Petrophysical Characteristics and Uncertainty Analysis Using Well Log Data


  • Omalsaad F. Hafad1 F. Hafad
  • Abdulaziz M. Abdulaziz2 M. Abdulaziz



Application of genetic algorithm, Centrifugal Pumps Maintenance, Preventive maintenance


In the present study, well logs data of 6 gas and oil wells from the Nile Delta (Qawasim and Abu Madi formations) and Western Desert (Bahariya formation) are investigated in details using Interactive Petrophysics (IP 3.6) software to examine the reservoir properties and characterize the reservoir architecture. In addition, uncertainty analysis was executed on the output petrophysical properties to account for the variations in the output values induced by random, systematic and model-based errors of the input data. The lithological and petrophysical analysis of log data from six wells showed that the Qawasim and Abu Madi formations are clean sandstone. Petrophysical analysis showed good porosity (22%-23.2%) in the pay zone of Qawasim and in Abu Madi (21%) formations. In Bahariya formation, the calculated porosity falls between 16% and 22% for the identified pay zones. The average water saturation of Abo Madhi Pay zones close to 36%, while Qawasim pay zones fall between 19.6 to 24.6 % and in Bahariya pay zones fall between 15.7% to 27.8 %. Typically, low average volume of clay (VCLAVG) reports in both Qawasim and Abu Madi pay zones that fall between 8 % and 12 %, and such value may markedly increase to approach 17.9% as reported in Bahariya zone of pay zones of WD-1 well. Normally, uncertainty and sensitivity analysis in the studied wells showed that in Qawasim formation the N/G is largely affected by clay volume cut-offs, Gamma ray clean, measured Gamma ray and Sw cut-offs. While porosity calculations were strongly affected by clean Gamma ray, measured Gamma ray and porosity cut-offs and hydrocarbon density. However, the major influences on Sw calculations are restricted to Archie parameters (m and n), Sw cut-offs, Gamma ray clean and deep resistivity.  Alternatively, clay volume showed a significant sensitivity to clean Gamma ray, measured Gamma ray, porosity cutoff, and clay volume cut-offs.


Rider, M.H. (1996), The Geological Interpretation of Well Logs. 2nd Ed, Gulf Pub Corp, Houston, ISBN-10: 0884153541, p. 280.

Serra, O. (1984), Fundamentals of Well Log Interpretation: 1, The Acquisition of Logging Data, Elsevier, Amsterdam, ISBN 0-444-42132-7 (U.S.: V. 1), p.423.

Adams, S.J. (2005), Quantifying Petrophysical Uncertainties. Society of Petroleum Engineers.

Moore, W.R., Ma, Y.Z., Urdea, J. and Bratton, T. (2011), Uncertainty analysis in well-log and petrophysical interpretations, in Y. Z. Ma and P. R. La Pointe, eds., Uncertainty analysis and reservoir modeling: AAPG Memoir 96, P. 17–28.

Hertz, D.B. (1964). Risk Analysis in Capital Investment, Harvard Business Review, 42, No.1, p. 95-106

Synergy web site (June 2010), http://

Schlumberger (2010), "Interactive Petrophysics Version 3.6 User’s Manual", Synergy Ltd., Ternan House, North Deeside Road, Banchory, Kincardineshire AB31 5YR, Scotland

John T. Dewan (1986), Open-Hole Nuclear Logging - State of the Art, SPWLA Twenty Seventh Annual Logging Symposium

Bertozzi, W., Ellis, D.V., and Wahl, J.S. (1981), the Physical Foundations of Formation Lithology Logging with Gamma Rays, Geophysics 46 (10), pp-1439-1455.

Dewan, J.T. (1983), Essentials of modern open-hole log interpretation, PennWell Books, Tulsa, 361p. ISBN-10: 0878142339

Theys, P. (1997), Accuracy – Essential information for a log measurement, SPWLA 38th Annual Logging Symposium, Paper V.




How to Cite

F. Hafad, O. F. H., & M. Abdulaziz, A. M. A. (2023). Petrophysical Characteristics and Uncertainty Analysis Using Well Log Data. International Journal of Engineering Research, 1(1), 77–91.