A new multi-sample EOS model for the gas condensate phase behavior analysis

A. Mehrabian, F. Crespo

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


Equations of State EOS are vastly being used to predict the phase behavior of reservoir fluids. The accuracy of EOS modeling technique over conventional correlation models would benefit an improved property prediction of these fluids. Once the crude oil or gas condensate fluid system has been probably characterized using limited laboratory tests, its PVT behavior under a variety of conditions can be easily studied. In this paper, the PVT behavior of gas condensate from a reservoir in South Pars retrograde gas field in Iran was modeled using the three-parameter Patel and Teja Equation of State. The multi-sample characterization method is used to arrive at one consistent model for retrograde gas in the whole reservoir. The fluid samples are first analyzed for consistency. To ensure that there is not any abnormal changes in fluid/reservoir properties, and then the consistent fluid data are used to obtain parameters for EOS model. A simplified lumping procedure along with a consistent C 12+ pseudo-component split using the Pederson splitting method is used for the samples in order to uniquely characterize the heavy fraction component of the reservoir fluid. The results of constant composition expansion and constant volume depletion laboratory tests as well as the experimental dew point pressures are used for EOS tuning. The results demonstrated a very good match of PVT properties predicted using the EOS model with experiment and laboratory tests for this field. These results confirm the usefulness of the EOS tuning on heavy fraction properties for all samples. The EOS model developed for this particular field may be used in simulation studies concerning recovery projects.

Original languageEnglish (US)
Pages (from-to)1025-1033
Number of pages9
JournalOil and Gas Science and Technology
Issue number6
StatePublished - Nov 2011

All Science Journal Classification (ASJC) codes

  • General Chemical Engineering
  • Fuel Technology
  • Energy Engineering and Power Technology


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