The Unified Decision Framework: Integrating Technical, Financial, and Contractual Constraints for Optimal Strategy Generation in Complex Oil Field Developments

Abstract

This paper introduces an integrated digital platform designed to eliminate the persistent fragmentation among technical, financial, and managerial teams in upstream oil and gas projects. The platform unifies a wide range of project domains, including technical aspects (such as subsurface, surface, and operational) and commercial/managerial domains (such as financial and contractual), enabling project managers and executives to efficiently evaluate complex development scenarios and make transparent, organization-wide decisions. The platform features a fully coupled technical-financial modeling engine implemented in Python. Data exchange between commercial simulators and in-house financial modules is automated through API-based integration. The dynamic optimization necessary to link reservoir, well, and process models to project economics is achieved via various multi-objective optimization methods. Specialized modules (e.g., knowledge management, contractual tracking, downhole pumps performance) continuously feed quantified information, uncertainties, and constraints into this core engine. For instance, the contractual module dynamically aligns strategies with specific obligations, such as cost recovery thresholds defined by contractual terms and budget limits imposed by the project phase. Field validation was successfully conducted across two mature fields and 46 production/injection wells in southwest Iran over a 24-month testing period. The deployment confirmed the system's robustness and practicality as a scalable digital transformation framework. Key performance results demonstrate a significant enhancement in efficiency and accuracy. Specifically, the average decision cycle time was reduced by 91%, decreasing from four weeks to just three days. Furthermore, forecasting accuracy for operating expenses (OPEX) was substantially improved, achieving a reduction in Mean Absolute Percentage Error from a baseline of over 30% to less than 10%. The system also facilitates large-scale scenario generation, enabling the assessment of thousands of technical-financial combinations in parallel. This specific capability supports critical operational functions such as optimal rig scheduling, ESP management, minimizing unnecessary drilling, and production planning. Finally, executives gained access to an integrated decision dashboard linking operational performance, cost recovery, and contractual Key Performance Indicators (KPIs), thus ensuring transparency and traceability across the board. The primary novelty lies in the sophisticated strategy-generation mechanism that tightly integrates historical performance data, quantified statistical distributions, and contractual requirements into a unified decision framework. This robust cross-domain coupling enables rapid convergence toward the most balanced development strategy. This approach simultaneously satisfies technical, financial, managerial, and contractual constraints, ensuring unmatched consistency and transparency across the entire decision chain.