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Odin is a framework powered by AI, created to analyze and rank various complex assets, including both drilled and planned wells, equipment, and drilling crews. This product offers a straightforward method for such evaluations, allowing operators to rate these assets within individual sites, across multiple locations or over a period of time. Odin plays a crucial role in the planning phase of well construction, offering strategies to cut costs and accelerate project schedules, thereby enhancing the overall efficiency of well construction workflows.


A multi-metric-based approach where each metric in turn depends on multiple factors, is the basis of Odin.  State-of-the-art explainable AI (XAI) techniques helped build a hierarchical and an analytically sound unifying scheme that supports easy roll/unroll for macro/micro-level analysis​.  Odin brings in synergy between multiple indices by using interdependent metrics and common factors.

Harness the power of the past to shape the future with our advanced analytics platform.


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By learning from historical data, Odin intelligently groups assets through complex comparisons, allowing for nuanced understanding and strategic alignment. When a new asset emerges, it's swiftly categorized with the most fitting group, ensuring consistency and insight. The goal is to emulate the best-in-class, continuously evolving through learning and adaptive course corrections.

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Odin enables real-time scoring and ranking, providing a powerful tool for monitoring and comparing well performance in various aspects. Users can assess how a well stacks up against its own historical data, as well as against other wells within the same cluster, offering a comprehensive view of efficiency and productivity of operations.

Odin allows for comparisons across different depth ranges and time intervals, giving users a detailed understanding of performance trends. Additionally, Odin's capabilities extend to evaluating the effectiveness of corrective actions, by allowing users to compare scores before and after such interventions. This real-time feedback loop is invaluable for making informed decisions and optimizing well operations on the fly.

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