data analytics

The full potential of data can only be realized when it is viewed not in isolation but as part of the dynamic triad of hydrocarbons, the data, and the people who interpret it and act on it.

Over decades of exploration and production, the oil and gas sector has accumulated vast amounts of legacy data in various formats. Artificial intelligence and machine learning present an opportunity to transform how this unstructured data is processed and used, enabling significant improvements in operational efficiency and decision-making.

Organic data governance emphasizes flexibility, stakeholder engagement, and a culture that values data integrity.

As part of a subnational climate coalition, the state is moving forward with a satellite data project to track methane emissions.

Data quality and mission clarity matter more than ever, according to experts speaking at this year’s International Petroleum Technology Conference in Kuala Lumpur.

The massive system brings advanced capabilities for simulation, AI, and data analysis to drive breakthroughs in cancer research, materials discovery, energy technologies, and many other fields.

In the Marcellus, Repsol is slicing and dicing legacy data to evolve its completions strategy, while in the Permian, ExxonMobil is mastering the 4-mile lateral drillout using lessons learned.

The trial phase of the agentic program used AI agents and combined large-language-model technology with data collected from more than 15% of ADNOC’s onshore and offshore wells.

SLB said it plans to integrate INT’s technology into its digital data and artificial intelligence platforms.

The authors make the case that data science captures value in well construction when data-analysis methods, such as machine learning, are underpinned by first principles derived from physics and engineering and supported by deep domain expertise.