Predicting performance of gas condensate reservoirs

Abstract

Multiphase flow behavior in gas condensate reservoirs is analyzed, and in particular estimating gas condensate well deliverability. Inflow performance relationship (IPR) measures for gas condensate wells are analytically generated and made available. The inflow performance relationship measures of gas condensate wells incorporate the effect of condensate banking as pressure near the well bore drops below the dew point. The inflow performance relationship measures are based on formation rock relative permeability data and Constant Composition Expansion (CCE) experiment data.

Description

CROSS REFERENCE TO RELATED APPLICATIONS[0001]This application claims priority from U.S. Provisional Application No. 61 / 724,534, filed Nov. 9, 2012. For purposes of United States patent practice, this application incorporates the contents of the Provisional Application by reference in entirety.BACKGROUND OF THE INVENTION[0002]1. Field of the Invention[0003]The present invention relates to reservoir analysis of performance of subsurface hydrocarbon reservoirs, and more particular to prediction of the performance of gas condensate reservoirs.[0004]2. Description of the Related Art[0005]Gas condensate reservoirs differ from dry gas reservoirs. Understanding the phase and fluid flow behavior relationships has been required in order to make accurate engineering computations for gas condensate systems. Condensate dropout occurs in the reservoir as the pressure falls below the dew point. As a result of such condensate dropout, gas phase production from gas condensate wells decreases signifi...

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Benefits of technology

[0012]The present invention also provides a new and improved data storage device having stored in a computer readable medium computer operable instructions for causing a data processing system to obtain measures in a computer system of predicted performance of a gas condensate well in a subsurface reservoir. The instructions stored in the data storage device cause the data processing system to receive component composition expansion data based on measurements from fluid from the well; relative permeability data regarding formations containing the gas condensate of the well; and bottom hole pressure data of the well. The instructions stored in the data storage device cause the data processing system to obtain a measure of dew point of gas condensate in the well based on the component composition expansion data, and determine if the bottom hole pressure of the well is above the dew point of the gas condensate of the well. If the bottom hole pressure of the well is not above the dew point, the instructions cause the data processing system to form an estimated productivity index of the gas condensate well for single phase flow of the well, then form an estimated productivity index of the gas condensate well for two phase flow of the well and form an estimated predicted performance of the well as a function of formation relative permeability and the estimated productivity index of the gas condensate well for two phase flow. If the bottom hole pressure of the well is above the dew point, the instructions cause the data processing system to obtain a measure of borehole pressure of the well, and form an estimated predicted performance of the well as a function of borehole pressure and relative gas permeability of the well. The instructions then cause the data processing system to assemble in memory the estimated predicted performance the well.

Problems solved by technology

As a result of such condensate dropout, gas phase production from gas condensate wells decreases significantly.

Well productivity is an important issue in the development of most low and medium permeability gas condensate reservoirs.

Liquid build up around the well has been found to cause a significant reduction in productivity, even in lean gas condensate reservoirs where the maximum liquid drop out indicated by test data is as low as 1%.

However, accurate forecasts of gas condensate productivity has been difficult because of the need to understand and account for complex processes that occur in the near-well region.

So far as is known, none of these estimation methods have been simple to use.

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