Polymer flooding was selected as the preferred enhanced recovery process for a high permeability (2-5 Darcy) heavy oil (250 – 500 cP) reservoir with a strong bottom aquifer in South Oman. Several key uncertainties were identified through simulation modelling which would have a crucial impact on the process efficiency. These uncertainties formed the basis of a field trial design, and a detailed surveillance programme aimed at reducing these key uncertainties. The presence of a strong bottom aquifer in this field resulted in near original reservoir pressure, which could provide a challenge to injectivity. The close proximity of injectors to the oil water contact reduces the efficiency of the polymer flood through water fingering, and polymer loss to the aquifer. Additional uncertainties include: reservoir heterogeneity, Kv/Kh, permeability distribution, baffles, natural fractures, remaining oil saturation, injectivity, induced fracturing and inflow profile along the horizontal well (producers and injectors). Hence, extensive data gathering was carried out in order to reduce these uncertainties through updating the static and dynamic models and allowing for a better understanding of the field behavior prior to polymer injection. This paper details a fully integrated evaluation of the gathered data through a multi-disciplinary team during the drilling of the trial wells. The data includes: open hole logs, borehole images, core analysis, fluid sampling, dielectric measurements, vertical interference testing, production logging and existing dynamic production data. Also, single well water and polymer injectivity test and extended leak-off test were carried out to understand the injectivity and fracture behavior. The wealth of well data coupled with geological and dynamic data reduced the overall reservoir properties and fluid distribution uncertainties. Furthermore, the data were crucial to design the optimum injection and data gathering requirements during the field trial. Finally, the paper provides an overview of the surveillance aspects of the field trial.

Achieving consistent optimum field development choices in technically complex portfolios requires sound individual and corporate technical capabilities. Within the largest Exploration and Production Company in the Sultanate of Oman, some key gas and contaminated hydrocarbon Field Development Plans are produced by dedicated specialized study teams that are part of the company's so-called Field Development Centre. In order to tackle projects involving technically complex challenges such as tight reservoirs, rich gas condensates, contaminated hydrocarbons or high pressure developments, a number of organizational elements are put in place to ensure continuous growth of staff and corporate capabilities along with corporate knowledge dissemination. First, each project team remains integrated throughout its project life time. The integration of subsurface and surface disciplines allows early identification of realistic and robust development options. It also facilitates knowledge sharing with activities such as field visits conducted jointly between subsurface and surface engineers. The benefits of this integration are demonstrated with examples from several gas condensate and sour oil study cases. Second, experienced professionals provide project specific guidance and coaching to junior staff over several projects. This scheme allows maximizing the impact of the experienced staff while allowing hands-on learning from younger recruits. Third, benefiting from a ring-fenced organization to conduct studies facilitates the retention of corporate knowledge and the replication of best practices. However, this does not imply that knowledge and capabilities remain centralized as several conduits are in place to ensure dissemination across the organization. Asset staffs with identified technical development gaps are assigned for the duration of a project to the study team where they actually develop their skills through direct project contribution. Specialized forums, physical and web-based, are also available to share information and solutions learnt from previous projects. Finally, fundamental technical capabilities and knowledge bases are developed at corporate level in order to consistently address key challenges encountered in various assets (e.g. gas condensate modeling and optimization, tight units recovery improvement, fraccing optimization and associated production forecasting). A wide scope integrated multi-year project covering all company gas activities within several formations has been kicked-off for this purpose. This fundamental project involves various contributors from the company such as Subject Matter Experts and experienced asset staff, specialized external service providers and academia. More specifically, the project aims at developing a comprehensive corporate understanding of its gas reservoirs, and at developing consistent datasets and validated effective modeling workflows to be disseminated through standards, websites and trainings. This paper provides an overview of the work practices and tools that have been put in place within a large company in order to ensure the steady development of staff and corporate technical capabilities while consistently addressing the development of its most complex oil and gas reservoirs.

In any E&P organization, drilling new wells is part of field development activity. This allows company to bring into production additional oil from different fields. Number of new wells drilled varies from company to company from a few to hundreds as in case of Petroleum Development Oman (PDO). Drilling new wells is a capital-intensive activity. Contribution to the overall production from new wells makes for higher returns on investment. New oil production, is an integrated activity involving a number of departments and different stakeholders. Information and data come from different sources and has to be validated by different stakeholders. Over the years, this has been done in a traditional manner with smart use of spreadsheets. However, with increase in activity, this way of working became cumbersum and time consuming. In business planning, it is important to select an optimum set of activities for drilling which will generate most new oil from allocated resources and budget. It should also be able to quantify opportunity oil in changing requirements. This means generating alternative sequences and comparing them against a set of KPIs and constraints. This exercise is required to be carried out within a cluster and across different clusters in a business unit. With the use of smart spreadsheets, this was getting difficult and time consuming. Resulting in suboptimal drilling sequence and missed opportunity to increase New Oil production.

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.

This paper describes key factors related to intelligent horizontal well completion systems and surveillance activities for a polymer field trial within a sandstone reservoir in the South of Oman. The existing field predominantly comprising of horizontal producer wells drilled and located at the crest of the reservoir to ensure optimum oil production rates via artificial lift techniques. Many wells have encountered early water breakthrough, resulting in large volumes of un-swept oil. Improved sweep efficiency, hence improved oil recovery is expected by polymer flooding using a horizontal well approach [1]. The polymer field trial location consists of: 4 horizontal producers each completed with wire wrap screens, blanks and external zonal isolation packers within the reservoir section for segmentation and isolation. Each producer has a downhole gauge for real-time pressure and temperature monitoring. Three horizontal smart injectors each consisting of 4 zones completed with 7 inch pre-drilled liners, blanks and external zonal isolation packers across the reservoir section for segmentation and zonal isolation. These injectors are internally completed with intelligent completion systems with remote access and control whereby each of the 4 zones consists of a mechanical retrievable packer for zonal isolation, on-off intelligent flow control valve with hydraulic multi-drop module system for conformance control, quartz pressure-temperature gauge, double ended pump down DTS system for real-time monitoring and internally lined GRE tubulars in order to prevent polymer degradation. Two horizontal observation wells each completed with GRE casings and predrilled liner joints for logging along with downhole gauges for real-time pressure-temperature monitoring. One vertical observation well completed with GRE casing and carbon steel casing below the oil water contact for surveillance purposes. A detailed surveillance plan for the current producers, injectors and observation wells is of utmost importance for pre and post injection data gathering in order to successfully evaluate key subsurface risks and uncertainties associated with the polymer flood technique. The field trial has been designed and executed with an optimum approach to ensure continuous real-time surveillance. This is facilitated by remote access and control thereby minimizing well interventions for surveillance activities for the duration of the trial.