Arabian Journal of Geosciences

, Volume 8, Issue 12, pp 10497–10508 | Cite as

Prediction of permeability anisotropy using Dar-Zarrouk parameters of deep resistivity logs: a case study in the northern Western Desert of Egypt

Original Paper
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Abstract

This study is a trial to predict the relationship between the formation resistivity data and some petrophysical properties of rocks in Tut and Khalda oil fields at the northern Western Desert, Egypt. First, the deep resistivity (deep laterolog (LLD)) and gamma ray (GR) logs are smoothed by a linear combination of simple fitting functions that satisfy the smoothness criteria, and consequently the behavior of both logs can be simulated. Next, the smoothed log data are divided into branches, where high and frequent excursions in GR and LLD logs occur. In subsequent steps, the Dar-Zarrouk parameters are calculated and followed by a smoothing process for each branch. Based on a visual inspection of these parameters with effective porosity logs, the Dar-Zarrouk parameters are divided into zones and then interpreted in terms of shale content and the potentiality of the two oil fields. The permeability trend observed in core samples showed that the calculated parameters provide an adequate qualitative prediction for the petrophysical properties including the overall permeability trends. Despite the fact that the predicted permeability trends in Khalda oil field coincides with those measured from core samples, a weak correlation is observed, which can be attributed to the reservoir heterogeneity with dominance of laminated and dispersed shale and/or iron oxides. The potentiality of the proposed method lies in its simplicity, requiring only GR, LLD, and effective porosity logs. However, it would be more meaningful if the above method is tested in areas with diverse geological environment.

Keywords

Dar-Zarrouk parameters Well logging Petrophysical properties Egypt 
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Notes

Acknowledgments

A part of this paper was presented at the Istanbul International Conference and Oil and Gas Exhibition, Istanbul, Turkey, 17–19 September, 2012. The first author (MA) would like to express appreciation to Prof. A.T. Başokur for providing his software and for his support. We wish to thank Prof. A. Ghonemi and Prof. Kh. Gemail for their careful review of the manuscript, which has improved the readability of the text.

References

  1. Anselmetti FS, Eberli GP (1999) The velocity-deviation log: a tool to predict pore type and permeability trends in carbonate drill hole from sonic and porosity or density logs. AAPG Bull 83(3):450–466Google Scholar
  2. Asquith GB, Gibson CR (1997) Basic well log analysis for geologists. AAPG, Tulsa, 215 ppGoogle Scholar
  3. Attwa M (2012) Field application “data processing, processing and interpretation”. In: Attwa M (ed) Electrical methods “practical guide for resistivity imaging and hydrogeophysics”. LAP LAMBERT. Academic Publishing GmbH and Co. KG, Saarbrücken, pp pp 70–pp 98Google Scholar
  4. Attwa M, Günther T (2013) Spectral induced polarization measurements for predicting the hydraulic conductivity in sandy aquifers. Hydrol Earth Sys Sci (HESS) 17:4079–4094CrossRefGoogle Scholar
  5. Attwa M and Nabih M (2012) Using the deep resistivity log to identify the permeability trends: case studies in the Western Desert, Egypt. Istanbul International Geophysical Conference and Oil & Gas Exhibition, Istanbul, Turkey, extended abstracts, 17-19 September, Reservoir Characterization (RC) topic, p 216Google Scholar
  6. Attwa M, Günther T, Grinat M, Binot F (2009) Transmissivity estimation from sounding data of Holocene tidal flat deposits in the North Eastern part of Cuxhaven, Germany. 15th Annual International Meeting, EAGE, expanded abstracts, p 29Google Scholar
  7. Attwa M, Akc I, Basokur A, Günther T (2014a) Structure-based geoelectrical models derived from genetic algorithms: a case study for hydrogeological investigations along Elbe River coastal area, Germany. J Appl Geophys 103:57–70CrossRefGoogle Scholar
  8. Attwa M, Basokur A, Akca I (2014b) Hydraulic conductivity estimation using direct current (DC) sounding data: a case study in East Nile Delta, Egypt. Hydrogeol J 22:1163–1178. doi: 10.1007/s10040-014-1107-3 CrossRefGoogle Scholar
  9. Başokur AT (1999) Automated 1-D interpretation of resistivity soundings by simultaneous use of the direct and iterative methods. Geophys Prospect 47:149–177CrossRefGoogle Scholar
  10. Bateman RM (1985) Log quality control. Boston International Human Resources Development Corporation, Boston, p 398Google Scholar
  11. Bhattacharya PK, Patra HP (1968) Direct current electrical sounding. Elsevier, Amsterdam, p 135Google Scholar
  12. Campbell DL (1977) Model for estimating electric macroanisotropy coefficient of aquifers with horizontal and vertical fractures (short note). Geophysics 42:114–117CrossRefGoogle Scholar
  13. Christensen NB (2000) Difficulties in determining electrical anisotropy in subsurface investigations. Geophys Prospect 48:1–19CrossRefGoogle Scholar
  14. Daniels JJ, Keys WS (1990) Geophysical well logging for evaluating hazardous waste sites. In: Ward SH (ed) Geotechnical and environmental geophysics, Vol. 1, Review and Tutorial. Society of Exploration Geophysicists, pp 263–285Google Scholar
  15. Danielsen BE, Madsen HB (2013) Resistivity logging as a tool for identifying initial weathering in crystalline rocks. Near Surface Geophys 11(3):353–362. doi: 10.3997/1873-0604.2012065 Google Scholar
  16. Desbrandes R (1968) Théorie et interprétation des diagraphies. Publications de l’ Institut Franςais du Pétrole, 545 ppGoogle Scholar
  17. Dewan JT (1983) Essentials of modern open-hole log interpretation. PennWell Books (PennWell Publishing Company), Tulsa, Oklahoma, 361 ppGoogle Scholar
  18. Ellis DV, Singer JM (2007) Well logging for earth scientists, 2nd edn. Springer, GermanyCrossRefGoogle Scholar
  19. El-M Shokir EM, Alsughayer AA, Al-Ateeq A (2006) Permeability estimation form well log responses. J Can Pet Technol 45(11):41–46Google Scholar
  20. Ernstson K (2006) Magnetic, geothermal, and radioactivity methods. In: Kirsch R (ed) Groundwater geophysics—a tool for hydrogeology. Springer pp 275–320Google Scholar
  21. Flathe H (1955) Possibilities and limitations in applying geoelectrical methods to hydrogeological problems in the coastal area of northwest Germany. Geophys Prospect 3:95–110CrossRefGoogle Scholar
  22. Frohlich RK (1974) Combined geoelectrical and drill-hole investigations for detecting freshwater aquifers in northwestern Missouri. Geophysics 39:340–352CrossRefGoogle Scholar
  23. Hantar G (1990) North Western Desert. In: Said R (ed) The geology of Egypt. Balkema Publishers, pp 293-319Google Scholar
  24. Keller GV (1982) Electrical properties of rocks and minerals: In: Carmichael RS (ed.), Handbook of physical properties of rocks. CRC PressGoogle Scholar
  25. Khalil MH (2006) Geoelectric resistivity sounding for delineating salt water intrusion in the Abu Zenima area, West Sinai, Egypt. J Geophys Eng 3:243–251CrossRefGoogle Scholar
  26. Khalil MH (2012) Reconnaissance of freshwater conditions in a coastal aquifer: synthesis of 1D geoelectric resistivity inversion and hydrogeological analysis. Near Surface Geophys 10:427–441CrossRefGoogle Scholar
  27. Kosinski WK (1978) Geoelectrical studies for predicting aquifer properties in southern Rhode Island. Dissertation, University of Rhode Island, KingstonGoogle Scholar
  28. Kosinsky WK, Kelly WE (1981) Geoelectric soundings for predicting aquifer properties. Groundwater 19:163–171CrossRefGoogle Scholar
  29. Levorsen, AI (1967) Geology of petroleum. W.H. Freeman and San Francisco, pp 350Google Scholar
  30. Lima OAL, Niwas S (2000) Estimation of hydraulic parameters of shaly sandstone aquifers from geoelectrical measurements. J Hydrol 235:12–26CrossRefGoogle Scholar
  31. Maillet R (1947) The fundamental equations of electrical prospecting. Geophysics 12:529–556CrossRefGoogle Scholar
  32. Mohaghegh S, Balan B, Ameri S (1997) Permeability determination from log well data. SPE Form Eval 12(3):170–174. doi: 10.2118/30978-PA CrossRefGoogle Scholar
  33. Moore WR, Zee ma Y, Bratton T (2011) uncertainty analysis in well-log and petrophysical interpretations. In: Ma YZ, La Pointe PR, (eds) Uncertainty analysis and reservoir modeling. AAPG Memoir 96, pp 17–28Google Scholar
  34. Moustafa AR, Saoudi A, Moubasher A, Ibrahim IM, Molokhia H, Schwartz B (2003) Structural setting and tectonic evolution of the Bahariya Depression, Western Desert, Egypt. GeoArabia Gulf PetroLink, Bahrain 8(1) pp 34Google Scholar
  35. Niwas S, Celik M (2012) Equation estimation of porosity and hydraulic conductivity of Ruhrtal aquifer in Germany using near surface geophysics. J Appl Geophys 84:77–85CrossRefGoogle Scholar
  36. Niwas S, Singhal DC (1981) Estimation of aquifer transimissivity from Dar-Zarrouk parameters in porous media. J Hydrol 50:393–399CrossRefGoogle Scholar
  37. Niwas S, Singhal DC (1985) Aquifer transmissivity of porous media from resistivity data. J Hydrol 82:143–153CrossRefGoogle Scholar
  38. Oteri AU (1981) Geoelectric investigation of saline contamination of chalk aquifer by mine drainage water at Tilmanstone, England. Geoexploration 19:179–192CrossRefGoogle Scholar
  39. Pfannkuch HO (1963) Contribution a l’ etude des deplacements de fluiedes miscibles dans un milieu poreux. Rev Inst Fr Petrole 18:215–270Google Scholar
  40. Purvance D, Andricevic R (2000) Geoelectrical characterization of the hydraulic conductivity field and its spatial structure at variable scales. Water Resource 36:2915–2924CrossRefGoogle Scholar
  41. Saluja V, Niwas S (2007) Estimation of permeability of shaly sand from induced polarization relaxation time spectra. J Indian Geophys Union 11(3):135–142Google Scholar
  42. Santini R, Zambrano R (1981) A numerical method of calculating the kernel function from Schlumberger apparent resistivity data. Geophys Prospect 29:108–127CrossRefGoogle Scholar
  43. Schlumberger (1984) Resistivity measurement tools. Schlumberger pp 39Google Scholar
  44. Schlumberger (1995) Well evaluation conference of Egypt. Schlumberger Technical Editing Services, ChesterGoogle Scholar
  45. Singh CL, Singh SN (1970) Some geophysical investigations for potential groundwater in part of Azamgrah area. Pure Appl Geophys 82:270–285CrossRefGoogle Scholar
  46. Soliman SM, El-Badry OA (1980) Petrology and tectonic framework of the Cretaceous, Bahariya Oasis. Egypt J Geol Soc U AR 27(1-2):p 1153Google Scholar
  47. Sturrock JT, Lesmes D, Morgan FD (1999) Permeability estimation using spectral induced polarization measurements. Proceedings of the Symposium on the Application of Geophysics to Engineering and Environmental Problems (SAGEEP), March 14-18, Oakland, pp 409-415Google Scholar
  48. Suau, J, Grimaldi P, Poupon, A and Souhaite, G (1972) DuaILaterolog-Rxo tool. SPE-AIME, 47th Ann. Meet., (San Antonio), paper SPEGoogle Scholar
  49. Tong M, Tao H (2007) Experimental study of induced polarization relaxation time spectra of shaly sands. J Pet Sci Eng 59:239–249CrossRefGoogle Scholar
  50. Tong M, Tao H (2008) Permeability estimating from complex resistivity measurement of shaly sand reservoir. Geophys J Int 173:733–739CrossRefGoogle Scholar
  51. Tong MS, Wang WN, Li L, Jiang YZ, Shi DQ (2004) Estimation of permeability of shaly sand reservoir from induced polarization relaxation time spectra. J Petrol Sci Eng 45(1-2):1–10CrossRefGoogle Scholar
  52. Tong M, Li L, Wang W, Jiang Y (2006) Determining capillary-pressure curve, pore-size distribution, and permeability from induced polarization of shaley sand. Geophysics 71(3):N33–N40CrossRefGoogle Scholar
  53. Weller A, Nordsiek S, Debschütz W (2010) Estimation permeability of sandstone samples by nuclear magnetic resonance and spectral-induced polarization. Geophysics 75(6):E215–E226CrossRefGoogle Scholar
  54. Weller A, Slater L, Binely A, Nordsiek S, Xu S (2015) Permeability prediction based on induced polarization: insights from measurements on sandstone and unconsolidated samples spanning a wide permeability range. Geophysics 80(2):D161–D173CrossRefGoogle Scholar
  55. Zisser N, Kemna A, Nover G (2010) Relationship between low-frequency electrical properties and hydraulic permeability of low-permeability sandstones. Geophysics 75(3):E131–E141CrossRefGoogle Scholar
  56. Zohdy AA (1974) Use of Dar Zarrouk curves in the interpretation of vertical electrical sounding data. U.S. Geological Survey Bulletin 1313-D: p 41Google Scholar

Copyright information

© Saudi Society for Geosciences 2015

Authors and Affiliations

  1. 1.Faculty of Science, Geology DepartmentZagazig UniversityZagazigEgypt

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