Machine learning is a subset of artificial intelligence (AI) that enables computer systems to learn from data and improve without being explicitly programmed. Machine learning is the most practical application of AI that can be deployed in the enterprise today. The Organization for Economic Co-operation and Development (OECD) estimates that AI could add up to $16 trillion to global GDP by 2030. This equates to over 10% of his gross world product.
Machine learning is a rapidly growing area in the oil and gas industry that has the potential to revolutionize the way companies explore and produce oil and gas. It can be used to analyze seismic data, well logs, and other geological data to identify potential oil and gas reservoirs. Machine learning algorithms can also analyze production data and identify patterns that can be used to improve well performance. This can increase production rates and reduce downtime. In addition, this analysis can also be used to identify potential hazards, thus preventing nuisances and increasing operational safety.
The oil and gas industry has experienced two major disruptions in just three years, in the form of COVID-19 and the Ukraine conflict. The former has impacted global energy demand, while the latter has wreaked havoc on oil and gas supply chains following sanctions against Russia, the world’s largest energy supplier. This has created a need for enhanced oversight and performance optimization across all project design, construction, logistics, inventory management and maintenance functions. Above all, companies also want to better monitor market demand in order to adjust production. The goal is to find every opportunity to reduce costs in the long run.
The AI market is projected to grow significantly from 2022 to 2026
Machine learning benefits companies in this scenario by driving automation, process improvement, and demand forecasting. We can help you modernize maintenance, detect leaks, streamline data management and documentation, and optimize your inventory and supply chain. Nonetheless, the challenge of recruiting machine learning experts who understand oil and gas datasets remains a significant hurdle to its adoption.
To learn more about oil and gas companies and their adoption of machine learning, see GlobalData’s new thematic report, Machine Learning in Oil and Gas.
