Improved Leak Detection by Method Diversity

Author(s):  
Ruprecht M. J. Pichler

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.

Author(s):  
XianYong Qin ◽  
LaiBin Zhang ◽  
ZhaoHui Wang ◽  
Wei Liang

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.


Author(s):  
Jim C. P. Liou

There are many causes for a pipeline to leak. Third party punctures usually result in sizable leaks. The onset of such leaks generates a sudden change in the pipeline pressure and flow. Methods exist that rely upon these sudden changes for leak detection. Leaks previously undetected are not detectable by such methods. These pre-existing leaks are usually small in size but can exist for long time. The cumulation of leaked products may pose a greater hazard then the larger and sudden leaks. The operational experience of major pipeline company in the United States has demonstrated that all leak detection methods have their limitations, and that complementary leak detection methods should be used simultaneously (Mears 1993). Hence, we propose a leak detection system that uses, simultaneously, two independent but complementary methodologies: mass balance and transient flow simulations.


Author(s):  
Lai-Bin Zhang ◽  
Zhao-Hui Wang ◽  
Wei Liang

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.


Author(s):  
Harry SMITH ◽  
Kirsty MCNEIL ◽  
Tom RECORD ◽  
Dan BUZATU ◽  
Georgian ILIESCU ◽  
...  

Author(s):  
David G. Parman ◽  
Ken McCoy

Pipeline risk mitigation in high consequence areas can be facilitated through the use of a high sensitivity external leak detection (HSELD) system. Such systems have been implemented for both off-site and on-site pipeline applications, including the Longhorn Pipeline (Texas) and the Madrid Barajas International Airport (Spain). We define high-sensitivity external leak detection as a leak detection system that will continuously and automatically detect very small amounts of liquid fuels and is physically independent of pipeline pumping operations. In addition, such systems monitor their own integrity on a continuous basis, without requiring periodic recalibration or operator interaction. The HSELD system we describe incorporates a distributed sensor cable, installed in a slotted PVC conduit which is run in close proximity to the pipeline. Many pipeline leaks start out as very small cracks or holes resulting from corrosion and wear. In their initial stages, such leaks go undetected by standard leak detection methods, but over time large volumes of liquid fuel may leak into the environment. In high consequence areas, such as above aquifers and other environmentally sensitive areas, the leak may go undetected until traces show up in water samples. The critical characteristic of an effective HSELD is its ability to detect and accurately locate very small volumes of liquid fuels, so that these small leaks can be identified, cleaned up and repaired before environmental damage is done.


Author(s):  
Marti´n Di Blasi ◽  
Carlos Muravchik

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.


Author(s):  
Travis Mecham ◽  
Galen Stanley ◽  
Michael Pelletier ◽  
Jim C. P. Liou

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.


Author(s):  
Rick Barlow ◽  
Ted Farquhar ◽  
Anar Tleukulov

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.


Author(s):  
Shane Siebenaler ◽  
Eric Tervo ◽  
Paul Vinh ◽  
Chris Lewis

The pipeline industry is improving its ability to detect and locate leaks through emerging technologies. There has been a variety of research in recent years aimed at further development of sensor-based technologies for leak detection. A key obstacle to retrofitting existing pipelines with leak detection technologies is the cost and risk of installing hardware, particularly those sensors that require excavation near the pipe. There are many advantages to employing leak detection systems that can leverage existing instrumentation access locations. One such technology may be negative-wave leak detection systems. Negative-wave technologies work by measuring dynamic pressure changes in the pipe. It should be noted that some negative-wave systems require line modifications to accommodate multiple transmitters. While such systems have been on the market for many years, there is insufficient data available about their performance under various pipeline operating conditions for widespread adoption. In an effort to close many information gaps on the performance envelope of negative-wave technologies, a PRCI-funded field test was performed on a 41-kilometer segment of a 30-inch diameter heavy crude oil pipeline. Products from three suppliers were installed at either end of the test segment. Actual commodity withdrawals were conducted at a remote valve site approximately 21 kilometers into the segment during various operations to test the systems’ abilities to detect the withdrawals without direct user interaction. These test points included withdrawals during steady-state flowing, pump startup, and shutdown conditions. Data were collected from each system to determine their abilities to detect leaks under various conditions, abilities to locate the leak, false alarm rates, and response times. This test provided significant insight into the performance of such systems over the range of conditions tested. The key focus of this paper is the approach for conducting such multi-vendor commodity withdrawals. This project required some unique considerations for its execution. Such considerations are also documented to provide input to others who are considering such a test.


Author(s):  
Ricardo Dantas Gadelha de Freitas ◽  
Andre´ Laurindo Maitelli ◽  
Andre´s Ortiz Salazar

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.


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