Zhiqiang Hu

Shallow free gas trapped within or beneath polar permafrost can be destabilized by drilling-induced thermal and pressure perturbations, but its acoustic response is difficult to separate from variations in lithology and freezing state. This study develops a saturation-constrained, Biot–Gassmann-informed semi-empirical screening model for a four-phase representative volume containing a mineral skeleton, pore ice, unfrozen water, and methane gas. The classical poroelastic equations establish the governing physical dependencies, whereas the reported P-wave velocity is calculated with a stress-sensitive corrected travel-time relation because permeability, tortuosity, ice morphology, and gas-patch dimensions are unavailable. A conditional freezing degree ensures that ice, water, and gas saturations remain non-negative and sum to unity. At 10 kHz, increasing gas saturation from 0 to 0.20 reduced velocity from 2893 to 1879 m/s and increased attenuation from 3.87 to 37.29 dB/m. At 5% gas saturation, increasing pore pressure from 0.1 to 5.5 MPa reduced velocity by 20.7% and attenuation by 89.3%. An 8000-realization analysis sampling 17 uncertain inputs identified gas saturation as the strongest negative correlate with velocity (rho = −0.659) and the dominant positive correlate with attenuation (rho = 0.851); freezing degree was the strongest positive velocity correlate (rho = 0.565). Ablation showed that phase substitution, the empirical ice-cementation correction, and their interaction contributed 908, 469, and 284 m/s, respectively, to the 1662 m/s thawed-to-frozen velocity increase. The attenuation formulation uses calibrated screening coefficients and a frequency-squared surrogate at 10 kHz; transfer to seismic or ultrasonic frequencies requires recalibration. The model is therefore intended for relative anomaly screening and predrilling risk ranking rather than stand-alone saturation inversion.

This study utilizes a large-scale numerical simulation model to investigate the hydrodynamic behavior and particle transport characteristics of gas–liquid–solid three-phase flow in vertical wellbores featuring multi-source confluence and curved geometries. Simulation results indicate that increasing flow velocity shifts the dominant control mechanism from surface tension to inertial forces, transitioning the flow pattern from slug flow to churn flow. In curved pipe sections, centrifugal phase separation and geometric shielding effects cause significant flow asymmetry and maintain large bubble stability at the inner wall. Additionally, the multi-inlet structure induces shear rate gradients that result in the spatial coexistence of two distinct bubble scales. Furthermore, localized gas concentrations exceeding 70% at the upper inlet can trigger severe gas-locking phenomena and intense pressure pulsations.

To address the large deviation in annular trapped pressure prediction during testing and production stages of deepwater high-temperature and high-pressure wells, conventional models neglect the elastic uplift effect of the wellhead. This study overcomes the limitations of the plane strain model and establishes a three-dimensional thermos–hydro–mechanical coupled annular pressure prediction model based on the longitudinal stiffness constraint of the subsea wellhead. The deepwater wellbore–formation system is treated as a composite elastic structure. A generalized plane strain assumption is introduced to define the elastic boundary conditions and longitudinal segmentation characteristics of the wellhead. Based on generalized Hooke’s law, the three-dimensional stress–strain constitutive equation of casing is modified. A displacement model incorporating axial–radial coupling is derived, and an equivalent longitudinal stiffness coefficient of the wellhead is introduced. A coupled axial force equilibrium equation and a three-dimensional annular volume compatibility equation are established. Considering multi-annulus coupling, a volume compatibility matrix equation is formulated, and a successive approximation iterative algorithm with a relaxation factor is developed. Using a deepwater high-temperature, high-pressure gas well in the South China Sea as a case study, the effects of wellhead stiffness, free section length, and annular temperature rise on annular pressure are investigated via a single-variable method and compared with traditional rigid models. Results show that the subsea wellhead exhibits elastic uplift behavior. Its longitudinal stiffness has a reverse S-shaped nonlinear influence on annular pressure. Increasing the free section length significantly reduces annular pressure. The proposed model predicts values 17–21% lower than traditional rigid models, providing a more realistic representation of annular pressure evolution. The findings offer theoretical support and engineering guidance for deepwater well integrity design and annular pressure risk management.

To address the failure risks associated with long-term service of subsea Christmas tree-wellhead systems under the complex marine environment of the South China Sea, a multi-factor coupled mechanical analysis method is proposed to evaluate the system’s mechanical characteristics and ensure the safety of deepwater oil and gas production. A dynamic model of lateral vibration under seismic loading is established, considering the combined effects of earthquakes, ocean currents, and seabed soil resistance. Based on the actual operating parameters of a well in the Lingshui area of the South China Sea, a three-dimensional finite element model of the subsea Christmas tree-wellhead assembly was developed in ABAQUS 2023. The combined effects of ocean currents, seismic loading, and corrosion over long-term service were simulated to compute and analyze the distributions of stress, bending moment, and associated failure risk. The results indicate that, under a once-in-a-century current combined with seismic waves of intensity V–VI, the system risk remains controllable. However, when the seismic intensity exceeds level VII, the maximum stress and bending moment reach 324.9 MPa and 6.02 MN·m, respectively, surpassing the allowable limits for an X56-grade surface conductor. Considering corrosion effects over a 25-year service life, the extreme stress values increase by 1–5% while the bending moment increases slightly; corrosion significantly amplifies the system’s failure risk. An analysis of the mudline burial height of the subsea wellhead during long-term service shows that, within a range of 1–7 m, variations in system loading are minimal. Based on the mechanical characteristics analysis, it is recommended that the design of subsea Christmas trees and wellheads incorporate regional seismic history, specify X56-grade surface conductors to mitigate corrosion effects, and install leakage-monitoring devices at critical locations to ensure the long-term service safety of the subsea Christmas tree-wellhead system.

Sinusoidal buckling of drill strings will be easily caused during drilling process of extended-reach horizontal wells due to the factors such as excessive well length and larger friction torque, which will cause measurement errors of well depth and vertical depth and furthermore influence the accurate calculation of ECD. We have corrected the traditional ECD calculation model, considered the measurement errors of well depth and vertical depth caused by the sinusoidal buckling of drill strings, and established a set of equivalent circulating density (ECD) calculation model suitable for extended-reach horizontal wells to meet the requirements for fine ECD control during the drilling operation. We have combined the data from an extended-reach horizontal well in the East China Sea and compared the ECD data obtained from the recorded stand pipe pressure with the prediction results from Landmark commercial software、the model in this work and the conventional model. Results show that the prediction results by the model in this work are closest to the recorded values when drill string sinusoidal buckling occurs. Besides, the ECD value predicted by the model considering the measurement errors of well depth and vertical depth caused by the sinusoidal buckling of drill strings is smaller due to the factor that the length of drill strings with sinusoidal buckling is larger than the actual well depth. With the identical case well data, the larger the sinusoidal buckling degree of downhole drill strings, the smaller the predicted ECD value. The model can reduce risks for drilling operations of extended-reach horizontal wells and provide more accurate reference data for their well control operations.

The Arctic region is rich in oil and gas resources and has great potential for development. It has become a new hot spot for international development. However, the harsh climatic and geological conditions and fragile ecosystems in the Arctic region put forward stringent technical requirements for oil and gas development. Polar permafrost has an impact on the growth of plant roots and the absorption of water. When drilling activities are carried out, the permafrost layer may be broken, resulting in the erosion of polar soil and disorder of the water balance, thus affecting local vegetation and ecosystems. Moreover, the legal system of polar environmental protection is lacking, and it is necessary to form a perfect risk assessment method to improve the relevant laws and regulations. Therefore, it is very important to study the environmental risk identification technology for polar drilling. For polar drilling, it is necessary to establish a risk source classification and identification method for environmental pollution events. However, at present, it mainly faces the following challenges: poor polar environment, lack of monitoring data, and lack of a legal system for polar environmental protection. By systematically discussing risk identification technology, the application and applicable models of different types of risk evaluation methods are categorized and summarized, the advantages and disadvantages of different types of risk evaluation methods and their application effects are analyzed based on the unique environment of the polar regions, and then the development direction of the future environmental risk identification technology for polar drilling is proposed. In order to accelerate the development of polar drilling environmental risk identification technology, research should be focused on the following three aspects: ① Promoting the multi-dimensional integration of polar drilling environmental pollution index data, to make up for the short board of less relevant data in the polar region. ② Combining the machine modeling algorithm with risk evaluation of polar drilling environmental pollution to improve the scientificity and accuracy of the evaluation results. ③ Establishing a scientific and accurate polar drilling environmental pollution risk identification system to reduce pollution risk.

This study thoroughly investigates the complex origins of abnormal formation pressure in offshore oil and gas wells, taking the Rio del Rey Basin in Cameroon as a case study. Renowned for its abundant oil and gas resources, the area faces unique challenges in predicting overpressure due to its high-temperature and high-pressure reservoir characteristics. By quantitatively analyzing the main mechanisms such as undercompaction, high-temperature fluid expansion, and mud diapirism, the study addresses the complexities of overpressure prediction. This paper introduces an innovative analytical framework that combines hierarchical clustering algorithms with the LightGBM model. Further refined by the application of Bayesian optimization, the model intelligently adjusts hyperparameters to enhance predictive accuracy. Utilizing well logging data and applying machine learning techniques, the paper classifies and identifies different mechanisms causing abnormal pressures, achieving a model prediction accuracy of 0.942. The research findings highlight the predominant role of the undercompaction mechanism, accounting for approximately 70% of the abnormal high-pressure events in the study area. Fluid expansion and shale diapirism contribute smaller but significant proportions of 10% and 20%, respectively. These quantitative insights into the pressure mechanisms are vital for optimizing drilling operations and reducing risks in oil and gas exploration. The study’s hybrid approach, integrating geophysical analysis with advanced computational techniques, sets a precedent for future research. It provides new avenues for applying machine learning to understand complex geological phenomena in similar geological environments and makes a significant contribution to the strategic planning of hydrocarbon exploration and production activities.

Shale oil represents a relatively new form of unconventional oil and gas resource, and the extensive exploration and development of shale oil resources carry significant implications for China’s oil and gas supply and demand dynamics. At present, within the realm of low-maturity shale oil extraction technologies, the reservoir must be subjected to elevated temperatures ranging between 400 to 60 °C. Prolonged exposure of wellbores to such high temperatures can result in a substantial decrease in cement strength, the formation of microcracks due to cement cracking, and damage stemming from thermal stresses on the casing. Casing damage stands out as a prominent factor contributing to wellbore integrity failures and well shutdowns within the context of shale oil development. Given the limited natural energy reservoirs of shale oil formations, it becomes necessary to supplement the reservoir’s energy during the development process. Furthermore, shale oil exhibits high viscosity and poor flowability, and conventional water injection methods yield limited efficacy. This situation can induce significant shifts in the stress field and rock mechanical parameters, potentially activating specific formations and complicating the load dynamics on the casing. Consequently, the risk of failure increases. In light of these considerations, this study uses numerical simulations to study the integrity of high-temperature injection and production wellbores in shale oil and aims to encompass a comprehensive evaluation and analysis of the principal factors that influence casing damage, the fluctuations in thermal stress, and the yield strength of various steel grades of casings exposed to alternating stress conditions. Subsequently, this paper developed a model for simulating the temperature and pressure within shale oil and steam injection wellbores to support engineering design analysis. The research results indicate that the application of pre-stress results in a significant increase in stress at the casing pipe head while causing a noticeable decrease in stress within the pipe wall. When N80 casing is used, the entire casing experiences thermal stresses surpassing the casing’s yield limit. Stress concentration may arise at both ends of the external seal, potentially leading to casing contraction, shear failure, and, under non-uniform stress conditions, casing bending deformation. The temperature of steam injection significantly influences the temperature field of the casing wall, with stress values experiencing a marked reduction when the steam injection temperature decreases from 350 °C to 200 °C, underscoring the substantial impact of temperature on casing thermal stress. As the steam injection process advances along with injection-production cycles, shear stresses at the interface can exceed the bond strength, resulting in relative slippage between the cement and the casing. The bonding force between the wellbore and the cement primarily depends on the interface’s friction, particularly in the context of friction during wellhead lifting. This study endeavors to determine rational injection and production parameters under varying conditions, optimize completion methods, reduce casing damage, and extend the casing’s operational life; it aims to offer critical technical support for the safe and efficient development of shale oil resources.

In offshore drilling, accidents such as gas invasion, overflow, and kicks are unavoidable, and they can escalate into blowouts and other catastrophic events, resulting in casualties and significant economic losses. Therefore, ensuring drilling safety requires precise monitoring of gas invasion and overflow. Currently, most overflow monitoring methods used at drilling sites are based on threshold criteria. However, the monitoring parameters obtained during actual drilling operations often contain noise signals, which makes it challenging for threshold-based methods to achieve a balance between improving accuracy and minimizing false positives. This paper proposes a novel method called Pattern-Recognition-based Kick Detection (PRKD) for diagnosing overflow in offshore drilling. The PRKD method utilizes the overflow evolution process by integrating multiphase flow calculations, data filtering theory, pattern recognition theory, the Bayesian framework, and other theoretical models. By analyzing the shape and wave characteristics of the curves, PRKD effectively detects and monitors gas intrusion and overflow based on single parameters. Through case analysis, it is demonstrated that the proposed method achieves high precision in monitoring drilling overflow while maintaining a low false positive rate. By combining advanced computational techniques with pattern recognition algorithms, PRKD improves the accuracy and reliability of kick detection, enabling proactive responses to potential risks, protecting the environment and human lives, and optimizing drilling operations. The case analysis shows that by integrating the probabilistic information of pre-drilling kicks and various characteristic parameters, when the noise amplitude is less than 8 L/s, the PRKD model exhibits superior detection performance. Moreover, when the noise amplitude is 16 L/s, the PRKD model detects the continuous overflow approximately 200 s after the actual overflow occurs and predicts a 95.8% probability of overflow occurrence at the specified location, meeting the on-site requirements. The gas invasion monitoring method proposed in this paper provides accurate diagnostic results and a low false positive rate, offering valuable guidance for gas invasion monitoring in drilling operations.

In offshore drilling, accidents such as gas invasion, overflow, and kicks are inevitable, and they can escalate into blowouts and other catastrophic events that result in casualties and substantial economic losses. Therefore, maintaining drilling safety requires accurate monitoring of gas invasion and overflow. The majority of overflow monitoring methods currently utilized at drilling sites are threshold-based. However, monitoring parameters acquired during actual drilling operations frequently contain noise signals, making it difficult for threshold-based methods to strike a balance between improving accuracy and minimizing false positives. In this paper, Pattern Recognition-based Kick Detection (PRKD) is proposed as a novel method for diagnosing overflow in offshore drilling. This method utilizes the overflow evolution process by integrating multi-phase flow calculations, data filtering theory, pattern recognition theory, the Bayesian framework, and other theoretical models. The PRKD effectively detects and monitors gas intrusion and overflow based on single parameters by analyzing the shape and wave characteristics of the curves. The case analysis demonstrates that the proposed method for monitoring drilling overflow achieves high precision while maintaining a low false positive rate. By combining advanced computational techniques with pattern recognition algorithms, the PRKD improves the accuracy and reliability of kick detection, enabling proactive responses to potential risks, protecting the environment and human lives, and optimizing drilling operations.