Across the energy sector, artificial intelligence (AI), cloud computing, data collection, and predictive maintenance are playing a critical role in speeding the transition to a cleaner energy function.
Participants said that digital technology has already transformed oil and gas production activities on the surface. AI has reduced equipment costs through predictive maintenance algorithms that improve maintenance cycle planning, eliminate unscheduled downtime, and extend the life of drilling equipment.
“How do I maximize my transportation [of materials] to make sure all deliveries are not arriving at the same time?” one commenter asked, to illustrate the challenge. Data can improve scheduling to ensure “they’re not sitting there for eight hours at a time.” An optimized schedule reduces costs by conserving the number of tools a company needs.
Improving delivery and work schedules involves sharing data among service providers, well operators, and logistics companies. The biggest challenge to integrating the data across all operations is that some companies are reluctant to share information they consider proprietary. Systems compatibility also can be an issue, especially for companies that have multiple legacy systems from acquisitions.
The next challenge will happen underground. Sensors will be better able to determine where to drill and where to fracture, which will increase production from each well and reduce the need for additional drilling sites. Data collected from inside the wellbore can enhance financial forecasting and other activities.
Rigs, equipment, and supplies used in the drilling process, such as deliveries of sand and water, can be coordinated to reduce the amount of time rigs sit idle. That, in turn, allows rigs to be moved from one drill site to another more quickly, meaning that fewer rigs can drill more wells.