Northern Exposure: Monitoring and Testing a Subarctic Liquids Pipeline

2004 ◽  
Author(s):  
Rick Barlow ◽  
Ted Farquhar ◽  
Anar Tleukulov
Keyword(s):  
Detection System ◽  
Leak Detection ◽  
Slope Instability ◽  
Central Component ◽  
Frozen Ground ◽  
Regulatory Requirement ◽  
Integrity Monitoring ◽  
Oil Pipeline ◽  
Recent Case Study ◽  
History Of

The subarctic location of Enbridge’s Norman Wells pipeline provides unique conditions affecting both construction and operations. These include the huge variations in annual air temperature, permanently frozen ground (permafrost), hundreds of river crossings and potential slope instability. The regulatory authorities recognized this environmental sensitivity and stringent conditions for construction and operation were applied. In this difficult environment, loss of integrity must be detected rapidly and at low thresholds. To ensure that integrity monitoring maintains or improves these thresholds, frequent testing is necessary. Testing of the integrity of this remote northern oil pipeline provides significant operational challenges. This remote 869km (540 mile) NPS12 crude oil pipeline has been operating in the Canadian subarctic since 1985. This paper will outline the implementation, assessment and future directions of the integrity monitoring testing of the pipeline’s leak detection capability. The history of this pipeline in the Canadian Northwest Territories will be outlined with emphasis on the special regulatory issues of this sensitive sub arctic environment. The development of a Computational Pipeline Modeling (CPM) leak detection system to meet these regulations will be summarized with reference to the guidelines of CSA Z662, Appendix E. A central component of meeting this regulatory requirement is an annual test program that uses controlled fluid withdrawal to test the CPM system and operational responses. The special methods and procedures used to meet the challenges of this program will be noted. The extent and frequency of testing make this probably one of the most tested liquid pipeline leak detection systems in the world. These controlled fluid withdrawal tests are used to enhance the Enbridge response to operational emergencies. Many factors must be considered when designing these tests. A detailed description of the preparation and field logistics required for the pipeline CPM test will be presented. The special needs of conducting tests in an environmentally sensitive region will also be outlined. A review of how these tests address the considerations of API 1149 and API 1155 are summarized. Since pipeline completion, over 70 test events have been conducted. A recent case study will detail some of the issues associated with testing. Future plans for enhancements using additional testing methodologies will be presented with particular mention of a simulation-based alternative.

Extreme Testing: Assessing CPM Leak Detection Systems on a Northern Oil Pipeline

2012 ◽  
Author(s):  
Paul Vinh ◽  
Lichun Zhang ◽  
Rick Barlow
Keyword(s):  
Cost Benefit Analysis ◽  
Detection System ◽  
Pilot Project ◽  
Leak Detection ◽  
Lessons Learned ◽  
Appropriate Technology ◽  
Detection Sensitivity ◽  
Integrity Monitoring ◽  
Transient Model ◽  
Oil Pipeline

Pipelines in remote and ecologically sensitive regions pose special challenges for pipeline integrity monitoring. These challenges include difficulties of access, reliability issues of communication and instrumentation that may impact the leak detection technology applied in these regions. The selection, application and continuous testing of an appropriate technology to detect possible leaks are important to pipeline integrity monitoring. The paper reports theoretical assessment and extensive testing on an Enbridge subarctic liquid pipeline. It also reports the comprehensive cost-benefit analysis to guide the leak detection instrument design/configuration and the evaluation of the capabilities of alternative computational pipeline monitoring (CPM) technologies for leak detection. The selected test pipeline is an 869 kilometer (540 mile), NPS 12 inch pipeline that transports sweet crude through environmentally sensitive areas. This pipeline currently uses a real-time transient model (RTTM) style CPM as the leak detection system (LDS). The pipeline LDS is tested annually by a number of industry-recognized methodologies. These include fluid withdrawal tests, simulated leak tests and an API-1130 instrument adjustment approach. This pipeline is also assessed by API-1149 for its theoretical CPM leak detection sensitivity. A pilot project invited commercial CPM-style vendors to participate in an LDS test using data from fluid withdrawal and simulated leak tests. Five vendors responded and were included in the test suite. The paper describes the design and implementation of the test process. The results of the commercial systems are presented in aggregated form and the participating vendors remain anonymous. Performance assessment focuses on the LDS evaluation factors of sensitivity and accuracy. The paper concludes with a “lessons learned” review of issues associated with test design.

Leak Detection Method Based on Pressure Wave Change

2006 ◽  
Author(s):  
XianYong Qin ◽  
LaiBin Zhang ◽  
ZhaoHui Wang ◽  
Wei Liang
Keyword(s):  
Pressure Wave ◽  
Detection System ◽  
Sudden Change ◽  
Leak Detection ◽  
Special Focus ◽  
Oil Pipeline ◽  
Scada System ◽  
Wave Change ◽  
Ole For Process Control ◽  
Pipeline Pressure

Reliability, sensitivity and detecting time under practical operational conditions are the most important parameters of a leak detection system. With the development of hardware and software, more and more pipelines are installed with advanced SCADA (Supervisory Control and Data Acquisition) system, so the compatibility of the leak detection system with SCADA system is also becoming important today. Pipeline leakage generates a sudden change in the pipeline pressure and flow. The paper introduces leak detecting methods according to the pipeline pressure wave change. In order to improve the compatibility of the leak detecting system, “OPC (Ole for process Control)” technology is used for obtaining the pressure signals from the distributed data collection system. Special focus is given on analysis of the pressure signals. It is successful to denoise the signals by means of wavelet scale shrinkage, and to capture the leak time tag using wavelet transform modulus maximum for locating the leak position accurately. A leak detecting system is established based on SCADA system. Tests and practical applications show that it locates leak position precisely. Good performance is obtained on both crude oil pipeline and product pipeline.

scholarly journals The challenges and solution of implementing a leak detection system on a complex crude oil pipeline network in Romania

2021 ◽  
Vol 7 (1) ◽  
pp. 60-73
Author(s):  
Harry SMITH ◽  
Kirsty MCNEIL ◽  
Tom RECORD ◽  
Dan BUZATU ◽  
Georgian ILIESCU ◽  
...  
Keyword(s):  
Crude Oil ◽  
Detection System ◽  
Leak Detection ◽  
Pipeline Network ◽  
Oil Pipeline

Improved Leak Detection by Method Diversity

1998 ◽  
Author(s):  
Ruprecht M. J. Pichler
Keyword(s):  
Transient Flow ◽  
Detection System ◽  
Type System ◽  
Leak Detection ◽  
Operating Conditions ◽  
Detection Methods ◽  
Special Focus ◽  
Oil Pipeline ◽  
Knowledge Based ◽  
Noise Factors

Leak detection systems for liquid pipelines are installed to minimize spillage in case of a leak. Therefore reliability, sensitivity and detection time under practical operating conditions are the most important parameters of a leak detection system. Noise factors to be considered among others are unknown fluid property data, friction factor, instrument errors, transient flow, slack-line operation and SCADA update time. The opening characteristics and the size of leaks differ considerably from case to case. Each software-based leak detection method available today has its particular strength. As long as just one or two of these methods are applied to a pipeline a compromise has to be found for the key parameters of the leak detection system. The paper proposed illustrates how a combination of several different software-based leak detection methods together with observer-type system identification and a knowledge-based evaluation can improve leak detection. Special focus is given to leak detection and automated leak locating under transient flow conditions. Practical results are shown for a crude oil pipeline and a product pipeline.

Leak Detection in a Pipeline Using Modified Line Volume Balance and Sequential Probability Tests

2006 ◽  
Author(s):  
Marti´n Di Blasi ◽  
Carlos Muravchik
Keyword(s):  
Dynamic Range ◽  
Detection System ◽  
Real Data ◽  
Leak Detection ◽  
Normal Operation ◽  
Ratio Test ◽  
Oil Pipeline ◽  
Probability Ratio ◽  
Volume Balance ◽  
Sequential Probability

The use of statistical tools to improve the decision aspect of leak detection is becoming a common practice in the area of computer pipeline monitoring. Among these tools, the sequential probability ratio test is one of the most named techniques used by commercial leak detection systems [1]. This decision mechanism is based on the comparison of the estimated probabilities of leak or no leak observed from the pipeline data. This paper proposes a leak detection system that uses a simplified statistical model for the pipeline operation, allowing a simple implementation in the pipeline control system [2]. Applying linear regression to volume balance and average pipeline pressure signals, a statistically corrected volume balance signal with reduced variance is introduced. Its expected value is zero during normal operation whereas it equals the leak flow under a leak condition. Based on the corrected volume balance, differently configured sequential probability ratio tests (SPRT) to extend the dynamic range of detectable leak flow are presented. Simplified mathematical expressions are obtained for several system performance indices, such as spilled volume until detection, time to leak detection, minimum leak flow detected, etc. Theoretical results are compared with leak simulations on a real oil pipeline. A description of the system tested over a 500 km oil pipeline is included, showing some real data results.

High Speed Data Communications and High Speed Leak Detection Models: Impact of Thermodynamic Properties for Heated Crude Oil in Large Diameter, Insulated Pipelines — Application Pacific Pipeline System

2000 ◽  
Author(s):  
Travis Mecham ◽  
Galen Stanley ◽  
Michael Pelletier ◽  
Jim C. P. Liou
Keyword(s):  
Physical Properties ◽  
Crude Oil ◽  
High Speed ◽  
Detection System ◽  
Large Diameter ◽  
Leak Detection ◽  
San Joaquin Valley ◽  
Pipeline System ◽  
Oil Pipeline ◽  
Detection Model

Recent advances in SCADA and leak detection system technologies lead to higher scan rates and faster model speeds. As these model speeds increase and the inherent mathematical uncertainties in implicit method solutions are reduced, errors and uncertainties in measurement of the physical properties of the fluids transported by pipeline come to dominate the confidence calculations for computer generated leak alerts in the control center. The ability to collect more data must be supported by the need for better model data in order to achieve optimal leak detection system performance. This is particularly true when the products transported are non-homogeneous and have strong viscosity-vs-temperature relationships. These are characteristics of crude oils in California’s San Joaquin Valley where significant heating is required to pump these oils in an efficient manner. Proper characterization and correct mathematical expression of these physical properties in leak models has become critical. This paper presents these new developments in the context of an implementation of this new technology for the Pacific Pipeline System (PPS). PPS is a recently constructed and commissioned 209 km (130-mile), 50.8 cm (20″) diameter, insulated, hot crude oil pipeline between the southern portion of California’s San Joaquin Valley and refineries in the Los Angeles basin. Operational temperatures in this line vary from ambient to 82.2°C (180°F) with pressures ranging from 345 kPa (50 psi) to 11,720 kPa (1700 psi). Due to the unique geometry of the line, facilities along the route include pumping stations, metering stations and numerous “throttle-type” pressure reduction facilities. On PPS, a high-speed leak detection model is supported by a fiber optic (OC-1) communication backbone with data rate capacities in excess of 50 Megabits Per Second (MPS). Total scan times for the distributed communication system have been reduced to 1/4 second — each facility reports data to the SCADA host four times each second. A corresponding 1/4 second leak detection model cycle leads to selection of Methods of Characteristics segments on the order of 260 meters (850 feet). This resolution, in conjunction with the advanced instrumentation package of PPS, makes detection of very small leaks realizable. This paper starts with an overview of the system and combines a mix of the theoretical requirements imposed by the mathematical solutions with a practical description of the laboratory procedures and propagated experimental errors. The paper reviews temperature-related errors and uncertainties and their influence on leak detection performance.

A Wavelet Approach to Pipeline Leak Detection by Pressure Analysis

2004 ◽  
Author(s):  
Ricardo Dantas Gadelha de Freitas ◽  
Andre´ Laurindo Maitelli ◽  
Andre´s Ortiz Salazar
Keyword(s):  
Wavelet Transforms ◽  
Intelligent System ◽  
Detection System ◽  
Leak Detection ◽  
Oil Field ◽  
Phase Flow ◽  
Time Frequency ◽  
Oil Pipeline ◽  
Multi Phase Flow ◽  
Multi Phase

One of the most challenging tasks in an oil field is implementation of a software-based leak detection system on a multi-phase flow pipeline. When a leak occurs in a multi-phase flow pipeline, the flow cannot be measured with accuracy. So, none of the various pipeline leak detection methodologies can offer good performance on a multi-phase flow pipeline. This paper will discuss implementation of a leak detection system in a particular oil field using state-of-the-art signal processing techniques to apply to the data collected in a oil pipeline. This leak detection system is still in development and uses a more practical approach to the problem than traditional methods and was implemented on a PC under the Windows operating system. Windowing, joint time-frequency analysis and wavelets were considered to develop methods of detecting leaks by watching for the wavefront. The idea behind these techniques is to cut the signal of interest into several parts and then analyze the parts separately. It is impossible to know the exact frequency and the exact time of occurrence of the leak frequency in a signal. In other words, a leak signal can simply not be represented as a point in the time-frequency space. It is very important how one cuts the signal to implement the analysis. The wavelet transform or wavelet analysis is probably the most recent solution to overcome the shortcomings of the Fourier transform. The wavelet transforms are used to perform atomic decompositions of the pressure signal that comes from a single point of a pipeline. A number of time-frequency decompositions are attempted. What is expected of this decomposition is that it fits the perceptible changes in the pressure and then an Artificial intelligent System (AIS) decides if the variations in the signal are inherent (common-cause variations) or external to the process (failed instrument, occurrence of a leak, causes that are not part of the process). The AIS learns about continual changes in the pipeline. This is useful as pipeline operation always changes and instrument drift could occur over a long time period.

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.

OIL PRODUCTS EXPORT CONTROL BASED ON ARTIFICIAL NEURAL NETWORK

2018 ◽  
pp. 43-52
Author(s):  
Timur Rafaelevich Vasiliev ◽  
Andrey Gennadievich Kokuev
Keyword(s):  
Neural Network ◽  
Measurement System ◽  
Flow Measurement ◽  
Detection System ◽  
Leak Detection ◽  
Diagnostic Systems ◽  
Factors Affecting ◽  
Oil Pipeline ◽  
Advantages And Disadvantages ◽  
The Neural Network

The operation principle of the parametric leak detection system in oil pipeline systems is considered. The structure of this leak detection system is described. Factors affecting the accuracy of flowmeters measurement used in leak detection are analyzed. Characteristics and features of operation and installation of ultrasonic flowmeters are considered. The analysis of works which investigate creating diagnostic systems of flowmeters is carried out. Their advantages and disadvantages are described. The aim of the study is to develop a flow measurement system using indirect parameters, which could diagnose the state of its testimony and double measuring tools during their systematic maintenance or repair. A virtual sensor acts as a system and is implemented on the basis of software and is capable of duplicating the flowmeter. The structure of the neural network is given on the basis of which this system is built. A possible example of application of this measurement system has been considered. Application of neural network for solving this problem will allow to create a mathematical model of measurement that is not dependent on uncontrolled parameters. Implementation of this neural network solves the problem of artificial generation of signals from sensors used in the calculation of the system of detecting leaks at the time of their output. The preliminary results of the research are presented. The results obtained in the process of model realization are compared with experimental data.

Commissioning a Real-Time Leak Detection System on a Large Scale Crude Oil Pipeline During Start Up

2006 ◽  
Author(s):  
Joanna Mabe ◽  
Keefe Murphy ◽  
Gareth Williams ◽  
Andrew Welsh
Keyword(s):  
Crude Oil ◽  
Real Time ◽  
Large Scale ◽  
Detection System ◽  
Leak Detection ◽  
Oil Pipeline ◽  
Start Up ◽  
Environmental Requirements ◽  
The Moment ◽  
Operational Data

This paper describes the process of incremental pipeline filling and the phased commissioning of a real-time leak detection system for the 1768 km long BTC crude oil pipeline. Due to stringent environmental requirements, it is essential for the leak detection system to work from the moment that crude oil is introduced into the pipeline. Without any prior operational data and with the pipeline partially filled, it is challenging for the leak detection system to monitor the integrity of the pipeline throughout the whole filling process. The application of the pig tracking software to track the oil front as the crude displaces nitrogen is also discussed.

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