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Pore throat size characterization of carbonate reservoirs by integrating core data, well logs and seismic attributes | ||
| Geopersia | ||
| مقاله 13، دوره 9، شماره 2 - شماره پیاپی 2228782، بهمن 2019، صفحه 395-410 اصل مقاله (2.47 M) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22059/geope.2019.269872.648430 | ||
| نویسندگان | ||
| Ali Kadkhodaie1؛ Sirous Hosseinzadeh2؛ Hossein Mosaddegh* 2؛ Rahim Kadkhodaie1 | ||
| 1Department of geology, Faculty of Sciences, University of Tabriz, Tabriz, Iran | ||
| 2Department of geology, Faculty of Sciences, Kharazmi University, Tehran, Iran | ||
| چکیده | ||
| Investigation of pore system properties of carbonate reservoirs has an important role in evaluating the reservoir quality and delineating high production intervals. The current study proposes a three-step approach for pore throat size characterization of these reservoirs, by integrating core data, well logs and 3D seismic volume. In this respect, first the pore throats size was calculated using Pittman and Winland models based upon routine core analysis data, and calibrating the results with the laboratory-derived capillary pressure curves. In the second step, the pore throat size as a continuous log was calculated using petrophysical data for each studied well. Finally, the calculated pore throat size log was tied to 3D seismic data at well locations. The results show that seismic attributes including acoustic impedance, amplitude envelope, filter 15/20-25/30 and derivative instantaneous amplitude are the best predictor set for converting the 3D seismic volume into a pore size cube by a probabilistic neural network mode. The methodology illustrated in this study, was employed on Ilam carbonate reservoir in one of the southwestern oilfields of Iran. The findings demonstrate that seismic data in combination with core and well log data could be considered as an effective tool for spatial modeling and characterization. | ||
| کلیدواژه‌ها | ||
| Pore throat size؛ Artificial Neural Network؛ seismic attributes؛ seismic inversion؛ carbonate reservoirs | ||
| عنوان مقاله [English] | ||
| - | ||
| مراجع | ||
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Asl, S.S., Aleali, M., 2016. Microfacies patterns and depositional environments of the Sarvak Formation in the Abadan Plain, Southwest of Zagros, Iran. Open Journal of Geology, 6: 201.## Bornard, R., Allo, F., Coléou, T., Freudenreich, Y., Caldwell, D. H., Hamman, J. G., 2005.Petrophysical seismic inversion to determine more accurate and precise reservoir properties (SPE94144). In67th EAGE Conference & Exhibition.## Bosch, M., Mukerji, T., Gonzalez, E. F., 2010. Seismic inversion for reservoir properties combining statistical rock physics and geostatistics: A review. Geophysics, 75: 165–176.## Buryakovsky, L., Chilingar, G. V., Rieke, H. H., Shin, S., 2012. Fundamentals of the petrophysics of oil and gas reservoirs. ## John Wiley & Sons.Dai, J., Xu, H., Snyder, F., Dutta, N., 2004. Detection and estimation of gas hydrates using rock physics and seismic inversion: Examples from the northern deepwater Gulf of Mexico. The Leading Edge, 23: 60-66.## Dolberg, D. M., Helgesen, J., Hanssen, T. H., Magnus, I., Saigal, G., Pedersen, B. K., 2000. Porosity prediction from seismic inversion, Lavrans Field, Halten Terrace, Norway. The Leading Edge, 19: 392–399.## Dorrington, K. P., Link, C. A., 2004. Genetic–algorithm/neural–network approach to seismic attribute selection for well–log prediction. Geophysics, 69: 212–221.## Grana, D., Della Rossa, E., 2010. Probabilistic petrophysical–properties estimation integrating statistical rock physics with seismic inversion. Geophysics, 75: O21–O37.## Hampson, D. P., Schuelke, J. S., Quirein, J. A., 2001. Use of multiattribute transforms to predict log properties from seismic data. Geophysics, 66: 220–236.## HRS User’s Guide, 2015. CGGVeritas Hampson–Russell, Calgary, Alberta, Canada.## Kolodzie, Jr, S., 1980.Analysis of pore throat size and use of the Waxman–Smits equation to determine OOIP in Spindle Field, Colorado. In SPE Annual Technical Conference and Exhibition.Society of Petroleum Engineers, 21–24.## Mehrabi, H., Rahimpour–Bonab, H., Enayati–Bidgoli, A. H., Navidtalab, A., 2014. Depositional environment and sequence stratigraphy of the Upper Cretaceous Ilam Formation in central and southern parts of the Dezful Embayment,SW Iran. Carbonates and Evaporites, 29: 263–278.## Nelson, P. H., 2009. Pore–throat sizes in sandstones, tight sandstones, and shales. AAPG Bulletin, 93: 329–340.## Pendrel, J., Mangat, C., Feroci, M., 2006.Using Bayesian inference to compute facies–fluids probabilities. In CSEG Annual Meeting, Expanded Abstracts.## Pittman, E. D., 1992. Relationship of porosity and permeability to various parameters derived from mercury injection–capillary pressure curves for sandstone. AAPG Bulletin, 76: 191–198.## Rezaee, M. R., Jafari, A., Kazemzadeh, E., 2006. Relationships between permeability, porosity and pore throat size in carbonate rocks using regression analysis and neural networks. Journal of Geophysics and Engineering, 3: 370.## Russell, B. H., 2004. The application of multivariate statistics and neural networks to the prediction of reservoir parameters using seismic attributes.## Russell, B. H., 1988. Introduction to seismic inversion methods, Society of Exploration Geophysicists.## Scott, J. B., Barker, R. D., 2003. Determining pore‐throat size in Permo‐Triassic sandstones from low‐frequency electrical spectroscopy. Geophysical Research Letters, 30.## Sepehr, M., Cosgrove, J. W., 2004.Structural framework of the Zagros fold–thrust belt, Iran. Marine and Petroleum Geology, 21: 829–843.## Shahraeeni, M. S., Curtis, A., Chao, G., 2012. Fast probabilistic petrophysical mapping of reservoirs from 3D seismic data. Geophysics, 77: 01–019.## Tiab, D., Donaldson, E. C., 2015. Petrophysics: theory and practice of measuring reservoir rock and fluid transport properties. Gulf professional publishing.410 Hosseinzadeh et al. Geopersia, 9 (2), 2019## Wardlaw, N. C., Li, Y., Forbes, D., 1987. Pore–throat size correlation from capillary pressure curves. Transport in Porous Media, 2: 597–614.## Washbourn, E. W., 1921. Note on a method of determination the distribution pore size in a porous material: Proceeding of the National Academy of Science, 7: 115–116.## Yarmohammadi, S., Kadkhodaie–Ilkhchi, A., Rahimpour–Bonab, H., Shirzadi, A., 2014. Seismic reservoir characterization of a deep water sandstone reservoir using hydraulic and electrical flow units: A case study from the Shah Deniz gas field, the South Caspian Sea. Journal of Petroleum Science and Engineering, 118: 52–60.## Yilmaz, Ö., 2001. Seismic data analysis. Society of Exploration Geophysicists, 1: 74170–2740.## | ||
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