Determination of Total Organic Carbon (TOC) and Organic Facies from Well Log Data Using Intelligently Derived Equations and Cluster Analysis: a Case Study from Ahvaz Oilfield

Document Type : Research Paper

Authors

1 Department of Geology, Faculty of Science, University of Sistan and Baluchestan, Zahedan, Iran

2 Department of Geology, Faculty of Natural Sciences, University of Tabriz, Tabriz, Iran

3 Department of Geology, National Iranian South Oil Company (NISOC), Ahvaz, Iran

Abstract

Total organic carbon (TOC) is one of the important parameters for the evaluation of the hydrocarbon generation potential of source rocks. The measurement of this parameter requires conducting geochemical analysis on cutting samples, which is expensive and time consuming. In general, organic rich rocks are characterized by higher porosity, higher sonic transit time, lower density, higher gamma ray, and higher resistivity compared to other rocks. In this study, the linear and non-linear genetic algorithm models were used to estimate TOC from petrophysical data for the Kazhdumi, Gurpi, and Pabdeh source rocks in Ahwaz oilfield. The linear genetic algorithm model provided more reliable and acceptable results than the non-linear model. The genetic algorithm solutions for fitting coefficients to TOC equations were compared to a regression analysis. Performance analysis based on MSE and correlation coefficient indicates the higher performance of the intelligently derived equations in comparison to the statistical regression analysis. In the next step of the study, a cluster analysis technique was utilized for the classification of the estimated TOC log and the identification of geochemical zones. In the light of the acceptable results of the GA model, source rocks were classified into the organic-rich and organic-lean facies by using a cluster analysis method.
 

Keywords

References

[1]. Schmoker J. W., “Determination of organic-matter content of Appalachian Devonian shales from gamma-ray logs”, American Association of Petroleum Geologists Bulletin, Vol. 65, pp. 2165–2174, 1981.##
[2]. Passey O. R., Moretti F. U., and Stroud J. D., “A practical modal for organic richness from porosity and resistivity logs”, American Association of Petroleum Geologists Bulletin., Vol. 74, pp. 1777-1794, 1990.##
[3]. Kadkhodaie-Ilkhchi A., Rahimpour-Bonab H., and Rezaee M. R., A., “Committee machine with intelligent systems for estimation of total organic carbon content from petrophysical data: an example from Kangan and Dalan reservoirs in South Pars Gas Field”, Iran, Journal of Comput. Geosci., Vol. 35, pp. 459-474, 2008.##
[4] Kadkhodaie A., Rezaee M. R., and Rahimpour-Bonab H., A., “Committee Neural Network for Prediction of Normalized Oil Content from Well Log Data: an Example from South Pars Gas Field”, Persian Gulf, Journal of Petroleum Science and Engineering, Elsevier Publications., Vol. 65, pp. 23-39, 2009.##
[5]. Kamali M. R. and Mirshady A. A., “Total organic carbon content determined from well logs using ∆logR and neuro fuzzy techniques”, Journal of Petroleum Science and Engineering., Vol. 45, pp. 141–148, 2004.##
[6]. Mitchell M., An Introduction to genetic algorithms, MIT Press, Cambridge (MA)., 1996.##
[7]. Holland J. H., Adaptation in natural and artificial systems, University of Michigan Press, Ann Arbor., 1975.##
[8]. Goldberg D. E., Genetic algorithms in search, optimization, and machine learning, Addison-Wesley, Reading, MA., 1989.##
[9]. Michalewicz Z., Genetic algorithms +data structures=evolution programs, Springer Verlag, Berlin., 1992.##
[10]. Bordenave M. L. and Burwood R., “Source rock distribution and maturation in the Zagros orogenic belt: provenance of the asmari and bangestan reservoir oil accumulations”, Organic Geochemistry, Vol. 16, pp. 369-387, 1990.##
[11]. Alizadeh B. and Sepahvand S., “Petroleum source rock evaluation of Kazhdumi formation”, Southwestern Iran, GeoArabia., Vol. 6, No. 2, 282, 2001.##
[12]. Rabbani A. R. and Bagheri Tirtashi R., “Hydrocarbon source rock evaluation of the super giant ahwaz oil field, SW Iran”, Australian Journal of Basic and Applied Sciences, Vol. 4, No. 5, pp. 673-686, 2010.##
[13]. Jafarzadeh M. and Hosseini-Barzi M., “Petrography and geochemistry of Ahwaz sandstone member of asmari formation, Zagros, Iran: implications on provenance and tectonic setting”, Revista Mexicana de Ciencias Geológicas., No. 25(2), pp. 247-260, 2008.##
[14]. Chen C. H. and Lin Z. S., “A committee machine with empirical formulas for permeability prediction”, Comput,.Geosci., Vol. 32, pp. 485–496, 2006.##
Journal of Petroleum Research
Volume 25, Issue 84 - Serial Number 84
November and December 2015
Pages 161-172

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