期刊
JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING
卷 135, 期 -, 页码 50-58出版社
ELSEVIER
DOI: 10.1016/j.petrol.2015.08.015
关键词
Water-to-cement ratio; Yield stress; Maximum shear stress; Curing time; Electrical resistivity; Models
资金
- Center for Innovative Grouting Materials and Technology (CIGMAT) at the University of Houston, Houston, Texas
Behavior of smart oil well cement with varying water-to-cement ratio (w/c) was investigated. The oil well cement (Class H) was modified with 0.1% conductive filler (CF) to make the cement very sensing and smart and the rheological properties and piezoresistivity behavior with water-to-cement ratios of 0.38, 0.44 and 0.54 at two different temperatures (25 degrees C and 85 degrees C) were investigated. Electrical resistivity was identified as the sensing and monitoring property for the smart cement. The shear thinning behavior of the smart cement slurries have been quantified using the new hyperbolic rheological model and compared with another constitutive model with three material parameters, Herschel-Bulkley model. The results showed that the hyperbolic model predicated the shear thinning relationship for the smart cement slurries very well. The hyperbolic rheological model has a maximum shear stress limit were as the other model did not have a limit on the maximum shear stress. The electrical resistivity changes of the hydrating cement was influenced by the water-to cement ratio. The minimum electrical resistivity of the cement slurry was linearly related to the water-to-cement (w/c) ratio of the cement slurry and it decreased with increased w/c ratio. Additional of 0.1% CF also increased the 28 day compressive strength of the smart cement by over 10%. The piezoresistivity of smart cement at peak compressive stress was over 700 times higher than the unmodified cement which was less than 0.7%, making the smart cement very highly sensing. The piezoresistivity of the smart cement was influenced by the curing time and w/c ratio. A nonlinear piezoresistivity model has been developed to predict the compressive stress - electrical resistivity relationship for the smart cement. (C) 2015 Elsevier B.V. All rights reserved.
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