This paper expounds the value of integrated decision based planning in delivering field development plan (FDP) in a LEAN way. The basic philosophy of lean is waste minimization or elimination of non-value adding activities to improve efficiency, quality and lead-time. Integrated decision based planning is considered as the most pragmatic and efficient approach in integrated reservoir modelling process. Dynamic modeling is the most preferred tool assisting subsurface decisions making. Nevertheless, the data centric approach with support of scaled reservoir model has the advantage over the conventional full field physics-based models specially, in case of a complex reservoir. Embracing the basic lean principles with focused decision based reservoir modeling strategy can establish a new level of performance within the organization in delivering FDPs. The Saih Rawl oil field (SRS) in North Oman is a thin Lower Cretaceous carbonate reservoir with post diagenetic imprint. Post oil fill structural change has resulted in re-saturation and oil trapping due to local capillary imbibitions. The complexities resulting from the tilted water contact, hysteresis in oil mobility and Sor variation with depth, pose a huge challenge in dynamic simulation. In addition, drilling feasibility for horizontal infill wells was quite challenging due to subsurface collision issues and rig footprint interference with existing surface facilities. Integrated decision based planning, linked to the subsurface and surface decisions was adopted for framing the integrated reservoir modeling (IRM) strategy. The IRM strategy with Decision Based Models (DBM), including analytical and sector simulation models, were used to understand the sweep pattern, locate the remaining oil and rank the various water-flood patterns. Data analysis including normalized decline-curve-analysis (DCA) based conduit models and comprehensive field performance analysis using Spotfire (an integrated data visualization and analysis tool by TIBCO), was used to understand the key reservoir management risks and infill potential. Throughout the process, the basic philosophy of lean was adopted embracing several lean tools to improve productivity, quality and lead-time. Out of 12 subsurface feasible options studied, the proposed optimum option envisages an increase in the oil recovery factor by 9% by drilling an additional 92 infill wells in 22 patterns. The successful completion of frontend loading phase of SRS project has achieved reducing in the FDP study time to 19 months compared to an average of 36 months in the past and project implementation 4 years ahead of the original plan. Fast tracking of the project implementation was possible due to standardization of the equipment, maximum utilization of the existing infrastructure and constructive collaboration with the stakeholders. The key enablers for the successful delivering of the SRS FDP study were mainly the integrated decision based planning with data centric approach in reservoir modeling workflow and adoption of basic lean principles This approach emphasizes the importance of adopting lean tools in frontend delivery process. The decision based planning with reservoir models linked to the project decision can significantly improve the efficiency and quality of the FDP. The stakeholder alignment and strong collaboration with key stakeholders of the project can further reduce the lead-time of project execution. The decision based IRM planning used for this study sets a benchmark for future FDP studies. The Urban Plan study approach for this project has also become the standard for other LEAN FDPs.
Managing oil fields in the best way possible has always been in the centre of interests for various oil companies; production maintenance and optimisation, deferment minimisation, efficient monitoring of well reservoir & facility performances, cross-function collaboration, and many other related issues, all represent the building blocks in a successful and efficient field management structure. The Fahud cluster of Petroleum Development of Oman has been running for more than four decades, and still contributes significantly to the company's total production. Hence, it is becoming more important than ever to ensure that the field is managed both optimally and efficiently to adequately handle the large stock of wells and facility units, and all other related issues, such as operations, services, human resources, etc. For this, a series of initiatives were adopted with the aim of achieving an efficiently monitored & controlled asset as well as highly synchronised multi-team actions. In this paper, a web-portal based tool is presented; Nibras is a "smart" platform for Well & Reservoir Management (WRM). The standard data sources, web-accessibility, multi-levels of data presentation, exception-based surveillance, and compatibility with third-party tools, are just some of the many features and capabilities that Nibras possesses. These features has made it possible to detect problems and\or outstanding issues earlier, react to them faster, and thus decide better. Nibras has become a key enabler of the Fahud Collaboration Centre (the first operational collaborative work environment in Petroleum Development of Oman), as it provides a common ground for various asset teams from which data and information can be retrieved from standard sources. This has eliminated confusion and miscommunication that may typically result from referring to different tools, retrieving data from different sources, and presenting data in different formats. Nibras has been approved for pan-PDO implementation, as it represents a leap towards a smarter management of oil fields. The implementation of Nibras –alongside other smart initiatives- has resulted in reduced well downtime (and hence reduced deferments), early detection of problems, more efficient decision making, and better cross-team knowledge sharing.
Managing increasing volumes of produced water is one of the main challenges faced in waterflood fields. Better water mobility -compared to oil-, results in increasing water cut (WC) and reduced oil production, with time. In Qarn Alam, with mature brown fields depleted through waterflooding, oil producers are completed as open-hole horizontal wells. This means well experience water breakthrough from day one, due to poor oil-to-water mobility ratio, toe-heel effect, permeability variations and matrix fractures. Inflow Control Devices (ICD) has demonstrated good efficiency in delaying water breakthrough, however, when breakthrough is a given factor, ICDs lose that efficiency. The Autonomous Inflow Control Valve (AICV®) is a novel powerful tool that helps reducing WC in favour of oil, based on contrasts in fluid viscosities. The tool has a movable piston that opens/closes autonomously -without any connection to surface-, to reduce the unwanted water production, where choking increases with increasing WC. AICV technology was deployed in several oil producers, in carbonate reservoir brown field. The field has produced for decades, and is facing an increasing water management challenge. AICV completions were designed such that wells are divided into compartments isolated by swellable packers. The comparison of historical production data without and with autonomous inflow shows clearly the benefit of installing autonomous inflow control. Preliminary assessment showed an average 75% reduction in water-cut and 20% average increase in oil rate.
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