Estimating the Lengthy Missing Log Interval Using Group Method of Data Handling (GMDH) Technique

Mohammed Ayoub; Ahmed Abdelhafeez Mohamed

doi:10.4028/www.scientific.net/AMM.695.850

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Estimating the Lengthy Missing Log Interval Using Group Method of Data Handling (GMDH) Technique
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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 695Estimating the Lengthy Missing Log Interval Using...

Estimating the Lengthy Missing Log Interval Using Group Method of Data Handling (GMDH) Technique

Abstract:

Estimation of well log properties is crucial in identifying the trends and the properties in oil and gas industry, which will enable firms to avoid problems during operation procedures. In this paper, Group Method of Data Handling (GMDH) technique is utilized to generate a generic model with superior prediction capabilities. NeuraLog^TM software is used in order to convert the scanned image logs into digit one that can be used by MATLAB code. Group Method of Data Handling is utilized to predict the same missing interval. An aggregate of 601 field data sets were utilized to create the model. These information sets were separated into training, cross validation and testing sets in the degree of 2:1:1. Trend analyses as well as graphical and statistical tools have been utilized in order to assess the model performance.

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Periodical:

Applied Mechanics and Materials (Volume 695)

Pages:

850-853

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.695.850

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Online since:

November 2014

Authors:

Mohammed Ayoub*, Ahmed Abdelhafeez Mohamed

Keywords:

Group Method of Data Handling, Missing Log Intervals, Well Log

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References

[1] Fertl, W. H. (1983, January). RP 4 Advances in Well Logging and Well Logging Interpretation. In 11th World Petroleum Congress. World Petroleum Congress.

Google Scholar

[2] Timur, A. (1982). Advances in well logging. Journal of Petroleum Technology, 34(06), 1-181.

Google Scholar

[3] Banchs, R. E., & Michelena, R. J. (2002). From 3D seismic atrributes to pseudo-well-log volumes using neural networks: Practical considerations. The Leading Edge, 21(10), 996-1001.

DOI: 10.1190/1.1518436

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[4] Saggaf, M. M., & Nebrija, L. (2003). Estimation of missing logs by regularized neural networks. AAPG bulletin, 87(8), 1377-1389.

DOI: 10.1306/03110301030

Google Scholar