Multi-objective optimization and performance investigation of cementing materials with high thermal conductivity based on response surface methodology

Objective Geothermal energy has emerged as a strategic clean energy for the low-carbon transformation of the world's energy mix. Correspondingly, its efficient exploitation and utilization are crucial to the early achievement of the goals of peak carbon dioxide emissions and carbon neutrality. For geothermal resource exploitation, the thermal conductivity of cementing structures determines the efficiency of heat transfer from strata to geothermal well casings, establishing it as a key factor influencing the efficiency of geothermal energy extraction. Therefore, the research and development of cementing materials with high thermal conductivity can provide robust support for efficient geothermal resource exploitation.

Methods  The top three factors influencing the thermal conductivity of cementing materials with high thermal conductivity were determined using orthogonal experiments with water-cement ratio and the contents of graphite, iron powder, silicon carbide, and quartz sand as the factors. Furthermore, 3-factor and 3-level experiments were designed using response surface methodology (RSM), and regression models with thermal conductivity, compressive strength, and fluidity as response values were established. Accordingly, the impacts of various factors and their interactions on the performance of the cementing materials with high thermal conductivity were analyzed. Finally, the optimal mixing ratios of the cementing materials were determined using multi-objective optimization.

Results and Conclusions Orthogonal experiment results indicate that the effects of factors influencing the thermal conductivity of cementing materials decreased in the order of graphite content (10%), water-cement ratio (0.57), iron powder content (30%), quartz sand content (30%), and silicon carbide content (10%). The regression models of thermal conductivity, compressive strength, and fluidity, developed with water-cement ratio, graphite content, and iron powder content as independent variables using RSM, yielded coefficients of determination (R²) of 0.986 7, 0.984 8, and 0.973 7, respectively, demonstrating high reliability of the models. Analysis of variance (ANOVA) results indicates that graphite content, water-cement ratio, and iron powder content produced extremely significant impacts on the thermal conductivity (P<0.01), followed by the interactions of water-cement ratio with graphite content and iron powder content (P <0.05). Water-cement ratio had extremely significant impacts on the compressive strength, while graphite content, iron powder content, and the interaction between water-cement ratio and graphite content exerted significant impacts on it. Furthermore, water-cement ratio and graphite content produced extremely significant impacts on the fluidity. Multi-objective optimization reveals that the optimal mixing ratios of cementing materials with high thermal conductivity consisted of a water-cement ratio of 0.573, a graphite content of 9.95%, and an iron powder content of 28.62%. Under the optimal mixing ratios, the thermal conductivity, compressive strength, and fluidity were 3.136 W/(m·K), 17.53 MPa, and 22.1 cm, respectively, with deviations of less than 5% against the predicted values. The optimal mixing ratios and regression models proposed in this study provide a reliable basis for the engineering application of geothermal well-oriented cementing materials with high thermal conductivity.