Artificial Intelligence in the Oil Industry: A Treasure for Maximizing Wealth

The oil and gas industry sits atop one of the world’s largest industrial data repositories, accumulated over decades of seismic surveys, sensor readings, and refining operational data. This data wealth has served as raw material that made the sector one of the earliest adopters of artificial intelligence at an operational scale, prompting major companies such as Saudi Aramco and Abu Dhabi National Oil Company (ADNOC) to become among the first industrial users of these technologies in the Middle East. Energy companies use machine learning to analyze historical seismic data and identify areas with a high probability of oil and gas presence, then narrow down the most suitable sites for drilling exploratory wells. After a discovery is made, digital technologies help build three-dimensional models of reservoirs, providing a more accurate picture of their characteristics and aiding in determining the best ways to develop them. One published example illustrates the amount of time AI can save: programs based on this technology completed the well modeling required to develop an offshore field in a single night, compared to work that previously took months of manual effort, according to the Journal of Petroleum Technology in April 2026.

However, the irony is that harnessing the speed of AI first requires work that may take months, or even years. A significant portion of oil industry data has accumulated over decades, with some still recorded or stored in different systems and formats. Consequently, companies must digitize, clean, standardize, and convert this data into processable formats before using it to train machine learning models. This represents one of the biggest obstacles to expanding AI use in the energy sector: the problem is not a lack of data, but rather making the vast amounts of available data efficiently usable.

Aramco’s Fourth Industrial Revolution Center in Dhahran aggregates more than 5 billion data points daily, while the Oil Supply Planning and Scheduling Department of ADNOC receives readings from more than 100,000 sensors distributed across operational facilities, pipelines, refineries, and ports. These readings are automatically compiled into nightly reports available to engineers the following morning. Supply movements are displayed on a wall comprising 150 integrated screens spanning approximately 67 meters, enabling tracking of oil and gas flows across the network. This facilitates planning, scheduling, and monitoring of flows from production facilities to their final destinations. Aramco states that predictive maintenance models can detect early signs of corrosion before failures occur, helping reduce unplanned downtime.

In the UAE, ADNOC operates the RoboWell system for autonomous well control, which uses algorithms that allow wells to automatically adjust their operations in response to changing operating conditions, thereby enhancing efficiency and contributing to emission reductions. The system was first deployed in 2023 at the North East Bab field, the company’s first “smart” field, before being rolled out at the Nasr offshore field in July 2024.