During deepwater drilling operations, when influx gas invades the wellbore, gas hydrates may form through the combination of the gas with free water in the drilling fluid under favorable temperature and pressure conditions. This process can alter the physical properties and flow behavior of the wellbore fluid, potentially leading to safety incidents. To prevent natural gas hydrate formation, mitigate wellbore blockages caused by hydrates, and address the associated safety hazards, this study conducted laboratory experiments to investigate hydrate formation and remediation under multiple deepwater drilling conditions. The hydrate formation boundaries for four different drilling fluid systems—seawater-based bentonite mud, seawater polymer mud, Plus/KCl mud, and HEM mud—were determined for varying well depths and pressure–temperature conditions, and corresponding trend lines were fitted. Key results reveal that a higher carbon content promotes hydrate formation, and the phase equilibrium curves also reveal significant differences among the four drilling fluids. The hydrate aggregation states and blockage processes were clarified for three typical drilling scenarios: drilling, well killing, and drilling suspension. Hydrate formation risk is negligible during normal circulation but increases dramatically during well-killing operations, significantly shrinking the safe operational window. A comparative analysis identified that adding 1% P(M-VCL), a kinetic hydrate inhibitor, to the drilling fluid was the most effective solution, demonstrating superior performance in delaying hydrate nucleation and preventing agglomeration. The study established a complete formation–inhibition–remediation approach for hydrate management in deepwater drilling, thereby enhancing operational safety and efficiency.

Shallow gas drilling in polar seas poses severe geological hazards, particularly unexpected eruptions that threaten platform safety and the marine environment. Accurate prediction of shallow gas occurrence and eruption risk is therefore essential for safe deep-water operations. However, previous studies seldom considered the coupled effects of gas pressure and pore-structure evolution on acoustic wave velocity, leading to deviations in hazard assessment. In this study, laboratory experiments and numerical simulations were conducted to clarify these mechanisms. Results revealed a non-monotonic relationship between porosity and P-wave velocity in shallow gas-bearing sediments: P-wave velocity decreases with increasing porosity at low porosity levels but increases beyond a critical threshold. This is attributed to changes in particle interactions and cementation that enhance the shear modulus. The inflection porosity for shallow gas (78%) highlights the diagnostic role of pore-structure evolution in predicting shallow gas distribution. A mathematical correlation between P-wave velocity and formation pressure was further established, and MP-PIC simulations showed that higher pressure coefficients significantly accelerate eruption rates, with a 0.1 increase in the pressure coefficient raising the instantaneous eruption velocity by 5.27 m³/min. Based on these findings, a quantitative evaluation method was developed to assess shallow gas hazard risk, providing engineering guidance for site selection and real-time risk prediction, and contributing to safer offshore drilling and ecological protection in polar environments.

In ultra-deep drilling environments, downhole measurement tools often fail or cannot be deployed due to extreme high-temperature and high-pressure (HPHT) conditions. Consequently, mud-logging data become one of the few reliable real-time information sources for evaluating drilling performance and identifying abnormal conditions. This study proposes a data-driven framework for automatic identification of drilling operation statuses using machine learning, with a particular focus on ultra-deep and HPHT wells. A support vector machine (SVM)-based classification workflow was established to recognize nine representative drilling operation statuses from mud-logging data. Through systematic model optimization, the proposed method achieved a classification accuracy of 91.33%. By incorporating a sliding window-based time-series optimization strategy, the overall accuracy was further improved to 95.22%, while the recognition accuracy of HPHT-related operations increased from 77.67% to 89.33%. These results demonstrate that the optimized model possesses strong adaptability and stability under extreme HPHT conditions. This study specifically targets HPHT environments with limited downhole data and incorporates time-series optimization to enhance model robustness. The proposed framework provides a reliable approach with potential for generalization for intelligent operation recognition in ultra-deep drilling, supporting real-time decision-making and improving operational safety and efficiency in challenging environments.

In deepwater oil and gas development, conventional well-by-well drilling and completion involve repeated equipment deployment, resulting in low efficiency. The Liza project in the Stabroek Block, Guyana, adopts a batch drilling and completion mode, significantly improving operational efficiency. However, inter-well towage of a suspended riser introduces challenges to riser integrity and safety. This study reviews key technologies in batch drilling and develops a mechanical model for riser hard hang-off using OrcaFlex 11.5 to assess the effects of wave height, wind speed and direction, and towing speed on riser stress and universal joint angular displacement. Simulations under representative Guyana conditions show that riser stress increases with wave height. The most critical scenario occurs when towing against the current with a following wind, where the maximum safe towing speed is 0.80 m/s, governed by angular displacement limits. Additionally, batch operations significantly reduce drilling and connection time and offer environmental benefits. These results provide guidance for optimizing deepwater batch drilling and ensuring towing safety.

The suction pile well construction technique is increasingly adopted in deepwater drilling projects. The soil–structure interaction mechanism during the penetration and installation of the wellhead suction pile in clay is complex. Given the critical demand for precise installation outcomes in engineering practice, the influence of penetration velocity on installation performance requires significant consideration. Through scale-model experimental methods, various penetration velocities were configured primarily by adjusting suction pump flow rates. The influences of these velocities on penetration resistance, penetration depth, and related metrics were systematically assessed. A case study was conducted based on the engineering parameters of a wellsite in the South China Sea. A theoretical algorithm for WSP penetration resistance was developed and subsequently refined through experimental data. Coefficient optimization was established via theoretical assessment of strain-rate dependency and experimental data calibration. The optimized algorithm demonstrated strong agreement with field measurements, achieving a coefficient of determination ($R^2$) exceeding 0.9. Compared to conventional theoretical approaches, it incorporated explicit consideration of penetration velocity. The analysis indicates that in soft clay, the penetration resistance of wellhead suction piles exhibits significant sensitivity to penetration rate, increasing with higher velocities. The influence of penetration rate on penetration depth is relatively weak. This computational approach offers design guidance for installation procedures and enables the implementation of the suction pile well construction mode in the South China Sea.

The deep formations of the Yingqiong Basin are situated in a high-temperature and high-pressure (HTHP) environment, characterized by a narrow formation pressure window and consequently high operational risks. Accurate prediction of Equivalent Circulating Density (ECD) is crucial for wellbore stability control and well control safety during the drilling of extended-reach wells (ERWs) in this block. Existing calculation methods fail to account for the errors in well depth and true vertical depth (TVD) measurements caused by drill string buckling, which affect the ECD calculation. Therefore, to achieve precise ECD control, this study addresses the HTHP characteristics of ERWs in the Yingqiong Basin. It takes into consideration the variations in drilling fluid performance parameters, the influence of cuttings, and the well depth/TVD measurement errors induced by drill string buckling. On this basis, the traditional ECD calculation model is modified, and a set of ECD calculation models tailored to ERWs in the Yingqiong Basin is established. This model aims to meet the requirements for fine ECD control in drilling operations within the block and reduce operational risks. By comparing the error rates between the prediction results of the traditional ECD calculation model and those of the proposed model in this study, using the on-site measured ECD data from Well LD10-X-X in the Yingqiong Basin, the results demonstrate that for HTHP ERWs in the Yingqiong Basin, incorporating the well depth and TVD measurement errors caused by drill string buckling can enhance the accuracy of ECD prediction.