This study presents an analytical investigation of transient gas-pressure dynamics in a ring-type pipeline with multiple spatially distributed withdrawals. A reduced quasi-one-dimensional, isothermal formulation is developed from the mass and momentum conservation equations, with hydraulic resistance represented through linearization and localized withdrawals modeled using Dirac delta functions. The resulting transient pressure equation is treated by the Laplace transform under the adopted closed-loop boundary conditions, yielding an analytical infinite-series solution that is subsequently evaluated through a converged truncated-series representation. The results reveal a clear distinction between pressure-magnitude sensitivity and spatial peak-location persistence. Changes in withdrawal number, distribution, and intensity substantially affect the magnitude and temporal attenuation of pressure, whereas the pressure maximum remains concentrated within a comparatively stable hydraulic coupling region under the investigated conditions. Finer local spatial evaluation further resolves this region near approximately 11.5 km for most of the investigated transient interval, showing that the original 12-km location represents the nearest sampled coordinate rather than an exact invariant pressure-maximum location. Sensitivity analysis with respect to the linearized hydraulic resistance coefficient likewise indicates that hydraulic damping affects pressure magnitude more strongly than the location of the pressure maximum. The observed spatial persistence is therefore interpreted as a characteristic of the investigated ring configuration, parameter range, and modelling assumptions rather than as a universal invariance property of arbitrary pipeline networks. From an engineering perspective, the identified coupling region may provide a physics-informed candidate/reference location for pressure monitoring and may complement conventional measurements in SCADA- and IoT-supported systems. The study thus provides an analytical framework for interpreting transient hydraulic redistribution in closed-loop gas pipelines and establishes a basis for subsequent numerical, experimental, and field-scale validation.
Leak detection and integrity management technologies are becoming increasingly critical in the mining industry due to the extensive use of long-distance slurry and water pipelines, their exposure to harsh environmental conditions, and the environmental consequences associated with undetected leaks. Existing solutions are often reactive, or limited to single leak detection techniques, lacking an integrated framework that combines physical modeling, real-time monitoring, and decision support. This work presents a Pipeline Reliability and Integrity Management System (PRIMS), an innovative integrated system for leak detection, prevention, and localization tasks, tailored to the mining sector. The system employs a multi-layer architecture, including the virtual representation of the pipeline, real-time monitoring of hydraulic and operational conditions, and auser interface for operational recommendations and support. The system implementation is supported by state-of-the-art physics-based methods for pipeline integrity, such as the Extended Real-Time Transient Model (E-RTTM), Mass Balance, and Negative Pressure Wave models, which enable the system for leak detection and localization purposes, supporting operational recommendations. The PRIMS has been tested on a case study in the mining industry, where this article explores how this system enhances operational safety, reduces environmental risks, and aligns with international standards and regulations, demonstrating significant technological progress in pipeline management, enabling safe and efficient operation of pipelines.
High-pressure hydrogen blending in natural gas pipelines is a key pathway for large-scale hydrogen utilization, while mixing uniformity directly affects pipeline safety and measurement accuracy and remains a critical issue to be addressed. This study proposes a novel blending strategy composed of a multi-hole injection element and a static disturbance element, and develops a high-fidelity numerical simulation framework based on Large Eddy Simulation (LES) to elucidate the mixing mechanisms under unsteady turbulent conditions. The predictive accuracy of the method was validated using a T-junction pipeline configuration. The effects of key parameters, including injection direction, injection hole number, hydrogen blending ratio, mainstream velocity, and operating pressure, on mixing performance and pressure drop were systematically investigated. The results show that: (1) the developed numerical method is able to accurately capture the mixing behavior of hydrogen and natural gas and the proposed blending method exhibited good performance in terms of mixing uniformity and energy efficiency under different conditions; (2) Under typical operating conditions, the use of counter-flow injection with 25 uniformly distributed holes increased the outlet mixing uniformity to over 99%, while maintaining the overall pressure drop below 10 kPa; (3) The mixing process was governed by a multistage cooperative mechanism of disturbance excitation, shear entrainment, and diffusive mixing, and the counter-flow injection generated high-speed shear layers and recirculation vortices that enhanced radial blending, while the downstream baffles induced forced perturbations, promoting rapid and uniform hydrogen diffusion over a short distance. The proposed LES solution procedure can provide a powerful tool for analyzing hydrogen-natural gas mixing, and the model proposed and results obtained could offer theoretical and engineering insights for the design and optimization of high-pressure hydrogen blending equipment.
Understanding the structural behavior of cured-in-place pipe (CIPP) liners under radial compression is essential for ensuring the long-term reliability of trenchless rehabilitation systems. This study presents a comprehensive experimental and numerical investigation of CIPP liners under radial compression, aiming to elucidate their material behavior, structural response, and design implications. Three-point bending and tensile tests were conducted to characterize the mechanical properties and failure mechanisms of the liner material, consisting of three layers of fiberglass cloth. Full-scale radial compression tests examined the influence of loading speed, liner diameter, thickness, and loading times on ring stiffness and bearing capacity, revealing a progressive deformation process through initial, elliptical, and dumbbell stages, with failure governed primarily by geometric instability. To account for cumulative cyclic effects, a loading times correction factor was incorporated into a Spangler-based bearing capacity calculation, enabling quantitative evaluation of stiffness degradation and strength reduction under repeated loading. Sensitivity analysis indicated that liner thickness has the greatest influence on structural performance, followed by diameter, loading times, and loading speed. A three-dimensional finite element model was developed and validated against experimental data, accurately reproducing load–deformation behavior and stress evolution. The proposed calculation method and numerical model provide a reliable framework for optimizing liner design, predicting long-term performance, and supporting engineering safety assessment of CIPP rehabilitation systems.
Gravity-induced stratification of hydrogen–methane(H₂–CH₄) mixtures remains a debated safety concern in hydrogen-blended natural gas pipelines, particularly in vertical and quiescent sections. In this work, a unified thermodynamic–transport framework is developed to quantitatively evaluate both the equilibrium distribution and the transient timescale of H₂–CH₄ mixtures under gravity. The framework integrates(i) a minimum-energy model based on Helmholtz free energy minimization with the Peng–Robinson real-gas equation of state and(ii) a transient convection–diffusion model coupling gravitational drift with molecular diffusion. Model predictions agree with benchmark literature and experimental data within 2%. Results show that temperature accelerates diffusion, pressure delays equilibration without altering steady-state distributions, and pipe height primarily controls the stratification timescale rather than its magnitude. Even under extreme conditions (−10°C, 10 MPa, 30 vol% H₂, 1 km height), the steady-state top–bottom hydrogen volume fraction difference remains below 1.5%, while more than 2.7 × 10³ years are required to reach equilibrium. Under typical urban gas conditions, the concentration difference after 10 days is below 0.01%. These findings demonstrate that gravity-induced stratification of H₂–CH₄ mixtures is physically possible but engineering-irrelevant within practical pipeline lifetimes, providing a time-explicit and quantitatively justified basis for pipeline design and safety assessment.
An indoor horizontal experimental flow loop was constructed to investigate safe restart strategies for gathering pipelines in high-water-cut oil fields following unplanned shutdowns. The system enables cyclic shutdown-restart operations of oil-gas-water three-phase flow under varying conditions, with synchronous flow pattern visualization and high-frequency pressure/temperature data acquisition. Experiments revealed that a distinct horizontal oil-water stratification develops during shutdown. Based on this observation, a temperature drop prediction model was developed, which couples the external soil temperature field and explicitly accounts for the three-phase distribution. During restart, the reduction in flow area due to the gelled oil layer and its non‑Newtonian shear-shedding behavior are identified as the key mechanisms governing the pressure transients. Accordingly, a three-phase restart pressure prediction model was established by decomposing the total pressure into frictional pressure drop, gelled oil layer shear pressure drop, and inertial pressure drop. Experimental validation demonstrates that the coupled model can effectively predict the post‑shutdown temperature distribution and the full restart pressure evolution, including the peak pressure and subsequent decay.
The hydrogen embrittlement (HE) susceptibility of the L245MH and L360MH pipeline steels was evaluated in a 6.3 MPa high-pressure hydrogen environment, through slow strain rate tensile (SSRT) tests and comprehensive microstructural characterization. SSRT results in both 6.3 MPa H2 environment showed that L360MH generally shows higher HE susceptibility than L245MH steel under tested conditions studied. The microstructure of both steels was characterized by optical microscope (OM), scanning electron microscope (SEM), electron backscatter diffraction (EBSD), and transmission electron microscopy (TEM), and these analytical tools were also used to study the crack path and the fracture morphology of samples fractured in hydrogen. The microscopic study revealed that some of the lamellar deformation layers in the microstructure along the rolling direction in L360MH were associated with hydrogen-induced serrated cracking seen on the fracture surface of SSRT samples failed in hydrogen environment, which negatively influences HE susceptibility index of the steels. Moreover, the crystallographic analysis of the fracture surfaces and secondary cracks in both steels exposed to gaseous hydrogen environments reveals a fundamental difference in their hydrogen-induced cracking mechanisms: The crack paths in L245MH are more consistent with slip-assisted hydrogen cracking, as the analyzed crack segments preferentially align with {110}-type slip-planes. In contrast, the cracking behavior of L360MH may involve the combined contribution of cleavage- or quasi-cleavage-related cracking and localized slip-assisted propagation. Some crack segments show preferential alignment with {100}-type plane traces, suggesting a quasi-cleavage-related cracking, whereas others are closer to {110}-type slip-planes, indicating possible crack path transition associated with localized plastic deformation.
Natural gas, as a clean and efficient energy carrier, plays a crucial role in reducing carbon emissions, and transient simulation of natural gas networks is essential for planning, operation, and safety assessment. However, conventional methods based on globally uniform time steps suffer from low computational efficiency and poor responsiveness in emergency scenarios, while adaptive approaches relying on a posteriori local truncation error (LTE) may involve delayed feedback and additional computational costs associated with step rejection and rollback. To address these limitations, this paper proposes a boundary-excitation-based a priori adaptive time-stepping method (BEATS) for offline simulations with available boundary information, together with a structural fidelity evaluation framework. Unlike conventional approaches, the method performs structured analysis from boundary conditions, enabling structure-aware global time resolution planning. Structural events are identified via change-point detection, and local fluctuation is quantified using total variation to construct a non-uniform time-step distribution, followed by solution using an implicit central difference scheme with the Newton–Raphson method. Case study results indicate that both the uniform time-stepping method and BEATS achieve approximately 99% pointwise accuracy while maintaining high structural fidelity, whereas BEATS attains a speedup of 62.82% to 84.44%. Further analysis reveals that acceleration originates from the reduction in time levels, while accuracy is preserved through rational time-step allocation. Overall, BEATS introduces structural fidelity as a complementary control objective, providing an alternative framework for efficient and reliable transient simulation.
High-pressure transmission pipelines are expected to play a central role in scaling low-carbon hydrogen supply; however, prescriptive design under ASME B31.12–PL may introduce pressure-capacity penalties relative to conventional natural-gas design under ASME B31.8. This paper quantifies, in a strictly code-based manner, the Maximum Allowable Pressure (MAP, i.e., the maximum allowable internal design gage pressure) reductions associated with the material performance factor Hf in ASME B31.12–PL Option A. A parametric framework is used to evaluate allowable internal design gage pressure for identical combinations of steel grade, nominal diameter, and wall thickness under consistent baseline assumptions. The results highlight a systematic contraction of MAP under Option A and a diminishing-returns trend, in which increases in material strength or wall thickness that would raise MAP under ASME B31.8 can be partially offset when the corresponding design point falls into a lower Hf band, leading to a stepwise plateauing of allowable pressure under ASME B31.12–PL. In addition, the framework identifies regions of the design space in which the allowable hoop stress exceeds 40% of the specified minimum yield strength, thereby activating fracture-resistance and fracture-propagation control requirements under ASME B31.12–PL. Overall, the study demonstrates that Hf plays a dual normative role under Option A, simultaneously limiting allowable pressure and, in certain cases, triggering supplementary integrity requirements that must be considered during early-stage design of hydrogen transmission pipelines.
In the United States, there have been approximately 8,000 pipeline accidents since 1986, resulting in over 500 deaths, 2300 injuries, and $7 billion in property loss, with 35% of failures caused by deterioration in aging infrastructure. However, an aging system does not necessarily mean it is faulty and, if well maintained, does not need to be replaced. To address the need for targeted maintenance, cured-in-place pipe (CIPP) has emerged as a trenchless technology for structural rehabilitation. To facilitate a thorough understanding of the performance of CIPP liners for pipeline rehabilitation, this paper provides a comprehensive review of experimental and computational investigations into CIPP liners across both global system responses and constituent material levels. At the system level, CIPP liner serves as a reinforcement, capable of reducing stress and displacement in corroded host pipes by up to 45% and 70%, respectively. Computational studies further demonstrate that well-bonded liners significantly improve rehabilitation performance. Any wrinkles or annular gaps can easily induce buckling or cracking. At the material level, the review evaluates woven fiber fabric composites and advanced polymeric adhesive layers. Experimental studies provide essential characterization data, and computational approaches enable detailed representation of textile architectures. Additionally, representative volume element (RVE) modeling is reviewed for its performance in predicting composite properties based on microstructural variables. This systematic review establishes a paradigm for understanding CIPP compositions and properties, supporting not only the rehabilitation of deteriorated underground pipelines but also the extension of the service life of global underground infrastructure.
Subsea pipelines are vital for global energy security, yet their operation in harsh marine environments introduces severe integrity and maintenance challenges. While existing literature extensively covers the physics of non-destructive testing (NDT) sensors, a critical research gap remains regarding the practical integration of these technologies under demanding offshore operational constraints, such as high-pressure subsea launchers and severe hydrodynamic slugging. To address this gap, a comprehensive evaluation of both Pre-ILI tools, including cleaning and gauging, and advanced In-Line Inspection (ILI) technologies such as Magnetic Flux Leakage (MFL), Ultrasonic Testing (UT), and Eddy Current Testing (ECT), is provided by this study. Furthermore, offshore pigging challenges—such as launcher dimensional limitations, elevated wall thicknesses, concrete weight coatings, debris management, and complex seabed routing—are systematically examined alongside state-of-the-art mitigation strategies and counter-measures, which are ultimately synthesized into a comprehensive summary matrix for rapid engineering reference. Based on this extensive analysis, it is demonstrated that the accuracy of conventional defect detection is significantly compromised by dynamic subsea conditions unless tailored inspection protocols and specific operational modifications are implemented. Consequently, a practical decision-making framework is established by this research so that tool selection can be optimized, operational risks can be mitigated, and safe deployment procedures can be ensured in deepwater environments. Furthermore, critical knowledge gaps within current inspection capabilities are identified, and a strategic roadmap is proposed so that the long-term structural integrity and operational sustainability of offshore pipeline networks can be robustly maintained by future technological advancements.
Pipelines are critical infrastructure for oil and gas transportation, and their safe operation is closely related to environmental protection and public safety. Magnetic flux leakage (MFL) detection is a widely used non-destructive testing (NDT) technique, but accurate defect identification and reconstruction remain challenging. MFL signals are nonlinear, noisy, and strongly affected by operating conditions. Artificial intelligence (AI) and big data technologies have been used in MFL signal processing, ranging from traditional machine-learning models based on handcrafted feature extraction to end-to-end deep learning and further to physics-informed data-driven models. This study presents a systematic review of data‑driven methods for MFL detection by analyzing 98 articles from 53 journals and addressing four research questions. Based on these articles, the review compares different models and shows their distinct advantages and limitations. For example, convolutional neural networks (CNNs) perform well in image-based defect classification but are less effective in extracting long-range temporal dependencies, and the standard You Only Look Once (YOLO) series offers high detection efficiency but is limited in identifying small defects. Physics-informed data-driven models can improve accuracy by incorporating prior physical knowledge, but their performance depends strongly on the validity of the underlying assumptions. This review summarizes the performance, applicability, and limitations of past data-driven methods and discusses future research issues, including MFL data-quality evaluation, model generalization under changing working conditions, and adaptive use of physical information.
Targeting the dual challenges of intense noise interference and limited labeled data in pipeline girth weld inspection, this study explores the intelligent recognition mechanism of Digital Radiography images. To address these pain points, a synergistic recognition framework is proposed, integrating adaptive denoising, collaborative enhancement, and geometry-adaptive detection networks.. An intelligent noise reduction method is designed to solve the problem of high image noise. To address the poor quality of images, an image enhancement algorithm is proposed. A collaborative Fourier Transform is used to enhance the image through different channels. Finally, an improved YOLOv8-MSDCN model is constructed by combining the model of MSDCN with YOLOv8. This model realizes the coupling between geometric deformation adaptation and channel feature enhancement. The relationship between the position and number of MSDCN modules is investigated. It is found that when three MSDCN modules are embedded in the backbone, the model has the best recognition, with a precision of 0.87, mAP@0.5 of 0.86, and recall of 0.81. This proves that the integration of adaptive preprocessing and the fused detection mechanism significantly enhances the reliability of DR defect recognition.
Pipeline systems that transport oil, gas, and water are essential infrastructure components and must effectively absorb joint deformations caused by ground movements to maintain operational integrity. However, in assessing ground deformation components orthogonal to the pipe axis, the current ISO 16134 procedure estimates maximum deflection solely based on the bending limit angle, neglecting axial tensile behavior. Monotonic loading tests on bellows expansion joints of various sizes conducted in this study revealed that, for a standard pipe length of 6 m, the tensile limit angle was consistently smaller than the bending limit angle. This finding indicates that tensile deformation reaches its limit state before bending under such conditions. To address this limitation, we propose a supplementary maximum-deflection formula based on the tensile limit angle. When applied in parallel with the ISO 16134 procedure, the proposed formula reduces the risk of overestimating maximum deflection under permanent ground deformation. Consequently, it enhances the safety and reliability of pipeline systems design.
The allowable nickel content in low alloy steels is restricted in standards used for selection of pipelines and structural materials resistant to hydrogen embrittlement. ISO 15156/NACE MR0175 limits Ni to ≤1 wt.% for sour service, motivated by reported decreases in sulfide stress cracking (SSC) resistance with increasing Ni; SSC is a hydrogen‑assisted failure caused by absorbed hydrogen in hydrogen sulfide (H₂S) solutions. Hydrogen permeation through nickel‑containing steels was measured using the Devanathan–Stachurski permeation cell, with 10-3 M thiosulfate acidified brine at the charging side, reproducing sulfide chemistry without H₂S bubbling. Steels with 0–5 wt.% Ni were quenched and tempered to comparable microstructures and hardness near the 22 HRC limit. Nickel increased the corrosion potential, reduced the thermodynamic driving force for the hydrogen evolution reaction, and promoted the formation of sulfide films. The resulting lattice hydrogen concentration on the charging side (C₀) decreased monotonically with Ni, by up to an order of magnitude at 5 wt.% Ni (≈0.06 to 0.004 ppm). Trapping was not significantly enhanced by Ni, as trapped hydrogen in 3–5 wt.% Ni steels was lower than in 0–1 wt.% Ni steels. The implications of these observations for the nickel effect in SSC and other hydrogen‑assisted stress‑cracking modes of low alloy steels are discussed.
An experimental design involving a 10-point, three-component mixture design was used to investigate mixed corrosion inhibitor performance. The components consisted of surfactants with same tail lengths but distinct head groups (hexadecyltrimethylammonium bromide, benzyldimethylhexadecylammonium chloride, and hexadecyl succinic anhydride). The adsorption-desorption kinetics of mixtures of different mass ratios were investigated at their critical micelle concentration (CMC) using electrochemical measurements combined with mixed-order kinetic models. A rotating cylinder electrode (RCE) system was used to investigate the corrosion of API 5L X60 steel in CO2-saturated 1 wt.% NaCl brine at 30 °C in the presence and absence of inhibitors. Equilibrium surface coverage (θss), adsorption rate constant (ka), desorption rate constant (kd) and adsorption equilibrium constant (KL) were fitted to a special cubic model and plotted on a ternary diagram. Results were used to determine an optimum mixture ratio of the three surfactants based on their ability to minimize or maximize different response parameters. Selected points were used to check the accuracy of the model, with one being the mixture that provided the highest surface coverage, and the other being the mixture that provided the highest ka or KL within a certain surface coverage threshold. Results revealed that mixtures of surfactants with different head group polarities showed non-ideal interactions that increased CMC values, indicating hindered micelle formation and requiring higher concentrations. Mixed-order kinetic modelling revealed predominantly second-order behaviour, with the special cubic model effectively describing adsorption kinetics for cationic-anionic mixtures but poorly predicting equilibrium surface coverage.
This study investigates an internal corrosion-induced failure of a mountainous coalbed methane (CBM) pipeline under intermittent gas supply. The transported medium contained impurities such as H₂S, CO₂, and moisture, which collectively created an acidic corrosive environment. Due to terrain-induced gas–liquid–solid separation, these corrosive components accumulated locally, leading to severe locally uniform corrosion and wall thinning, ultimately resulting in pipeline rupture. A detailed analysis was conducted on the macroscopic morphology of the failed pipeline, corrosion product composition, and underlying corrosion mechanisms. A novel "multi-field coupling" failure mechanism is proposed, that is, the synergistic failure mechanism among the gas-liquid-solid multiphase flow field caused by terrain relief, the alternating stress field caused by periodic start and stop, and the local corrosion field caused by water accumulation in the coalbed methane pipeline in mountainous areas. This study provides important insights for corrosion prevention and safety management in similar pipeline systems operating under complex terrain and intermittent flow conditions.
This article investigates the vulnerability of buried steel gas pipelines subjected to Gaussian-shaped localized subsidence in cohesionless sands (c = 0). The study aims to assess both (i) the transmission of free-field ground curvature to the pipeline and (ii) the resulting structural responses. In this context, a comprehensive parametric investigation involving 1080 three-dimensional finite element simulations is conducted using PLAXIS 3D, covering wide ranges of sand stiffness and strength parameters, pipeline geometries, burial conditions, and subsidence-profile characteristics. A surrogate model (named meta-model) is developed to predict curvature transmission using a dimensionless relative stiffness coefficient R*. The regression formulation achieves a high coefficient of determination (R² = 0.9884) with a low residual standard deviation (σ = 0.0211). Validation against centrifuge and full-scale experimental datasets from literature supports the robustness of the model, while comparisons with existing meta-models from the literature position the present 3D-based formulation with respect to earlier simplified approaches. Three additional meta-models are developed to predict: (i) the peak axial stress, (ii) the maximum shear stress, and (iii) the cross-sectional ovalisation. These models show strong agreement with numerical results (R² > 0.88, mean relative error below 14%), enabling rapid predictions without further finite element analyses. Finally, a probabilistic application demonstrates how the framework can be embedded within a reliability-based approach, supporting the assessment of structural integrity and the prevention of failure in buried pipelines under Gaussian-shaped localized subsidence.
Pipe jacking is widely used in urban underground pipe networks and cross-region pipeline projects. Conventional inspection and replacement practices based on fixed distances or experience cannot track changing ground conditions and tool status in real time, particularly under complex ground conditions. Cutting tools can experience abnormal wear or fail, resulting in unplanned stoppages, reduced tunnelling efficiency, and increased project risk. This study proposes and validates a framework for intelligent management of cutting-tool wear in pipe jacking machines by combining multi-source monitoring, machine learning, and adaptive decision-making. The proposed system adopts an offline retrospective validation mode, in which prediction performance was evaluated on historical project data and control strategies were verified in a simulation environment. First, a data acquisition system was established to integrate machine operating parameters, geotechnical and mechanical properties, and slurry-system information. An attention-based long short-term memory (LSTM) model was developed to learn from these data and achieve accurate time-series prediction of tool wear. Then, an adaptive control strategy was designed to dynamically optimize tunneling parameters and to plan the tool-replacement window effectively. The proposed framework was validated on a natural gas pipeline pipe-jacking project (DN2200, jacking length 268 m) containing fully weathered, strongly weathered, and moderately weathered granite strata. The results show that the proposed system outperforms traditional methods in tool-wear prediction (RMSE reduced to 1.12 mm and R² increased to 0.915), tunneling efficiency (increased by about 14.7%), and risk management. This work presents a model and a practical technical approach for more intelligent management of pipe-jacking construction.
This study investigates the temperature field distribution and leakage localization associated with small-hole leakage in buried dense-phase CO2 long-distance pipelines through systematic experimental and numerical analyses. A numerical model coupling porous media resistance and non-equilibrium phase change was developed to simulate the leakage dispersion process. Large-scale experimental tests were conducted to obtain near-field temperature variation data, and a dynamic thermophysical property lookup method based on the National Institute of Standards and Technology (NIST) database was integrated to enable long-duration leakage simulations. The effects of leakage pressure, leakage diameter, soil porosity, and leakage direction on the soil temperature distribution near the leakage point were systematically analyzed. The results indicate that the soil temperature near the leakage point decreases with increasing leakage pressure, soil porosity, and leakage diameter, accompanied by an expansion of the low-temperature affected zone. Among these factors, the leakage diameter exerts the most significant influence on the temperature field. When soil porosity increases from 0.15 to 0.6, the radius of the low-temperature zone above the leakage point expands from 0.9 m to over 1 m. As the leakage diameter increases from 2 mm to 5 mm, the maximum temperature drop reaches 95.9°C, and the affected region may extend to the ground surface. When leakage pressure rises from 8 MPa to 10 MPa, the radius of the low-temperature zone expands from 1 m to approximately 1.5 m. Based on the observation that the axial temperature drop along the pipeline follows a Gaussian distribution, empirical relationships were established between the temperature distribution parameters and both leakage diameter and soil porosity. Furthermore, a Bayesian inversion method based on the Markov Chain Monte Carlo (MCMC) algorithm was proposed to infer the leakage location and diameter, achieving inversion errors within 1%. This research provides a theoretical foundation and technical support for the optimized deployment of fiber-optic monitoring systems and emergency localization of small-hole leakage in buried CO2 pipelines.
