Open Access
Oil Gas Sci. Technol. – Rev. IFP Energies nouvelles
Volume 69, Number 7, December 2014
Page(s) 1143 - 1154
Published online 27 May 2013
  • Alavi M. (2004) Regional stratigraphy of the Zagross fold-thrust belt of Iran and its proforeland evolution, Am. J. Sci. 304, 1–20. [CrossRef]
  • Behrens R.A., Macleod M.K., Tran T.T., Alimi A.O. (1998) Incorporating seismic attribute maps in 3D reservoir models, SPE Reserv. Eval. 1, 122–126.
  • Bhatt A., Helle H.B. (2002) Committee neural networks for porosity and permeability prediction from well logs, Geophys. Prospect. 50, 645–660. [CrossRef]
  • Chiu S. (1994) Fuzzy model identification based on cluster estimation, J. Intelligent Fuzzy Syst. 2, 3, 267–278.
  • Daiguji M., Kudo O., Wada T. (1997) Application of wavelet analysis to fault detection in oil refinery, Comput. Chem. Eng. 21, S1117–S1122 Suppl.. [CrossRef]
  • Darabi H., Kavousi H., Moraveji A., Masihi M. (2010) 3D Fracture Modeling in Parsi Oil Feld Using Artificial Intelligence Tools, J. Petrol. Sci. Eng. 71, 67–76. [CrossRef]
  • Deutsch C.V., Journel A.G. (1992) GSLIB-Geostatistical Software Library and user’s guide, Oxford University Press, Oxford, 340 p.
  • Deutsch C.V. (2002) Geostatistical reservoir modeling, Oxford university press, New York.
  • Deutsch C.V. (2006) A sequential indicator simulation program for categorical variables with point and block data, Comput. Geosci. 32, 1669–1681. [CrossRef]
  • El Ouahed A.K., Tiab D., Mazouzi A. (2005) Application of artificial intelligence to characterize naturally fractured zones in Hassi Messaoud Oil Field, Algeria, J. Petrol. Sci. Eng. 49, 122–141. [CrossRef]
  • FitzGerald E.M., Bean C.J., Reilly R. (1999) Fracture-frequency prediction from borehole wireline logs using artificial neural networks, Geophys. Prospect. 47, 1031–1044. [CrossRef]
  • Geman S., Geman D. (1984) Stochastic Relaxation, Gibbs Distribution and the Bayesian Restoration of Images, IEEE Trans. Pattern Anal. Mach. Intell. 6, 6, 721–741. [CrossRef] [PubMed]
  • Gokceoglu C., Yesilnacar E., Sonmez H., Kayabasi A. (2004) A neuro-fuzzy model for modulus of joint rock masses, Comput. Geotechnics 31, 375–383. [CrossRef]
  • Gringarten E. (1998) Stochastic simulation of fractures in layered systems, Comput. Geosci. 26, 729–736. [CrossRef]
  • Gringarten E., Deutsch C.V. (1999) Methodology for Variogram Interpretation and Modeling for Improved Reservoir Characterization, Annual Technical Conference and Exhibition. Houston, Texas, 3-6 Oct., SPE 56654, 13 p.
  • Haller D., Porturas F. (1998) How to characterize fractures in reservoirs using borehole and core images: Case studies, Geol. Soc. London Spec. Publ. 136, 249–259. [CrossRef]
  • Hsu K., Brie A., Plumb R.A. (1987) A new method for fracture identification using array sonic tools, J. Pet. Technol. June, SPE Paper 14397, 677–683. [CrossRef]
  • Ja’fari A., Kadkhodaie-Ilkhchi A., Sharghi A., Ghanavati K. (2012) Fracture density prediction from petrophysical log data using adaptive neuro-fuzzy inference system, J. Geophys. Eng. 9, 105–114. [CrossRef]
  • Journel A.G. (1983) Nonparametric estimation of spatial distributions, Math. Geol. 15, 445–468. [CrossRef]
  • Journel A.G. (1993) Geostatistics: Roadblocks and Challenges, in Soares A. (ed.), Geostatistics Troia ’92, Kluwer Academic Publishers, Dordrecht, The Netherlands, pp. 213–224. [CrossRef]
  • Kadkhodaie-Ilkhchi A., Rezaee M.R., Rahimpour-Bonab H., Chehrazi A. (2009) Petrophysical data prediction from seismic attributes using committee fuzzy inference system, Comput. Geosci. 35, 2314–2330. [CrossRef]
  • Kadkhodaie-Ilkhchi A., Takahashi Monteiro S., Ramos F., Hatherly P. (2010) Rock Recognition from MWD Data: A Comparative Study of Boosting, Neural Networks and Fuzzy Logic, IEEE Trans. Geosci. Remote Sensing Lett. (GSRL) 7, 4, 680–684. [CrossRef]
  • Kelkar M. (2000) Application of Geostatistics for Reservoir Characterization Accomplishments and Challenges, J. Can. Pet. Technol. 39, 25–29.
  • Khoshbakht F., Memarian H., Mohammadnia M. (2009) Comparison of Asmari, Pabdeh and Gurpi formation’s fractures, derived from image log, J. Petrol. Sci. Eng. 67, 65–74. [CrossRef]
  • Labani M.M., Kadkhodaie-Ilkhchi A., Salahshoor K. (2010) Estimation of NMR log parameters from conventional well log data using a committee machine with intelligent systems: A case study from the Iranian part of the South Pars gas field, Persian Gulf Basin, J. Petrol. Sci. Eng. 72, 175–185. [CrossRef]
  • Liu Y., Journel A. (2007) A package for geostatistical integration of coarse and fine scale data, Comput. Geosci. 35, 527–547. [CrossRef]
  • Matheron G., Beucher H., de Fouquet C., Gralli A., Guerillot D., Ravenne C. (1987) Conditional simulation of the geometry of fluvio-deltaic reservoirs, Proc. SPE, Annual Technical Conference and Exhibition, Dallas, Texas, 27–30 Sept., SPE 16753, pp. 591–599.
  • Matlab User’s Guide (2007) Matlab CD-ROM, MathWorks, Inc.
  • Ouenes A. (1999) Practical application of fuzzy logic and neural networks to fractured reservoir characterization, Comput. Geosci. 26, 953–962. [CrossRef]
  • Petrel User’s Guide (2009) Petrophysical modeling, CD-ROM, Schlumberger Company.
  • Seifert D., Jensen J.L. (1999) using sequential indicator simulation as a tool in reservoir description: issues and uncertainties, Math. Geol. 31, 527–550. [CrossRef]
  • Serra O. (1989) Formation MicroScanner image interpretation, Schlumberger Education Services.
  • Song X., Zhu Y., Liu Q., Chen J., Ren D., Li Y., Wang B., Liao M. (1998) Identification and distribution of natural fractures, SPE International Oil and Gas Conference and Exhibition in China, Beijing, China, 2-6 Nov., SPE Paper 50877.
  • Tokhmchi B., Memarian H., Rezaee M.R. (2010) Estimation of the fracture density in fractured zones using petrophysical logs, J. Petrol. Sci. Eng. 72, 206–213. [CrossRef]
  • Western W.A., Bloschl G., Grayson R.B. (1998) How well do indicator variograms capture the spatial connectivity of soil moisture? Hydrol. Process. 12, 1851–1868. [CrossRef]
  • Yarus J.M., Chambers R.L. (2006) Practical Geostatistics – An Armchair Overview for Petroleum Reservoir Engineers, (Distinguished Author Series), J. Petrol. Technol. 58, 11, 78–86, SPE 103357. [CrossRef]

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