Integrated Subsurface–Surface Intelligence for Comprehensive Reservoir Management: A Horizontal Well Case Study from ADNOC Offshore

Abstract

This paper presents the results of a stochastic seismic inversion and rock physics study of a carbonate field in the Abstract This case study outlines ADNOC Offshore's integrated well planning and execution strategy, designed to minimize uncertainty reduced risk via integrated subsurface-surface technologies. A horizontal producer was drilled in a complex pressure sink area with high gas and water risk, using advanced real-time technologies like Pressure While Drilling and PVT benchmarks for maximum reservoir contact. Real-time geosteering, Deep Azimuthal Resistivity (DAR) inversions, mud gas analysis, and Logging While Drilling (LWD) resistivity helped identify hydrocarbon zones and lithology, ensuring precise placement and reservoir integrity during drilling. A comprehensive pre-well modeling workflow was implemented using offset well data to predict reservoir characteristics such as pressure, resistivity, structural dips, and boundaries. The 6″ horizontal section was successfully drilled to the landing point, where formation pressure exceeded the Saturation Pressure (PSAT) threshold limit, justifying completion in the primary target zone. A Triple Combo Bottom Hole Assembly (BHA) equipped with Deep Azimuthal Resistivity (DAR) tools and formation pressure testing facilitated real-time geosteering, resistivity mapping, and structural interpretation. Advanced Mud Logging enabled continuous gas monitoring and hydrocarbon analysis, integrated with thirteen formation pressure tests that confirmed reservoir heterogeneity. Gas wetness and mobility ratios indicated a light oil phase with consistent fluid properties, confirming optimal well placement within the target zone. The Reservoir Engineering team utilises an integrated analysis platform that combines OHL, PLT, RST, and pressure data, facilitating time-lapse saturation mapping and isobaric visualisation. This methodology enhances both spatial and temporal resolution in reservoir assessments, supporting more accurate interpretation of saturation and pressure dynamics. By integrating data driven analysis with multi-disciplinary data, the well successfully achieved 100% reservoir contact across a 4,800-ft horizontal drain, meeting its production target and enhancing sweep efficiency to reach 2,000 barrels per day. Deep Azimuthal Resistivity (DAR) technology enabled precise mapping of continuous bottom boundaries and identification of three distinct resistivity layers, capturing formation dips ranging from flat to 0.7°, and confirming the presence of high-resistivity zones beneath the reservoir. Advanced Mud Logging further validated hydrocarbon type, mobility, and consistency, with surface gas responses aligning closely with subsurface resistivity trends. This comprehensive data integration facilitated precise wellbore placement approximately 10 feet above the bottom boundary, effectively avoiding water-prone zones. Selective completions, utilizing inflow control devices (ICDs) and packers, were employed to manage drawdown and prevent excessive pressure drops. Additionally, production rates were strategically controlled at the heel and toe of the well to minimize drawdown and delay gas liberation, thereby preserving long-term reservoir integrity and ensuring sustainable production performance. This case highlights the strategic value of integrating data-driven pressure testing at the landing point with Deep Azimuthal Resistivity (DAR), open-hole logs and advanced mud logging for comprehensive reservoir characterization. DAR enabled forward-looking structural and fluid mapping for proactive geosteering, while pressure testing provided quantitative validation. Mud logging offered continuous surface gas insights, confirming fluid type and continuity. The synergy of these technologies enhanced early structural recognition, fluid validation, and well placement, setting a benchmark for efficient, low-risk reservoir development in mature carbonate settings.