We have screened 65 Schlumberger AI and machine learning patents, filed in 2024-25. This is more than any other energy company. We expect AI to improve shale well productivity, entrench the reliance on Schlumberger tools and services, while also reducing costs, labor, time and net energy use in oil and gas.
Schlumberger is a leading global oil services company, headquartered in Houston, with 109,000 employees, listed on NYSE, generating $36bn of revenue in 2025, at a 24% adjusted EBITDA margin.
Schlumberger has been vocal about leaning into AI. In 2026, the company stated that “customers continued to invest in AI and automated solutions to improve performance and efficiency”.
Numerically, Schlumberger has filed more AI/machine learning patents than any other energy company across our company screens, including 3x more than its next largest rival. And its AI solutions were well reviewed in our recent screen of 40 AI case studies in oil and gas.
Hence in this data-file, we have reviewed 65 of SLB’s patents, which were first filed in 2024-25, and include the keywords “machine learning” or “artificial intelligence”.
Key focus areas across these patents are charted below. They include improved geosteering, to keep well trajectories on track, supplemented by enhancements in logging, telemetry and other drilling systems. Secondly, improved geological models are being generated. Third, fracturing operations are being optimized, often in real time, increasingly using fibre optic data, to ensure uniformity across perforations and clusters. Fourth, artificial lift is being optimized and downtime is being predicted. Finally, a portion of the tools were aimed at facilitating reporting, automating data-handling, so it did not take operators so much time, and would also be higher in reliability. Specific examples are in the data file.
Our strong conclusion is that these AI innovations will entrench reliance on SLB tools and frameworks (over 40 specific examples are named in the patents), while paying for themselves via lower costs, faster decisions, higher production, higher productivity, and savings in materials, labor, time and energy.
Underlying details, including a summary of each of 65 key Schlumberger’s AI/machine learning patents are captured in the data-file.