Gas Leakage Research Articles

Study on the influence of cement slurry viscosity on acoustic emission response and deformation characteristics of slurry-coal cemented body

In the process of grouting sealing, the cementation failure of slurry and coal interface exists in the gas extraction borehole, which leads to unstable and gas leakage in the sealing section and affects the efficient gas extraction in the borehole. In order to study the influence of slurry viscosity on the failure characteristics of slurry-coal cemented body, this paper explores the law of influence of slurry viscosity on the acoustic emission response characteristics and deformation characteristics of slurry-coal cemented body under uniaxial compression through laboratory tests, data analysis and quantitative research of image processing. The results show that: (1) Changing the slurry viscosity can achieve the strength control of the cemented body, which can be increased by up to 42.65 %. (2) In the process of uniaxial compression, the cementation structure of slurry-coal cemented body breaks down successively, and its proportion and strength lead to the distribution difference of AE signals and the fluctuation of b-value. Combined with the phase response characteristics of the two, the change of failure mode can be analyzed to provide a reliable evaluation of crack propagation in the cemented body. (3) The b-value of the sample of slurry-coal cemented body with high-viscosity slurry does not fluctuate significantly, and is relatively stable at a low level near 1.0. The results are helpful to promote the research and development of sealing materials and sealing technology.

YOLOGAS: An Intelligent Gas Leakage Source Detection Method Based on Optical Gas Imaging

YOLOGAS: An Intelligent Gas Leakage Source Detection Method Based on Optical Gas Imaging

Lubrication of endotracheal tube cuffs reduces gas leakage during positive pressure ventilation

Lubrication of endotracheal tube cuffs reduces gas leakage during positive pressure ventilation

Implementation of cooling slots at the pressure side rims of squealer tips

The blade tip is a particularly critical component of the high pressure turbine due to the hot overtip leakage gas being responsible for efficiency losses and thermal degradation, often limiting engine life. Squealer tip designs reduce the over-tip leakage mass flow, increasing efficiency, but the thin pressure side rims can be vulnerable to damage because of their large surface area and the difficulties of shielding them from hot overtip leakage flow. This paper considers a new approach to cooling these pressure side rims, by employing an inclined slot inside a recessed step. Compared to conventional cooling strategies, in which coolant is provided by multiple cylindrical holes, the slot feature improves cooling effectiveness by more than 50% in key regions of the pressure side rim, whilst also allowing for a substantial reduction in coolant mass flow. The concept design is developed and explored using Computational Fluid Dynamics (CFD) calculations, and the performance is validated experimentally in a linear cascade with representative Mach and Reynolds numbers.

A novel hybrid information-based PF-WOA algorithm for gas source localization in 3D space

Abstract In recent years, dangerous gas leakage events occur frequently. Rapid and accurate location of gas leakage sources by mobile robots is the key to avoid the expansion of disasters. In order to solve the problem of discontinuous gas concentration gradient and sparse gas environment in three-dimensional space, particle filter, and whale swarm optimization algorithm are integrated to locate gas source. Firstly, the Z-shape search and comb search are used to locate the plume, and then, the particle filter algorithm is combined with the whale optimization method to guide the particle movement, and the random inertial disturbance term is designed to improve the convergence speed and search accuracy of the algorithm. Experimental results in three-dimensional environment show that the proposed information-driven particle filter whale optimization hybrid algorithm effectively guides the robot in localizing gas source within a certain range, significantly enhancing both the efficiency and accuracy of localization compared to other algorithms.

Numerical Investigation of the Blast-Induced Injuries Using an Open-Source Detailed Human Model.

Blasts are a threat both in military and civil contexts due not only to explosive devices but also to gas leakages or other accidents. Numerical models could aid to plan response strategies in the short and long term. Nevertheless, due to modeling complexities, a standardized computational framework has not been established yet. In this challenging context, the present study assesses the prediction of blast-induced traumas by using the total human model for safety (THUMS) human model, which has never been attempted before to the authors knowledge. The pedestrian model is publicly available, hence the demonstration of its suitability to predict blast injuries could benefit the establishment of a common modeling framework. Therefore, the THUMS human model was exposed to different blast scenarios both in free field and partially confined spaces and the response of vital organs was investigated. Trauma patterns to internal organs of the THUMS were consistent with available experimental data and injury thresholds. In conclusion, THUMS open-source human model demonstrated its validity to reproduce primary blast-related injuries, addressing the development of standardization of numerical simulations of human response to explosions.

Irregular Eccentric Wellbore Cementing: An Equivalent Circulation Density Calculation and Influencing Factors Analysis

In the field of cement, if the formation cannot be given sufficient pressure to maintain stability during construction, pressure control failure may occur, leading to the leakage of liquids and gasses from the formation to the wellbore. In addition, irregular wellbore diameter and casing eccentricity are important factors that are easily overlooked and affect the prediction of ECD (Equivalent Circulation Density) calculation. This results in major accidents and ecological disasters, further impacting the global environment. This study focuses on a well in the eastern oilfields of China, and based on a rheological experiment of high temperature and high pressure, an irregular eccentric wellbore model is established according to the measured wellbore diameter and eccentricity data to calculate the ECD of the whole cementing process. Then, a data set is constructed and analyzed using the random forest method to quantitatively evaluate influencing factors such as displacement, rheology, density, and eccentricity on the bottomhole and wellbore ECD. Results find that the density of cement slurry and drilling fluid has the most significant impact on the maximum ECD, with the impact reaching 0.3142 and 0.2902, respectively, and the main factors that affect the minimum ECD are the density and rheological changes in the drilling fluid, reaching 0.7014 and 0.2846. These research findings will contribute to the precise control of wellbore pressure during cementing operations, further ensuring the safety of cementing operations, and laying a technical foundation for the automation and intelligentization of subsequent cementing operations.

Numerical study of a chemical looping combustion system: Effects of fuel type and particle size distributions on the operating performance

Chemical looping combustion (CLC) using biomass offers a promising pathway for achieving negative carbon emissions. However, the different properties of coal and biomass affect reaction performance, which has not been fully explored in the CLC system. Additionally, the effects of particle size distributions (PSDs) of solid fuels and oxygen carriers (OCs) are inadequately addressed. In this study, a 3D reactive model using the computational particle fluid dynamics (CPFD) method is developed to investigate the effects of PSDs of both solid fuels and oxygen carriers on operating performance with coal and biomass as fuels. Results indicate that the average residence time in FR of coal and biomass particles is 0.86 s and 0.68 s, respectively, but biomass outperforms coal in reaction efficiency. For coal-fueled CLC, the average residence time is 0.46 s for coal particles with diameters of 100–200 μm, whereas it reaches 0.86 s for coal diameters of 300–700 μm. However, the reaction performance is better with smaller coal sizes due to char gasification being the rate-limiting step. In comparison, for biomass-fueled CLC, the reaction efficiency remains consistent across various particle sizes under the specified conditions due to the rapid release of volatile components and the low content of char. Additionally, it is found that the OC conversion ratio is mainly determined by their residence time in the zones with relatively higher concentrations of the combustible gas in FR. Employing OCs with overly wide PSDs such as 300–800 μm can compromise the material seal above the AR, increase the risk of gas leakage and decrease the separation efficiency of the inertial separator.

Air Leakages at Microvalves: Pressure Decay Measurements and Extended Continuum Modelling of Knudsen Flows

To improve the performance of valves in relation to the leakage rate, a comprehensive evaluation of the valve characteristics and behavior during pressure exposure is important. Often, these low gas flow rates below 0.1 cm3/min cannot be accurately measured with conventional flow sensors. This paper presents a small and low-cost test rig for measuring gas leakage rates accurately, even far below 0.1 cm3/min, with the pressure decay method. These leakage flows are substantiated with a flow model, where we demonstrate the feasibility of modeling those gas flows with an extended Navier–Stokes framework to obtain more accurate theoretical predictions. As expected, the comparison to the experimental results proves that the classical Navier–Stokes system is unsuitable for modeling Knudsen flows. Hence, self-diffusion of gas, a wall-slip boundary condition, and an effective mean free path model were introduced in a physically evident manner. In terms of the calculated mass flow, while self-diffusion and slip boundary conditions explain deviations from the classical Navier–Stokes equation for Knudsen numbers already smaller than 1, the effective mean free path model has an effect, especially when Kn > 1. For simplified conditions, an analytical solution was presented and compared to the results of an OpenFOAM CFD-solver for flow rates through more complex gap-flow geometries of the flap valve. Hereby, acceptable deviations between 10% and 20% were observed. A comparison with measurement results was carried out. The reproducibility of the measurement method was verified by comparing multiple measurements of one silicon microvalve sample to a state-of-the-art flow sensor. Three geometrically similar passive silicon microvalves were measured with air overpressure decreasing from 15 kPa relative to atmospheric pressure. Maximum gas volume flowing in a blocking direction of 1–26 µL/min with high reproducibility and marginal noise were observed.

Research on gas pipeline leakage identification based on SE-2DCNN with ultra-weak fiber Bragg grating distributed acoustic sensing system

Abstract A new method for identifying gas pipeline leaks using an ultra-weak fiber Bragg grating (UWFBG) distributed acoustic sensing (DAS) system is proposed. To enhance the accuracy of gas leakage detection, an improved convolutional neural network (CNN) incorporating a two-dimensional structure based on the squeeze-and-excitation (SE) attention mechanism was introduced. The principle of acoustic leakage sensing using this technology is explained in detail, and an experimental setup simulating gas pipeline leaks is constructed. During this process, 9,340 DAS data points across varying leakage volumes and pipeline pressures were collected to create ten distinct datasets. The Mel-frequency cepstral coefficients (MFCC) are employed as the feature input for the optimized SE-2DCNN model, which performs identification tasks. The results show that this optimized model achieves an average leakage identification accuracy of 95.33%, demonstrating superior performance over other methods. This approach offers a robust reference for accurately detecting gas pipeline leakages.

Design of Gas Leakage Monitoring System Based on Android Application and NodeMCU ESP8266

Gas leakage is a serious problem that can threaten public safety and health and cause significant material losses. This research aims to design and implement a gas leak monitoring system that can be accessed remotely based on Android applications and NodeMCU ESP8266. NodeMCU ESP8266 is chosen as the main microcontroller equipped with an MQ-2 gas sensor to detect the presence of hazardous gas. This research incorporates Internet of Things (IoT) technology to allow users to remotely monitor the condition of gas leaks, thereby increasing the level of safety in the use of gas in households or small industries. The hardware design includes the use of an MQ-2 gas sensor that is sensitive to certain gas concentrations, as well as setting up an ESP8266 NodeMCU to transmit detection data to a Firebase server for later access through an Android application. The Android application was developed using Android Studio with a focus on an intuitive user interface to monitor the status of gas leaks in real-time. he research methods used include system design, hardware and software implementation, and thorough system testing by simulating gas leak scenarios to test the reliability and response of the system. The results show that the system can detect gas leaks with high accuracy. It is expected that the system developed in this research can be a practical and effective solution in reducing the risk of accidents caused by gas leaks, as well as making a positive contribution in increasing awareness of the safety of gas use in the community.

Ultrasonic Array-Based Multi-Source Fusion Indoor Positioning Technology

Underground mining involves numerous risks, such as collapses, gas leaks, and explosions, posing significant threats to worker safety. In this work, we develop an indoor localization system that uses Bluetooth for coarse positioning and ultrasonic arrays for precision calibration. This system is particularly useful for automated mining operations in underground environments where satellite positioning signals are unavailable. The indoor localization system consists of ultrasonic receiver arrays and an improved multi-transmitter-multi-receiver algorithm, enabling accurate localization within the mining environment. Geometric Dilution of Precision (GDOP) analysis is incorporated to optimize the network layout, and an inertial navigation module is integrated to track the posture of moving objects, enabling precise trajectory determination over large areas, such as coal mines. In the experiment, three traditional methods were compared, and the proposed tracking approach demonstrated a positioning accuracy within 10 cm, reducing error by 20% compared to conventional techniques. This high-precision indoor localization method proves beneficial for underground mining applications.

Design and Implementation of a GSM-Based Home Protection System Against Gas Cylinder Explosion

The aim of this work is to design and implement a GSM-based smart home protection system against the possible life-threatening firing and damage of properties due to gas cylinder explosions. These hazardous explosions are increasingly happened in Bangladesh in the recent years and hence, become serious concerns for the safety of individuals residing in a house. The system designed and implemented in this work can identify unnatural gas leakage by using gas sensors and also, sense unusual temperature increases due to firing inside a house or a restaurant by using temperature sensors. The proposed system ensures multi-level security. The audio and visual alerts are ensured by the use of fire alarms and LEDs respectively. Using GSM module, the system also makes emergency calls and sends SMS to the owner and the nearby fire station to take prompt actions. One servo motor stops the gas valve to cease the gas leakage and another one starts the water valve to flow water to reduce the temperature. Additionally, an exhaust fan is used to reduce the room temperature and let the gas flow out. Therefore, the proposed system is a potential solution to reduce life risks and property damage due to gas cylinder explosion.

Shale gas leakage and fault activation: Insight from the 2021 Luxian MS 6.0 earthquake, China

In the region of large gas fields, extensive research has been conducted on earthquakes induced by industrial production in shale gas fields. However, limited attention has been given to the impact of post-earthquake events on shale gas reservoir leakage and fault activation. The Luxian MS 6.0 earthquake, which occurred on 16 September 2021 in the Luzhou shale gas field, has raised concerns about post-earthquake shale gas leakage. Post-earthquake measurements of soil gases (Rn, CO2, CH4, and H2) and isotopic analyses (δ13CCO2, δ13CCH4 and δDCH4) in the Luzhou shale gas field area reveal that the Huayingshan fault zone, a natural pathway for shale gas leakage, was not activated by the Luxian earthquake and did not exhibit any further shale gas leakage after the 2021 earthquake. Furthermore, the seismogenic fault, which was impacted by the earthquake, did not damage the shale gas reservoir, causing shale gas leakage. This study provides an important foundation for future research on shale gas extraction and seismic activity in the region.

Study on the Influence of Casing Surface Morphology on the Plugging Performance of Downhole CO2 Plugging with Sn58Bi

Aimed at the problem of gas flurries in carbon dioxide (CO2) geologic sequestration in the wellbore, this paper proposes a sealing method in which the downhole casing is processed with threaded grooves and then plugged with a low-melting-point alloy plug. Based on this method, a small-scale experimental setup was developed for alloy plug molding and gas sealing in this study. Molding and gas sealing experiments with Sn58Bi alloy plugs inside casings with different surface morphologies were carried out. The gas leakage pathway was determined. The microstructure of the interface between the alloy plug and casing was analyzed using an optical microscope. The influence of the inner surface roughness, threaded groove, length-to-diameter ratio, and ambient temperature on the gas sealing performance of the alloy plugs was analyzed. The experimental results show that, with an increase in ambient temperature, the gas sealing performance of the casing increases significantly; when the inner surface of the casing is processed through threaded grooves, the gas sealing performance is better than with smooth hole casing; the gas sealing performance of the alloy plug presents an obvious linear positive correlation with their length-to-diameter ratio. This research provides theoretical support for downhole CO2 plugging using Sn58Bi in the casing.

Research on the Dynamic Leaking and Diffusion Law of Hydrogen-Blended Natural Gas under the Soil–Atmosphere Coupled Model

With the breakthrough in mixing hydrogen into natural gas pipelines for urban use, the widespread application of hydrogen-blended natural gas (HBNG) in energy delivery is imminent. However, this development also introduces significant safety concerns due to notable disparities in the physical and chemical properties between methane and hydrogen, heightening the risks associated with gas leaks. Current models that simulate the diffusion of leaked HBNG from buried pipelines into the atmosphere often employ fixed average leakage rates, which do not accurately represent the dynamic nature of gas leakage and diffusion. This study uses computational fluid dynamics (CFD) 2024R1 software to build a three-dimensional simulation model under a soil–atmosphere coupling model for HBNG leakage and diffusion. The findings reveal that, in the soil–atmosphere coupling model, the gas diffusion range under a fixed leakage rate is smaller than that under a dynamic leakage rate. Under the same influencing factors in calm wind conditions, the gas primarily diffuses in the vertical direction, whereas under the same influencing factors in windy conditions, the gas mainly diffuses in the horizontal direction.

Real-time detection of urban gas pipeline leakage based on machine learning of IoT time-series data

China is advancing urban gas pipeline safety through the strategic deployment of methane detectors. This study introduces a systematic approach for identifying underground gas leaks, and overcoming challenges such as biogas interference and environmental factors. Abnormal methane sequences, defined by expert experience, undergo data preprocessing, including cleansing, compressing, and extracting rising segments. Feature engineering is performed on these rising segments across three dimensions: temporal, volatility, and temperature features. Different classification algorithms, including K-nearest neighbor, decision tree, and support vector machine, are employed for gas leakage recognition. The decision tree proves most effective, achieving a 92.86% recall rate for methane leakage segments. Additionally, feature importance ranking from the decision tree model highlights the maximum value of preprocessed methane concentration time series and the fitting slope of the rising segment as crucial features for methane leakage detection.

Natural gas leakage detection from offshore platform by OGI camera and unsupervised deep learning

Natural gas leak from offshore platform poses a potential to cause explosion disaster and bring significant causalities and economic losses. Existing deep learning-based leak detection approaches are limited by the requirement of a large number of labeled leak datasets, and also has worse performance in the complex and changeable marine environment. This study proposes a detection approach of natural gas leakage from offshore platform by integrating optical gas imaging (OGI) camera and unsupervised deep probability learning. In this approach, unsupervised deep learning is applied to learn the changeable infrared features of offshore platform, and variational Bayesian inference is integrated to provide the larger epistemic uncertainty contour corresponding to the infrared natural gas plume. An epistemic uncertainty-based detection score is proposed as the detection criterion to improve the accuracy of natural gas plume detection and localization. An OGI imaging experiment of natural gas leak from offshore platform is conducted to construct the benchmark dataset. With such datasets, two pre-defined parameters, namely Monte Carlo sampling number m = 100 and dropout probability p=0.1 are determined to guarantee the detection accuracy and efficiency. Comparison between the proposed approach and prevalent unsupervised deep learning approach is also conducted. The results demonstrate that our proposed approach has the higher detection accuracy with AUC = 0.9753, as well as the real-time capability with inference time of 4s/frame. Overall, our proposed approach provides a more accurate and generalized approach of natural gas detection for safety monitoring and detection management of offshore platforms.

Germanium doped D-shaped PCF-SPR methane high sensitivity sensor

Abstract A D-shaped photonic crystal fiber doped with germanium dioxide methane gas sensor based on SPR effect is proposed. The substrate of the fiber is silicon dioxide doped with germanium dioxide, and the polished surface is used as a substrate for gold-plated and methane-sensitive membranes where the sensing area is in direct contact with methane gas. Effects of different germanium dioxide doping concentrations and the structural parameters of the photonic crystal fiber on the performance of the sensor are numerically investigated by the finite element method. Simulation results show that when the germanium dioxide doping concentration is 4.1%, the maximum sensitivity of sensor is 82 nm/% with a maximum resolution of 1.2195 × 10–4 in the range of 0 ∼ 3.5% methane concentration. The proposed sensor not only has a simple structure, but also exhibits high sensitivity, thus the sensor has great potential in pre-warning and remote monitoring of methane gas leakage.

Hydrocarbon accumulation and reconstruction in the Ediacaran Dengying carbonate reservoirs of the southeastern and central Sichuan Basin, SW China

The carbonate reservoirs of the Ediacaran Dengying Formation (Z2dn) in the southeastern Sichuan Basin (SESB) and central Sichuan Basin (CSB) experienced different tectonic movements during the Caledonian, Yanshanian, and Himalayan orogenies, resulting in distinct hydrocarbon accumulation processes in these two regions. Based on a detailed analysis of diagenetic sequences, pore-fluid pressure evolution, hydrocarbon charge history, and regional tectonic structural analysis, the hydrocarbon accumulation processes in the Dingshan and Ziyang areas can be divided into three stages, namely Triassic to Jurassic, Jurassic to Cretaceous, and from Late Cretaceous to the present. The first stage was characterized by the formation of paleo-oil pools, marked by an episode of oil charge in the Z2dn reservoirs, as evidenced by solid bitumen and bitumen-bearing inclusions. During the second stage, pore fluid pressure increased from normal to overpressure due to oil cracking in the favorable preservation conditions, leading to the formation of paleo-gas pools in the SESB and CSB. The timing of gas charge in the Dingshan and Ziyang area was at 173 Ma and 165 Ma, respectively, according to the trapping temperature of gas inclusions. The third stage was marked by a pressure drop from overpressure to normal pressure, possibly due to gas dissipation during the Yanshanian-Himalayan uplift. The destruction of paleo-gas pools in the Dingshan area, accompanied by gas leakage through faults and fractures, was caused by intense tectonic movement in the SESB. In contrast, the low gas productivity in the Ziyang area of the CSB was attributed to the migration of natural gas into the Weiyuan area. The fluid evolution of carbonate reservoirs and various tectonic characteristics reveal similar hydrocarbon accumulation but different reconstruction processes in the SESB and CSB, providing greater insight into the mechanism of hydrocarbon enrichment in the Sichuan Basin and other multi-cyclonic composite basins.