Machine Learning for Carbon Footprint Reduction
How a major oil company utilized machine learning to adapt to changing environmental regulations in California to continue its heavy oil production at lower cost and lower emission.
This project is a successful example of an Industry-University Partnership program that resulted in the development of a low-code ML tool for petroleum engineering subject matter experts. Based on California environmental regulations energy companies are obligated to stop using steam injection simulation. This project developed an end-to-end data-driven process to ingest oil and gas production data from thousands of wells over several decades to identify best candidate wells to receive chemical enhancement treatments and increase production levels in heavy oil operations while eliminating GHG emissions associated with cyclic steam operations.Â