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.

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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.

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