The rapid development of oil and gas intelligent operations depends on artificial intelligence (AI), automation, and data analytics to achieve optimal conditions in oil and gas operations.
Digital-twin technology uses virtual copies of physical assets to perform complex analyses that improve performance while actively identifying mechanical failures before they materialize. Revolutionary drone and robotic technologies transform field operations by enabling autonomous systems to perform critical inspections in hazardous environments. These solutions eliminate hazardous conditions for workers, develop comprehensive data acquisition systems, and achieve cost-effective operation. The autonomous systems use advanced sensors and AI-powered image recognition to spot tiny faults in infrastructure and track environmental conditions while delivering critical operational data.
Cloud computing, alongside industrial Internet of Things (IIoT) platforms, provides exceptional capabilities for data consolidation. The connected ecosystems enable businesses to distribute operational data between upstream, midstream, and downstream sectors, thus eliminating functional divisions and enabling data-driven group decisions. The drive for sustainability enables the technological development of AI and advanced analytics systems that strengthen carbon-capture approaches and reduce energy usage and supervisory methane releases. Modern systems are used more frequently to match operational developments and environmental targets.
Cybersecurity is becoming a strategic imperative. The rapid digital transformation of operations leads to advancements in blockchain and encryption that create protected, transparent supply-chain data management. Innovative solutions develop from technology suppliers working with software companies to establish new partnerships with traditional oil and gas businesses. Businesses that work together to create integrated technological systems that use machine learning, predictive analytics, and autonomous systems establish new operational standards. The energy industry stands on the verge of a technical breakthrough enabled by the advancement of AI and analytics that will create new efficiencies and safety standards for intelligent energy management in the future.
Summarized Papers in This May 2025 Issue
SPE 221158 Digital Transformation Leads to Smart Production Surveillance in Amazon Brownfield by Roberto Fuenmayor, Hugo Quevedo, and Christian Bonilla, SLB, et al.
IPTC 23455 Immersive Collaboration Platform Accelerates Upstream Growth by Badr Al-Harbi, Muhammad Al‑Readean, and Amell Al-Ghamdi, Saudi Aramco, et al.
OTC 35351 Digital-Twin System Provides Model-Based Operational Support by Chinenye E. Ogugbue, Zachary M. Greenawalt, and Yevgeniy Kondratenko, BP, et al.
Recommended Additional Reading
SPE 220932 Success Cases and Lessons Learned After 20 Years of Oilfield Digitalization Efforts by L. Saputelli, Frontender, et al.
SPE 222876 An Integrated Solution for Operational Planning in an Intelligent Underground Gas Storage System by H. Jiang, Chongquing XiangGuoSi Underground Gas Storage, et al.
SPE 223450 Agile Delivery of Business Through Integrated Planning, Application of Minimum Functional Objective, and Digitization by K. Ussenbayeva, Tengizchevroil, et al.
Cenk Temizel, SPE, is an energy professional with 20 years of experience. He worked at Saudi Aramco; Aera Energy, a Shell/ExxonMobil affiliate; Halliburton; and Schlumberger in the Middle East, the US, and the UK. Before joining the industry, Temizel was a teaching/research assistant at the University of Southern California and Stanford University. He serves as a technical reviewer for petroleum engineering journals and conference committees. Temizel has authored approximately 150 publications in reservoir management, production optimization, enhanced recovery processes, machine learning, and intelligent fields, and holds several US patents. He is the recipient of the SPE Regional Reservoir Description and Dynamics Award. Temizel holds a BS degree from Middle East Technical University and an MS degree from the University of Southern California, both in petroleum engineering.