Recent advances in pipeline monitoring and oil leakage detection technologies: principles and approaches.

Pipelines are widely used for the transportation of hydrocarbon fluids over millions of miles all over the world. The structures of the pipelines are designed to withstand several environmental loading conditions to ensure safe and reliable distribution from point of production to the shore or distribution depot. However, leaks in pipeline networks are one of the major causes of innumerable losses in pipeline operators and nature. Incidents of pipeline failure can result in serious ecological disasters, human casualties and financial loss. In order to avoid such menace and maintain safe and reliable pipeline infrastructure, substantial research efforts have been devoted to implementing pipeline leak detection and localisation using different approaches. This paper discusses pipeline leakage detection technologies and summarises the state-of-the-art achievements. Different leakage detection and localisation in pipeline systems are reviewed and their strengths and weaknesses are highlighted. Comparative performance analysis is performed to provide a guide in determining which leak detection method is appropriate for particular operating settings. In addition, research gaps and open issues for development of reliable pipeline leakage detection systems are discussed

Recent Advances in Pipeline Monitoring and Oil Leakage Detection Technologies: Principles and Approaches

Pipelines are widely used for the transportation of hydrocarbon fluids over millions of miles all over the world. The structures of the pipelines are designed to withstand several environmental loading conditions to ensure safe and reliable distribution from point of production to the shore or distribution depot. However, leaks in pipeline networks are one of the major causes of innumerable losses in pipeline operators and nature. Incidents of pipeline failure can result in serious ecological disasters, human casualties and financial loss. In order to avoid such menace and maintain safe and reliable pipeline infrastructure, substantial research efforts have been devoted to implementing pipeline leak detection and localisation using different approaches. This paper discusses pipeline leakage detection technologies and summarises the state-of-the-art achievements. Different leakage detection and localisation in pipeline systems are reviewed and their strengths and weaknesses are highlighted. Comparative performance analysis is performed to provide a guide in determining which leak detection method is appropriate for particular operating settings. In addition, research gaps and open issues for development of reliable pipeline leakage detection systems are discussed. Document type: Articl

Detection of Solids in a Flow Stream Using Ultrasonics and Advanced Algorithms

Sand passing along gas production pipelines can cause major disruption to facilities and interrupt gas flow. This research focused on improving sand flow measurement in gas pipes. It provided an improved method to measure sand flow rate using commercial Acoustic Sand Detectors. Also it provided several methods to measure sand flow rate in gas pipes using ultrasonic sensors and various signal processing techniques which were more accurate than any other methods

A novel pipeline leak detection technique based on acoustic emission features and two-sample Kolmogorov–Smirnov test.

Pipeline leakage remains a challenge in various industries. Acoustic emission (AE) technology has recently shown great potential for leak diagnosis. Many AE features, such as root mean square (RMS), peak value, standard deviation, mean value, and entropy, have been suggested to detect leaks. However, background noise in AE signals makes these features ineffective. The present paper proposes a pipeline leak detection technique based on acoustic emission event (AEE) features and a Kolmogorov–Smirnov (KS) test. The AEE features, namely, peak amplitude, energy, rise-time, decay time, and counts, are inherent properties of AE signals and therefore more suitable for recognizing leak attributes. Surprisingly, the AEE features have received negligible attention. According to the proposed technique, the AEE features are first extracted from the AE signals. For this purpose, a sliding window was used with an adaptive threshold so that the properties of both burst- and continuous-type emissions can be retained. The AEE features form distribution that change its shape when the pipeline condition changes from normal to leakage. The AEE feature distributions for leak and healthy conditions were discriminated using the two-sample KS test, and a pipeline leak indicator (PLI) was obtained. The experimental results demonstrate that the developed PLI accurately distinguishes the leak and no-leak conditions without any prior leak information and it performs better than the traditional features such as mean, variance, RMS, and kurtosis

Review: optical fiber sensors for civil engineering applications

Optical fiber sensor (OFS) technologies have developed rapidly over the last few decades, and various types of OFS have found practical applications in the field of civil engineering. In this paper, which is resulting from the work of the RILEM technical committee “Optical fiber sensors for civil engineering applications”, different kinds of sensing techniques, including change of light intensity, interferometry, fiber Bragg grating, adsorption measurement and distributed sensing, are briefly reviewed to introduce the basic sensing principles. Then, the applications of OFS in highway structures, building structures, geotechnical structures, pipelines as well as cables monitoring are described, with focus on sensor design, installation technique and sensor performance. It is believed that the State-of-the-Art review is helpful to engineers considering the use of OFS in their projects, and can facilitate the wider application of OFS technologies in construction industry

Application of Layers of Protection Analysis (LOPA) for subsea production systems - A risk based model for determination of integrity levels in a global perspective

Depletion of onshore and shallow water reserves, in combination with new subsea technology, has made the petroleum industry advance into deeper water. However, new technology also brings new risks. Since most widely accepted standards and regulations are not directly aimed for subsea systems, new methods have to be developed. By developing a LOPA-model, which can be used specifically for subsea context, this thesis intends to be a part of filling that gap. The models main objective is to evaluate subsea production system risk and to determine the appropriate safety Integrity level (SIL) for all present independent protection layers. The method is semi-quantitative in nature, which means that the model output is based on a combination of generic statistical data, expert judgement and logical reasoning. According to the model validation, the result seems to be credible due to what is economically and technically feasible. For example, when a single satellite well subsea system was evaluated it ended up with SIL3 requirements for the “isolation of well function” and lower SIL requirements for other less critical safety functions

Integrating sensors for robots operating on offshore oil and gas platforms

This thesis presents a solution to integrate sensors and instruments on a robot to be used instead of operators on unmanned oil and gas offshore platforms. Operators have various tasks from inspection to maintenance in the platforms. Because of high costs of having operators in offshore platforms, there has been always an ambitious to design a fully unmanned automated platform to decrease the costs and increase human safety in oil and gas industry. These days Robotics is quite mature to be utilized in different industries. There are few manufacturers that produce robots in order that robots perform some activities in industrial environment. But the Robot usage in offshore platforms has higher risks and they have not been used before as a rigid solution, because of inaccessibility to platforms at all conditions (such as bad weather). In this thesis, I have collected the operator tasks which are possible to be done by robots, provided main requirements to use the robots in oil and gas offshore platforms and found the sensors and instruments to be suitable to mount on the robot to measure, collect and analyze required data. Finally, the proper way for data processing and analysis was done in MATLAB Simulink to present the result of measurements and data collection. The topic of this thesis was inspired from oil and gas offshore industry and robots are going to be used in one of the largest oil and gas offshore projects in North Sea (Yggdrasil) which will be started to operate from 2027. This EPC project (Engineering Procurement Construction) has been started from 2021 and currently is ongoing in detail engineering. The information regarding operators’ tasks and required specifications for sensors and instruments were provided based on this project requirements. The report of this thesis can be used in future for the sensors and their integration on robots. It was not possible to test or prototype on existing robots within master thesis schedule because of different schedule of the master thesis and this oil and gas project. Only simulation was carried on showing the results of this thesis