Solution of the Inverse Problem of Determining the Initial Hydrocarbons Composition in a Gas-Condensate Reservoir Using Field Data

The paper is devoted to the problem of determining the composition of reservoir gas for gas condensate fields. A methodology for planning gas condensate tests (GCT) is proposed, which allows to assess the possibility of obtaining conditioned samples of reservoir fluid. For the case when it is impossible to take conditioned samples, an approach for their interpretation is developed.
At the first step it is proposed to numerically create a set of compositions by adding to the gas of the laboratory “depleted” composition a certain amount of condensate equilibrated to it. The resulting compositions have different condensation onset pressures above the laboratory pressure. Subsequently, for each of the obtained compositions hydrodynamic (HD) modeling should be carried out and the composition for which the obtained values of condensate and gas flow rates and gas oil ratio (GOR) are close to the GCT data should be selected.
The analysis of numerical experiments on synthetic flow rate data for a typical well shows a significant dependence of GOR on the component composition and low sensitivity to changes in the main parameters of the HD model. When adjusting the HD model according to the actual data, it is proposed to first select from the set of reconstructed compositions the one for which the model GOR values will be closest to the actual data. The next step, when the selected composition is fixed, is the selection of other parameters of the HD model based on the data of gas and condensate flow rates. This methodology was demonstrated to determine the component composition and main reservoir parameters from GOR data for one real well.

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