Improved computing power and advancements in artificial intelligence and machine learning have increased collaboration between AI systems and human experts for raw data analytics and clean-up, data analytics, and interpretation.  Identifying patterns and correlations in the data enables engineers to make more informed decisions regarding reservoir characterization, well optimization, production management, and environmental safety. This session will include discussions on some of these developments.

This technical session aims to explore how AI can assist decision makers in the industry. Will professionals be able to harness the power of data analytics, machine learning, and predictive modeling to improve their decision-making process? How will AI better inform decisions related to capital investments, optimization of operations, risk reduction, or energy transition? Will we be able to leverage these cutting-edge methods and blend their insights with the experience and intuition of humans? Or will AI supplant human-made decisions?

Reliably acquiring, networking and securing data in a timely and relevant manner is foundational to any digital transformation and an important prerequisite for AI-driven solutions. 

Session 3 will discuss future-focused strategies including hardware selection, database architecture with focus on cloud infrastructure, edge computing and secure networking.

With growing digital capabilities subsurface modelling practices will change in all fronts. Digital enablers with certain level of AI have been utilized in exploration; in contrast subsurface models of producing fields are mostly generated by educated concepts of integrated teams. Progression from “human-intelligence” based practices towards AI will certainly be challenging. In this exciting Session we will have an open dialog aiming to anticipate the status, capabilities and role of AI based subsurface modelling for O&G industry in year 2030.

This session will focus on the AI challenges and opportunities for exploration and synergies with the energy transition. The future of exploration using AI is important to secure our energy future for transitional hydrocarbon supply, carbon storage, and geothermal prospects. Discussions will focus on pathways and opportunities across the data and analytics life cycle to reduce risk, identify volume, and overcome regulatory hurdles.

The recent decade witnessed a substantial increase in data collection and utilization across the oil and gas industry, thanks to the rapid advancements in sensors, monitoring technologies, and AI innovations. This data-driven transformation has been significantly improving operational efficiency, enhancing safety measures, and uncovering insights that were previously hidden in the vast data. In this session, we will discuss and envision the future of drilling and completion in the era of AI and automation.

With the unprecedented scale of data acquisition and downhole surveillance, the future of field development lends itself readily to analysis and optimization via Artificial Intelligence techniques. For example in the case of unconventionals, rock/fluid properties, completions design, spacing and timing considerations provide a rich, multi-disciplinary and highly non-linear system where the objective functions are further conditioned by economic and operational considerations. Conventional applications include intelligent wells, dynamic flow control systems and subsurface/facilities coupled systems. This session will explore this theme and finalize by discussing the role of AI in accelerating the energy transition, with an eye on the integration of field development and carbon management.

The digital transformation in the oil and gas industry has laid a solid foundation for AI to support production operations in their pursuit of maximizing revenues efficiently while prioritizing environmental stewardship. The immense scale of operations, effective allocation of substantial operational expenditures, and adherence to state and federal emissions regulations present unique challenges for production engineers and field personnel. AI and emerging technologies have a crucial role in enhancing planning, execution, monitoring, and decision-making processes, both in the present and future workflows.

In this session, we will explore the current workflows that stand to gain the most from AI integration, the cutting-edge capabilities on the horizon, and the long-term vision of a comprehensive synergy between engineering disciplines. This synergy will be driven by top-tier petroleum professionals utilizing state-of-the-art tools and technology, combined with the advanced capabilities and expertise of artificial intelligence.