Drilling into success:  the dynamic duo of AI and Lessons Learned

In the landscape of drilling operations, finding innovative ways to enhance performance and increase cost estimation accuracy is paramount.

Fortunately, the emergence of artificial intelligence (AI) has opened the doors to groundbreaking advancements in these areas. Combining lessons learned in drilling with AI can synergise in the design of wells and the estimation of future drilling costs.

Utilising Lessons Learned in Drilling in Conjunction with AI

One of the most valuable assets in the energy industry is the acquired knowledge from previous projects, commonly known as lessons learned. Combining lessons learned with AI-driven analytics can produce powerful insights that drive efficiencies in well design and drilling cost estimation.

By intelligently incorporating past drilling experiences, companies can identify trends, patterns, and best practices that have proven successful. This holistic approach minimises the risk of repeating errors, enhances decision-making, streamlines operations, and optimises cost efficiencies.

Enhanced Well Design

AI has the potential to transform the well design process significantly. By leveraging historical lessons learned, and complex operational algorithms, AI systems can identify optimal drilling parameters, trajectories, and casing designs. AI algorithms can learn from patterns in geology, wellbore stability, and reservoir behaviour, enabling engineers to create highly efficient well designs.

Through continuous learning and adaptation of lessons learned, AI-based well design systems can refine their recommendations, helping to minimise drilling risks, increase production rates, and reduce overall project costs.

Accurate Drilling Cost Estimation

Drilling cost estimation plays a crucial role in well planning, drilling budgeting, and drill-or-drop decision-making. Traditionally, cost estimation relied on past experiences and expert judgment, which often led to discrepancies and inaccuracies. By leveraging AI techniques to factors such as well depth, mud type, and even weather conditions, and applying statistical simulation methodology in cost estimation model, energy companies can analyse vast amounts of historical project data. As a result, they generate more accurate cost estimates.

This ensures better financial planning and drilling project profitability.

Mitigating Risks

The integration of AI and lessons learned helps mitigate potential risks associated with well design and drilling operations. AI algorithms can analyse data to identify patterns and potential risks, but they may not fully grasp the context or foresee unique challenges. Lessons learned provide a qualitative layer to risk assessment. This proactive approach allows operators to implement necessary precautions, evaluate alternative strategies, and effectively manage risks. By leveraging the collective knowledge acquired from past projects, companies can significantly reduce costly downtime, operational failures, and HSE incidents.

Human Judgment and Decision-Making

Human judgment is crucial in evaluating the applicability of past experiences to new situations. Project managers and drilling teams can use their judgment to decide which lessons are most relevant and how to apply them effectively. While AI can provide recommendations based on data, it might lack the nuanced decision-making abilities of experienced professionals. Human judgment is vital in making decisions that consider the broader project context.

Continuous Improvement

The iterative nature of projects allows for continuous learning and improvement. Teams can actively adapt past experiences, fostering a culture of continuous improvement. AI systems require continuous updates and improvements based on evolving data. However, they may not inherently understand the need for cultural or procedural changes without human input.

The combination of AI and lessons learned represents a powerful synergy that can transform the oil and gas industry’s approach to well design and drilling cost estimation. By harnessing the capabilities of AI algorithms and integrating valuable knowledge from previous projects, companies can drive efficiency, optimise well designs, and accurately estimate drilling costs. This dynamic duo not only improves project planning and decision-making but also mitigates risks and enhances overall operational performance. Embracing AI and leveraging lessons learned, the industry can achieve cost-effective drilling operations while paving the way for a more sustainable and efficient future.

The AGR iQx™ drilling engineering software provides a dedicated feature for capturing lessons learned called “Experiences.” This functionality streamlines the collection, storage, and analysis of past experiences and lessons learned, allowing for easy output based on criteria such as rig, location, casing type, or similar events, etc.

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