Purpose Geothermal energy, as a strategic clean energy for the global energy structure's low-carbon transformation, plays a critical role in achieving the "double carbon" goals. In geothermal resource development, the thermal conductivity of cementing structures determines the heat transfer efficiency from rock formations to the outer casing of geothermal wells, making it a key factor influencing efficient geothermal extraction. Therefore, the development of high thermal conductivity cementing materials can provide essential support for the efficient exploitation of geothermal resources.

Method Taking water-cement ratio, graphite content, iron powder content, silicon carbide content, and quartz sand content as the main experimental factors, orthogonal experiments were conducted to identify the 3 most significant factors affecting the thermal conductivity performance of high thermal conductivity cementing materials. Further, a 3-factor and 3-level response surface experiment was designed using Response Surface Methodology (RSM) to establish a regression model with thermal conductivity, compressive strength, and flowability as response values. The effects of each factor and their interaction effects on the performance of high thermal conductivity cementing materials were analyzed, and finally, the optimal mix proportion of such materials was determined through multi-objective optimization.

Results and Discussion  Orthogonal test results indicated that the factors influencing thermal conductivity in descending order of significance and their optimal levels were: graphite content (10%), water-cement ratio (0.57), iron powder content (30%), quartz sand content (30%), and silicon carbide content (10%). A quadratic polynomial regression model was constructed using RSM, with water-cement ratio, graphite content, and iron powder content as variables and thermal conductivity, compressive strength, and flowability as objectives. The coefficients of determination R²were 98.67%, 98.48%, and 97.37%, respectively, demonstrating high model reliability. ANOVA results from RSM showed that graphite content, water-cement ratio, and iron powder content had extremely significant effects on thermal conductivity (P<0.01), while interactions between water-cement ratio and graphite content, and water-cement ratio and iron powder content were significant (P<0.05). Water-cement ratio had an extremely significant effect on compressive strength, with graphite content, iron powder content, and the water-cement ratio-graphite content interaction also showing significant impacts. Water-cement ratio and graphite content had extremely significant effects on flowability. Multi-objective optimization yielded an optimal mix of water-cement ratio 0.573, graphite content 9.95%, and iron powder content 28.62%, with predicted values of thermal conductivity (3.237 W/(m·K)), compressive strength (16.77 MPa), and flowability (21.5 cm). The errors between predicted and laboratory-verified results were less than 5%. Consequently, the proposed model and optimal proportion offer a robust foundation for the practical application of high thermal conductivity cementing materials in geothermal engineering.