Leak Location Research Articles

Sustained Casing Pressure Assessment Based on Gas Leakage Rate by the State of Equation for Real Gas

ABSTRACTGas leakage is one of the most concerning issues in wells for exploring conventional or unconventional oil and gas reservoirs, carbon sequestration, and geothermal energy. Wellbore barriers, such as tubing, casing, and cement, are the primary components that prevent the undesirable flow of subsurface fluids. However, due to the complexity of the operating condition in a harsh environment, the tubing integrity is prone to failure, causing gas leakage and forming a sustained casing pressure (SCP) at the wellhead. This work proposes a prediction model considering the real gas effect when evaluating SCP. The proposed model involves gas flow, leakage, and accumulation in the wellbore. With the pressure and temperature obtained by the flow equations as boundaries, the model estimates the gas flow rate at the leakage point and SCP. Subsequently, comparing the current leakage model with the conventional method demonstrates the model's performance. Finally, the current model is applied to an ultra‐deep well to determine the leakage location by inversion. Further sensitivity studies reveal the influences of wellbore conditions on SCP, including the production rate, depth of liquid level, and annular fluid density. The study indicates that the traditional method based on ideal gas underestimates the mass flow rate by approximately 22% compared to the current model. When the adiabatic index of the conventional method is approximated as the isentropic coefficient, the mass flow rate may agree well with the current model. It is acceptable to predict the leakage flow rate by assuming that the production gas is pure methane and ignoring the influence of gas composition. The leakage position is the most influential factor for SCP. These results would help engineers predict SCP and determine the leakage location in wells.

Water Pipeline Leak Detection Method Based on Transfer Learning

In order to improve the accuracy of leakage detection in water pipelines, this paper proposes a novel method based on Transformer and transfer learning. A laboratory test platform was established to obtain datasets with rich leakage characteristics. An enhanced feature extraction technique using a shift window input method mapped the NPW sequences into embedding vectors, effectively capturing the fine-grained features while reducing the sequence length, thereby enhancing the Transformer’s retention of sequence details. An improved Transformer encoder was pre-trained on the Experimental pipeline dataset and refined with limited leakage data from real pipelines for accurate detection. Additionally, a novel signal difference-based method was introduced for precise leak localization. The pressure signal was denoised, and the inflection points were identified by subtracting two signals. The points between the inflection and lowest signal points were traversed, with slope calculations optimizing the time delay computations. A leakage simulation test was conducted on a section of a raw water pipeline in Shanghai, and the test results confirmed the effectiveness of these methods. A 100% detection rate, zero false alarms, and a relative positioning error of less than 3.14% were achieved on a test set of 45 instances.

Distributed Fiber Optic Strain Sensing Technology for Monitoring Soil Deformation Induced by Leakage in Buried Water Pipelines: A Model Test Study.

Water pipelines in water diversion projects can leak, leading to soil deformation and ground subsidence, necessitating research into soil deformation monitoring technology. This study conducted model tests to monitor soil deformation around leaking buried water pipelines using distributed fiber optic strain sensing (DFOSS) technology based on optical frequency domain reflectometry (OFDR). By arranging strain measurement fibers in a pipe-soil model, we investigated how leak location, leak size, pipe burial depth, and water flow velocity affect soil strain field monitoring results. The results showed that pipeline leakage creates a "saddle-shaped" spatial distribution of soil strain above the pipeline, effectively indicating ground subsidence locations. When only one survey line is arranged, it is preferable to place the optical fiber directly above the pipeline. Surface monitoring fibers primarily detected tensile strain, with more pronounced peak values observed under conditions of larger leak size, higher flow velocity, shallow burial depth, and top-pipe leakage location. Monitoring fibers below the pipeline showed mainly unimodal distribution, with peak strain coinciding with the leak location. The sequential timing of strain changes at different fiber positions enabled the determination of soil seepage direction. This study demonstrates that DFOSS technology can provide important support for the early warning of such geological disasters.

Application of an adaptive observer for the detection and location of pipeline leak

Leakages in hydrocarbon transport pipelines are a recurring problem. Their real-time diagnosis is a priority task. Timely resolution of leaks helps avoid human casualties, environmental harm, and infrastructure damage. This work focuses on simulating the hydrodynamic behavior along a pipeline to enable timely leak detection and localization through a novel computational tool. The proposed mathematical model identifies discrepancies between the mass and momentum equations and an adaptive observer’s estimation, which considers the leaking fluid like a system perturbation. The flow volume balance method confirms the existence of a leakage. A fluid quantifier estimates the total leaked volume during the detection period. The estimation error between the measured and estimated variables for the adaptive observer approximates the leakage location. The developed software was validated by comparing the results with a real leak scenario in a 20-inch diameter, 15 km long liquefied petroleum gas pipeline. The results demonstrate the tool’s feasibility for real-time leak detection, localization, and quantification, showcasing its potential for addressing recurring pipeline leaks.

Water Pipeline Leak Detection and Localization With an Integrated AI Technique

Water Pipeline Leak Detection and Localization With an Integrated AI Technique

Acoustic leak localisation based on multipath identification

Acoustic leak localisation based on multipath identification

An Analytical Solution for the Steady Seepage of Localized Line Leakage in Tunnels

This paper proposes an analytical solution for the seepage field when a localized line leakage occurs in a tunnel by accurately considering the boundary conditions at the leakage site, which overcomes the problem of current methods, such as the equivalent method or methods improving on the existing analytical solution for fully drained tunnels, being unable to give an accurate analytical solution. First, the semi-infinite seepage region is converted into a rectangular seepage region using two conformal transformations. Subsequently, in order to accurately consider the boundary conditions at the leakage site, the rectangular seepage region with a discontinuous boundary is divided into three subregions with continuous boundaries, and the water head solution for each subregion is given by using the separated variable method. Finally, the principle of orthogonality of trigonometric functions is specially adopted to construct a non-homogeneous system of equations to solve the unknowns in the analytical solution, and through the inverse transformation of the conformal transformation, an analytical solution for the steady-state seepage field when localized line leakage occurs in a tunnel is obtained. The solution proposed is verified by its satisfactory agreement with the numerical simulation results and existing experimental results, and is much more accurate than the existing analytical solution. In addition, the proposed analytical solution is much less computationally demanding compared to numerical simulations. Finally, the capability of the proposed analytical solution is demonstrated by a parametric analysis of the tunnel burial depth, leakage location, and leakage width, and some meaningful conclusions are drawn.

AIoT-Driven Leak Detection in Real Water Networks Using Hydrophones

AbstractAcoustic sensing technology is a familiar approach to detect leakage in urban water networks. Critical issues like false alarms, difficult leak locations, missed leaks, unknown site conditions, and high repair costs are still prevalent. The situation warrants developing a more sophisticated and efficient leak detection approach in real water networks. Hydrophone based acoustic technology has a strong promise for high precision detection of leaks. However, AIoT approach using hydroacoustic data for real water leak detection are rarely reported. The current study, therefore, proposes an integrated signal analysis and machine learning-based ensemble model for leak detection using a hydrophone-based smart IoT system. The results show that the most significant features are peak frequency and maximum amplitude. Random forest is the most robust classifier for cost effective long-term monitoring, and the proposed voting ensemble classifies leaks and no leaks with high accuracy on both unseen data and new sites. Specifically, proposed models have very few alarms and missed leaks are reported, a significant problem in models developed using accelerometers and noise loggers. The study shows a significant contribution to the domain of leak detection for real urban water networks.

Genetic algorithm optimized frequency‐domain convolutional blind source separation for multiple leakage locations in water supply pipeline

Genetic algorithm optimized frequency‐domain convolutional blind source separation for multiple leakage locations in water supply pipeline

A Numerical Study of the Leakage and Diffusion Behavior of Hydrogen Dispensers in Hydrogen Refueling Stations Under Different Leakage Conditions

The investigation of hydrogen leakage and diffusion behavior is of great importance for the assessment of safety risks and the establishment of safety regulations for hydrogen refueling stations. However, the uncertainty associated with the location of hydrogen leaks and the complex environment pose challenges in understanding the diffusion characteristics of hydrogen leaks. In this research, a numerical analysis is performed to study the diffusion of hydrogen leaks in both horizontal and vertical directions under three different environments, considering two different sizes of leak holes. The results show that horizontal and vertical hydrogen leaks have different effects on the hydrogen diffusion behavior. The presence of a canopy and obstacles inhibits hydrogen diffusion and dilution, which could be the cause of more severe accidents. Moreover, the size of the leak hole also impacts the scale of the flammable gas cloud. The effect of leaking direction to the canopy is also considered. In comparison with the semi-open space, the pressure on the canopy is higher in an enclosed space.

Clinical analysis of 8 cases of spontaneous cerebrospinal fluid rhinorrhea with aspiration pneumonia

Objective: To investigate the clinical characteristics, treatment, and efficacy of spontaneous cerebrospinal fluid rhinorrhea (CFR) combined with aspiration pneumonia. Methods: In this case series study, a total of 8 patients diagnosed with spontaneous CFR combined with aspiration pneumonia were admitted to the Department of Otorhinolaryngology Head and Neck Surgery at Yuhuangding Hospital Affiliated with Qingdao University from March 2020 to March 2022. There were 3 males and 5 females, with ages ranging from 45 to 57 years. Endoscopic repair of CFR was performed for all patients. Retrospective analysis was conducted on the symptoms, chest CT findings, the leak location of CFR, and laboratory virological test results. The healing of the operative cavity and the recovery of pulmonary inflammation were followed up. Results: All the 8 patients had obvious postnasal cerebrospinal fluid drip with different degrees of dry cough, which was aggravated when lying flat and sleeping. Bone defects of CFR were predominantly located in the sphenoid sinus, lamina cribrosa and ethmoid roof. Chest CT scans upon admission showed multiple flocculent ground glass opacities and inflammatory changes in both lungs. Tests for TORCH (TOX, RV, CMV, HSV), EB (Epstein-Barr) virus nucleic acid, nine respiratory pathogens, 2019-nCoV oropharyngeal swab, and serum immunoglobulin(Ig)M/IgG were all negative. Seven patients were cured after endoscopic repair of CFR. CFR occurred again in one patient due to head trauma, and no recurrence was observed for 3 months after reoperation. Postoperative chest CT scans confirmed the resolution of aspiration pneumonia in all 8 patients. Conclusions: Aspiration pneumonia may arise from the aspiration of cerebrospinal fluid in patients with spontaneous CFR. Early diagnosis and timely repair of CFR contribute to the recovery of aspiration pneumonia.

Treatment of a staple-line leak after laparoscopic sleeve gastrectomy using an esophagoduodenal Niti-S Mega-stent.

A 56-year-old female with class 3 obesity, was previously submitted to laparoscopic sleeve gastrectomy (LSG) two weeks before current admission. The patient was admitted due to fever, abdominal pain and vomiting. CT revealed a 13.5cm collection between the gastric wall and left hepatic lobe. Piperacillin-Tazobactam was initiated, and percutaneous drainage of the purulent collection was performed. The upper endoscopy showed pus in the gastric lumen and a 10-mm leak at the esophago-gastric junction with contrast extravasation. Argon plasma coagulation (40W, 2L/min) was applied at the orifice margins to promote healing. After 0,038'' guidewire placement through the proximal jejunum, a Niti-S™-MEGA™ (Mega-Stent) 28x230mm (Taewoong Medical™) was deployed under fluoroscopic control. CT at 72h showed absence of leakage. Oral nutrition was started uneventfully. Ambulatory endoscopy was scheduled for eight weeks later to remove the stent, which was easily accomplished with a foreign body forceps. Granulation tissue was observed in the previous leak location and no extraluminal contrast was observed at fluoroscopic evaluation, confirming complete healing and successful endoscopic treatment. Three weeks after stent removal, the patient presented with dysphagia. Upper endoscopy revealed a short and narrowed lumen stenosis at 28cm from the incisives, which was easily manage through TTS balloon dilation. No additional complications were observed.

High-accuracy detection and location of gas leaks based on adaptive weighted data fusion using an ultrasonic transducer array

This paper proposes a gas leak detection and location method with high accuracy based on an adaptive weighted data fusion algorithm using an ultrasonic transducer array. First, the approximate entropy theory is combined with a support vector machine (SVM) to judge whether there is a gas leak, achieving a recognition accuracy of 95.69%. Once a leak is identified, a leak localisation algorithm is applied. To obtain more stable features and reduce environmental noise, the sound pressure amplitude and time-delay difference are extracted using an optimised signal processing method and normalised least mean squares (NLMS) adaptive filter, respectively. The energy decay (ED) localisation algorithm is then fused with the time difference of arrival (TDOA) algorithm to determine the location of the leak. Experimental results demonstrate that under a pressure of 15 kPa in the measured container with a distance of 1 m between the leak and transducer array, the location error is within 5 mm, which is more accurate than previously proposed methods. Additionally, the adaptive weighted data fusion algorithm overcomes the limitations of the TDOA and ED algorithms.

On the Significance of Parameter Uncertainties for Prediction of Leak Noise Wave Speed in Buried Pipes

Abstract The modern world is facing the challenging issue of water wastage due to leaks, which is causing severe economic, environmental and social impacts. Consequently, the inspection and maintenance of buried water pipes is crucial and there is still a lack of investigations towards the uncertain parameters affecting the wave speed associated with the predominantly fluid-borne wave s=1, the main carrier of leak noise. This study investigates the effects of uncertainties present in the pipe and soil parameters which are affecting the speed of propagation of the leak noise wave. To achieve this, a sensitivity analysis is performed using Monte Carlo simulations and Sobol’ indices. Uncertainties are commonly associated with the material and geometrical properties of the pipe along with the surrounding soil characteristics. However, the significance of these parameters varies depending on the type of soil in which the water pipe is buried. In clay soil, the soil-related parameter plays a crucial role compared to sandy soil and this is verified through some experimental work carried out in two water pipe systems with very different properties, one in the UK and the other one in Brazil. This research is of fundamental importance for determining the most critical parameters affecting the leak noise wave, allowing to evaluate and integrate uncertainty information into decision-making of current technologies, such as loggers and leak noise correlators, aiming enhanced detection and location of water leakage in buried plastic water pipes.

SENSITIVITY ASSESSMENT OF A GRADIENT-BASED LEAK LOCALIZATION PROCEDURE FOR PRESSURE SENSOR FAULTS USING A LABORATORY MODEL OF A TRANSMISSION PIPELINE

This research addresses the topic of leakage localization in liquid transmission pipelines. Particularly, it deals with the standard gradient-based procedure used for performing such a task. The procedure relies on pressure gradient calculations based on pressure data collected from measurement points distributed along the pipeline. This study aimed to verify this procedure regarding its sensitivity to typical systematic errors related to pressure transducers. The primary measure evaluated was the accuracy of the calculated coordinate of a leak spot. The uncertainty of the leak localization result was also estimated following the Guide to the Expression of Uncertainty in Measurement convention. A laboratory model of the pipeline was used to practically implement and test the procedure. During experiments, low-intensity leakages with a level of 0.25–2.00% were simulated. Regarding typical systematic errors, the bias (zero moving) type and the proportional ratio type were considered, which were numerically simulated in the measurement data. The findings reveal how sensitive the examined procedure is in relation to these errors, considering their different levels and scenarios related to used pressure transducers.

Dynamic evolution of flame and overpressure of leakage and explosion of hydrogen-blended natural gas in utility tunnels

In order to ascertain the true characteristics of the leakage explosion loads of hydrogen-blended natural gas (HBNG) in utility tunnels, the influence of leakage location on the concentration field distribution of HBNG leakage in utility tunnels was studied through the CFD technique. Furthermore, the characteristics of explosion flame and overpressure load distribution of HBNG of inhomogeneous distribution under effect of different ignition delay times and ignition positions were also investigated. The results show that the greater the distance between the leakage location and the air outlet, the more readily HBNG can propagate throughout the utility tunnel. This, in turn, leads to more prominent downstream gas cloud stratification. The development of explosion flame is primarily seen in the direction of low resistance and ample space within the utility tunnel. With the increase in ignition delay time (tid) and the backward shift of the leakage location (Llk), the average flame velocity generally exhibits a decreasing trend. Overall, the peak overpressure exhibits a concave trend. Under circumstances where the leakage source is in the front or middle section of the tunnel, the average peak overpressure demonstrates a general tendency of increase followed by decline with the increase in tid. In comparison, in the case of a leakage source located at the back end, it decreases gradually as tid increases. The most severe explosion overpressure load is readily induced when the leakage source is located at the front end. In the case of a leakage source located in the front section of the tunnel, the overpressure load at each measuring point decreases continuously and then rises as the ignition position moves backward. However, in the case of a leakage source located in the rear section of the tunnel, the average value of peak overpressure induced by ignition in the middle of the tunnel is the greatest, while the average value of peak overpressure induced by ignition at the back end is the smallest. The maximum explosion overpressure load is found at the front-most leakage source under front-end ignition conditions. The findings of this study offer scientific substantiation for the structure of the utility tunnel, which is designed for explosion withstanding, prevention, and control as well as risk assessment.

Research on hydrogen diffusion and sensor arrangement strategy in a marine engine room

This paper investigates the diffusion behavior and spatiotemporal concentration distribution of hydrogen in the marine engine room under different leakage conditions. By analyzing the response times and alarm rates of sensors, it identifies the optimal positions for sensor installation. When hydrogen leaks in the upper and lower layer sequentially, the maximum diffusion volumes within 150s are 1804.0 m3 and 2281.9 m3, while the minimum diffusion volumes are 784.7 m3 and 1377.9 m3. These findings reveal significant differences in hydrogen diffusion behavior under different leakage locations and directions. Sensor arrangement recommendations are made for specific height ratios (h/H) where alarm rates are highest and response times shortest. The recommended installation positions are S4∼S6, S11∼S12 at h/H = 0.30, and S6, S12∼S11, S16, S25 at h/H = 0.52, and S3, S19, S2, S5, S10, S14, S20∼S22 at h/H = 0.97, as well as near the interfaces of hydrogen pipelines, valves, and gas equipment interfaces with a high risk of leakage.

Optimizing acoustic signal processing for localization of precise pipeline leakage using acoustic signal decomposition and wavelet analysis

Pipelines play a crucial role in today's infrastructure. However, they are easily affected by environmental conditions. Therefore, regular inspections are essential to ensure the integrity of pipelines. This study introduces a new approach that combines variation mode decomposition (VMD) and empirical wavelet transform (EWT) with continuous wavelet transform (CWT) for acoustic data to improve the signal-to-noise ratio (SNR) and accurately detect pipeline leakage location in the time domain.The acoustic data was gathered in three distinct scenarios inside an open environment, where external noise considerably influenced the original signal.VMD and EWT are employed to enhance the signal-to-noise ratio (SNR). VMD efficiently distinguishes high-frequency noise and assures distinct mode separation, whilst EWT delivers precise temporal localization for non-stationary signals. Based on the results of VMD and EWT, certain IMFs were selected for further study and SNR is computed among the respective chosen IMFs and original signals to measure the improvement. Subsequently, the CWT was utilized on the chosen IMF for feature extraction, effectively finding leakage locations in the time domain.This study illustrates the feasibility of successfully mitigating noise and extracting signals in open and noisy environments, thus enhancing the accuracy of leak detection. The results establish a robust basis for subsequent investigations in pipeline leak detection and demonstrate the applicability of advanced signal processing approach to real-time leak detection systems.

Localization of hidden leaks in water supply networks by hydraulic methods

AbstractThe hydraulic gradient method is an effective approach for localizing hidden leaks in water supply networks. Relative errors in leakage location depend significantly on head measurement errors, necessitating the use of high-precision pressure gauges with an accuracy class of 0.25 or better. An optimization function, defined as the ratio of the localization relative error to the probability of detection, was used to determine the optimal location for the control section. Dependencies of localization relative error on the pressure gauge accuracy class, section length, and piezometric head are obtained. Presented multi-leakage estimation model enables the assessment of the multi-leakage probability, enhancing decision-making efficiency for emergency repairs in water supply networks.

Oil pipeline multiple leakage detection and localization based on sensor fusion

Oil pipeline simultaneous leak localization solely using pressure and flow rate measurements at its boundaries is inherently challenging. Localizing simultaneous leaks in a long-distance oil pipeline solely using pressure and flow rate measurements at its boundaries presents significant challenges. This difficulty is attributed to the presence of noisy measurements and the interdependence of two equations that incorporate variables associated with leaks, leading to inherent uncertainty. Additionally, existing leak detection methodologies predominantly utilize a single sensor, which contributes to a high incidence of false alarms, particularly in complex operational environments. Developing nonlinear equations based on momentum and continuity principles is proposed as a comprehensive solution for estimating multiple leak locations in oil pipelines. In this study, multiple leaks in long-distance oil pipelines are estimated using a two-stage decision-making scheme. Arrays of sensors are proposed for improving the reliability and accuracy of simultaneous leak estimations, replacing the traditional reliance on single sensors along pipelines. The Fisher fusion technique combines inaccurate measurements to improve estimation accuracy. This method integrates sensor measurements even when noise is present, demonstrating its effectiveness. Comprehensive simulationsare conductedusing OLGA multiphase flow simulation software to evaluate the robustness and practicality of the proposed approach under various real-time conditions found in long-distance oil pipelines. The system’s state convergence and precision in simultaneous leak estimations highlight the effectiveness of the proposed strategy in oil pipeline control. Across various scenarios, the leak detector showed a 28 % improvement for a 50 Km oil pipeline.