Summary
TotalEnergies is scaling their surface data platform, powered by Cognite Data Fusion, across upstream drilling and wells operations. The platform will enable them to accelerate financial leverage from AI and data and help them reach key operating goals.
The Challenge
TotalEnergies, a leading global integrated energy company, has an ambitious multi-energy strategy with plans to maximize energy production across its portfolio, monitor and reduce emissions, and maintain their strong commitment to safety and HSE. Getting there requires reducing CapEx and OpEx by optimizing asset operations and delivering more productivity through their digital programs.
Even though TotalEnergies has had a long track record of digital leadership and transformation, their existing application-centric approach has introduced complexity into their technology ecosystem. Often, data remains siloed and difficult to access, making it difficult to develop and scale insights, AI, and future innovations as quickly as they’d like.
- Data Access and Acquisition: With over 200 different databases across their operations, data is often siloed and hard to use. In addition, only about 20% of data from offshore sites can be accessed in real-time, preventing timely insight generation.
- Data Quality and Usability: TotalEnergies’ high volume of data requires significant manual cleaning and with varying levels of quality. This makes it difficult for operators to rely on for predictions and critical decisions.
- Organizational & Cultural Inertia: There are often big gaps between the field-level operators (who need simple, reliable tools) and data scientists/physicists (who need clean, contextualized data).
The Solution
In 2025, TotalEnergies partnered with Cognite to accelerate their overall digital maturity in a phased approach that would help ensure long-term, scalable digital transformation across TotalEnergies' upstream assets. This project focuses on key opportunities in data management and access, moving to a more governed data product model, and enabling more teams to generate valuable insights.
Data Management And Access
Given their challenges with consistent data access and management, their first priority was to invest in a new surface data platform, powered by Cognite Data Fusion. This platform connects, aggregates, and contextualizes structured and unstructured data from SAP, Epermit, Sharepoint, OsiSoft PI, Arcgis, NPDMS and more into a single source of truth. As the technology needs for TotalEnergies evolve over time, data from new programs and sources (robotics, drones, etc) can be added seamlessly.
From Application Data to Data Products
Additionally, this surface data platform enables TotalEnergies to move towards a Data Product model, where data from 15 exploration and production domains (including Field Operations, Production Performance, Engineering, Logistics, and others) can be more tightly governed. In this new model, cross-functional teams with expertise in the data can collaborate to enrich the volume and quality into trusted “products” that can be used scalably and with high fidelity over the long lifecycle of their assets (20-30 years).
Enabling More Teams, Workflows, and Use Cases
With the technological infrastructure and governance model in place, TotalEnergies will be able to create more specific digital products and applications for individual sites and use cases at much lower cost. Not only will it be easier to leverage data for applications, but the data will also be available for more ad hoc insights. This will enable them to drive significant operational value in areas such as augmented worker, asset maintenance, production optimization, supply chain, and asset integrity.
With Cognite, TotalEnergies saw a clear path to make more data available, leverage more digital tools and AI, convert more knowledge into digital applications, and make it easier to collaborate across disciplines.
The Impact
Over the next three years, TotalEnergies plans to roll out the surface data platform to 36 of their upstream assets, reaching a new level of scale that would have taken much longer without Cognite’s technology.
Collectively, these elements are projected to translate into significant financial and operational gains for the organization. The Data Product Model and Cognite Platform reduce the time and resources typically spent on preparing data for analysis, accelerating time-to-value for AI and other digital use cases and freeing teams to focus on high-impact improvements rather than data wrangling. This means more optimized production, fewer outages, extended asset life, and reduced CapEx/OpEx with successes that can be easily scaled and replicated across the portfolio.