The accurate prediction of static formation temperature (SFT) is essential for ensuring safety and efficiency in ultra-deep well drilling operations. Excessive downhole temperatures (>150 °C) can degrade drilling fluids, damage temperature-sensitive tools, and pose serious operational risks. Conventional methods for SFT determination—including direct measurement, temperature recovery inversion, and artificial intelligence models—are often limited by post-drilling data dependency, insufficient spatial resolution, high computational costs, or a lack of adaptability to complex wellbore geometries. In this study, we propose a new pseudo-3D Kriging interpolation framework that explicitly incorporates real wellbore trajectories to improve the spatial accuracy and applicability of pre-drilling SFT predictions. By systematically optimizing key hyperparameters (θ = [10, 10], lob = [0.1, 0.1], upb = [20, 200]) and applying a grid resolution of 100 × 100, the model demonstrates high predictive fidelity. Validation using over 5.1 million temperature data points from 113 wells in the Shunbei Oilfield reveals a relative error consistently below 5% and spatial interpolation deviations within 5 °C. The proposed approach enables high-resolution, trajectory-integrated SFT forecasting before drilling with practical computational requirements, thereby supporting proactive thermal risk mitigation and significantly enhancing operational decision-making on ultra-deep wells.

During ultra-deep well drilling, the bottomhole circulating temperature (BHCT) can easily exceed 150 °C, causing a series of problems such as drilling-fluid degradation, downhole instrument failure, and intensified well-control risks. Conventional surface-cooling methods experience sharply diminishing effectiveness under deep well conditions, while an insulated drill-pipe (IDP) offers good engineering feasibility as a passive cooling technique. However, existing studies lack a transient wellbore-formation coupled model validated by field data, and the influence patterns and interaction mechanisms of key parameters of the insulation coating under varying well depths remain unclear. Therefore, this study integrates a thermal-resistance representation into a transient wellbore-formation heat-transfer framework to characterize the insulation effect via an overall heat-transfer coefficient. Based on this framework, the cooling mechanism is systematically investigated from two perspectives: heat-absorption rate and cumulative blocked heat. Based on this model, the cooling mechanism is systematically investigated from two perspectives: heat-absorption rate and cumulative blocked heat. The results show that a 2000 m IDP section reduces BHCT from 161.81 °C (with a conventional drill-pipe, CDP) to 144.15 °C after 50 h of circulation. This yields an additional cooling of 17.66 °C and a cumulative blocked heat of 180.03 GJ. Parameter analysis further shows that lower thermal conductivity, longer coating length, and placement 200–400 m above the bottomhole enhance cooling, whereas coating thickness exhibits a marginal benefit threshold of 1 mm. More importantly, Sobol’ global sensitivity analysis reveals a distinct evolution of the dominant parameter controls with increasing well depth: at 6000 m measured depth (MD), coating length is the absolute governing factor; at 8000 m, coating position and length become equally important; at 10,000 m, the coupling between thermal conductivity and length emerges as critical; and at 12,000 m, thermal conductivity, thickness, position, and length jointly determine the cooling performance. This evolutionary pattern provides a depth-dependent priority framework for IDP parameter design, offering clear guidance for engineering application across varying well depths.