Petroleum Industry Value Chain Optimization: the Inevitability of Artificial Intelligence and Data Science in Midstream and Downstream Development

Abstract Implementing artificial Intelligence (AI) and data science holds significant potential for optimizing Midstream and Downstream operations in the petroleum industry, fostering margin enhancement opportunities and overall value chain optimization. This involves streamlining processes such as production, logistics, pipeline monitoring, refinery operations, plant safety, and environmental impact reduction. Artificial intelligence involves developing intelligent systems that operate autonomously, learn from experiences, and improve performance with increasing knowledge. On the other hand, data science focuses on extracting, cleaning, and analyzing data to drive valuable insights. In the midstream stage, which pertains to crude or refined petroleum transportation, digital twin technology plays a crucial role, offering applications like pipeline monitoring and logistics optimization. Downstream is the refinery, processing and purifying of crude oil and natural gas. Companies like Shell and Chevron leverage in real-time data from sensors, cameras, and drones to create dynamic representations of operations and equipment for real-time monitoring and analysis. However, maintaining accurate and up-to-date digital twin models poses challenges. This is where AI techniques like optimization (model creation and updating), generative modelling, data analytics, predictive analytics, and decision-making come to play. For instance, according to Abn resource, Shell Lubricants introduced the AI-powered Chatbot tool, Shell LubeChat, in 2018, enhancing customer service for business-to-business lubricant clients and optimizing profits. Cognite Data Fusion, a data solution, codifies industrial knowledge into software for seamless integration with existing ecosystems, facilitating scalability from proofs of concepts to operation-driven scenarios. Maintenance systems often struggle to intelligently schedule tasks without contextualized data from various sources provided by Cognite Data Fusion. Artificial intelligence and Data science solutions are instrumental in helping midstream and downstream operators achieve optimal performance, contributing to both profitability and sustainability.