In reservoirs with compositional variations,fluid characterization may be complex since one must be able to identify and represent the different compositions and properties at each point of the reservoir.Two challenges in this task are to determine these variables based on DST fluid samples,since it is not always possible to obtain punctual open hole samples without contamination by oil-based drilling fluid,and to obtain a model able to predict fluid properties at unsampled regions of the reservoir.Hence,the aim of this paper is to present a methodology to determine the representative depth of each sample,in which the PVT properties are more realistically located,and reveal a strategy to extrapolate those data to other areas. The methodology is suitable for any reservoir with non-homogeneous fluid and consists of using production logs to calculate the depth at which PVT data will be associated.Its application is crucial especially for reservoirs with heterogeneous rocks,where the production contributions over an interval can be irregular,leading to a misinterpretation of fluid properties location when this method is not applied. Furthermore,fluid properties extrapolation is always necessary for reservoirs with compositional varia-tions,at least at the beginning of the field development. For a heterogeneous field studied,assuming other criteria for positioning the PVT samples,data dispersion did not allow visualizing a fluid distribution pattern.After applying the methodology,a reliable correlation was obtained,indicating a compositional gradient along the areal extent of the field.In addition,while monitoring observation wells during a production pilot,new fluid characteristics were revealed,which were also relevant to generate the fluid model.Therefore,due to these analyses,it became easier to understand the thermodynamic phenomenon that caused the compositional variation,the predictability of regions without data was enhanced and the fluid characterization for reservoir simulation was deeply improved,facts that were essential to optimize the field development plan. The expenditures for data acquisition for reservoir characterization can be partially wasted if data handling is not done carefully.This paper thus has the purpose of improving the use of data in scenarios of complex reservoir fluids.
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