Influence of Property Modeling Practices on Estimated Hydrocarbon Pore Volume
- Vivian K. Bust (Shell International Exploration & Production) | Paul F. Worthington (Park Royd P&P (England) Limited)
- Document ID
- Society of Petroleum Engineers
- SPE Reservoir Evaluation & Engineering
- Publication Date
- February 2014
- Document Type
- Journal Paper
- 6 - 14
- 2014.Society of Petroleum Engineers
- 4.1.2 Separation and Treating, 4.1.5 Processing Equipment, 5.1.1 Exploration, Development, Structural Geology
- hydrocarbon pore volume, zonal modeling, geocellular modeling
- 1 in the last 30 days
- 674 since 2007
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The emergence in geoscience of 3D geocellular modeling has raised questions about the correspondence of hydrocarbon volumetric deliverables with those derived from 2D zonal modeling. These differences of approach are compounded because the contemporary 3D methods use net-reservoir volumetric algorithms whereas the more established 2D methods have traditionally used net-pay volumetric algorithms. Both methods are initialized using 1D "alon gwellbore" datasets. Key parameters for comparison are initial hydrocarbon pore volume (IHPV) for 2D and 3D modeling and equivalent hydrocarbon column (EHC) for 1D along-wellbore modeling. The focus is twofold. The first objective has been to generate a functional petrophysical model as a basis for volumetric comparisons. The reservoir notionally comprises an oil accumulation within a water-wet, lithologically-clean sandstone that is partially saturated with high-salinity brine. The sandstone comprises five rock types (RTs), each of which has a defined set of interpretive algorithms. The second objective has been to compare static volumetric estimates of EHC and/or IHPV for a range of case models. This objective was approached using three workflows. Initially, 1D along-wellbore screening studies used different case models representing various stratigraphic sequences. These allowed a preliminary assessment of results arising from the use of net-reservoir and net-pay volumetric algorithms without the influence of mapping practices. The findings were corroborated by field studies. Second, 2D zonal modeling led to values of IHPV based on both net-reservoir and net-pay algorithmic protocols. Third, 3D geocellular modeling also led to values of IHPV based on both protocols. These data allowed equitable comparisons of 2D zonal deliverables with those from 3D geocellular models because a consistent inter-well interpolation methodology was used for all 2D and 3D cases. The analysis incorporated the influence of stratigraphic sequences of the five RTs with their different petrophysical characteristics. Comparisons of 2D and 3D models showed that IHPV values delivered by established 2D zonal models with net-pay algorithmic protocols are mostly lower than those values delivered by contemporary 3D geocellular models with net-reservoir protocols by approximately 4% on average, but the differences are highly variable. These outcomes, which have implications for reserves estimation, are strongly governed by the stratigraphic distribution of the RTs. They re-emphasize that each case must be investigated separately and thoroughly.
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Archie, G.E. 1942. The electrical resistivity log as an aid in determining some reservoir characteristics. In Transactions of the American Institute of Mining and Metallurgical Engineers, No. 142, SPE-942054-G, 54–62. New York: American Institute of Mining and Metallurgical Engineers Inc.
Caers, J. 2005. Petroleum Geostatistics. Richardson, Texas: Society of Petroleum Engineers.
Cosentino, L. 2001. Integrated Reservoir Studies. Paris: Editions Technip.
Gringarten, E. and Deutsch, C.V. 1999. Methodology for Variogram Interpretation and Modeling for Improved Reservoir Characterization. Presented at the SPE Annual Technical Conference and Exhibition, Houston, 3-6 October. SPE-56654-MS. http://dx.doi.org/10.2118/56654-MS.
Leverett, M.C. 1941. Capillary Behavior in Porous Solids. In Transactions of the American Institute of Mining, Metallurgical, and Petroleum Engineers, Vol. 142, Paper SPE-941152-G, 152–169. Dallas, Texas: Society of Petroleum Engineers of AIME.
Morris, R.L. and Biggs, W.P. 1967. Using Log-Derived Values of Water Saturation And Porosity. Presented at the SPWLA 8th Annual Logging Symposium, London, March. Paper No. X1-26.
Nelson, P.H. 1994. Permeability-Porosity Relationships in Sedimentary Rocks. The Log Analyst 35 (3): 38–62. SPWLA-1994-v35n3a4.
Paterson, M.S. 1983. The equivalent channel model for permeability and resistivity in fluid-saturated rock—A re-appraisal. Mech. Mater. 2 (4): 345-352. http://dx.doi.org/10.1016/0167-6636(83)90025-X.
Rae, S.F. and Neve, P. 1994. Experiences in Incorporating a 3D Geological Model Into a Reservoir Simulator. Presented at the European Petroleum Computer Conference, Aberdeen, 15-17 March. SPE-27564-MS. http://dx.doi.org/10.2118/27564-MS.
Rose, W.D. and Bruce, W.A. 1949. Evaluation of capillary character in petroleum reservoir rock. In Transactions of the American Institute of Mining and Metallurgical Engineers, Vol. 186, SPE-949127-G, 127–142. Dallas, Texas: American Institute of Mining and Metallurgical Engineers Inc.
Schlumberger. 2000. Log Interpretation Charts, 15. Sugar Land, Texas: Schlumberger Oilfield Communications.
Timur, A. 1968. An Investigation of Permeability, Porosity, and Residual Water Saturation Relationships for Sandstone Reservoirs. The Log Analyst 9 (4): 8–17.
Walsh, J.B. and Brace, W.F. 1984. The effect of pressure on porosity and the transport properties of rock. Journal of Geophysical Research: Solid Earth 89 (B11): 9425-9431. http://dx.doi.org/10.1029/JB089iB11p09425.
Worthington, P.F. 2008. The Application of Cutoffs in Integrated Reservoir Studies. SPE Res Eval & Eng 11 (6): 968–975. SPE-95428-PA. http://dx.doi.org/10.2118/95428-PA.
Wyllie, M.R.J. and Rose, W.D. 1950. Some theoretical considerations related to the quantitative evaluation of the physical characteristics of reservoir rock from electric log data. In Transactions of the American Institute of Mining and Metallurgical Engineers, Vol. 189, SPE-950105-G, 105–118. Dallas, Texas: American Institute of Mining and Metallurgical Engineers Inc.