Chevron accelerates AI Adoption, Transforming Data into Drilling Insights
Chevron is rapidly integrating artificial intelligence across its operations, with a core focus on leveraging data to optimize everything from oil exploration to workplace safety. The $250 billion energy giant is prioritizing practical AI deployments over lengthy proof-of-concept projects, aiming for tangible returns on investment and a important boost in operational efficiency.
A senior official stated that “Data is the ultimate accelerant for all of our AI use cases,” emphasizing the company’s commitment to data-driven decision-making. This shift is particularly crucial in complex environments like offshore drilling in the Gulf of Mexico, where Chevron navigates challenging conditions miles beneath the ocean floor.
Modernizing Infrastructure with Microsoft and SLB
In 2019, Chevron embarked on a modernization initiative dubbed ‘Triple Crown,’ partnering with Microsoft and oilfield services company SLB to standardize and enhance its cloud-based tools. This collaboration resulted in the integration of Azure-native applications into SLB’s DELFI cognitive exploration and protection (E&P) platform. DELFI E&P now empowers Chevron to process, visualize, and interpret data from multiple sources across the entire energy lifecycle – from exploration to midstream operations.
Chevron possesses “an enormous amount of data,” according to a company representative, but historically, much of this data resided in unstructured formats across various share points. While the company maintained “vrey robust systems of record,” unlocking the value within this unstructured data required a new approach.
Scaling AI in the Cloud for Broader Impact
For years, Chevron developed effective algorithms, but these were typically deployed at a limited scale on-premises. The company is now aggressively scaling these algorithms in the cloud to achieve greater efficiency and broader impact. This transition allows Chevron to analyze significantly larger areas, moving beyond evaluating a single three-mile-by-three-mile block in the Gulf of Mexico to encompass much wider operational zones.
The Microsoft-SLB collaboration has yielded three key products: fdplan,DrillPlan,and DrillOps. FDPlan utilizes high-performance computing (HPC) to integrate subsurface models, enabling faster and more informed decision-making. for example, in the Gulf, FDPlan assists chevron in analyzing various reservoir growth options to identify the most optimal scenarios. DrillPlan is tailored for engineers designing drilling plans, while DrillOps supports teams actively engaged in well drilling.
Time Savings and Increased Efficiency
The impact of these AI-powered tools is already evident.Before the initiative, subsurface employees reportedly spent up to 75% of their time searching for data. Now, a company release noted, that time is decreasing, and the speed at which insights are generated is accelerating. DrillPlan, specifically, has reduced deepwater well planning by 30 days, and in Argentina, the planning cycle for an eight-well pad has been slashed from two weeks to less than a day.
One analyst noted that the move to the cloud has acted as “a real force multiplier,” propelling chevron into a new era of modernization.
Modular Systems and the Rise of ‘Chevron Assist’
Chevron’s AI team is now prioritizing modularity in its development efforts. Initially, the focus was on a simple search function for a complex SharePoint system. However, as user needs evolved, the team expanded the system to include a retrieval agent, an evaluation agent, and an orchestrator agent, demonstrating the power of a flexible, modular architecture.
Another key initiative is ‘Chevron Assist,’ a chat interface designed to streamline access to health, safety, and environmental (HSE) standards. This tool allows employees to quickly combine relevant standards for different crews – drilling, operations, and maintainance – eliminating the need to navigate through numerous documents. A senior official explained that the team realized they needed to approach the problem from the user’s perspective, leading to significant improvements in workflow efficiency.
Prioritizing Deployment Over Endless Pilots
Chevron is deliberately avoiding prolonged proof-of-concept (POC) projects, recognizing their limited value. The company’s strategy centers on deploying promising use cases into production, ensuring a clear link to the bottom line and a strong value proposition.
“We know that with a curated data set and really enthusiastic, well-meaning group of users and a super narrowly defined use case, there’s almost 100% certainty that your POC will be successful,” a company representative stated. However, the focus remains on delivering tangible results, not simply demonstrating potential.
Building Trust and Addressing the Human element
Successfully deploying next-generation tools requires addressing the crucial element of trust. Enterprise leaders must understand the expectations of users at all levels and ensure that the new systems are reliable and user-friendly. A company representative emphasized that if employees don’t trust the tools, they won’t fully embrace them, hindering the potential for widespread adoption.
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