General approach to characterizing reservoir fluids for EoS models using a large PVT database

Farhad Varzandeh, Erling Halfdan Stenby, Wei Yan

Research output: Contribution to journalJournal articleResearchpeer-review

200 Downloads (Pure)

Abstract

Fluid characterization is needed when applying any EoS model to reservoir fluids. It is important especially for non-cubic models such as PC-SAFT where fluid characterization is less mature. Furthermore, there is a great interest to apply non-cubic models to high pressure high temperature reservoir fluids as they are believed to give better description of density and compressibility over a wide temperature and pressure range. We proposed a general approach to characterizing reservoir fluids and applied it to PC-SAFT. The approach consists in first, developing the correlations based on the DIPPR database, and then adjusting the correlations based on a large PVT database. The adjustment was made to minimize the deviation in key PVT properties like saturation pressures, densities at reservoir temperature and stock tank oil densities, while keeping the n-alkane limit of the correlations unchanged. The general approach can also be applied to other EoS models for improving their fluid characterization and we showed this for SRK and PR. In addition, we developed a PNA based characterization method for PC-SAFT based on the same general principles. We made a comprehensive comparison in PVT calculation involving 17 EoS-characterization combinations and 260 reservoir fluids. The new characterization methods generally improved the PVT calculation results.
Original languageEnglish
JournalFluid Phase Equilibria
Volume433
Pages (from-to)97–111
Number of pages15
ISSN0378-3812
DOIs
Publication statusPublished - 2017

Keywords

  • Equation of state
  • Reservoir fluids
  • C7+ characterization
  • PC-SAFT
  • PVT database

Fingerprint Dive into the research topics of 'General approach to characterizing reservoir fluids for EoS models using a large PVT database'. Together they form a unique fingerprint.

Cite this