This paper presents a feasibility study for the development of the unexploited outlying area of a gas condensate field operating under gas recycling mode to optimize condensate recovery. Heavier components have migrated to the flanks which is the motivation to exploit this area. To maintain reservoir pressure the voidage replacement ratio must be maintained at 100%. However, due to high demand for natural gas, a certain percentage is replaced with non-hydrocarbon makeup gas. This strategy has the potential to reduce the condensate recovery as well as affect the quality of the produced gas.A reservoir simulation study was conducted to maximize the condensate and clean gas recovery through development of the flanks. Two major scenarios were created consisting of more than twenty different development strategies based on well location, number of wells and well production rates. Additional sensitivities on blow down time, under-injection, injection stream composition and compression were considered for both scenarios. The influence of the surface infrastructure on production performance has been quantified by the application of Integrated Asset Modeling, which improves the accuracy of the standalone reservoir simulation scenarios.The study highlighted a significant upside in terms of oil recovery by exploiting the outlying area of the field. Multiple optimization scenarios were performed and a maximum gain of approximately 10% in recovery was observed above the base case. Integrated Asset Modeling led to more optimistic estimates of future recovery and reduced makeup gas production, through the removal of simplifying assumptions related to back pressure and injection composition.

Carbonate Reservoirs are well known for their heterogeneity in terms of porosity and permeability. In this field case from UAE onshore a sharp degradation of petrophysical quality was noted at the gas-water contact, in relation to diagenetic cementation, and led to an independent modelling for the aquifer, as well as an independent modelling of the reservoir with a data filter for the gas pool only. A merge of the 2 grids was then performed. In this field a major bias on well data distribution from crest to aquifer affects the geostatistical histogram evaluation: wells are concentrated in the crest down to mid-flanks while there are few wells from mid-flanks to the aquifer. Consequently distribution histograms of petrophysical data from the whole model should not respect well data histograms (whether, core-, log- or cell-derived). The methodology of separating gas and aquifer modelling, and of separating well derived histograms from model-derived ones led to the following results: – Better capture of the reservoir degradation with depth in the gas pool, – Better capture of the sharp degradation break in the aquifer. This paper is focusing on the methodology of how to build two separate models in the gas pool and the ‘aquifer for each petrophysical property and how to combine them in one property model to honour reservoir heterogeneity. Integration of all data at all scales and constant QC between database sources (logs, cores, seismic, dynamic history) were the means to produce a geomodel capturing the key heterogeneities of the reservoir, those with major impact on fluid front migration during production.

The objective of this paper is to address the challenges that are frequently encountered in simulation studies when using local grid refine (LGR) within upscaled models. The difficulties mainly arise due to the unreliability of populating the fine grids with reservoir properties and attributes. Dynamic modeling of a pilot is an important task to predict fluid flow and reservoir behavior which is a major step of pilot design. Dynamic models usually have many limitations when it comes to geological description due to the upscaling of fine-grid static model. Using local grid refinement (LGR) alone for the pilot area within a coarse dynamic model also would not enhance reservoir description of the pilot area without a realistic reservoir description. This work was aimed to provide an improved method for the proper simulation of pilot project in order to optimize the design of the pilot injector, borehole location and length. Furthermore, the model would be used to plan an efficient reservoir monitoring program including an optimized well data gathering with sponge coring for defining the remaining oil saturation. To overcome these limitations, the proposed method introduces a special fine scale LGR covering the pilot area within the upscaled dynamic model. Whereas the upscaled model has 36 layers, the LGR contains exactly the same fine-scale layering scheme and reservoir properties as the static model with 160 layers. Thus, it eliminates the upscaling process within the LGR. This process will ensure a better quality history match, for example the TDTs and RSTs derived saturations when compared against the fine layer LGR from the dynamic model. The dynamic model in this study is a large sector model (Nx 167, Ny 98 and Nz 36) with a detailed LGR (Nx 130, Ny 145 and Nz 160). The fluid properties were calculated from a 10-components equation of state (EOS). After the addition of the LGR, the model history match was updated. Several prediction cases were then studied to optimize well location (injector and observation wells) in order to convert the existing inverted five-spot gas pattern into water injection line-drive. Several saturation maps and profiles were generated to predict the breakthrough time for each observer and utilized to design the future pilot monitoring program. The new data will be utilized for future updates of the history match and performance of pilot under the optimum scheme of sweep and thus well spacing. Introduction This study simulates a giant carbonate reservoir (1200 sq. km) anticline structure the field is situated onshore in UAE. It has been on production for more than 45 years. The reservoir comprises a series on interbedded shallow marine bioclastic carbonate of Lower Cretaceous Thamama Group. The average thickness of the reservoir is about 50 meters (+160 feet) at the crest. The porosity range is 8% to 35%. The permeability range is 10 to 1000+ mD in the upper part of the reservoir and 1 to 10 mD in the lower part of the reservoir. Porosity and permeability decreases from crest to flank, good reservoir quality are related to depositional lithofacies and favorable diagenetic process. The reservoir contains a light oil of an average API of 37°. The main production mechanism is peripheral and mid-dip pattern water injection along with crestal gas injection in the gas cap and pattern gas injection in the north area of the field. The pilot is situated in one of the nine inverted five-spot patterns located in the north where gas injection commenced in 1997.

The objective of this paper is to address the challenges that are frequently encountered in simulation studies when using local grid refine (LGR) within upscaled models. The difficulties mainly arise due to the unreliability of populating the fine grids with reservoir properties and attributes. Dynamic modeling of a pilot is an important task to predict fluid flow and reservoir behavior which is a major step of pilot design. Dynamic models usually have many limitations when it comes to geological description due to the upscaling of fine-grid static model. Using local grid refinement (LGR) alone for the pilot area within a coarse dynamic model also would not enhance reservoir description of the pilot area without a realistic reservoir description. This work was aimed to provide an improved method for the proper simulation of pilot project in order to optimize the design of the pilot injector, borehole location and length. Furthermore, the model would be used to plan an efficient reservoir monitoring program including an optimized well data gathering with sponge coring for defining the remaining oil saturation. To overcome these limitations, the proposed method introduces a special fine scale LGR covering the pilot area within the upscaled dynamic model. Whereas the upscaled model has 36 layers, the LGR contains exactly the same fine-scale layering scheme and reservoir properties as the static model with 160 layers. Thus, it eliminates the upscaling process within the LGR. This process will ensure a better quality history match, for example the TDTs and RSTs derived saturations when compared against the fine layer LGR from the dynamic model. The dynamic model in this study is a large sector model (Nx 167, Ny 98 and Nz 36) with a detailed LGR (Nx 130, Ny 145 and Nz 160). The fluid properties were calculated from a 10-components equation of state (EOS). After the addition of the LGR, the model history match was updated. Several prediction cases were then studied to optimize well location (injector and observation wells) in order to convert the existing inverted five-spot gas pattern into water injection line-drive. Several saturation maps and profiles were generated to predict the breakthrough time for each observer and utilized to design the future pilot monitoring program. The new data will be utilized for future updates of the history match and performance of pilot under the optimum scheme of sweep and thus well spacing. Introduction This study simulates a giant carbonate reservoir (1200 sq. km) anticline structure the field is situated onshore in UAE. It has been on production for more than 45 years. The reservoir comprises a series on interbedded shallow marine bioclastic carbonate of Lower Cretaceous Thamama Group. The average thickness of the reservoir is about 50 meters (+160 feet) at the crest. The porosity range is 8% to 35%. The permeability range is 10 to 1000+ mD in the upper part of the reservoir and 1 to 10 mD in the lower part of the reservoir. Porosity and permeability decreases from crest to flank, good reservoir quality are related to depositional lithofacies and favorable diagenetic process. The reservoir contains a light oil of an average API of 37°. The main production mechanism is peripheral and mid-dip pattern water injection along with crestal gas injection in the gas cap and pattern gas injection in the north area of the field. The pilot is situated in one of the nine inverted five-spot patterns located in the north where gas injection commenced in 1997.

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