accurately generate reservoir boundaries from inversion result profiles and images. In many instances, the boundary identification system generates reservoir boundaries from inversion results in real-time. Additionally, in some instances, the boundary identification system further improves the accuracy of the ensemble image model by diversifying the inputs and using ensembling on the individual model outputs during inference.