scholarly journals Detecting Pipeline Leaks

2017 ◽  
Vol 139 (11) ◽  
pp. 34-39
Author(s):  
Vicki Niesen ◽  
Melissa Gould
Keyword(s):  
Detection System ◽  
Leak Detection ◽  
American Petroleum Institute ◽  
False Alarms ◽  
Case Scenario ◽  
Detection Program ◽  
Computer Simulators ◽  
Improved Technology ◽  
The Impact ◽  
Do So

This article explores technological advancements for detecting pipeline leaks. An ideal leak detection system should not only quickly detect both small and large leaks, but also do so reliably and not trigger false alarms. Operations in gas pipelines can differ quite a bit from those for liquids, so the experience gained in one type of line may not be entirely applicable when changing jobs. Fortunately, computer simulators are increasingly sophisticated, enabling operators to become comfortable handling a variety of situations. In December 2015, the American Petroleum Institute released a set of guidelines (RP 1175), written by a representative group of hazardous liquid pipeline operators, that established a framework for leak detection management. The focus of the guidelines is getting pipeline operators to use a risk-based approach in their leak detection program, with the goal of uncovering leaks quickly and with certainty. The best-case scenario is for leaks to not occur at all, and the industry is making great strides to keep them from happening. The combination of improved technology and risk-based management should enable operators to keep leaks small and contained, and reduce the impact on the environment as much as possible.

A Novel Approach to Evaluating Leak Detection CPM System Sensitivity/Reliability Performance Trade-Offs

2014 ◽  
Author(s):  
Shyam Chadha ◽  
Daniel Hung ◽  
Samir Rashid
Keyword(s):  
False Alarm ◽  
Capital Investment ◽  
Performance Metrics ◽  
Leak Detection ◽  
American Petroleum Institute ◽  
False Alarms ◽  
Good Reliability ◽  
Trade Off ◽  
Trade Offs ◽  
Reliability Performance

As defined in American Petroleum Institute Recommended Practice 1130 (API RP 1130), CPM system leak detection performance is evaluated on the basis of four distinct but interrelated metrics: sensitivity, reliability, accuracy and robustness. These performance metrics are captured to evaluate performance, manage risk and prioritize mitigation efforts. Evaluating and quantifying sensitivity performance of a CPM system is paramount to ensure the performance of the CPM system is acceptable based on a company’s risk profile for detecting leaks. Employing API RP 1130 recommended testing methodologies including parameter manipulation techniques, software simulated leak tests and/or removal of test quantities of commodity from the pipeline are excellent approaches to understanding the leak sensitivity metric. Good reliability (false alarm) performance is critical to ensure that control center operator desensitization does not occur through long term exposure to false alarms. Continuous tracking and analyzing of root causes of leak alarms ensures that the effects of seasonal variations or changes to operation on CPM system performance are managed appropriately. The complexity of quantifying this metric includes qualitatively evaluating the relevance of false alarms. The interrelated nature of the above performance metrics imposes conflicting requirements and results in inherent trade-offs. Optimizing the trade-off between reliability and sensitivity involves identifying the point that thresholds must be set to obtain a balance of a desired sensitivity and false alarm rate. This paper presents an approach to illustrate the combined sensitivity/reliability performance for an example pipeline. The paper discusses considerations addressed while determining the methodology such as stakeholder input, ongoing CPM system enhancements, sensitivity/reliability trade-off, risk based capital investment and graphing techniques. The paper also elaborates on a number of identified benefits of the selected overall methodology.

Pipeline Rupture Detection Using Real-Time Transient Modelling and Convolutional Neural Networks

2018 ◽  
Author(s):  
Joel Smith ◽  
Jaehee Chae ◽  
Shawn Learn ◽  
Ron Hugo ◽  
Simon Park
Keyword(s):  
Neural Networks ◽  
Real Time ◽  
Detection System ◽  
High Reliability ◽  
Leak Detection ◽  
Sudden Onset ◽  
False Alarms ◽  
Pipeline System ◽  
Transient Model ◽  
Social License

Demonstrating the ability to reliably detect pipeline ruptures is critical for pipeline operators as they seek to maintain the social license necessary to construct and upgrade their pipeline systems. Current leak detection systems range from very simple mass balances to highly complex models with real-time simulation and advanced statistical processing with the goal of detecting small leaks around 1% of the nominal flow rate. No matter how finely-tuned these systems are, however, they are invariably affected by noise and uncertainties in a pipeline system, resulting in false alarms that reduce system confidence. This study aims to develop a leak detection system that can detect leaks with high reliability by focusing on sudden-onset leaks of various sizes (ruptures), as opposed to slow leaks that develop over time. The expected outcome is that not only will pipeline operators avoid the costs associated with false-alarm shut downs, but more importantly, they will be able to respond faster and more confidently in the event of an actual rupture. To accomplish these goals, leaks of various sizes are simulated using a real-time transient model based on the method of characteristics. A novel leak detection model is presented that fuses together several different preprocessing techniques, including convolution neural networks. This leak detection system is expected to increase operator confidence in leak alarms, when they occur, and therefore decrease the amount of time between leak detection and pipeline shutdown.

Near Real-Time Automated Detection of Small Hazardous Liquid Pipeline Leaks Using Remote Optical Sensing and Machine Learning

2016 ◽  
Author(s):  
Maria S. Araujo ◽  
Shane P. Siebenaler ◽  
Edmond M. Dupont ◽  
Samantha G. Blaisdell ◽  
Daniel S. Davila
Keyword(s):  
Machine Learning ◽  
Crude Oil ◽  
Real Time ◽  
Optical Sensors ◽  
Environmental Conditions ◽  
Detection System ◽  
Leak Detection ◽  
False Alarms ◽  
Different Types ◽  
Pump Stations

The prevailing leak detection systems used today on hazardous liquid pipelines (computational pipeline monitoring) do not have the required sensitivities to detect small leaks smaller than 1% of the nominal flow rate. False alarms of any leak detection system are a major industry concern, as such events will eventually lead to alarms being ignored, rendering the leak detection system ineffective [1]. This paper discusses the recent work focused on the development of an innovative remote sensing technology that is capable of reliably and automatically detecting small hazardous liquid leaks in near real-time. The technology is suitable for airborne applications, including manned and unmanned aircraft, ground applications, as well as stationary applications, such as monitoring of pipeline pump stations. While the focus of the development was primarily for detecting liquid hydrocarbon leaks, the technology also shows promise for detecting gas leaks. The technology fuses inputs from various types of optical sensors and applies machine learning techniques to reliably detect “fingerprints” of small hazardous liquid leaks. The optical sensors used include long-wave infrared, short-wave infrared, hyperspectral, and visual cameras. The utilization of these different imaging approaches raises the possibility for detecting spilled product from a past event even if the leak is not actively progressing. In order to thoroughly characterize leaks, tests were performed by imaging a variety of different types of hazardous liquid constitutions (e.g. crude oil, refined products, crude oil mixed with a variety of common refined products, etc.) in several different environmental conditions (e.g., lighting, temperature, etc.) and on various surfaces (e.g., grass, pavement, gravel, etc.). Tests were also conducted to characterize non-leak events. Focus was given to highly reflective and highly absorbent materials/conditions that are typically found near pipelines. Techniques were developed to extract a variety of features across the several spectral bands to identify unique attributes of different types of hazardous liquid constitutions and environmental conditions as well as non-leak events. The characterization of non-leak events is crucial in significantly reducing false alarm rates. Classifiers were then trained to detect small leaks and reject non-leak events (false alarms), followed by system performance testing. The trial results of this work are discussed in this paper.

scholarly journals Application-Aware Anomaly Detection of Sensor Measurements in Cyber-Physical Systems

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2448 ◽  
Author(s):  
Amin Ghafouri ◽  
Aron Laszka ◽  
Koutsoukos
Keyword(s):  
Anomaly Detection ◽  
Detection System ◽  
Traffic Signals ◽  
False Alarms ◽  
Real Time Control ◽  
Application Performance ◽  
Time Control ◽  
Anomaly Detector ◽  
Application Aware ◽  
The Impact

Detection errors such as false alarms and undetected faults are inevitable in any practical anomaly detection system. These errors can create potentially significant problems in the underlying application. In particular, false alarms can result in performing unnecessary recovery actions while missed detections can result in failing to perform recovery which can lead to severe consequences. In this paper, we present an approach for application-aware anomaly detection (AAAD). Our approach takes an existing anomaly detector and configures it to minimize the impact of detection errors. The configuration of the detectors is chosen so that application performance in the presence of detection errors is as close as possible to the performance that could have been obtained if there were no detection errors. We evaluate our result using a case study of real-time control of traffic signals, and show that the approach outperforms significantly several baseline detectors.

Real Time Statistical Leak Detection on the RRP Crude Oil Network, Holland

2002 ◽  
Author(s):  
Joep Hoeijmakers ◽  
John Lewis
Keyword(s):  
Crude Oil ◽  
Real Time ◽  
Detection System ◽  
Leak Detection ◽  
Field Application ◽  
Normal Operation ◽  
False Alarms ◽  
Pipeline Network ◽  
Oil Pipeline ◽  
Detection Systems

Prior to the year 2000, the RRP crude oil pipeline network in Holland and Germany was monitored using a dynamic leak detection system based on a dynamic model. The system produced some false alarms during normal operation; prompting RRP to investigate what advances had been made in the leak detection field before committing to upgrade the existing system for Y2K compliance. RRP studied the available leak detection systems and decided to install a statistics-based system. This paper examines the field application of the statistics based leak detection system on the three crude oil pipelines operated by RRP. They are the 177 km Dutch line, the 103 km South line, and the 86 km North line. The results of actual field leak trials are reported. Leak detection systems should maintain high sensitivity with the minimum of false alarms over the long term; thus this paper also outlines the performance of the statistical leak detection system over the last year from the User’s perspective. The leak detection experiences documented on this crude oil pipeline network demonstrate that it is possible to have a reliable real-time leak detection system with minimal maintenance costs and without the costs and inconvenience of false alarms.

CFD Analysis of a Possible Leakage of Coolant in the MEGAPIE Spallation Source Target

2005 ◽  
Author(s):  
Brian L. Smith ◽  
Sergey V. Shepel
Keyword(s):  
Structural Integrity ◽  
Detection System ◽  
Model Development ◽  
Leak Detection ◽  
Cooling Capacity ◽  
Spallation Source ◽  
Computational Fluid Dynamics Cfd ◽  
Tracking Model ◽  
The Impact ◽  
Level Set Approach

The paper reports first steps in an analysis, using Computational Fluid Dynamics (CFD), of a leak of hot (>250°C) lead bismuth eutectic (LBE) from the MEGAPIE spallation source target into the helium-filled gap between the target hull and a close-fitting, double-walled safety container. Issues addressed are: (1) determining the initial impact pressure of the LBE on the inner shell of the safety container, which could result in the gap between the shells being closed, and its cooling capacity compromised; (2) LBE freezing on the cold shell surface could delay action of the leak detection system, and hence the beam trip control; and (3) heat transfer from the hot LBE to the D2O circulating between the safety container walls could induce boiling and subsequent pressurization of the circuit. Steps in the model development needed for the simulation are described, which include, in particular, the implementation of a liquid/gas interface-tracking model based on the Level Set approach. Results confirm that the safety container will be adequately cooled by the D2O during normal target operation, but first indications are that boiling might occur within the D2O circuit if substantial amounts of LBE leak from the target vessel unless its outer surface is coated with an insulating layer. Pressures generated by the impact of a slug of LBE on the safety window do not threaten its structural integrity, and no delay of the leak detection equipment as a consequence of LBE freezing is anticipated.

Evaluating the Reliability and Sensitivity of a Leak Detection System on a Liquid Pipeline

2006 ◽  
Author(s):  
Michael Twomey
Keyword(s):  
Detection System ◽  
Evaluation Process ◽  
Leak Detection ◽  
False Alarms ◽  
Detection Systems ◽  
Number Of False Alarms ◽  
Main Challenge ◽  
Bid Evaluation ◽  
Performance Limitations

Detecting leaks in a liquid pipeline is not the most difficult task for a leak detection system (LDS); detecting leaks without giving false leak alarms is the main challenge. An operator will have trouble identifying a real leak if he has to sift through many false alarms. Therefore pipeline leak trials should test the reliability (number of false alarms) of a leak detection system as well as its ability to detect real leaks. This paper reviews how a number of pipeline operators tested their leak detection systems with simulated leaks, verifying the reliability as well as the sensitivity of their new leak detection systems. These simulated leaks were introduced by removing product from the pipeline by bleeding. The paper also outlines a simple table based on the API 1155 guidelines to evaluate software based leak detection systems that can be used as part of the bid evaluation process to hold the leak detection vendor accountable to deliver the performance promised in his bid proposal. This paper high-lights some of the performance limitations to watch for when selecting and testing an LDS, For example; will a pipeline leak detection system detect the quoted minimum leak if the normal operations include transients? Does the system block leak alarms to reduce frequent false alarms? Are the leak detection times based on the time it takes to declare a “Leak Warning” or on the time it takes to declare a “Leak Alarm”? Finally, the paper discusses how to perform more realistic leak tests.

Well Succeeded Application of Acoustic Technology for Pipelines (Single Phase and Multi Phases) Leak Detection in More Than 40 Pipelines in Brazil

2004 ◽  
Author(s):  
Julio Alonso
Keyword(s):  
Crude Oil ◽  
Single Phase ◽  
Detection System ◽  
High Sensitivity ◽  
Leak Detection ◽  
False Alarms ◽  
Production Pipeline ◽  
Oil And Natural Gas ◽  
The Government ◽  
Oil Gas

In 2001 was installed the first ALDS-Acoustic Leak Detection System in Brazil, in a multiphase (slug) production pipeline (crude oil + gas + water) in the middle the rain forest. This Leak Detection System was approved and gained confidence from the pipeline community in this country. After this, many other Acoustic Systems were installed in other multiphase pipelines, single phase as crude oil and natural gas and Naphtha, in buried and submarine pipelines. The confidence against false alarms made many pipelines operators to request the Acoustic Technology for their pipelines protection. Also, the ALDS has high sensitivity, detecting small holes. Very important consideration also deserves the leak detection speed; due the acoustic technology, the ALDS alarms the leak in seconds! This action made possible to shutdown pumps avoiding big disasters. The ALDS is also able to locate the leak, with precision of meters, even in buried or submarine pipelines. Brazil has one of the strongest laws to protect the environment (9605, from February 13th, 1998) in the word and requires leak detection system to protect any pipeline before the government approval. The ALDS is being systematically required as the most effective leak detection system.

A Study of Multi-Method Based Subsea Pipeline Leak Detection System

2016 ◽  
Author(s):  
Yanyao Li ◽  
Tianyu Zhang ◽  
Weidong Ruan ◽  
Yong Bai ◽  
Chuntian Zhao
Keyword(s):  
Pattern Recognition ◽  
Detection System ◽  
Leak Detection ◽  
Recognition System ◽  
Economic Losses ◽  
Environmental Damage ◽  
False Alarms ◽  
Ratio Test ◽  
Balance Principle ◽  
Statistical Analysis Method

Pipelines are of most importance to subsea systems. The leakage of pipelines which may be caused by aging or corrosion will lead to serious environmental damage and significant economic losses. In this paper, a submarine pipeline leak detection system is developed to protect environment and also improve the safety of subsea system via quick detection and relatively correct location. The leak detection system includes data acquisition devices, wireless communication devices, the calculation part is also involved, like data processing module, leak detection module, pattern recognition module and positioning module. The corrected flow balance principle and a statistical analysis method, namely Wald’s Sequential Probability Ratio Test (SPRT), are used to decide whether it is leak-free or leak-present. Besides, a pattern recognition system is developed to minimize false alarms. The method of Hydraulic Grade Line was employed to locate the leakage. Our study provides a quick response to leak detection as well as leak location. A quick and convenient method to leak detection and location is provided by this paper.

Optimization of Averaging Window Length and Alarming Hold Time in Volume Balance RTTM Leak Detection to Minimize False Alarms and Spill Volume

2018 ◽  
Author(s):  
Shawn Learn ◽  
Ehsan Shahidi
Keyword(s):  
Detection System ◽  
Hold Time ◽  
Leak Detection ◽  
False Alarms ◽  
Pipeline System ◽  
Window Length ◽  
Post Processing ◽  
Volume Balance ◽  
The Common ◽  
Moving Averaging

Reliability and sensitivity are two main performance metrics of leak detection systems as defined by API 1130 [1]. Proper thresholding scheme is one of the primary factors in having a sensitive and reliable leak detection system with timely detection. In RTTM leak detection, if not dealt with properly, severe pipeline pressure transients can degrade the performance of the leak detection system. One of the common basic methods of reducing the effect of pressure transients is using moving averaging windows; having looser thresholds on the shorter averaging windows, while maintaining tighter thresholds on the longer ones. The thresholds are typically set to meet the API 1149 [2] curve for the pipeline. While the post-processing of filtered data and alarm assessment has been explored via different methods such as sequential probability ratio test, to the authors’ knowledge, there is currently no systematic way of selecting the averaging windows to minimize false alarms prior to the post-processing of the average-filtered data. Moreover, to be able to maintain tight thresholds, especially in shorter averaging windows, one of the common methods is to apply dynamic thresholds, i.e. temporarily expanding thresholds when transients occur. While effective in some scenarios, the main disadvantage of this method is that the imbalance caused by a transient may not clear until the entire averaging window period is passed. This causes either extended periods of degraded performance, or more false positives. This paper utilizes an alarming hold time (also referred to as alarm persistence [3]) to remedy this problem where the averaging window length is reduced while maintaining detection time and sensitivity. To find the optimal set of threshold values, hold times, and averaging window lengths, a Particle Swarm Optimization (PSO) is performed. The ‘fitness function’ of the optimization algorithm is designed to minimize total spill volume for leak scenarios and have minimum false alarms for no-leak scenarios. The former is achieved via setting the objective function to the spill volume and the latter is enforced via applying constraints to the optimization algorithm. For no-leak scenarios, the historical operational data of a pipeline system is used. For leak scenarios, the historical data is modified by introducing a bias in the inlet volume of the section to simulate a leak. The result of the PSO provides a set of alarming parameters, threshold value, averaging window length, alarm hold time, and clearing threshold that provide the minimum false alarm rate and spill volume for different detectability ranges. The optimization method proposed in this paper can be applied to any mass or volume balance-based leak detection system that utilizes moving averaging windows. However, the leak detection parameters found with this method depend on the pipeline system.

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