Objectives: This article investigates the corrosion behavior and mechanical-property changes of S135, G105, and V150 drill pipe materials in a high-temperature-resistant, potassium amino poly-sulfonate drilling fluid, which has good lubrication performance and contains CO₂/H₂S, by applying an 80% yield-limit-load simulation. The results show that the CO₂-corrosion behavior of G105, S135, and V150 drill pipes are obvious under the simulated constant-load-stress-corrosion environments at the wellhead, well-middle, and bottomhole positions. Compared to uncorroded drill pipes, S135 and V150 drill pipes have increased strength and yield ratios, decreased fracture elongation, and increased sensitivity to hydrogen embrittlement under H₂S action, and V150 has a greater risk of stress-hydrogen embrittlement. The strength and yield ratios of G105-material drill pipes decrease, while the fracture elongation increases; the intensity-change amplitude levels are ranked V150 > G105 > S135, and the fracture-elongation-change amplitude is ranked G105 > S135 > V150. The tensile-performance-change amplitude and the SSCC (Sulfide-Stress-Corrosion Cracking) sensitivity of G105 and V150 drill pipes were the highest at the bottomhole. S135 drill pipe materials were most affected by pitting and tensile action at the wellhead, and they had the with the largest SSCC sensitivity.

The generation and propagation mechanisms of acoustic waves from leakage below the annular liquid level in gas wells have attracted widespread attention. To study the characteristics of acoustic sources beneath the liquid level, a physical model of leakage in the casing–tubing annulus was established by simulating the distribution patterns of the flow field and acoustic field within the annulus under tubing leakage conditions. Distinct from the traditional acoustic analysis of wellbore leakage in gas wells, this study focuses on acoustic waves generated by leaks located below the annular protection fluid level. It analyzes the flow regime and acoustic source characteristics beneath the liquid level under various operating conditions (including leakage aperture, velocity, and position). The research summarizes the evolution patterns of flow regimes when gas leaks into the annular protection fluid under different conditions and elucidates the generation mechanism of sub-liquid leakage noise and its propagation mechanism across the liquid surface. This work lays the theoretical foundation for detecting sub-liquid leakage at the wellhead using acoustic methods.

A mechanical structure of a fiber Fabry–Perot interferometric vibration sensor for monitoring oil and gas pipelines has been proposed, and design analysis research on performance improvement has been carried out. By designing a serpentine beam structure, the mechanical sensitivity of the sensor is enhanced. Meanwhile, by designing a vertically symmetrical gravity-sensing structure, the cross-axis sensitivity of the sensor is reduced. The results of simulation analysis show that the mechanical sensitivity of the proposed design structure is 89.20 μm/g, which is 32.44 times that of the conventional structure. Moreover, due to the design of low cross-axis sensitivity, the optical sensitivity of the vibration sensor will not be degraded because of its installation status on the pipeline. The proposed mechanical structure provides a design reference for the application of the fiber Fabry–Perot interferometric vibration sensor on oil and gas pipelines, and offers potential for the development of a high-performance comprehensive safety risk monitoring system for oil and gas pipelines.

In response to the limitations of experimental methods for detecting oil and gas well tubing leaks, this study developed a full-scale indoor simulation system for oil tubing leakage. The system consists of three components: a wellbore simulation device, a dynamic leakage simulation module, and a multi-parameter monitoring system. The wellbore simulator employs a jacketed structure to replicate real-world conditions, while the leakage module incorporates a precision flow control device to regulate leakage rates. The monitoring system integrates high-sensitivity acoustic sensors and pressure sensors. Through multi-condition experiments, the system simulated complex scenarios, including leakage apertures of 1–5 mm, different leakage positions relative to the annular liquid level, and multiple leakage point combinations. A comprehensive acoustic signal processing framework was established, incorporating time–domain features, frequency–domain characteristics, and time–frequency joint analysis. Experimental results indicate that when the leakage point is above the annular liquid level, the acoustic signals received at the wellhead exhibit high-frequency characteristics typical of gas turbulence. In contrast, leaks below the liquid level produce acoustic waves with distinct low-frequency fluid cavitation signatures, accompanied by noticeable medium-coupled attenuation during propagation. These differential features provide a foundation for accurately identifying leakage zones and confirm the feasibility of using acoustic detection technology to locate concealed leaks below the annular liquid level. The study offers experimental support for improving downhole leakage classification and early warning systems.

Deep and ultra-deep well drilling frequently encounters narrow pressure window formations with multiple pressure systems, leading to the simultaneous occurrence of formation gas influx (overflow) and drilling fluid loss (lost circulation). Existing studies have largely focused on gravity-displacement-type coexistence within the same layer, while the flow characteristics of the scenario of upper overflow and lower lost circulation (Scenario 2) and the scenario of upper lost circulation and lower overflow (Scenario 1) remain poorly understood. In this study, a large-scale visualised experimental device for wellbore gas-liquid two-phase flow under coexisting overflow and lost circulation conditions was designed and constructed based on geometric and Reynolds number similarity criteria. The device has an annular equivalent diameter of 130.9 mm and a total length of 10 m; two distinct coexisting configurations are reproduced by independently adjusting the gas-injection point and the lost-circulation port. Three flow patterns—bubbly, cap-bubble, and churn flow—were identified in the large-diameter annulus. Under Scenario 1, the flow pattern remains essentially unchanged as the lost-circulation rate increases. Under Scenario 2, a clear bubbly-to-cap-bubble transition is triggered once the lost-circulation rate exceeds 5 m ³ /h. Mechanistic analysis reveals that these contrasting behaviours arise from a fundamental difference in loss mode: gas and liquid are discharged simultaneously at an unchanged gas-liquid ratio in Scenario 1, whereas only liquid is lost in Scenario 2, progressively increasing the in-situ gas-liquid ratio. Based on this mechanistic distinction, correction methods for apparent gas and liquid velocities were formulated for each configuration; after correction, the maximum pressure-gradient prediction error was reduced to below 10% and the average error to below 4%. The findings provide experimental evidence and theoretical support for well-control design under coexisting overflow and lost circulation conditions in deep and ultra-deep wells.

For gas leakage monitoring in obstacle environments such as oil and gas stations, the layout of fixed sensors directly affects the validity of monitoring data and the accuracy of subsequent leakage source localization. To achieve effective coverage of high-risk areas with a limited number of sensors and reduce deployment costs, this paper proposes a multi-objective optimization method for sensor layout based on the non-dominated sorting genetic algorithm-II (NSGA-II). Based on multi-scenario computational fluid dynamics simulation data, the peak concentration, hazardous concentration duration, and leakage probability at each monitoring point are extracted as risk characteristic indicators. The NSGA-II analytic hierarchy process is employed to determine the weight of each indicator, and a comprehensive risk classification model for the monitored area is established. This is adopted for solution seeking. Through non-dominated sorting and crowding distance calculation, the Pareto optimal front is searched in the solution space. The optimized layout scheme is applied to the leakage source term estimation based on particle filter, and the performance of different layout schemes is compared and analyzed with the source localization error as the evaluation index. Case studies show that the sensor layout optimized by the non-dominated sorting genetic algorithm achieves effective coverage of high-risk areas. With the same number of sensors, its high-risk area coverage rate outperforms that of the multi-objective particle swarm optimization algorithm (MPSOA). Following the application of the optimized layout, the localization accuracy of leakage source term estimation is significantly improved. Compared with the traditional grid and circular layouts, the source localization error is reduced by approximately 44%. Compared with the layouts optimized by the MPSOA and genetic algorithm (GA), the error is decreased by 30.4% and 33.3%, respectively. The proposed sensor layout optimization method based on the NSGA-II can effectively balance monitoring coverage and economic cost, and significantly improve the localization accuracy of gas leakage sources. This study provides a theoretical basis and technical support for the optimal deployment of fixed gas sensor networks in complex scenarios.