In this paper, we present a field example where a streamline simulator was used to rank multi-million cell geostatistical reservoir descriptions and to find the optimum level of vertical upscaling for finite-difference simulation. During geostatitstical reservoir characterization, it is a common practice to generate a large number of realizations of the reservoir model to assess the uncertainty in reservoir descriptions and performance predictions. However, only a small fraction of these models can be considered for comprehensive flow simulations because of the high computational costs. A viable alternative is to rank these multiple ‘plausible’ reservoir models based on an appropriate performance criterion that adequately reflects the interaction between heterogeneity and the reservoir flow mechanisms. In this study, we explore the use of ranking based on streamline time of flight connectivity derived from a streamline simulator. The time of flight reflects fluid front propagation at various times and its connectivity at a given time provides us with a direct measure of volumetric sweep efficiency for arbitrary heterogeneity and well configuration. The volumetric sweep efficiency is the simplest measure that reflects the interaction between heterogeneity and the flow field. It is a dynamic measure that can be easily updated to account for changing injection/production conditions. We show that the proposed connectivity criterion can also be used to evaluate the effects of vertical upscaling in the dynamic performance and to determine the optimal level of upscaling for numerical simulation purposes. Our field study involves a Middle Eastern carbonate reservoir under a moderate to strong aquifer influx. The reservoir is on primary depletion and has no injectors. Multiple geostatistical reservoir descriptions were generated using a hierarchical approach whereby the larger level of uncertainty is defined first followed by smaller levels. The aquifer is modeled with a constant pressure boundary and for each time update, the location of the boundary was modified to account for the water encroachment. Using the field-wide sweep efficiency as a performance measure, the realizations were ranked, and used for flow simulation to assess risks associated with various development strategies. Subsequently, three selected realizations were upscaled for the purpose of comprehensive history matching and performance prediction. Background With the wide-spread use of geostatistics, it has now become a common practice to generate a large number of realizations of the reservoir model to assess the uncertainty in reservoir descriptions and performance predictions. Most commonly, these multiple realizations account for spatial variations in petrophysical properties within the reservoir and thus, represent a very limited aspect of uncertainty. For reliable risk assessment, we need to generate realizations that capture a much wider domain of uncertainty such as structural, stratigraphic, as well as petrophysical variations. From a practical point of view, we want to quantify the uncertainty and at the same time keep the number of realizations manageable. In this study, we will adopt an approach that is based on hierarchical principles. Thus, the uncertainty having the most potential impact is identified first. For example, with limited well control, the structural uncertainty derived from the seismic interpretations can have the most impact on the flow performance. Or, for faulted reservoirs, the uncertainty with respect to locations of faults can have the most impact. Then, the next level of uncertainty is identified and so on. The last level of uncertainty is the multiple geostatistical realizations of reservoir properties for a given set of input parameters. The petrophysical uncertainties generally tend to have a much lower impact on the reservoir performance compared to factors affecting large-scale fluid movements.

TX 75083-3836, U.S.A., fax 01-972-952-9435.

TX 75083-3836, U.S.A., fax 01-972-952-9435. AbstractIt is a common observation that well test permeability values do not match with thickness weighted core permeability averages. This is not a surprise because of the differences in the measurement scales where, unlike well test measurements, core samples represent a very small portion of the reservoir around the well bore. In addition, the presence of fractures and/or high permeability channels will further enhance the difference between the two sources of data. Therefore, reservoir descriptions based on core measurements alone cannot honor well test results. They need to be modified properly without violating the underlying geological and geostatistical information.In this paper, we present a methodology to properly enhance permeability fields that also accounts for fracture distribution in the reservoir. The basic idea is that radial upscaling around a wellbore within a given investigation radius should match the permeability obtained from well tests. The enhancement is caused by two factors: microfractures, which cannot be explicitly represented in the reservoir description, and macro-fractures, which can be interpreted using 3-D seismic data. To account for these two different types of fractures, we calculate two different enhancement factors, one for the base level (microfractures) and one for the higher level (macro-fractures). The base level, after appropriate interpolation, is applied across the entire reservoir, whereas the higher level is applied only to locations where macro-fractures are interpreted from 3-D seismic data.The technique was successfully applied to a Middle Eastern carbonate reservoir. A significant correlation is observed between the enhancement required to match the well test data and the fracture density (macro-fractures obtained from 3-D seismic data) within a given investigation area. A correlation function is then obtained between the enhancement factor and the fracture density for a given grid block, which in turn is used to apply enhancement to interwell locations. Thus, the resulting permeability field did not only honor the well test results but also the fracture distribution and the underlying geological and geostatistical descriptions. In a later stage, a tensorial approach was used to upscale permeability to account for the anisotropy in permeability distribution. Using this approach, a proper anisotropy of permeability distribution, matching the fracture orientation, has been obtained.

TX 75083-3836, U.S.A., fax 01-972-952-9435. AbstractThis paper presents the result of fully 3D integrated reservoir description and flow simulation study of a giant oil field in Middle East using the state of the art technology. The overall goal is to develop a representative reservoir model to form the basis for reservoir management and longterm development planning. This is done by generating alternate reservoir descriptions, based on stochastic models, to quantify uncertainties in the future performance. The data that were integrated include well cores and logs, geological interpretation (stratigraphy, rock type, depositional model), seismic (structure, curvature analysis and inversion-derived porosity), well test, SCAL, production data and fracture distribution.The 3D multiple realizations were generated by considering rock type and petrophysical properties at well location, obtained from well logs and cores, and simultaneously constrained by seismic derived porosity. The simulations of properties were generated using simultaneous sequential Gaussian simulation where the seismic constraint was introduced via Bayesian Updating procedure. Special consideration was given to the spatial modeling of data where soft information was derived both from hard data and depositional environment. Fracture distribution, derived from seismic curvature analysis, was used in the integration process to match the core-based derived permeability with well test permeability. This distribution was used to obtain permeability anisotropy distribution using newly developed tensorial approach.A total of forty-eight realizations were generated considering four major types of uncertainties: structure, spatial model, petrophysical properties and simulation path. The results have been used as the basis for fluid in place (STOIIP) calculation using Monte Carlo simulation technique. These realizations are then ranked based on the sweep efficiency, obtained from multiphase streamline simulations, and the STOIIP. Three realizations, representing medium, low and high realizations, were selected and upscaled. An optimum vertical upscaling level was determined using streamline simulator and developing quantitative criterion. This ensures that the representative heterogeneity of the reservoir was maintained during the upscaling process.Comprehensive history matching was done for the three selected realizations for the entire nineteen years of production history using objective criterion so that the quality of the three matches is similar. The observed data matched include water cuts and measured pressures. The parameters used to match the history are restricted to the parameters that have not been accounted for in the static model. Using probabilistic concepts, uncertainties in future performance were quantified for various scenarios.

TX 75083-3836, U.S.A., fax 01-972-952-9435.