Implementing large-scale projects within a company are challenging tasks and often provide a good learning curve that can be beneficial to understand the complexity of the work involved. An integrated subsurface to surface asset modeling solution was implemented at the country level to automate production capacity planning while optimizing shortfall and opportunity identification (Hafez et al., 2018).

Several structured business processes support the developed system; it orchestrates the analytical processes followed by the corresponding approval system. A robust data management process was implemented and backed with a business process that includes more than 150 configurable exception rules. Besides, the developed solution leverages the rigor of the first principle and data-driven models to provide a desired and stable outcome ranging from potential evaluation, quota definition, capacity management, business plan validation, and other business processes. The developed solution can isolate wells, sectors, reservoirs, and/or fields for further evaluation. Given the challenge of balancing market demand with profits and subsurface deliverability, a time-efficient, balanced, and integrated solution is expected to provide an edge to an organization in this competitive environment.

The Integrated Capacity Model (ICM) system has already been utilized for capacity and deliverability of 2019 and 2020 ADNOC business plans demonstrating 99% agreement with field capacity tests. The system shown +3% profit gains through various production optimization scenarios, while recommending which assets, fields, and/or reservoirs can be targeted to achieve those targets.

Developing and implementing the solution at such a large scale surfaced various challenges at organizational, infrastructure, and solutions/workflows. This paper discusses those challenges and the ‘lessons’ learned during the implementation of this solution. Various value-added use cases are presented.

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