Ai Enabled Digital Twins Enabling Integrated Production Optimization and Autonomous Operations

Abstract

Abstract ADNOC has deployed an AI enabled Production System Optimization (AiPSO) solution to digitally transform production operations and maximize asset performance across thousands of wells, multiple production networks, and reservoirs. AiPSO addresses legacy surveillance approaches, delayed diagnostics, and continuously evolving operating practices by delivering real-time, integrated production intelligence from reservoir to export. The solution enables early event detection, GenAI assisted engineering decisions, and closed-loop optimization, ensuring daily operations remain compliant with operating and reservoir guidelines while sustainably improving production reliability and maximizing value across ADNOC's upstream assets. AiPSO is implemented as an Integrated Production System Digital Twin spanning reservoirs, wells, and surface networks, built on hybrid physics-based and AI driven models. A scalable Industrial Data and AI Foundation underpins the platform, automating real time data ingestion, contextualization, and model orchestration via a centralized DataOps pipeline. Core workflows include exception-based surveillance, automated diagnostics, closed loop production optimization, and integrated field management. Generative AI capabilities advance from an AiPSO Copilot for engineers to domain-specific advisory services and AiPSO Agent, dramatically accelerating the diagnosis-to-action cycle. Real-time engineering operating envelopes are employed to define safe operating limits and enable autonomous well control as the execution layer of the solution. Field deployment of AiPSO has delivered measurable production improvements through over 25 advanced digital workflows implemented across ADNOC's fields. The Phase 1 rollout across eight producing fields in 2025-2026 enabled real-time surveillance, automated diagnostics, and intelligent production optimization, resulting in a sustained 1-2% production uplift with no incremental CAPEX. Key workflows include exception-based well surveillance, artificial-lift diagnostics, multiphase flowmeter validation, and integrated production network monitoring significantly improved asset visibility and decision quality. The Intelligent Production System Digital Twin allowed earlier identification of reservoir, well, and surface constraints, reducing time-to-intervention and improving production stability. Smart surveillance shifted operations from reactive response to proactive constraint management, while GenAI enabled workflows accelerated root-cause analysis and recommendation cycles, shortening engineering response times and increasing operational confidence. By generating real-time engineering operating envelopes, AiPSO enables safe closed-loop control through autonomous well adjustments. This transition from manual, siloed workflows to integrated and increasingly autonomous operations establishes a scalable, resilient foundation for real-time production optimization and proactive asset management. AiPSO is a multi-field scale deployment of an AI-driven, digital twin enabled production optimization system spanning from reservoir to export facilities. AiPSO demonstrates tangible production uplift through fully operationalized workflows and a progression toward autonomy in daily operations. The introduction of Generative AI evolving from conversational engineering copilots to action-ready AiPSO Agents represents a novel extension of digital oilfield practices. AiPSO provides the core foundation for autonomous production optimization across large, complex assets, setting a new benchmark for digital transformation in upstream operations