Search Results (575)

High gas–oil ratio (GOR) well streams challenge the stable operation of oilfield gathering systems because positive-displacement multiphase pumps lose volumetric efficiency, amplify pressure pulsation, and suffer seal degradation as the inlet gas fraction rises. Targeting GOR = 100–300 Nm³/t (≈480–1450 scf/STB), this study proposes a jet pump-based oil–gas multiphase transportation system together with an evaluation framework that couples localized computational fluid dynamics (CFD) with a one-dimensional (1D) transient pipeline network model. The methodological novelty is a GOR-dependent source-term closure embedded in the 1D momentum equation: the pump pressure rise is evaluated at every time step as $\mathsf{\Delta }{p}_{\mathrm{p}\mathrm{u}\mathrm{m}\mathrm{p}}\left(t\right)=k_g\left(\mathrm{G}\mathrm{O}\mathrm{R}\right)·{\Pi }_p\left(\mathrm{G}\mathrm{O}\mathrm{R},p_w\right)·\left(p_w-p_s\right)$ from CFD-derived maps of entrainment ratio, pressure recovery, and high-gas correction, so that the jet pump enters the network simulation as a dynamic source rather than a steady boundary condition, a capability that neither pump-level transient CFD nor conventional 1D codes provide. Transient simulations under slug disturbances give three main results. (i) At GOR = 200 Nm³/t and constant working-fluid pressure, slug arrivals drive the outlet pressure transiently below the ±5% band (0.76–0.84 MPa), and it returns to the band of the 0.80 MPa set point within ≈150 s. (ii) As GOR increases from 100 to 300 Nm³/t, ${\displaystyle \frac{{\sigma }_p}{p_{\mathrm{s}\mathrm{e}\mathrm{t}}}}$ rises from 0.031 to 0.089 and the peak-to-peak ratio from 0.18 to 0.50, with stability criterion C1 violated beyond ≈275 Nm³/t. (iii) Three applicability zones are delineated: preferred (100–200), controllable (200–260), and marginal (260–300 Nm³/t), where the marginal zone requires inlet peak-shaving, ≥30% working-fluid pressure margin, and feedforward–feedback control. Mesh independence (${\mathrm{G}\mathrm{C}\mathrm{I}}_{\mathrm{f}\mathrm{i}\mathrm{n}\mathrm{e}}=0.23–0.35$%) and a CFD–1D transfer mismatch ≤3% support internal consistency; the delineated boundaries remain model predictions pending experimental and field validation. Full article

Variations and unstable characteristics of two-phase flow in oil and gas pipelines readily induce severe equipment vibration and internal liquid sloshing, which seriously endanger the safety of pipeline systems. Existing investigations on conventional T-junctions have been restricted to single working conditions, without systematic optimization of structural parameters across multiple flow regimes or full evaluation of integrated separation and slug suppression performance. To address this research gap, this work proposed an optimized four-branch T-junction. The geometric configuration of the T-junction was optimized, and a test prototype was fabricated for gas–liquid two-phase flow experiments. Combined with experimental measurements and computational fluid dynamics (CFD) simulations, the overall performance of the optimized T-junction was comprehensively analyzed under diverse flow patterns and operating conditions. The test results indicated that the gas separation efficiency exceeded 90% under stratified flow, whereas slug flow brought strongly time-dependent separation performance. The gas separation efficiency was maintained above 40% for all test cases. The optimized structure reduced liquid slug velocity and length and significantly suppressed liquid level fluctuations in the downstream separation tank. The numerical predictions agreed well with experimental data, which validated the reliability of the present numerical framework. This study provides technical references for the design of inline pipe separators that realize both gas–liquid separation and slug mitigation. Full article

Accurate identification of multiphase flow patterns in vertical pipelines is critical for operational safety and efficiency in the oil and gas industry. Yet, conventional methods struggle with subjectivity and transitional regimes. This study develops and integrates three neural network architectures: a convolutional neural network (CNN) for spatial features, a transformer neural network (TNN) for long-range dependencies, and a physics-encoding network (PEN) for embedding physical constraints. These are combined into a hybrid framework trained on an experimental dataset of 2131 images from a wire mesh sensor, annotated using a semi-automated pipeline. Results show the hybrid model achieved 95.91% test accuracy with a macro F1-score of 0.96, the highest of the four models evaluated, with its main advantage in transitional regimes. A multi-seed ablation shows that the convolutional branch provides the dominant discriminative signal, while the transformer and physics-inspired branches added complementary improvements that are consistent across runs. This hybridisation mitigates individual model weaknesses, with the physics-inspired branch acting as a spatial regulariser that improves interpretability, providing a robust and objective tool for reliable pipeline monitoring. Full article

As the primary carrier for oil and gas transportation, pipelines are critical for the entire industry. Pipelines are continuously subjected to corrosion and abrasion in the oil and gas delivery process, leading to gradual wall thickness reduction, shortened service life, and deteriorated operational safety. Ultrasonic testing has been widely adopted for monitoring pipeline wall thickness. Conventional ultrasonic transducers possess rigid configurations, which hinder large-area inspection and exhibit poor adaptability to complex curved components. In contrast, flexible ultrasonic sensors show prominent advantages, with their small size, light weight, and excellent conformal contact with curved surfaces. Flexible piezoelectric thin-film sensors have been used in a wide range of fields. As one of the most representative piezoelectric polymers, poly(vinylidene fluoride–trifluoroethylene) (P(VDF-TrFE)) combines favorable piezoelectric coefficients and intrinsic flexibility, making it popular. Some research groups have investigated the influences of modified filler particles, doping ratios, and fabrication process optimization on the performance of P(VDF-TrFE)-based piezoelectric composites, while others have concentrated on the practical applications of existing flexible piezoelectric sensors. This study emphasizes a rapid customized fabrication strategy for flexible sensors instead of single-specification standardized probes; hence, it does not share the same comparison benchmark as conventional fixed-dimension sensors. Systematic research on flexible piezoelectric thin-film sensors is presented, including piezoelectric material modification, substrate design, laminated structural design, fabrication workflows, establishment of the testing platform, and the development of matched circuit systems. The material preparation and manufacturing processes are optimized, and a scalable technical route for fabricating flexible piezoelectric sensors is proposed. Using this route, flexible piezoelectric thin-film sensors can be rapidly tailored for different application scenarios to satisfy diverse engineering demands. Multiple experiments were conducted on pipeline samples with varying wall thicknesses and curvatures. The results verify that the sensor reaches a measurement precision of 0.01 mm, meeting the demands of high-precision pipeline structural health monitoring. Full article

Seismic monitoring networks increasingly develop capabilities that function as geographic information infrastructure, transforming continuous geophysical observations into spatial information that supports research, decision-making, and public awareness. In Texas, seismicity linked to oil and gas operations has increased since 2009 across major producing regions, prompting the Texas Legislature to establish the Texas Seismological Network and Seismology Research program (TexNet) in 2015. This paper examines TexNet’s seismic monitoring network, field operations, data-processing pipeline, and the information products, data services, and decision-support tools that transform seismic observations into accessible earthquake information. Since routine earthquake reporting began in 2017, TexNet has grown from an inherited network of eighteen broadband stations to a system directly maintaining 207 stations and incorporating 421 active stations to locate earthquakes across Texas. TexNet provides a suite of information products, data services, and decision-support tools—including the TexNet Earthquake Catalog, near-real-time notification systems, and open data products—that connect geophysical observations with the needs of researchers, regulatory agencies, industry, and the public. TexNet remains fundamentally a seismic monitoring network, with additional capabilities that support scientific, regulatory, and public information needs in Texas and other regions with induced seismicity. Full article

The oil and gas (O&G) industry is increasingly adopting non-metallic materials for pipelines and downhole components to mitigate corrosion, reduce maintenance costs, and improve performance in harsh service environments. Among high-performance polymers, polyether-ether-ketone (PEEK) has attracted significant attention owing to its excellent mechanical properties, thermal stability, and chemical resistance, making it a promising candidate for aggressive downhole applications. However, exposure to acids, hydrocarbons, water, CO₂, and supercritical CO₂ under high-pressure/high-temperature conditions can alter its microstructure and mechanical performance, necessitating a comprehensive understanding of its long-term behavior. This review summarizes the microstructure, properties, and current applications of PEEK in the O&G industry, including its emerging use in additive manufacturing. It further examines the fundamental mechanisms of gas and liquid diffusion, aging processes (physical, chemical, and thermal), and their effects on the morphology, thermal behavior, and mechanical properties of PEEK. By consolidating findings from studies conducted under representative O&G environments, this review identifies current knowledge gaps and future research priorities, providing guidance for the selection, qualification, and design of PEEK components for demanding oil and gas applications. Full article

Ensuring the integrity of external anti-corrosion coatings is critical to the safe operation of long-distance oil and gas pipelines. Construction-site images contain complex backgrounds, multi-scale targets, and many elongated or weak-boundary coating conditions, challenging conventional bounding-box regression under low-overlap conditions. We constructed a real-site dataset of 1388 images and 1756 annotated instances across six coating-condition categories from long-distance natural-gas pipeline construction sites. Building on YOLOv10n, we formulate a Scale–Aspect Adaptive Normalized Wasserstein Distance (SA-NWD) regression strategy that adjusts the NWD weight according to target scale and aspect ratio during training. Across six random seeds, SA-NWD achieved the highest mean Recall (0.459 vs. 0.437 baseline) and mAP@0.5 (0.451 vs. 0.431), whereas fixed-weight NWD achieved the highest mean mAP@0.5:0.95 (0.251 vs. 0.240 baseline). Ablation results support complementary scale and aspect-ratio guidance. Morphology-grouped analysis showed higher Recall for extremely elongated targets (0.714 vs. 0.659 for fixed-weight NWD), with lower cross-seed standard deviation (±0.027 vs. ±0.101). These results suggest that SA-NWD may benefit high-recall screening of morphologically complex coating conditions, while fixed-weight NWD may provide more stable high-IoU localization; both strategies retain the inference architecture, parameter count, and GFLOPs of the YOLOv10n baseline. Full article

The results of the experiments on the transport process of fluid flow through a pipeline under temperature gradient conditions between the internal and external environments, and on continuous gas generation at the contact boundary of the transported media, are presented in this paper. The test results showed that under non-isothermal flow conditions, a slippage effect will impact flow velocity and pressure, as well as the temperature distributions in variable cross-section pipes. Laboratory experiments were conducted in order to study the effects of the gas nucleus at the pipe walls on the hydrodynamic characteristics of the fluid flow. It is shown that the throughput capacity of the pipe is affected by the temperature difference between the oil and the pipe walls. The test results also demonstrated that at certain temperature gradients on the border layer, the pipe’s capacity reaches its maximum value. Quantitatively, the hydroconductivity of Q/ΔP increased from about 1.45 × 10⁻⁵ m³/(s·MPa) under relatively isothermal conditions to a maximum value of approximately 2.04 × 10⁻⁵ m³/(s·MPa) with a temperature difference in the oil–pipe-wall zone of about 3–5 K, which corresponds to an increase of about 41%. With a further increase in the temperature difference, the hydroconductivity decreased to about 1.64 × 10⁻⁵ m³/(s·MPa) at 10 K and then stabilized in the range of (1.60–1.64) × 10⁻⁵ m³/(s·MPa). This non-monotonic behavior is explained by the temperature-induced release of gas and the formation of a gas-saturated wall zone, which initially reduces the effective resistance of the wall and creates an apparent sliding effect. At high temperature differences, gas accumulation, thermal insulation of the wall area and two-phase flow disturbances limit this effect, which leads to the decrease and subsequent stabilization of the pipe capacity. Full article

Gleeble-3800 thermal simulation testing machine was adopted to investigate the evolution laws of microstructure and properties in the coarse-grained heat-affected zone (CGHAZ) of pipeline steels with different Cr mass fractions (0.2, 0.5, 0.8 wt.%) under welding heat inputs ranging from 8 kJ/cm to 20 kJ/cm. Combined with optical microscopy, scanning electron microscopy and electron backscatter diffraction, the coupled influencing mechanism of heat input and Cr content on the properties of CGHAZ was systematically analyzed. The results show that as the Cr content increases, the range of valid welding heat input for maintaining satisfactory CGHAZ impact toughness gradually narrows with increasing Cr mass fraction of the steel. Specifically, the 0.2Cr experimental steel maintains high toughness under a thermal input ranging from 8 to 20 kJ/cm, the 0.5Cr experimental steel exhibits relatively high toughness in the range 8 to 13 kJ/cm, while the 0.8Cr experimental steel shows high toughness only at 15 kJ/cm. The coupled effect of weld heat input and Cr content on CGHAZ properties originates from a combination of microstructural composition types, phase fractions, substructures, and grain sizes. Increasing the heat input and Cr content leads to a reduction in the bainite ferrite with superior toughness and an increase in the large-sized granular bainite with inferior toughness. Meanwhile, the effective grain size of the overall microstructure first decreases and then rises. Grain coarsening and an increased fraction of Martensitic/Austenitic (M/A) constituent are the key factors responsible for the deterioration of CGHAZ toughness in deep-sea oil and gas transportation pipeline steel. Full article

European energy markets have experienced significant instability as a result of consecutive global systemic shocks, particularly the COVID-19 pandemic and the geopolitical conflict in Ukraine. This paper analyses the development of crude oil and natural gas prices between 2019 and 2024 and discusses their implications for sustainable logistics, energy security and supply chain resilience in Europe. The study is based on secondary data from internationally recognized sources, including the International Energy Agency, OPEC, Eurostat, the European Council, the World Bank and the U.S. Energy Information Administration. An event-based comparative approach supported by descriptive price-change calculations was applied to distinguish between the pandemic-related demand shock and the geopolitical supply-side shock after 2022. The results show that crude oil prices declined from approximately 64 USD/barrel in 2019 to 41 USD/barrel in 2020, representing a decrease of about 3f5.9%, mainly in connection with reduced mobility, lower transport activity and industrial slowdown during the COVID-19 pandemic. In contrast, crude oil prices increased to approximately 100 USD/barrel in 2022, representing an increase of about 143.9% compared to 2020, coinciding with geopolitical uncertainty and supply-side pressures. The European natural gas market appeared particularly vulnerable to the 2022 crisis because of supplier dependence, pipeline infrastructure constraints and reduced Russian gas flows. EU natural gas demand declined by 55 billion m³, or 13%, in 2022, indicating the effect of high prices, energy savings and crisis adaptation. The findings suggest that crude oil shocks are mainly related to transport costs and freight rates, while natural gas shocks may influence energy-intensive production, warehousing, cold chains and broader supply chain stability. The study highlights the need for energy diversification, renewable and low-carbon energy development, energy efficiency and more resilient logistics strategies. Full article

Accurate tracking and localization of in-line inspection (ILI) tools are essential for mileage calibration, defect mapping, and blockage prevention in oil and gas pipelines. This review summarizes sensor-based approaches for external ILI-tool localization, emphasizing how sensing physics, deployment geometry, and signal interpretation determine practical performance. Extremely low-frequency (ELF) magnetic tracking is first examined through dipole modeling, sensor evolution, and weak-signal recovery under steel-pipe and soil shielding. Distributed fiber-optic sensing is then reviewed as a continuous-tracking alternative, with attention to fading mitigation, spatiotemporal denoising, and trajectory extraction from distributed acoustic sensing data. Acoustic arrays and hybrid schemes are discussed as complementary options for subsea or cable-free environments. Finally, the review assesses how data fusion and lightweight artificial intelligence (AI) can improve robustness while noting unresolved issues in field data availability, edge computing, and uncertainty quantification. The synthesis indicates that next-generation ILI tracking should combine heterogeneous sensing, physics-aware signal processing, and deployment-aware model design rather than rely on a single high-sensitivity sensor. Full article

Energy price shocks have been the main drivers of inflation in Europe during the last decade. This paper examines cross-country differences in the transmission and magnitude of energy supply shocks in the Visegrád Group countries (Poland, Czechia, Hungary, and Slovakia) over the period 2015–2026. To identify energy-related disturbances and evaluate their macroeconomic effects, we estimate Bayesian Structural Vector Autoregressive (BSVAR) models with sign restrictions and complement the analysis with Local Projections. The results indicate substantial heterogeneity in inflation responses across countries. Oil supply shocks increase inflation by approximately 0.8 percentage points in Czechia and 0.7 percentage points in Hungary, compared with around 0.5 percentage points in Poland and Slovakia. Similar response patterns are observed for gas supply shocks, suggesting that stronger commodity price pass-through contributes to the larger inflationary effects in Czechia and Hungary. The analysis also reveals methodological challenges in identifying the effects of increased LNG imports. Both models indicate LNG-related shocks are highly correlated with pipeline gas supply shocks. In fact, its imports have mitigated energy shortages and reduced price pressures. Full article

Magnetic leakage detection is one of the most commonly used methods for pipeline inspection, which mainly uses magnetic sensors to detect the magnetic leakage field on the internal and external surfaces of the pipeline to determine whether there are defects in the pipeline. The defect quantification algorithm includes a forward model and an optimization algorithm, in which the estimation of target defects using optimization algorithms is one of the key aspects of defect inversion. Most of the existing optimization algorithms are based on particle swarm algorithms (PSOs) and genetic algorithms (GAs), which are prone to premature problems and have low convergence accuracy. To address the problems in the process of defect inversion, this paper proposes a new inversion algorithm, which obtains part of the prior knowledge from the application context of defect inversion, and adopts the decay oscillation function as the nonlinear convergence factor based on the whale optimization algorithm (WOA). In addition, referring to the concepts of “genetic” and “mutation” in the GA, a diversity variation strategy based on dynamic step size is designed. The algorithm designed has the advantages of fast operation and high search accuracy. At the end of the paper, two sets of experiments are designed to compare the improved WOA with other existing optimization algorithms. The results demonstrate that the algorithm is significantly superior to other algorithms, both in the ideal case of simulation experiments and in the practical application of defect inversion. Full article

River-channel washout is one of the common geological hazards threatening the safety of long-distance oil and gas pipelines, particularly under storm-flood conditions, when pipeline sections crossing rivers and gullies are more susceptible to damage. Existing assessment methods for river-channel washout are effective for single river cross-sections or post-disaster field investigations; however, their application remains limited when dealing with long-distance pipeline systems characterized by numerous river- and gully-crossing sections and large spatial variability in upstream catchment conditions. To address this issue, this study investigates storm-flood discharge and scour-depth calculation methods suitable for river- and gully-crossing sections of long-distance oil and gas pipelines, and establishes a quantitative evaluation index system that considers river-channel washout susceptibility, pipeline vulnerability, and pipeline failure consequences. Based on investigation results of river-channel washout hazards along multiple pipeline systems, including the Zhongxian–Yichang section of the Zhongwu Pipeline, the Hubei–Hunan section of the Lanzhou–Zhengzhou–Changsha Pipeline, and the Phase I Jiangxi Natural Gas Pipeline Network, the hazard characteristics and influencing factors of river-channel washout affecting long-distance oil and gas pipelines are analyzed and summarized. The proposed method was applied to 19 river- and gully-crossing pipeline sections in the Phase I Jiangxi Natural Gas Pipeline Network under different rainfall intensities. The results show that, under light-to-moderate rainfall conditions, 15 sites were classified as relatively low risk and 4 sites as medium risk. Under both the 50-year and 100-year return-period rainstorm scenarios, 12 sites were classified as relatively low risk, 6 sites as medium risk, and 1 site as relatively high risk. The results also indicate that the risk probability of some sites increases with increasing rainfall intensity. Among them, Site No. 19 shows the highest risk probability, increasing from 0.0997 under light-to-moderate rainfall conditions to 0.1474 and 0.1488 under the 50-year and 100-year return-period rainstorm scenarios, respectively. The proposed method can provide a reference for meteorological risk assessment of river-channel washout hazards along long-distance oil and gas pipelines. Full article

Digital Twin (DT) technology has emerged as a transformative approach in pipeline engineering, enabling real-time monitoring, predictive analytics, and enhanced decision-making across the asset lifecycle. This review critically examines recent advancements in the application of digital twins for pipeline systems, with a particular focus on condition monitoring, leak detection, corrosion assessment, and predictive maintenance. The study synthesizes findings from a wide range of literature to identify key enabling technologies, including Internet of Things (IoT) sensors, data-driven modeling, computational fluid dynamics (CFD), and machine learning algorithms. Special attention is given to the integration of physics-based and data-driven models for improving the accuracy and reliability of digital twin frameworks. In addition, this paper proposes a unified reference architecture for pipeline digital twins, supported by a mathematical formulation of synchronization and a comparative synthesis of existing approaches. The review highlights how digital twins facilitate early fault detection and operational optimization by continuously synchronizing physical assets with their virtual counterparts. The review also emphasizes the importance of uncertainty-aware and reliability-informed digital twin frameworks for robust decision-making in safety-critical pipeline applications. Applications in subsea, oil and gas, and water distribution pipelines are explored, demonstrating the versatility of DT systems under different environmental and operational conditions. Despite significant progress, challenges remain in data integration, model validation, scalability, and cybersecurity. Furthermore, the lack of standardized architectures and interoperability frameworks limits widespread adoption. This paper concludes by outlining future research directions, including the development of hybrid modeling techniques, edge computing integration, and AI-driven autonomous decision systems. Overall, digital twin technology represents a paradigm shift in pipeline engineering, offering substantial potential to enhance safety, efficiency, and sustainability in complex infrastructure systems. Full article