SLB will be able to deploy a physics-informed AI model builder for oil and gas operations following a deal with Geminus AI, SLB announced Jan. 10.

The investment and technology partnership agreement between the two companies gives SLB exclusive access to deploy Geminus’s model builder, which fuses physics-based approaches with process data to produce AI models that can be deployed at scale. The technology is faster and less expensive than traditional AI approaches, SLB said.

In one user case, SLB delivered a Geminus hybrid AI-driven application to optimize economic performance while reducing carbon emissions at a natural gas plant. The application, created by Geminus’ physics-informed AI solution, was trained using data from SLB’s Symmetry process simulation software. The application took just days to create, including the underlying hybrid AI model, and has the capability to evaluate 20,000 complex scenarios in under a 10th of a second, SLB said.

In other use cases, the technology has improved the performance of electric submersible pumps and industrial wellsite chokes.

Rakesh Jaggi, digital and integration president for SLB, said in a press release the partnership will produce a step change in operational performance for customers.

“Geminus’ capability to fuse AI methods with physics-based simulation data will empower customers to quickly and easily create hybrid models of their operating assets that can be optimized in real time against numerous outcomes, such as opex reduction, increased productivity and carbon emissions minimization,” he said.

The Geminus platform uses physics-informed AI computing to translate constraints of the physical world inside digital models. It does not require heavy inputs of data, and models can be easily updated with the infusion of new data points, SLB said. Data scientists and modeling engineers can use the platform to predict the behavior of complex systems and make informed real-time decisions.