Petroleum Development Oman (PDO) is the leading exploration and production company in the Sultanate of Oman. The Company delivers the majority of the country's crude oil production and natural gas supply. The Company is owned by the Government of Oman (with a 60% interest), Royal Dutch Shell (34%), Total (4%) and Partex (2%). The first economic oil find was made in 1962, and the first oil consignment was exported in 1967.
Abstract The Nimr Cluster, located in South of the Sultanate of Oman within Block 6 and operated by Petroleum Development Oman (PDO), represents the largest and one of the most complex oil-producing assets in the country. The cluster comprises 23 interconnected fields and more than 3,000 drilled wells, many of which are in advanced stages of maturity. Aging infrastructure, increasing water cut, and declining reservoir pressure have led to a growing dependency on well intervention activities to sustain production and manage integrity. In Nimr cluster, over 1200 hoist interventions are executed every year. Consequently, efficient planning and deployment of hoist units have become critical to minimizing deferment and reducing restoration cycle time (RCT), which is defined as the duration from when a well is identified as requiring intervention to the moment it is returned to production. Historically, hoist planning in the Nimr Cluster was conducted using spreadsheet-based tools and manual data compilation. This approach was time-consuming, prone to human error, and limited in its ability to account for dynamic operational constraints. The fragmented nature of data sources, frequent manual updates, and subjective prioritization often resulted in suboptimal resource utilization, extended idle time, and delayed well restoration. This paper presents the development and field implementation of the Hoist Sequence Optimizer (HSO), a digital decision-support system designed to automate job prioritization, optimize hoist deployment, and enhance workflow transparency. The system integrates operational, production, integrity, and logistical parameters into a structured ranking and sequencing methodology. It generates dynamic intervention schedules to support daily and weekly planning decisions. Following deployment, planning time was reduced by approximately 90%, idle time of hoist units decreased, and compliance with intervention planning targets improved significantly. Implementation of the HSO also contributed to an estimated 20% reduction in restoration cycle time through improved visibility and strategic sequencing. Furthermore, the system enhanced collaboration between subsurface, operations, and planning teams. The results demonstrate that locally developed, end-user-driven digital solutions can deliver substantial operational improvements when aligned with field realities. The HSO provides a scalable and transferable framework for modernizing well intervention planning in mature-field environments without reliance on vendor-driven platforms.
Abstract This project addresses a fundamental systemic weakness in Operational Risk Management (ORM) within hydrocarbon operations: the disconnect between defined mitigation controls derived from formal Hazard Identification (HAZID) and their verifiable, timely execution by frontline field personnel. Historically, risk management has suffered from a "control execution gap" where theoretical safety measures remain siloed in desktop-based databases, away from the active work environment. The primary objective of this study is to transition the industry from a passive, document-centric compliance model to an active, digitally assured control execution workflow. The scope of this implementation encompasses all technical integrity mitigation actions generated by the central risk assessment platform which is used to manage SCEs deviations in PDO (Asset Pulse Platform). By leveraging the Mobile Mitigation Management System (M-MMS), the project ensures that the entire lifecycle of a mitigation from generation to final verification is managed entirely through a mobile environment at the point of work. The methodology involves automated ingestion of risk data, the generation of location-aware digital task packages, and real-time routing to ruggedized tablets assigned to field operators. Implementation results demonstrate three critical performance improvements: enforced control visibility for management, a significant reduction in the average time-to-completion for urgent tasks, and the establishment of a robust, immutable auditable trail. Ultimately, the M-MMS successfully transitions risk mitigation from a passive administrative overhead to an active, mandatory, and verifiable component of daily operational duties.
Abstract Digital transformation is critical to improving the reliability, availability, and operational efficiency of industrial electrical systems. This paper presents the implementation and operational experience of the Protection Relay Engineering Workstation (PREW) within Petroleum Development Oman's (PDO) electrical network. PREW enables secure remote communication, monitoring, and analysis of protection relays, significantly reducing fault response time, system downtime, and operational costs. Integrated into PDO's secure Process Control Domain (PCD), PREW adheres to modern cybersecurity standards and provides real-time access to protection relay data across geographically dispersed assets. Protection engineers can remotely analyze faults, retrieve disturbance records, and assess system conditions without physical site visits. A reference event demonstrates that PREW avoided a 1000 km round-trip travel and accelerated restoration by approximately 24 hours. The phased deployment over three years now covers approximately 50% of the network and has been incorporated into PDO's standard design and operational philosophy for new projects.
Abstract This paper presents a data-driven optimization initiative conducted in a critical sour gas plant aimed at unlocking hidden gas injection capacity without major capital expenditure. Through systematic data analysis, operational constraint identification, and process optimization, the study demonstrates how existing facilities can achieve improved performance while maintaining safety and operational integrity. The results show measurable increases in injection capacity and improved operational stability, providing a replicable methodology for similar assets facing capacity limitations.
Abstract Upper Shuaiba development drilling repeats one well design across many wells. The design is fixed. Execution is not. Two wells built to the same plan can take a very different number of days to drill, and because the wells are delivered in campaigns, that variance is paid for on every well. Reducing it is the aim of this work. This paper reports an integrated drilling workflow applied across three of the five Upper Shuaiba fields in Oman, on three rigs. The reservoir sits in a thin carbonate window, so the 6-1/8-in. laterals are steered continuously against real-time formation evaluation. The workflow combines optimized bottomhole assemblies, rotary steerable systems in the 12-1/4-in. and 6-1/8-in. sections, automated steering, drilling performance optimization (DPO) and real-time geosteering. Automated steering was engaged in about 90% of the steered sections in every field and on every rig, so it is a constant across the well set and cannot account for differences between wells. How much of each section the DPO workflow covered is the one thing that varies, and it is treated here as the variable under study. Coverage was examined in two hole sizes in two fields. In the 12-1/4-in. section of Field A, three benchmark wells drilled on the same rig span 0%, 31% and 81% DPO coverage. They delivered 34.2, 38.9 and 46.2 m/hr in that order, a 35% increase from the lowest to the highest utilization well, with no worsening of downhole dynamics at high utilization. In the 6-1/8-in. lateral of Field C, a well with the workflow effectively switched off delivered 18.7 m/hr, three wells at 1 to 8% coverage clustered at 27.4 m/hr, and three wells at 69 to 81% coverage averaged 34.1 m/hr, 24% above the low-coverage group. In both sections the improvement is concentrated at high coverage, and the low-coverage wells in Field C show that benefit does not accumulate in step with coverage. This is consistent with the approximately 70% coverage threshold reported for closed-loop optimization in published field studies, and the 24% is close to the 23.4% measured between automated and conventional sections on the Norwegian Continental Shelf by a different operator on a different rig fleet. These are commercial wells rather than a controlled trial, and the high-coverage cases in the 12-1/4-in. section are single wells; the relationship is reported as an association measured across the well set. The result held at campaign scale. One rig delivered 28 wells in 440 days against an authorized plan of 540 days, about 100 days ahead. The recovered rig days represent a multimillion-dollar saving on one rig. Performance did not climb over the fifteen months, and no small group of wells carried the average. At the well level, one well was delivered 5.51 days ahead of plan with zero non-productive time and another 7.86 days ahead. The operator's Well Engineering Directorate recognized the delivery performance on both.
