This paper describes the results of an integrated study to assess redevelopment options in a mature field with over 40 years of production. The field has been produced under gas cap drive and partly under an internal gas injection scheme to increase oil recoveries. The objective of the study was to confirm the effectiveness and possible expansion of the gas injection scheme and to assess merits of waterflooding.A two phased modeling approach was adopted and a coarse Phase 1 model for the entire reservoir stack was built using existing interpretations and data available from previous studies while seismic reinterpretation and petrophysical reevaluation to feed the detailed Phase 2 models was ongoing. The Phase 1 model helped to understand the plumbing between the sands and fault blocks and the key parameters impacting field level pressure and cumulative fluid history matches. In Phase 2, two separate models were built for groups of reservoirs at a much finer vertical scale to address sand specific saturation changes and individual well performance.A structured experimental design (ED) methodology using SUM (Shell proprietary software) was used to explore the full uncertainty space for potential history matches and use calibrated models with the remaining uncertainties to generate a range of forecasts. With the large number of reservoirs involved even a modest number of uncertainties resulted in a large number of ED parameters. The number of parameters and their associated uncertainties was partly narrowed down and constrained in Phase 1 allowing focusing on detailed reservoir specific parameters in Phase 2. In parallel with and complementing the simulation work, conventional contact mapping integrating the historical pressure, water cut and GOR data was carried out to locate potential areas with remaining oil. This paper will highlight how the phased modeling approach facilitated early integration of reservoir and well performance data for detailed static model construction, ways of managing uncertainty in a brown field with multiple reservoirs, large number of wells and more than 40 years of production history, and finally how traditional reservoir assessment techniques can complement reservoir modeling work. IntroductionThe studied field is located approximately 15 km offshore in water depths ranging from 10-40 m. The area of interest forms the northern part of a greater NNE-SSW trending highly faulted anticline and is separated from the main field by a major growth fault (Figure 1). The area of interest is divided into two main blocks, Block 1 and 2, by the main fault which is antithetic to a southern boundary growth fault. Block 1 shows crestal collapse faults, which were formed and affected by Mio-Pliocene inversion, that further divide it into compartments and form barriers and baffles to fluid flow. The southwestern flank of Block 1 has been intruded by two shale diapirs that have resulted in additional intrusion related fractures and faults. This hampers the aquifer connectivity to the west and southwest o...
Field X is one of largest oil fields in Brunei producing since 1970's. The field consists of a large faulted anticlinal structure of shallow marine Miocene sediments. The field has over 500 compartments and is produced under waterflood since 1980's through 400+ conduits over 50 platforms. A comprehensive review of water injection performance was attempted in 2019 to assess remaining oil and identify infill opportunities. Large uncertainties in reservoir properties, connectivity and fluid contacts required that data across multiple disciplines is integrated to identify new opportunities. It was recognized early on that integrated analysis of surveillance data and production history over 40 years will be critical for understanding field performance. Hence, reviews were first initiated using sand maps and analytical techniques. Tracer surveys, reservoir pressures, salinity measurements, Production Logging Tool (PLT) were all analyzed to understand waterflood progression and to define connectivity scenarios. A complete review of well logs, core data from over 30 wells and outcrop studies was carried out as part of modelling workflow. This understanding was used to construct a new facies-based static model. In parallel, key dynamic inputs like PVT analysis reports and special core analysis studies were analyzed to update dynamic modelling components. Prior to initiating the full field model history matching, a comprehensive impact analysis of the key dynamic uncertainties i.e., Production allocation, connectivity and varying aquifer strength etc. were conducted. An Assisted History Matching (AHM) workflow was attempted, which helped in identifying high impacting inputs which could be varied for history matching. Adjoint techniques were also used to identify other plausible geological scenarios. The integrated review helped in identifying over 50 new opportunities which potentially can increase recovery by over 10%. The new static model identified upsides in Stock Tank Oil Initially in Place (STOIIP) which if realized could further increase ultimate recoverable. The use of AHM assisted in reducing iterations and achieve multiple history matched models, which can be used to quantify forecast uncertainty. The new opportunities have helped to revitalize the mature field and has potential to almost increase the production by over 50%. A dedicated team is now maturing these opportunities. The robust methodology of integrating surveillance data with simulation modelling as described in this paper is generic and could be useful in current day brown field development practices to serve as an effective and economic manner for sustaining oil production and maximizing ultimate recovery. It is essential that all surveillance and production history data are well analyzed together prior to attempting any detailed modelling exercise. New models should then be constructed which confirm to the surveillance information and capture reservoir uncertainties. In large oil fields with long production history with allocation uncertainties, it is always a challenge for a quantitative assessment of History match quality and infill well Ultimate Recovery (UR) estimations. Hence a composite History Match Quality Indicator (HMQI) was designed with an appropriate weightage of rate, cumulative & reservoir pressure mismatch, water breakthrough timing delays. Then HMQI parameter spatial variation maps were made for different zones over the entire field for understanding and appropriately discounting each infill well oil recovery. Also, it is critical that facies variation is properly captured in models to better understand waterfront movements and locate remaining oil. Dynamic modelling of mature field with long production history can be quite challenging on its own and it is imperative that new numerical techniques are used to increase efficiency.
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