Research on Leak Monitoring Technology for Product Oil Pipeline

2012 ◽  
Author(s):  
Dongliang Yu ◽  
Bin Xu ◽  
Likun Wang ◽  
Dongjie Tan ◽  
Hongchao Wang ◽  
...  
Keyword(s):  
Acoustic Wave ◽  
Negative Pressure ◽  
Pressure Wave ◽  
Mechanical Damage ◽  
Pipeline System ◽  
Accident Risk ◽  
Long Distance ◽  
Chemical Corrosion ◽  
Oil Pipeline ◽  
Negative Pressure Wave

As an important tool for the long-distance transportation of product oil, pipeline construction has being developed rapidly in recent years in the world. In the long-term running, leak will occur occasionally and seriously endanger the operation safety of the pipeline system, which may be caused by internal & external factors including pipe aging, mechanical damage, chemical corrosion, and natural disaster, etc. In order to timely find out and accurately locate the leakage, and reduce the economic loss and the accident risk, it is necessary to research into leak monitoring techniques and apply them in field. Compared with crude oil pipeline, due to multi-batch transportation, multi-distribution operation and frequent regulation, leak monitoring for product oil pipeline is much more difficult. Once leak occurs, the oil loss at the leakage point induces an oil pressure drop, causing negative pressure wave as well as acoustic wave. Through analyzing negative pressure wave signals and acoustic wave signals acquired by sensors, it can find out and locate the leakage. For interference signals like background noises in the product oil pipeline, wavelet packet decomposition technology is used to denoise the acquired negative pressure wave signals and acoustic wave signals, and extract the feature signals. Meanwhile, the signal velocity in product oil is calculated dynamically to improve the location accuracy. Field Tests indicate that the technology combining negative pressure wave and acoustic wave is accurate and reliable, and has good performance.

Application of SOM Network in Ship Pipeline Leakage Detecting

2012 ◽  
Vol 468-471 ◽  
pp. 538-541 ◽  
Author(s):  
Hong Hao Yin ◽  
Hui Chen ◽  
Zhong Bo Peng
Keyword(s):  
Neural Network ◽  
Working Conditions ◽  
Negative Pressure ◽  
Pressure Wave ◽  
Oil And Gas ◽  
Pipeline System ◽  
Data Sampling ◽  
Long Distance ◽  
Som Network ◽  
Negative Pressure Wave

At present, ship pipeline leakage has become a great hidden risk of safe navigation and environmental pollution, but piping detecting technology mostly focuses on long-distance oil and gas pipeline, and does a little on the complicated pipeline system, for example, ship pipeline system. The frequently-used leakage detecting of negative pressure wave method, because the frequent adjustable pump or reset valve of ship pipeline system will also produce the negative pressure wave, may easily fail to report or even misreport. In order to monitor ship pipeline leakage effectively and greatly reduce fault alarm rate and missing alarm rate, SOM network (self-organizing feature map neural network) had been used to identify leakage from different working conditions. At first, the waveform characteristics of pressure and flow signals were analyzed by kurtosis calculating to obtain condition eigenvectors. From data sampling in terms of pipe working conditions, learning samples were obtained. Accordingly, the nonlinear mapping between SOM neural network inputs and outputs were well established via training. Afterwards, ship piping leakage was detected based on input eigenve

Projective Noise Reduction Algorithm for Negative Pressure Wave Signal Processing

2008 ◽  
Author(s):  
Dongliang Yu ◽  
Laibin Zhang ◽  
Liang Wei ◽  
Zhaohui Wang
Keyword(s):  
Noise Reduction ◽  
Negative Pressure ◽  
Pressure Wave ◽  
Random Noise ◽  
Background Signal ◽  
Long Distance ◽  
Noise Component ◽  
Wave Signal ◽  
Non Linear ◽  
Negative Pressure Wave

The appearance of a rupture, leak or damage in the long-distance oil & gas pipeline, which could cause a leak, usually generates a non-linear & chaotic negative pressure wave signal. By properly interpreting the negative pressure wave signature, it is possible to detect a leak along the pipeline. Most traditional noise reduction methods are established based on the linear system, which are not in line with the actual non-linear & chaotic situation. Therefore, the weak negative pressure wave signals, generated by small leaks, are often filtered out and cause false alarm and failure alarm. In order to resolve the problem, this paper uses the non-linear projective algorithm for noise reduction. First, the weak negative pressure wave signal series would be reconstructed using delay coordinates, in the high dimensional phase space, the background signal, the negative pressure wave signal and the noise signal are separated into different sub-spaces. Through the reconstruction of sub-spaces, the weak pressure wave signal can be isolated from the background signal as well as the random noise component reduced.

Monitoring of Natural Gas Pipeline Leaks

2010 ◽  
Author(s):  
Dongliang Yu ◽  
Likun Wang ◽  
Bin Xu ◽  
Hongchao Wang ◽  
Min Xiong ◽  
...  
Keyword(s):  
Acoustic Wave ◽  
Negative Pressure ◽  
Pressure Measurement ◽  
Pressure Wave ◽  
Wavelet Packet ◽  
Wavelet Packet Decomposition ◽  
Wave Method ◽  
Decomposition Technique ◽  
Natural Gas Pipeline ◽  
Negative Pressure Wave

Pipe is a very important tool for long-distance transportation of nature gas. In the long-term running, there will be inevitably an appearance of a rupture, leak or damage usually caused by manmade event or by nature disaster. Leaks may generate dangerous clouds of gas escaping from the high-pressure pipe and produce serious incidences involving fire and explosion endangering the life and property safety of people in and around the area. Monitoring of natural gas pipeline leaks will timely find out and locate these dangerous occurrences and reduce loss. Within the leak monitoring, the core contents are the accurate location of leaks as well as the rapid identification of different signal sources reducing false alarm ratio. Once a leak occurs, the supersonic jet of escaping gas can generate a non-linear & chaotic negative pressure wave signal based on static pressure measurement and an acoustic signal based on dynamic pressure measurement [1]. By properly interpreting these two kinds of signals together, it is possible to detect and locate the leak along the pipe. However, useful signals usually mix in the powerful backdrop signals and noises. In order to resolve the problem, the wavelet packet decomposition technique [2] is used to reduce the noises and get the feature signals of negative pressure wave and acoustic wave. Furthermore, a lot of different condition regulating signals for instance compressor start-stop, valve adjusting and gas turbulence can interfere with the accurate identification of leaks and result in false alarm. It is quite required to classify these similar signals. Thus, BP neural network [3] is used to quickly recognize the different pressure fluctuation signals. Finally, an integrated system developed by LabView is introduced to timely monitor the operation condition and locate the leak. Field tests indicate this system using negative pressure wave method, acoustic wave method, wavelet packet decomposition technique as well as BP network has a good effect.

Research of Heating Oil Pipeline Leak Detection Based on Negative Pressure Wave

ICPTT 2012 ◽  
2012 ◽  
Author(s):  
Chi Chen ◽  
Huijun Zhao ◽  
Xiaobin Wang ◽  
Ning Zhou ◽  
Shuli Wang
Keyword(s):  
Negative Pressure ◽  
Pressure Wave ◽  
Leak Detection ◽  
Oil Pipeline ◽  
Heating Oil ◽  
Negative Pressure Wave

Synergy in Leak Detection: Combining Leak Detection Technologies That Use Different Physical Principles

2014 ◽  
Author(s):  
Peter Y. Han ◽  
Mark S. Kim
Keyword(s):  
Negative Pressure ◽  
Pressure Wave ◽  
Leak Detection ◽  
Wave System ◽  
Oil Pipeline ◽  
Balance System ◽  
Volume Balance ◽  
Product Withdrawal ◽  
Negative Pressure Wave ◽  
Detection Technologies

Different leak detection technologies offer different benefits and limitations. Popular options include real-time transient models, statistical volume balance analysis and negative pressure wave systems. Atmos offers a combination of different systems to improve the leak detection performance on a pipeline. This paper outlines the very successful integration of a Statistical Volume Balance System and a Negative Pressure Wave System on a crude oil pipeline. The live product withdrawal tests demonstrated that the combined system maximized the reliability, detection speed, location accuracy and sensitivity of the overall leak detection system. This paper will examine the benefits and technical challenges of combining these two leak detection technologies. The integrated solution delivers the reliability and robustness of the Statistical Volume Balance System together with the rapid response time and location accuracy of the Negative Pressure Wave System. The field application of the two systems integrated on a 170 kilometer crude oil pipeline will be explained in detail, along with the results of some actual controlled product withdrawal tests on the pipeline.

Long Range Hot Oil Pipeline Leak Detection and Location Technique Based on Negative Pressure Wave

2006 ◽  
Author(s):  
Yibo Li ◽  
Liying Sun ◽  
Shijiu Jin ◽  
Likun Wang ◽  
Dongjie Tan
Keyword(s):  
Crude Oil ◽  
Long Range ◽  
Negative Pressure ◽  
Pressure Wave ◽  
Leakage Detection ◽  
Operational Parameters ◽  
Oil Pipeline ◽  
Oil Leakage ◽  
Transmission Pipeline ◽  
Negative Pressure Wave

Negative pressure wave (NPWs) technique is an effective method for oil leakage detection and location. However, conventional negative pressure wave technology failed to be applied to leakage location in China directly. China’s crude oil has to be transmitted over heating because of its high viscosity, high wax and high solidifying point. In this paper, conventional location method of instantaneous pressure wave was analyzed and techniques were developed to overcome the defects. Since temperature of the oil would drop continuously during transmission, temperature drop influence on physical characteristics of the crude oil and propagation velocity of pressure wave was studied in detail. In order to achieve high precision, wavelet transform algorithm was adopted to define inflexion of negative pressure wave when it propagates along the pipe, and wavelet threshold denoising technique was used to separate the characteristic inflexion of negative pressure wave when calculating the leak position. The problem of false alarms was solved by application of eigenvector indexes method. On the basis of that, a new oil leakage detection and location system was developed for hot oil transmission pipeline. In China, SCADA (supervisory control and data acquisition) system was installed on most oil transmission pipeline to monitor operational parameters for long range crude oil or product oil pipeline. Because it acquires pipeline operational parameters from the existing SCADA system, the cost and complexity of the new system was greatly reduced. The earliest leak detection and location system which installed on a hot oil transmission pipeline in PetroChina 5 years ago is still working well. It responds to leakage (1.5% of the total fluid) within 2 minutes and location error is less than 2% of the pipeline length between the two stations.

scholarly journals Application of VMD in Pipeline Leak Detection Based on Negative Pressure Wave

2021 ◽  
Vol 2021 ◽  
pp. 1-19
Author(s):  
Boxiang Liu ◽  
Zhu Jiang ◽  
Wei Nie
Keyword(s):  
Negative Pressure ◽  
Pressure Wave ◽  
Inflection Point ◽  
Time Difference ◽  
Permutation Entropy ◽  
Economic Losses ◽  
Pipeline System ◽  
Denoising Method ◽  
Noise Interference ◽  
Negative Pressure Wave

Leakage problems are common in the water supply pipeline system, which will threaten the health of residents and cause economic losses. Negative pressure wave (NPW) technology calculates the time difference through the inflection point to locate the leak. However, due to the nonlinear and nonstationary characteristics of the pressure signal, it is difficult to obtain an accurate inflection point of the NPW by the traditional method. Therefore, the advantages of applying variational mode decomposition (VMD) in NPW technology are explored. Firstly, the correlation coefficient and permutation entropy (PE) are used for effective intrinsic mode function (IMF) component selection and parameter optimization. Thus, an adaptive denoising method based on VMD (AD-VMD) is presented. Then, to effectively separate the detail features of the NPW, a novel inflection point extraction method based on VMD (IPE-VMD) is proposed. Simulation and experimental results show that AD-VMD can effectively suppress noise interference and conserve the mutation characteristic of the leakage. IPE-VMD can obtain a distinct maximum peak at the inflection point and has good robustness to noise interference. This method can calculate the time difference precisely and stably. In addition, the accuracy of the leak location is verified. The average relative positioning error is 5.13%.

A Novel IoT-Based Method for Real-Time Detection of Spontaneous Leaks in Pipelines, Gathering Systems, and Offshore Risers

2021 ◽  
Author(s):  
Matthew Grimes ◽  
Nico Van Rensburg ◽  
Stuart Mitchell
Keyword(s):  
Signal Processing ◽  
Transmission Lines ◽  
Negative Pressure ◽  
Pressure Wave ◽  
Long Distance ◽  
Non Invasive ◽  
Long Distance Transmission ◽  
Offshore Production ◽  
Offshore Risers ◽  
Oil Gas

Abstract This paper presents on a non-invasive, IoT-based method for rapidly determining the presence and location of spontaneous leaks in pressurized lines transporting any type of product (e.g., oil, gas, water, etc.). Specific applications include long-distance transmission lines, gathering networks at well sites, and offshore production risers. The methodology combines proven negative pressure wave (NPW) sensing with advanced signal processing to minimize false positives and accurately identify the presence of small spontaneous leaks within seconds of their occurrence. In the case of long-distance transmission pipelines, the location of the leak can be localized to within 20-50 feet. The solution was commercialized in 2020 and has undergone extensive testing to verify its capabilities. It is currently in use by several operators, both onshore and offshore.

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