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     Research Journal of Applied Sciences, Engineering and Technology

    Abstract
2012(Vol.4, Issue:17)
Article Information:

Modified Johnson Model for Permeability Estimation in Oil Well Cement During Early Hydration

Syahrir Ridha, Sonny Irawan, Bambang Ariwahjoedi, Khairun Azizi Bt. Mohd. Azizli, Muhd Fadhil Nuruddin and Hilfan Khairy
Corresponding Author:  Syahrir Ridha 
Submitted: December 16, 2011
Accepted: January 08, 2012
Published: September 01, 2012
Abstract:
Permeability is believed to be one of the major factors contributing to the fluid infiltration. Failure to control this property, especially during early hydration, may lead to secondary cementing operation that requires additional cost or in worst case may damage the well. Some models have been successfully applied in relating the cement permeability to its porosity. However, this models rather impractical for field use since measured porosity must be established first. In this study, the measured electrical conductivity was used as a tool to extract permeability of Class G oil well cement at elevated pressure up to 3000 psi and temperature up to 65oC during the first 24 h of hydration. The relationship between permeability and normalized conductivity follows power law correlation. Neither the Katz-Thompson equation nor Johnson equation differs much from the measured result, but the latter is closer to the exact result. Better result was obtained once it is fitted to the measured permeability data which resulting the modified version of Johnson model. New modified model is satisfied to the measured permeability data generated from other cement samples.

Key words:  Electrical conductivity, pressure and temperature, oil well cement, permeability estimation, , ,
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Cite this Reference:
Syahrir Ridha, Sonny Irawan, Bambang Ariwahjoedi, Khairun Azizi Bt. Mohd. Azizli, Muhd Fadhil Nuruddin and Hilfan Khairy, . Modified Johnson Model for Permeability Estimation in Oil Well Cement During Early Hydration. Research Journal of Applied Sciences, Engineering and Technology, (17): 2920-2925.
ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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