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The paper describes the upscaling and reservoir simulation of a giant Middle East oil field, the geological modeling of which is described in a companion paper. 1 The main objective of the study was the simulation of the irregular water advance observed in some parts of the field as a consequence of peripheral water injection.Three scales of heterogeneity were identified in the characterization phase: the matrix, the stratiform Super-K intervals, and the fractures. To accommodate the different hydraulic properties of each heterogeneity system, a dual-media approach (dual porosity and dual permeability) was used.The assignment of the effective properties to the simulation grids (matrix and fracture grids) was performed independently for the three heterogeneity systems. In particular, the geostatistical facies model was upscaled with algebraic methods, while the stratiform Super-K layers and fracture properties were reproduced explicitly at the simulation gridblock scale through an original upscaling procedure.The history match was achieved in a short time by a small variation of the fractal dimension of the fracture distribution and without resorting to any local modification.Simulation results showed that the fracture system was the controlling factor in terms of water advance and breakthrough, while the impact of the stratiform Super-K layers proved to be of second order.In a later stage, the model was used to run production forecasts under different exploitation scenarios.The conclusions of this study indicate that for such porous and fractured reservoirs with stratiform Super-K occurrences, a detailed characterization of all the heterogeneity systems, coupled with a dual-media formulation, is necessary for accurate reservoir simulation and effective reservoir management.

As for some thick and highly fractured Iranian fields, the Cantarell complex located offshore Mexico presents features (decrease in the production GOR and bubble point pressure with time) that reveal the effect of convection. This effect on the past homogenization of the fluid properties is discussed and is supported by a thorough characterization of the thermodynamic properties of the actual reservoir fluids. In order to model convection, the reservoir simulator used for this study was adapted on purpose. Sensitivity runs were performed to demonstrate the necessity of accounting for convection for matching the past history of the Akal field, part of the Cantarell complex. Introduction Presentation of Cantarell Complex. The Cantarell complex is the most important oil field in Mexico, and the sixth largest in the world. In order to economically optimize its value, it has been decided to initiate a major recovery process by injecting nitrogen for pressure maintenance purposes. Cantarell field is a thick, highly fractured reservoir, therefore it is the kind of reservoir where convection phenomenon may occur. Convection is a complex process which is characterized by a vertical homogenization of fluid properties in the fractures. This may have an essential impact on production and injection profiles, in particular on the quantity of nitrogen in the effluents as well as nitrogen breakthrough times, thereby on the overall nitrogen injection efficiency. The Cantarell complex is located offshore approximately 85 km from Ciudad del Carmen. It includes four adjacent oil fields known as Akal, Chac, Kutz and Nohoch. Akal is the largest oil accumulation with more than 90% of the 35 billion bbl oil (Bbo) in place. The reservoir is an anticline producing from the fractured carbonates of the Cretaceous and upper Jurassic formations, which contains also many vugs and caves. The Upper Cretaceous is the most fractured and brecciated. Fracturing decreases with depth in the Middle and Lower Cretaceous. The average thickness of the whole reservoir is about 775 m and the depth of the top Cretaceous ranges between 1100 and 3600 mTVDSS. Below the Cretaceous sequence, the Upper Jurassic (Oxfordian, Kimmeridjian, Tithonian) is a stratigraphic reservoir with poor reservoir characteristics. Field production started in June 1979, reaching a peak of 1.157 MMbopd in April 1981, with 40 producing wells. A total of 184 wells were drilled in Cantarell, among which 173 wells in Akal. Cantarell crude is a 19 to 22° API Maya type, with an initial bubble point pressure close to 150 bar. Initially the reservoir pressure was above the bubble point pressure and was equal to 266 bar at 2300 mSS. Therefore there was no initial gas cap. The reservoir pressure rapidly reached the bubble point pressure and a secondary gas cap appeared in 1981. The Gas-Oil Contact was located at 1800 mSS in 1997. The corresponding cumulative production was around 5.5 billion stb. Presentation of Cantarell Complex. The Cantarell complex is the most important oil field in Mexico, and the sixth largest in the world. In order to economically optimize its value, it has been decided to initiate a major recovery process by injecting nitrogen for pressure maintenance purposes. Cantarell field is a thick, highly fractured reservoir, therefore it is the kind of reservoir where convection phenomenon may occur. Convection is a complex process which is characterized by a vertical homogenization of fluid properties in the fractures. This may have an essential impact on production and injection profiles, in particular on the quantity of nitrogen in the effluents as well as nitrogen breakthrough times, thereby on the overall nitrogen injection efficiency. The Cantarell complex is located offshore approximately 85 km from Ciudad del Carmen. It includes four adjacent oil fields known as Akal, Chac, Kutz and Nohoch. Akal is the largest oil accumulation with more than 90% of the 35 billion bbl oil (Bbo) in place. The reservoir is an anticline producing from the fractured carbonates of the Cretaceous and upper Jurassic formations, which contains also many vugs and caves. The Upper Cretaceous is the most fractured and brecciated. Fracturing decreases with depth in the Middle and Lower Cretaceous. The average thickness of the whole reservoir is about 775 m and the depth of the top Cretaceous ranges between 1100 and 3600 mTVDSS. Below the Cretaceous sequence, the Upper Jurassic (Oxfordian, Kimmeridjian, Tithonian) is a stratigraphic reservoir with poor reservoir characteristics. Field production started in June 1979, reaching a peak of 1.157 MMbopd in April 1981, with 40 producing wells. A total of 184 wells were drilled in Cantarell, among which 173 wells in Akal. Cantarell crude is a 19 to 22° API Maya type, with an initial bubble point pressure close to 150 bar. Initially the reservoir pressure was above the bubble point pressure and was equal to 266 bar at 2300 mSS. Therefore there was no initial gas cap. The reservoir pressure rapidly reached the bubble point pressure and a secondary gas cap appeared in 1981. The Gas-Oil Contact was located at 1800 mSS in 1997. The corresponding cumulative production was around 5.5 billion stb.

This paper presents a fully-integrated methodology for managing reservoir uncertainties during history matching, production forecasting and production scheme optimization. Based on the traditional experimental design methodology, this innovative approach, called the Joint Modeling Method, allows to model the production recovery as a function of both the deterministic uncertain parameters, such as petrophysical and production parameters, as well as non-continuous parameters such as geostatistical realizations and equiprobable matched models. In this new approach, the dispersion due to the non-continuous uncertainties is modeled in a rigorous statistical framework through the variance of the production recovery. The method was successfully applied on data derived from a North Sea real field case. The objective was to quantify the impact of the principle reservoir uncertainties on the cumulative oil production and to optimize future field development in a risk analysis approach. The uncertainties were mainly on petrophysical data, geostatistical facies distribution and aquifer strength. The study was performed in the following steps:sensitivity study. The most influential parameters were identified and the impact of geostatistical uncertainties was highlighted.history matching. The influential parameters were constrained to the available production data. In particular, the geostatistical model was locally modified using both FFTMA technique and the gradual deformation method.production scheme optimization. Experimental design and joint modeling were used to obtain probabilistic distributions of the optimized location of new wells in a non-producing zone.risk analysis: Finally, probabilistic incremental oil production was obtained using Monte-Carlo technique. Results show that this integrated methodology successfully enables to quantify the risk associated with the main reservoir uncertainties during the whole process of a reservoir engineering study (sensitivity, history match, production optimization and forecast). Introduction Thanks to growing measurement and computational facilities, reservoir modeling is getting more and more complex. Hence more and more prior uncertain parameters can be introduced in reservoir studies. The difficulty is then to identify the ones that are influential on production recovery and on economic field profitability and to quantify their impact. The "simplest" case where the reservoir engineer needs to deal with reservoir uncertainties is the appraisal case, when there is no production data to match. In that case, the uncertainty domain cannot be highly constrained and the impact on production forecasts may hence be very significant. To deal with those uncertainties, reservoir and production engineers commonly perform many reservoir simulations for different values of the uncertain parameters. This approach gives a qualitative idea of the influence of each uncertain parameter on the production response. However this method can quickly become very expensive when the number of uncertain parameters increases. Moreover, this is not a rigorous method since the impact of each uncertain parameter as well as the possible interactions between those uncertain parameters cannot be easily detected. Finally no direct quantitative relation between the responses and the uncertainties can be established.

TX 75083-3836, U.S.A., fax 01-972-952-9435. AbstractThe paper describes the upscaling and reservoir simulation of a giant Middle East oilfield, whose geological modeling is described in a companion paper (1). The main objective of the study was the simulation of the irregular water advance observed in some parts of the field, as a consequence of peripheral water injection.Three scales of heterogeneity were identified in the characterization phase, namely the matrix, the stratiform Super-K intervals and the fractures. To accommodate the different hydraulic properties of each heterogeneity system, a dual-media approach (dual porosity and dual permeability) was used.The assignment of the effective properties to the simulation grids (matrix and fracture grids) was performed independently for the three heterogeneity systems. In particular, the geostatistical facies model was upscaled using algebraic methods, while the stratiform Super-K layers and fractures properties were explicitly reproduced at the simulation gridblock scale, through an original upscaling procedure.The history match was achieved in a short time, by a small variation of the fractal dimension of the fracture distribution and without resorting to any local modification.Simulation results showed that the fracture system was the controlling factor in terms of water advance and breakthrough, while the impact of the stratiform Super-K layers proved to be of second order.In a later stage, the model was utilized to run production forecasts under different exploitation scenarios.Conclusions of this study indicate that for such porous and fractured reservoirs with stratiform Super-K occurrences, a detailed characterization of all the heterogeneity systems, coupled with a dual-media formulation, are necessary requisites for accurate reservoir simulation and effective reservoir management.