The purpose of this work is to proceed uncertainties analysis with respectto the physical properties of a petroleum reservoir, in the process ofgeological characterization and flow simulation model. The approach is appliedin a real case of Campos Basin, in Brazil, and may be helpful to the decisionanalysis concerning the profitability of the exploitation project. The sequenceis performed in four parts: the quantification of the sources of uncertaintiesconcerning the reservoir volume; the quantification of the factors affectingthe oil recovery factor; the quantification of the uncertainty range of therecoverable volume; and the estimation of the production profiles. The firstpart is executed through geostatistic simulation of the net-to-gross variable, associated with variation on the position of the oil-water contact. The secondpart consists on the use of numerical simulation runs to verify the sensibilityof the recovery factor to the variation in the vertical permeability, therelative permeability to water, and the productivity index of the wells, themost important variables in this specific case. The effect of each factor issupposed to be independent of the others, and only two cases, representing thepessimist and the optimist case, are simulated for each variable. As thisindependence is not perfect, two additional simulation runs may be required toadjust the width of the distribution. Having the probability distributions ofthe oil volume and of the recovery factor, Monte Carlo simulations are used toobtain the distribution of the recoverable volume. Each value of reserve isrelated to a production profile, to obtain the cash flow of the project, andevaluate the uncertainty concerning to the economic parameters. Introduction When exploiting a petroleum field, we deal with a lot of uncertaintiesconcerning the internal variables, as the geological characteristics, and therock and fluids properties, and the external variables, as the oil price, thecapital expenditure and the operating costs, that impact the profitability ofthe project. The quantification of these uncertainties is helpful to supportthe decision making, by the evaluation of the risks. The economic analysis of a development system is based on the cash flow ofthe project, that is a direct function of the production profile of thereservoir. But, unfortunately, the estimate of the production curves cannot bea deterministic approach, because, in the moment of decision, we have too fewavailable data, and most parameters have a wide range of possible values, whatcause an uncertainty range in the cash flow. The most important factor affecting the recoverable volume is the volume ofoil "in place", which value is not accurately estimated, by the fact that theappraisal wells are often in low quantity, and the costs of data acquisitionare high. The uncertainties concerning the position of the reservoirboundaries, the depth of the contacts between fluids, and the fault system are, in general, the main factors affecting the uncertainty in the volume. Thedetermination of these ranges are not a straight forward methodology, as itinvolves the seismic interpretation, the depositional model, and thecharacterization of the variability and heterogeneity of the porous rock, executed through integrated studies. The application of the geostatistic toolsgenerates a wide range of possible images for the rock variables, as the netpay of the formation, or the rock porosity, incrementing the range of thevalues of the reservoir volume. Therefore, the uncertainty analysis in thevalue of reservoir volume, that combine "soft information" and objectivestudies, is the first step in the risk and decision analysis. The other parameters that mostly affect the recoverable oil are related tothe recovery factor of the formation, as the vertical and horizontalpermeability, the relative permeability of the fluids, the viscosity of theoil, and the productivity of the wells. The reservoir simulation model is theideal instrument to include all these properties together with accuracy. Themain obstacle of its use is how to study the sensibility of various parametersand calculate the probability of each combination.

After 3 years of production, results indicated necessity to refine the geological model of Cretaceous turbidite reservoirs in an off-shore oil field of Campos Basin, Brazil. A stratigraphic analysis was developed to build a new stratigraphic-structural framework. Seismic interpretation was used to incorporate structural data by mapping the system of normal faults. Using concepts of sequence stratigraphy, seismic, biostratigraphic and lithologic data were used to define 12 major depositional sequences, spanning from Cenomanian to Maastrichtian. In 8 of these sequences, 12 turbidite systems were recognized and 9 of them focused for the present study. These turbidite systems compose the operational reservoir zones. Six of them were deposited during the Turonian and three during the Santonian. Erosive surfaces and regional unconformities affect the distribution of the turbidite systems. Action of erosion and faulting results in complex framework and lateral communications among reservoirs of different ages. Several oil-water contacts are present and controlled by some of the faults and the lateral communications. Modeling this complex system included many different techniques and softwares in steps of the work. The first step involved a topologic three-dimensional construction, including all of the major geologic information; relationships among the main turbidite systems were validated by production data. Next was creating a refined grid to populate the model with rock-properties; corner point geometry grid was built to honor the direction of major faults. Third was facies characterization; vertical proportion matrix was used to represent the horizontal non-stationary of the data and seismic amplitude was used as a constraint. Plurigaussian simulations were used to populate the model; this type of simulation is suitable to represent the multiple and non-sequential contact relations among facies. The fifth step was using Monte Carlo simulation to fulfill the model with porosity and permeability, based on petrophysic histograms from well data, classified by facies. Upscaling the model was the last step in order to finally transfer the geological data to the flow simulator. Preliminary results from the flow simulator reveal better fitting between this new geological model and the present production data. Introduction Along the years from 2000 to 2002, a series of perforations and workovers in this studied field indicated a partial inadequacy of the model then existent to explain the deviations found in relation to the expected results. A multidisciplinary team (petrophysicist, geophysicist, sedimentologist, reservoir geologist and engineer) was composed to perform an integrated study to update the geological model. An extensive revision work of all the available data and their internal organization into a three-dimensional (3D) model, to respect the main complexities and heterogeneities observed in the field reservoirs, was then put in practice. Part of the methods and results is next exposed. Preliminary Information The studied field is composed of 6 different blocks distributed in an area of 728 km2 with water depths varying between 800 and 1500m. The present work deals with its main producing block. The main reservoirs are Upper Cretaceous (Turonian and Santonian) turbidite sandstones, with good quality oil (28° API). A large number of stacking and partially connected reservoirs is recognized in different turbidite systems. These turbidites are characterized as amalgamated channel complexes. An increasing erosive character upwards causes, especially in Santonian reservoirs, erosive superimposed surfaces, including some unconformities. These complex stratigraphic sequences were later disturbed by normal faults, during episodic salt movements. Main flow restrictions should be related (i) to structural subjects (complex fault system) (ii) external geometry and internal heterogeneity of the reservoirs and (iii) the structural relationship among the different stratigraphic units.

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