Summary
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.
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