Ra. Almehaideb et al., EOS tuning to model full field crude oil properties using multiple well fluid PVT analysis, J PET SCI E, 26(1-4), 2000, pp. 291-300
Equations of State (EOS) are increasingly being used to model fluid propert
ies of crude oil and gas reservoirs. This technique offers the advantage of
an improved fluid property prediction over conventional black oil models.
Once the crude oil or condensate fluid system has been probably characteriz
ed, its PVT behavior under a variety of conditions can easily be studied. T
his description is then used, within a compositional simulator, to study an
d choose among different scenarios for EOR schemes, such as miscible gas in
jection for oil reservoirs or liquid recovery under lean gas injection for
condensate reservoirs. In this paper, crude oil from a reservoir in the Uni
ted Arab Emirates (UAE) was characterized using the Peng-Robinson Equation
of State (PR-EOS) to arrive at one EOS model that accurately describes the
PVT behavior of crude oil produced from the different wells in the reservoi
r. The multi-sample characterization method is used to arrive at one consis
tent model for crude oil for the whole reservoir. The fluid samples are fir
st analyzed for consistency to make sure that they are representative of oi
l produced, and then they are used to obtain parameters for EOS model. The
tuning procedure for the EOS is done systematically by matching the volumet
ric and phase behavior results with laboratory results. Also, a consistent
C7+ pseudo-component split using the Whitson splitting method is used for a
ll samples to arrive at a consistent model for crude oil for the whole rese
rvoir. Results showed a very good match of PVT properties predicted using t
he EOS model with laboratory tests for this field. These results demonstrat
e the usefulness of the multi-sample method in providing one EOS model for
the crude oil using PVT test results from different wells. The EOS model de
veloped for this particular field may be used in reservoir simulation studi
es to optimize hydrocarbon recovery. (C) 2000 Elsevier Science B.V. All rig
hts reserved.