Reality Check: Improving Real-Time Pipeline Monitoring Using Near Real-Time Fluid Data

2008 ◽  
Author(s):  
Joseph Jutras ◽  
Rick Barlow
Keyword(s):  
Real Time ◽  
Detection System ◽  
Leak Detection ◽  
Fluid Type ◽  
Transient Model ◽  
Oracle Database ◽  
Detection Model ◽  
The Past ◽  
Batch Data ◽  
Time Injection

MBS, the software based leak detection system employed by Enbridge, is a real time transient model and as such requires fluid characteristics of the various batches that enter the pipeline. In the past, of the 25 plus pipelines modeled, only 4 received fluid identifiers from the field. These fluid identifiers are a sub-string of the batch identifiers stored in flow computers located at custody transfer locations. On the remaining pipelines, Enbridge used fluid density from the field to infer fluid type and therefore characteristics. In the past whenever a number of fluids had the same density, MBS assigned a best-guess of fluid type. The ‘MBS Real Time Injection Batch Data’ project was proposed to bring fluid identifiers to MBS on the remaining lines with the purpose of improving MBS’ selection of fluid properties. Since injection points on the remaining lines were not custody transfer there were no flow computers at these locations. An existing application called Commodity Movement Tracking, or CMT, was used to provide fluid names to the leak detection model. CMT holds past, present, and future injection batch information in an Oracle database. Batch identifiers are queried, placed into the SCADA system, and forwarded on to MBS. This paper explores the new approach, introduced by the ‘MBS Real Time Injection Batch Data’ project, of providing MBS with batch identifiers.

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.

scholarly journals Computer-Aided Colon Polyp Detection on High Resolution Colonoscopy Using Transfer Learning Techniques

Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5315
Author(s):  
Chia-Pei Tang ◽  
Kai-Hong Chen ◽  
Tu-Liang Lin
Keyword(s):  
Real Time ◽  
Transfer Learning ◽  
Early Recognition ◽  
Detection System ◽  
Colon Polyp ◽  
Colon Polyps ◽  
Polyp Detection ◽  
Detection Model ◽  
Real Time Detection ◽  
Polyp Type

Colonoscopies reduce the incidence of colorectal cancer through early recognition and resecting of the colon polyps. However, the colon polyp miss detection rate is as high as 26% in conventional colonoscopy. The search for methods to decrease the polyp miss rate is nowadays a paramount task. A number of algorithms or systems have been developed to enhance polyp detection, but few are suitable for real-time detection or classification due to their limited computational ability. Recent studies indicate that the automated colon polyp detection system is developing at an astonishing speed. Real-time detection with classification is still a yet to be explored field. Newer image pattern recognition algorithms with convolutional neuro-network (CNN) transfer learning has shed light on this topic. We proposed a study using real-time colonoscopies with the CNN transfer learning approach. Several multi-class classifiers were trained and mAP ranged from 38% to 49%. Based on an Inception v2 model, a detector adopting a Faster R-CNN was trained. The mAP of the detector was 77%, which was an improvement of 35% compared to the same type of multi-class classifier. Therefore, our results indicated that the polyp detection model could attain a high accuracy, but the polyp type classification still leaves room for improvement.

Pipeline Diagnostics With Ultrasonic Meters

2016 ◽  
Author(s):  
Nicole Gailey ◽  
Noman Rasool
Keyword(s):  
Real Time ◽  
Measurement Errors ◽  
Flow Measurement ◽  
Detection System ◽  
Leak Detection ◽  
The United States ◽  
Time Data ◽  
Critical System ◽  
Detection Systems ◽  
Transient Models

Canada and the United States have vast energy resources, supported by thousands of kilometers (miles) of pipeline infrastructure built and maintained each year. Whether the pipeline runs through remote territory or passing through local city centers, keeping commodities flowing safely is a critical part of day-to-day operation for any pipeline. Real-time leak detection systems have become a critical system that companies require in order to provide safe operations, protection of the environment and compliance with regulations. The function of a leak detection system is the ability to identify and confirm a leak event in a timely and precise manner. Flow measurement devices are a critical input into many leak detection systems and in order to ensure flow measurement accuracy, custody transfer grade liquid ultrasonic meters (as defined in API MPMS chapter 5.8) can be utilized to provide superior accuracy, performance and diagnostics. This paper presents a sample of real-time data collected from a field install base of over 245 custody transfer grade liquid ultrasonic meters currently being utilized in pipeline leak detection applications. The data helps to identify upstream instrumentation anomalies and illustrate the abilities of the utilization of diagnostics within the liquid ultrasonic meters to further improve current leak detection real time transient models (RTTM) and pipeline operational procedures. The paper discusses considerations addressed while evaluating data and understanding the importance of accuracy within the metering equipment utilized. It also elaborates on significant benefits associated with the utilization of the ultrasonic meter’s capabilities and the importance of diagnosing other pipeline issues and uncertainties outside of measurement errors.

scholarly journals Leak Detection Systems for Short Pipelines

2000 ◽  
Author(s):  
Renan Martins Baptista
Keyword(s):  
Detection System ◽  
Leak Detection ◽  
Low Complexity ◽  
Transient Model ◽  
Service Companies ◽  
Detection Systems ◽  
Volume Balance ◽  
Pipeline Networks ◽  
Phase Liquid ◽  
Flow Detection

This paper describes procedures developed by PETROBRAS Research & Development Center to assess a software-based leak detection system (LDS) for short pipelines. These so-called “Low Complexity Pipelines” are short pipeline segments with single-phase liquid flow. Detection solutions offered by service companies are frequently designed for large pipeline networks, with batches and multiple injections and deliveries. Such solutions are sometimes impractical for short pipelines, due to high cost, long tuning procedures, complex instrumentation and substantial computing requirements. The approach outlined here is a corporate approach that optimizes a LDS for shorter lines. The two most popular implemented techniques are the Compensated Volume Balance (CVB), and the Real Time Transient Model (RTTM). The first approach is less accurate, reliable and robust when compared to the second. However, it can be cheaper, simpler, faster to install and very effective, being marginally behind the second one, and very cost-efective. This paper describes a procedure to determine whether one can use a CVB in a short pipeline.

Dynamic Modelling and Real-Time Leak Detection for NGL Pipelines

2004 ◽  
Author(s):  
Brent R. Young ◽  
J. Greg Cooke ◽  
Ron E. Daye ◽  
William Y. Svrcek
Keyword(s):  
Real Time ◽  
Detection System ◽  
Dynamic Modelling ◽  
Leak Detection ◽  
Balance System ◽  
Volume Balance ◽  
Control Scheme ◽  
Dynamic Simulation Model ◽  
Flow Pressure ◽  
Real Time Information

This paper describes the development and use of a dynamic simulation model and the implementation of a novel leak detection system. Experiences from the implementation and operation of the system will also be detailed from a user perspective. The dynamic model may be used for the transient simulation of the pipelines. The model was used to test the real-time leak detection system. The results of the simulation also prompted a change in the control scheme of the pipelines that resulted in less transient operation. The leak detection system is based upon rigorous thermodynamics and dynamic mass balance calculations driven by real-time information from field flow, pressure and temperature sensors. This system was successfully implemented to replace a simple volume balance system for NGL pipelines near Empress, Alberta.

Modeling of Ethylene in Pipeline Leak Detection System

2004 ◽  
Author(s):  
Jakob Bu¨chert
Keyword(s):  
Real Time ◽  
Detection System ◽  
Leak Detection ◽  
Practical Experience ◽  
Time Model ◽  
Pump Stations ◽  
Pipeline Model ◽  
Improve Determination

This paper describes experiences with an improved equation of state (EOS) for ethylene for an existing real time pipeline model. The main scope of the model is leak detection, batch, contaminant and pig tracking. Altogether the pipeline model includes transportation of batched liquid ethylene, ethane, propane, butane and natural gas liquids (NGL). The pipeline is approximately 1900 miles miles long and includes laterals, 33 pump stations, 9 injection/delivery stations and 5 propane terminals. Originally the model used a BWRS EOS for all the above products. At that time a number of false leak alarms were experienced related to pipeline sections containing ethylene. A case study was carried out, specifically for ethylene, to investigate the effect of replacing the BWRS EOS with a modified Helmholtz EOS. The study showed that replacing the EOS on average would improve determination of the ethylene densities by 1.6%–5.6% with an expected reduction in the alarm rate for ethylene cases by approximately 50%. As a result the modified Helmholtz EOS was implemented in the real time model. Results are presented to show the practical experience with the new EOS gained over the last years.

Remote and Intelligent Diagnostic Methods on Leakage Fault for Crude Oil Pipelines

2006 ◽  
Author(s):  
Lai-Bin Zhang ◽  
Zhao-Hui Wang ◽  
Wei Liang
Keyword(s):  
Real Time ◽  
Remote Monitoring ◽  
Data Exchange ◽  
Detection System ◽  
Leak Detection ◽  
Diagnostic Methods ◽  
Oil Fields ◽  
Detection Methods ◽  
Development Environment ◽  
Oil Pipelines

Oil and gas transportation pipelines are the key equipment in petroleum and chemical industry. At present, with the increase of transportation task in oil fields, real-time leak detection system becomes a demand that petroleum companies need to safeguard routines. At the heart of the leakage monitoring and detection procedures are the report of leakage event timely and of leakage point precisely. This paper presents a more realistic approach for using rarefaction-pressure wave technique in oil pipelines, which aims to two targets, one is the improvement of remote and intelligent degree, and the other is the improvement of the leakage location ability. This paper introduces a new scheme to meet the requirements of real time and high data transferring necessary for remote monitoring and leak detection methods for pipelines. The scheme is based on SCADA framework for remote pipeline leakage diagnosis, in which the Dynamic Data Exchange technology is utilized to construct the data-acquiring component to acquire the real-time information that could perform remote test and analysis. It also introduces a basic concept and structure of the remote leak detection system. Primarily, an embedded leak-detection package is designed to exchange the diagnostic information with the RTU data package of Modbus protocol, and then via fiber network, the SCADA-based remote monitoring and leak detection system is realized. Existing data acquisition apparatus applied in oil fields and city underground water pipeline is used, without changing the structure of pipeline supervisory system. This paper introduces the method of constructing DDE-based hot links between servers and client terminals, using Borland C++ Builder 6.0 development environment, and also explains the universality and friendliness of the method. It can easily access similar Windows’ applications simply by modifying Service names, Topic options and data Items. System feasibility was tested using negative-pressure data from oil-fields. Additionally, the applied results show that the whole running status of pipeline can be monitored effectively, and a higher automation grade and an excellent leak location precision of the system can be obtained.

Computational Pipeline Monitoring in Challenging Situations

2002 ◽  
Author(s):  
James E. Short
Keyword(s):  
Real Time ◽  
Detection System ◽  
Measurement Data ◽  
Leak Detection ◽  
Data Uncertainty ◽  
Computational Pipeline ◽  
Individual Measurement ◽  
General Terms ◽  
Pipeline Monitoring

This paper introduces a new, active methodology to modeling and leak detection intended to mitigate the effects of data uncertainty in such challenging situations, and presents three case studies. The American Petroleum Institute (API) has coined the phrase Computational Pipeline Monitoring (CPM) to encompass several methods of leak detection. The use of real-time transient hydraulic simulation tools, driven by data gathered by a Supervisory Control and Data Acquisition (SCADA) system, is one form of CPM system. Such real-time simulations impose SCADA-gathered data (typically pressures, flows, temperatures) onto a characterization of the pipeline (the model) and the fluids in the system. In a tuned CPM system, if the SCADA-gathered data cannot be successfully imposed on the model without transgressing the laws of fluid mechanics, this signifies a pipeline anomaly, which may be a release. However, in reality, many pipeline hydraulic anomalies are due to changing uncertainties in the data presented to the model and if annunciated to the pipeline operators would constitute a “false leak alarm.” While they typically are not large enough to compromise pipeline operations, uncertainties abound in the SCADA-gathered data. Even were the SCADA-gathered pressure and temperature data to contain no uncertainty, the fluid properties might not be sufficiently characterized for the simulation to accurately calculate how the fluid behaves under pressure and/or temperature changes. Measurement failure further complicates the task of the CPM application, as does slack line flow. Uncertainty in the CPM-driving data is not constant, it is ever-changing with variations in the pipeline flow rate, the characterization of the fluids in the line, and the quality of the individual measurement data, to mention only a few. CPM systems use a variety of methodologies to vary their sensitivity according to the uncertainty in the data used for their calculations. However, in general terms, the more uncertainty there is in the data, the lower the resulting system sensitivity becomes. Active features in a CPM leak detection system can mitigate the performance degradation due to varying data uncertainty.

Pipeline Leak Detection Technologies and Emergency Shutdown Protocols

2014 ◽  
Author(s):  
Gerhard Geiger
Keyword(s):  
Real Time ◽  
Potential Risk ◽  
Leak Detection ◽  
Measurement Equipment ◽  
Transient Model ◽  
Detection Systems ◽  
Emergency Shutdown ◽  
Field Instrumentation ◽  
Emergency Actions ◽  
Detection Technologies

Pipelines are the least expensive and most efficient way to move liquids and gases, but there is a high potential risk of danger in case of a leak. This paper therefore describes pipeline leak detection technologies and emergency shutdown protocols to ensure reliable and safe pipeline operations. The main focus of this paper is on internal leak detection systems which use existing field instrumentation and usually run continuously. External leak detection systems using dedicated measurement equipment such as probes and sensor cables are briefly considered. Particular emphasis will be placed on model-based techniques such as the Real Time Transient Model (RTTM) and Extended Real Time Transient Model (E-RTTM) methods. In case of a leak, appropriate emergency actions are required to limit the consequences and in particular to protect people and the environment. The last part of the paper therefore is devoted to emergency shut-down protocols.

Real-Time Intrusion Detection Based on System Call and ARTIS Model

2014 ◽  
Vol 926-930 ◽  
pp. 3157-3160
Author(s):  
Zhan Huang ◽  
Yu Ying Jiang ◽  
Lu Bin Li
Keyword(s):  
Intrusion Detection ◽  
Real Time ◽  
Intrusion Detection System ◽  
Detection System ◽  
Detection Methods ◽  
System Call ◽  
Detection Model ◽  
Fixed Length ◽  
Computer Intrusion Detection ◽  
Abnormal Behaviors

The main purpose of a computer intrusion detection system is to accurately distinguish between self and non-self. A novel intrusion detection model based on ARTIS model is proposed by introducing the Red Flower and Green Leaf concepts, and by coordinated use of RF variable length and GL fixed length detectors. Intrusion detection methods are optimized to ensure the quick detection of abnormal behaviors making the model more suitable for real-time intrusion detection and more accurately to distinguish between self-and non-self.

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