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

机译:利用实验设计优化油井水泥浆的流变性能

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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℃. 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.
机译:本文提出了一种基于二阶中心复合响应面模型的统计设计方法,以预测结合了偏高岭土(MK),硅粉(SF),稻壳问(RHA)或粉煤灰的油井水泥(OWC)泥浆的流变特性。灰分(FA)。拟议的模型适用于MK,SF,RHA或FA与新一代基于多羧酸盐的高范围减水剂(PCH)一起使用的OWC部分替代水平,范围为5%至15%,剂量范围为0.25%至1.5%,以及在23至60℃的不同温度下使用。通过统计分析和验证实验,验证了模型的意义和有效性。回归模型用于分析混合物比例和温度对OWC浆料流变性的影响。考虑到在不同温度下添加辅助胶结材料(SCM),可以将统计设计用于优化流变特性,例如屈服应力和塑性粘度,并更好地理解关键混合物参数(例如减水剂的用量)之间的权衡以及使用的SCM级别。

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