Shell will use AI-based technology from big-data analytics firm SparkCognition in its deep sea exploration and production to boost offshore oil output.
SparkCognition’s AI algorithms will process and analyze large amounts of seismic data in the hunt for new oil reservoirs by Shell, the largest oil producer in the U.S. Gulf of Mexico.
SparkCognition and Shell have formed a technology collaboration that aims to accelerate the pace of imaging and exploration of subsurface structures using generative AI technology.
By using advanced AI algorithms to process large amounts of data and automate the analysis, SparkCognition says it aims to improve efficiency and speed of exploration workflows, leading to increased production and higher success rates.
The traditional approach to subsurface imaging and data analysis is time intensive and costly, relying on terabytes of data, high-performance computing and complex physics-based algorithms to analyze and identify exploration opportunities. The proprietary generative AI approach being developed by Shell and SparkCognition uses deep learning to generate reliable subsurface images using far fewer seismic shots—as little as 1% in completed field trials—than traditionally necessary, while preserving subsurface image quality; this offers substantial workflow acceleration and HPC cost-saving opportunities, opening the door to novel applications and further innovation.
The patented approach to oil and gas exploration is being applied to other complex problems where a reduction of data and time can have significant implications. This includes opportunities in onshore exploration, satellite imaging for weather patterns, national security and threat assessment.
“We are thrilled to partner with Shell to bring the power of generative AI technology to oil and gas exploration,” said Bruce Porter, Chief Science Officer, SparkCognition. “Generative AI for seismic imaging can positively disrupt the exploration process and has broad and far-reaching implications across industries— driving greater efficiencies, lower cost and accentuating sustainability initiatives.”