Reliable predictions in compositional reservoir simulators require a proper equation of state to describe accurately the phase behavior of fluids both in sub/super-critical regions. In miscible processes such as CO2 and lean gas injections, the injected fluid is usually at it's super-critical temperature, and therefore the current forms of EOS might not be suitable, since their temperature-dependency term (Alpha Function) have been obtained using experimental data of pure components at sub-critical regions. The same problem exists for compositional simulation of gas condensate reservoirs in which the major components are above critical temperature.

A new alpha function was developed using sound velocity data of pure components at their super-critical temperatures, since sound data can be measured accurately at large temperature range. Sound velocity can be thermodynamically related to the EOS parameters. An appropriate form of alpha function has been hence obtained for each component at super-critical temperatures.

In this work, the sound velocity experimental data of pure methane, ethane, propane and carbon dioxide has been used to generate a new form of alpha function at super-critical temperatures using PR EOS. The new function was then tested and validated against different experimental data from binary, ternary and multi-component systems and was found satisfactory in improving the prediction results.

By adapting the new methodology and developing the new alpha function for other components at super-critical region, it diminishes the need for temperature-dependent BIPs and also decreases the task for tuning of a given EOS against experimental data.

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