Prediction of pore facies using GMDH-type neural networks: a case study from the South Pars gas field, Persian Gulf basin

Document Type : Research Paper

Authors

1 Department of Earth Science, Faculty of Natural Science, University of Tabriz,Tabriz, Iran

2 Department of Geology, University College of Sciences, University of Tehran, Tehran, Iran

3 Department of Mechanical engineering, Sharif University, Tehran, Iran

4 Department of Mechanical engineering, University of Guilan, Rasht, Iran

Abstract

The current study proposes a two-step approach for pore facies characterization in the carbonate reservoirs with an example from the Kangan and Dalan
formations in the South Pars gas field. In the first step, pore facies were determined based on Mercury Injection Capillary Pressure (MICP) data incorporation with the Hierarchical Clustering Analysis (HCA) method. In the next step, polynomial meta-models were established based on the evolved Group Method of Data Handling (GMDH) neural networks for the purpose of pore facies identification from well log responses. In this way, the input data table used for training GMDH-type neural network consists of CALI, GR , CGR , SGR, DT, NPHI, RHOB, PEF, PHIE and VDL logs. The MICP-HCA derived pore facies were considered as the desired outputs. Moreover, multi-objective genetic algorithms (GAs) are used to the evolutionary design of GMDH-type neural networks. Training error and prediction error of neural network have been considered as conflicting objectives for Pareto multi-objective optimization. The results of this study indicate the successful implementation of GMDH neural networks for classification of pore facies in the heterogeneous gas bearing carbonate rocks of South Pars gas field.

Keywords

Article Title [Persian]

-

References

Aali, J., Rahimpour-Bonab, H. and Kamali, M. R., 2006. Geochemistry and origin of the world's largest gas field from Persian Gulf, Iran. Journal of Petroleum Science and Engineering, 50: 161-175.##
Ahr, W.M., 2008. Geology of Carbonate Reservoirs: the Identification, Description, and Characterization of Hydrocarbon Reservoirs in Carbonate Rocks. (Hoboken: Wiley), 296 pp.##
Alsharhan, A.S., Nairn, A.E.M., 1997. Sedimentary Basins and Petroleum Geology of the Middle East. Elsevier, Netherlands, 843 pp.##
Amaefule, J.O., Altunbay, M., Tiab, D., Kersey, D.G., Keelan, D.K., 1993. Enhanced reservoir description: using core and log data to identify hydraulic (flow) units and predict permeability in uncored intervals/wells. Society of Petroleum Engineers Paper, 26436: 1–16.##
Arfi, A. S., Heliot, D., Zhan, J. L. & Allen, D. 2006. A new porosity partitioning-based methodology for permeability and texture analysis in Abu Dhabi carbonates. (SPE paper 101176.) Paper presented at the Abu Dhabi International Petroleum Exhibition and Conference, 5–8 November 2006.##
Bordenave, M.L. and Burwood, R., 1990. Source rock distribution and maturation in the Zagros orogenic belt: provenance of the Asmari and Bangestan reservoir oil accumulations. Organic Geochemistry, 16(1), 369-387.##
Chehrazi, A., Rezaee, R., Rahimpour-Bonab, H., 2011. Pore facies as a tool for incorporation of small-scale dynamic information in integrated reservoir studies. Journal of Geophysics and Engineering, 8: 202–24##
Ehrenberg, S.N., Nadeau, P.H. and Aqrawi, A.A.M., 2007. A comparison of Khuff and Arab reservoir potential throughout the Middle East.  American Association of Petroleum Geologists bulletin, 91(3): 275-286.##
Ebanks, W.J., 1987. Flow unit concept-integrated approach to reservoir description for engineering projects.  American Association of Petroleum GeologistsMeeting Abstracts, 1: 521-522.##
Farlow, S.J., 1984. Self-organizing methods in modeling: GMDH type algorithms (Vol. 54), Marcel Dekker Inc, CrC Press.##
Ghazban, F., 2007. Petroleum geology of the Persian Gulf. Tehran University press, Tehran, 734 pp.##
Iba, H., deGaris, H. and Sato, T., 1996. A numerical Approach to Genetic Programming for System Identification, Evolutionary Computation, 3(4): 417-452.##
Insalaco, E., Virgone, A., Courme, B., Gaillot, J., Kamali, M., Moallemi, A., Lotfpour, M. and Monibi, S., 2006. Upper Dalan Member and Kangan Formation between the Zagros Mountains and offshore Fars, Iran: depositional system, biostratigraphy and stratigraphic architecture. GEOARABIA-MANAMA-, 11(2): 75 pp.##
Ivakhnenko, A.G., 1971. Polynomial theory of complex systems. IEEE transactions on Systems, Man, and Cybernetics, 1(4), 364-378.##
Jamali, A., Ghamati, M., Ahmadi, B., &Nariman-Zadeh, N., 2013.Probability of failure for uncertain control systems using neural networks and multi-objective uniform-diversity genetic algorithms (MUGA). Engineering Applications of Artificial Intelligence, 26(2): 714-723.##
Jamali, A., Hajiloo, A., and Nariman-zadeh, N., 2010. Reliability-based robust Pareto design of linear state feedback controllers using a multi-objective uniform-diversity genetic algorithm (MUGA), Expert systems with Applications, 37 (1): 401-413.##
Jamali, A., Nariman-Zadeh, N., Atashkari, K., 2008. Multi-objective Uniform diversity Genetic Algorithm (MUGA), In Advanced in Evolutionary Algorithms, witoldkosinski (Ed.), IN-TECH, Vienna.##
Jamali, A., Nariman-zadeh, N., Darvizeh, A., Masoumi, A., Hamrang, S., 2009. Multi-objective evolutionary optimization of polynomial neural networks for modelling and prediction of explosive cutting process, Engineering Applications of Artificial Intelligence 22, (4-5): 676-687.##
Jennings, J.B., 1987. Capillary pressure techniques: application to exploration and development geology. American Association of Petroleum Geologists, 71, 1196–1209.##
Kamali, M.R. andRezaee, M.R., 2003. Burial history reconstruction and thermal modelling at Kuh-e Mond, SW Iran. Journal of petroleum Geology, 26(4): 451-464.##
Kashfi, M. S., 1992. Geology of the Permian ‘supergiant’ gas reservoirs in the greater Persian Gulf area Journal of Petroleum Geology, 15: 465–80.##
Konyuhov, A.I., Maleki, B, 2006. The Persian Gulf Basin: Geological history, sedimentary formations, and petroleum potential. Lithology and Mineral Resources, 41: 344–361.##
Kopaska-Merkel, D.C., Friedman, G.M., 1989. Petrofacies analysis of carbonate rocks: example from lower PaleozoicHunton Group of Oklahoma and Texas  American Association of Petroleum Geologists Bulletin, 73: 1289–306##
Lucia, F. J., 2007. Carbonate reservoir characterization. Springer, 2nd ed., New York, 226 pp.##
Ma, Z.Y., Wang, H., Sitchler, J., Gurpinar, O., Gomez, E., Wang, Y., 2014. Mixture decompositions and lithofacies clustering from wire line logs. Journal of Applied Geophysics, 102: 10–20.##
Marzouk, I., Takezaki, H. & Miwa, M. 1995. Geologic controls on wettability of carbonate reservoirs, Abu Dhabi, U.A.E. Paper presented at the SPE Middle East Oil Show, Bahrain, Manama, 11–14.##
Nariman-Zadeh, N., Darvizeh, A. Jamali, A., Moeini, A., 2005.Evolutionary design of generalized polynomial neural networks for modelling and prediction of explosive forming process, Journal of Materials Processing Technology, 164-165 : 1561-1571.##
Nariman-Zadeh, N., Darvizeh, A., Ahmad-Zadeh, R., 2003. Hybrid genetic design of GMDH-type neural networks using singular value decomposition for modelling and prediction of the explosive cutting process, Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 217: 779–790.##  
Nariman-Zadeh, N., Salehpour, M., Jamali, A., Haghgoo, E., 2010. Pareto optimization of a five-degree of freedom vehicle vibration model using a multi-objective uniform-diversity genetic algorithm (MUGA), Engineering Applications of Artificial Intelligence, 23(4): 543-551.##
Perez, H.H., Datta-Gupta, A., Mishra S., 2003. The Role of Electrofacies, Lithofacies, and Hydraulic Flow Units in Permeability Predictions from Well Logs: A Comparative Analysis Using Classification Trees. SPE Annual Technical Conference and Exhibition, Denver, Paper 84301-MS, 1–11.##
Rahimpour-Bonab, H., Asadi-Eskandar, A. andSonei, R., 2009. Effects of the Permian–Triassic boundary on reservoir characteristics of the South Pars gas field, Persian Gulf. Geological Journal, 44(3): 341-364.##
Rogers, S. J., Fang, J. H., Karr, C, L., Stanley, D. A., 1992. Determination of lithology from well logs using a neural network  American Association of Petroleum Geologists Bulletin, 76: 731–739.##
Saggaf, M.M., Nebrija, Ed. L., 2000. Estimation of lithologies and depositional facies from wire-line logs  American Association of Petroleum Geologists Bulletin, 84: 1633–46.##
Serra, O., Delfiner, P., Levertt, J. C., 1985. Lithology determination from well logs: case studies Society of Professional Well Log Analysts 26th annual logging symposium. Transactions Paper.##
Sfidari, E., Kadkhodaie-Ilkhchi, A., Najjari, S., 2012. Comparison of intelligent and statistical clustering approaches to predicting total organic carbon using intelligent systems.  Journal of Petroleum Science and Engineering, 86–87: 190–205.##
Sfidari, E., Kadkhodaie-Ilkhchi, A., Rahimpour-Bbonab, H., Soltani B. 2014. A hybrid approach for litho-facies characterization in the framework of sequence stratigraphy: A case study from the South Pars gas field, the Persian Gulf basin, Journal of Petroleum Science and Engineering, 121: 87-102.##
Skalinski, M. T., Gottlib-Zen, S. & Moss, B. 2005. Defining and predicting rock types in carbonates: An integrated approach using core and log data in Tengiz field. Paper presented at the SPWLA 46th Annual Logging Symposium, 26–29.##
Soto, R., Garcia, J.C., 2001. Permeability prediction using hydraulic flow units and hybrid soft computing systems. SPE 71455.##
Swanson, B.F. 1981. A simple correlation between permeabilities and mercury capillary pressures,   Journal of Petroleum Technology, 33: 2488–504.##
Szabo, F., Kheradpir, A., 1978.Permian and Triassic stratigraphy, Zagros basin, south-west Iran.  Journal of Petroleum Geology, 1: 57–82.##
Tang, H., Ji, H., 2006. Incorporation of spatial characteristics into volcanic facies and favorable reservoir prediction. SPE Reservoir Evaluation & Engineering, 9 (5): 565–573.##
Trask, P.D., 1932. Origin and Environment of Source Sediments of Petroleum (Houston, TX: Gulf Publishing Company)  323 pp.##
Vincent, B., Fleury, M., Santerre, Y., Brigaud, B. 2011. NMR relaxation of neritic carbonates: An integrated petrophysical and petrographicalapproach.Journal of Applied Geophysics, 74(1): 38-58.##
Ward Jr., J.H., 1963. Hierarchical grouping to optimize an objective function. Journal of the American Statistical Association, 48: 236–244.##
Wolff, M., Pelissier-Combescure, J., 1982. Faciolog, automatic electro-facies determination Society of Professional Well Log Analysts 23rd  annual logging symposium. Transactions Paper.##

Files

History

  • Receive Date: 01 March 2017
  • Revise Date: 03 July 2017
  • Accept Date: 04 December 2017

Share

How to cite

Statistics