CCSNet.ai

CCSNet.ai is a web application developed by Gege Wen at Stanford University, advised by Prof. Sally M. Benson.

CCSNet.ai is hosted on Microsoft Azure, providing an average of 1,000 predictions per day to researchers, students, regulators, and industrial users across North America, Europe, and Asia. This web app predicts CO$_2$ gas saturation plume migration and pressure for Synthetic Heterogeneous, Homogeneous, Purely layered, and User upload isotropic permeability maps.

The isotropic cases are predicted with pre-trained convolutional neural network models (Wen et al., 2021).

Anisotropic permeability maps are supported with the Synthetic Heterogeneous option, predicted with pre-trained enhanced Fourier neural operators (Wen et al., 2022).

[Paper video] [Web demo] [Stanford Center for Carbon Storage]