Optimization of rheological properties of oil well cement slurries using experimental design

This paper proposes a statistical design approach based on a second order central composite response surface model to predict the rheological properties of oil well cement (OWC) slurries incorporating metakaolin (MK), silica fume (SF), rice husk ask (RHA) or fly ash (FA). The proposed models are for OWC partial replacement levels ranging from 5 to 15% by MK, SF, RHA or FA used along with a new generation polycarboxylate-based high-range water reducing admixture (PCH) at dosages ranging from 0.25 to 1.5% and at different temperatures ranging from 23 to 60°C. The significance and validity of the models were confirmed by statistical analysis and verification experiments. The regression models were used to analyze the influence of the mixture proportion as well as temperature on the rheological properties of OWC slurries. The statistical design can be applied to optimize rheological properties such as yield stress and plastic viscosity considering the addition of supplementary cementitious materials (SCMs) at different temperatures, and to gain a better understanding of trade-offs between key mixture parameters such as the superplasticizer dosage and the level of SCMs used.