Downhole fluid analysis (DFA), together with focused-sampling techniques and
wireline-formation-tester (WFT) tools, provides real-time measurements of
reservoir-fluid properties such as the compositions of four or five hydrocarbon
components/groups and gas/oil ratio (GOR). With the introduction of a new
generation of DFA tools that analyze fluids at downhole conditions, the
accuracy and reliability of the DFA measurements are improved significantly.
Furthermore, downhole measurements of live-fluid densities are integrated into
the new tools. Direct pressure and temperature measurements of the flowline
ensure capture of accurate fluid conditions. To enhance these advanced features
further, a new method of downhole fluid characterization based on the
equation-of-state (EOS) approach is proposed in this work.
The motivation for this work is to develop a new approach to maximize the
value of DFA data, perform quality assurance or quality control of DFA data,
and establish a fluid model for DFA log predictions along with DFA fluid
profiling. The basic inputs from DFA measurements are weight percentages of
CO2, C1, C2, C3-C5, and
C6+, along with live-fluid density and viscosity. A new method was
developed in this work to delump and characterize the DFA measurements of
C3-C5 (or C2-C5) and C6+
into full-length compositional data. The full-length compositional data
predicted by the new method were compared with the laboratory-measured gas
chromatograph data up to C30+ for more than 1,000 fluids, including
heavy oil, conventional black oil, volatile oil, rich gas condensate, lean gas
condensate, and wet gas. These fluids have a GOR range of 8-140,000 scf/STB and
a gravity range from 9 to 50°API. A good agreement was achieved between the
delumped and gas-chromatograph compositions.
In addition, on the basis of the delumped and characterized full-length
compositional data, EOS models were established that can be applied to predict
fluid-phase behavior and physical properties by virtue of DFA data as inputs.
The EOS predictions were validated and compared with the laboratory-measured
pressure/volume/temperature (PVT) properties for more than 1,000 fluids. The
GOR, formation-volume factor, density, and viscosity predictions were in good
agreement with the laboratory measurements. The established EOS model then was
able to predict other PVT properties, and the results were compared with the
laboratory measurements in good agreement.
Consequently, the established EOS models have laid a solid foundation for
DFA log predictions in DFA fluid profiling, which has been integrated
successfully with DFA measurements in real time to delineate compositional and
asphaltene gradients in oil columns and to determine reservoir connectivity.
The latter results are beyond the scope of this work and have been given in
separate technical papers.
© 2010. Society of Petroleum Engineers
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- Original manuscript received:
27 June 2008
- Meeting paper published:
21 October 2008
- Revised manuscript received:
2 June 2010
- Manuscript approved:
16 June 2010
- Published online:
27 October 2010
- Version of record:
15 March 2011