Marine baseline and monitoring strategies for Carbon Dioxide Capture and Storage (CCS)

The QICS controlled release experiment demonstrates that leaks of carbon dioxide (CO2) gas can be detected by monitoring acoustic, geochemical and biological parameters within a given marine system. However the natural complexity and variability of marine system responses to (artificial) leakage strongly suggests that there are no absolute indicators of leakage or impact that can unequivocally and universally be used for all potential future storage sites. We suggest a multivariate, hierarchical approach to monitoring, escalating from anomaly detection to attribution, quantification and then impact assessment, as required. Given the spatial heterogeneity of many marine ecosystems it is essential that environmental monitoring programmes are supported by a temporally (tidal, seasonal and annual) and spatially resolved baseline of data from which changes can be accurately identified. In this paper we outline and discuss the options for monitoring methodologies and identify the components of an appropriate baseline survey

Detection and Localization of Leaks in Water Networks

Today, 844 million humans around the world have no access to safe drinking water. Furthermore, every 90 seconds, one child dies from water-related illnesses. Major cities lose 15% - 50% of their water and, in some cases, losses may reach up to 70%, mostly due to leaks. Therefore, it is paramount to preserve water as an invaluable resource through water networks, particularly in large cities in which leak repair may cause disruption. Municipalities usually tackle leak problems using various detection systems and technologies, often long after leaks occur; however, such efforts are not enough to detect leaks at early stages. Therefore, the main objectives of the present research are to develop and validate a leak detection system and to optimize leak repair prioritization. The development of the leak detection models goes through several phases: (1) technology and device selection, (2) experimental work, (3) signal analysis, (4) selection of parameters, (5) machine learning model development and (6) validation of developed models. To detect leaks, vibration signals are collected through a variety of controlled experiments on PVC and ductile iron pipelines using wireless accelerometers, i.e., micro-electronic mechanical sensors (MEMS). The signals are analyzed to pinpoint leaks in water pipelines. Similarly, acoustic signals are collected from a pilot project in the city of Montreal, using noise loggers as another detection technology. The collected signals are also analyzed to detect and pinpoint the leaks. The leak detection system has presented promising results using both technologies. The developed MEMS model is capable of accurately pinpointing leaks within 12 centimeters from the exact location. Comparatively, for noise loggers, the developed model can detect the exact leak location within a 25-cm radius for an actual leak. The leak repair prioritization model uses two optimization techniques: (1) a well-known genetic algorithm and (2) a newly innovative Lazy Serpent Algorithm that is developed in the present research. The Lazy Serpent Algorithm has proved capable of surpassing the genetic algorithm in determining a more optimal schedule using much less computation time. The developed research proves that automated real-time leak detection is possible and can help governments save water resource and funds. The developed research proves the viability of accelerometers as a standalone leak detection technology and opens the door for further research and experimentations. The leak detection system model helps municipalities and water resource agencies rapidly detect leaks when they occur in real-time. The developed pinpointing models facilitate the leak repair process by precisely determine the leak location where the repair works should be conducted. The Lazy Serpent Algorithm helps municipalities better distribute their resources to maximize their desired benefits

Development of instrumentation for acoustic monitoring

This thesis describes a source/sink flow acoustic wave sensor for the identification of leaks in gas pipelines. One of the many type of signals associated with the high velocity gas flowing out of a hole in the pipeline is the ramp or step pressure drop.;A large 3-inch diameter diaphragm was installed in an attempt to detect the low frequency waves associated with a leak. This diaphragm with source or sink flow through a 17mm internal diameter pipe acts as a pressure signal amplifier.;The deflection of the diaphragm due to the amplified force can be measured with a strain gage whose voltage is proportional to this deflection. A microphone should be used to record high frequency sound generated by the fluid inside the transmission line. (Abstract shortened by UMI.)

Water and Wastewater Pipe Nondestructive Evaluation and Health Monitoring: A Review

Civil infrastructures such as bridges, buildings, and pipelines ensure society's economic and industrial prosperity. Specifically, pipe networks assure the transportation of primary commodities such as water, oil, and natural gas. The quantitative and early detection of defects in pipes is critical in order to avoid severe consequences. As a result of high-profile accidents and economic downturn, research and development in the area of pipeline inspection has focused mainly on gas and oil pipelines. Due to the low cost of water, the development of nondestructive inspection (NDI) and structural health monitoring (SHM) technologies for fresh water mains and sewers has received the least attention. Moreover, the technical challenges associated with the practical deployment of monitoring system demand synergistic interaction across several disciplines, which may limit the transition from laboratory to real structures. This paper presents an overview of the most used NDI/SHM technologies for freshwater pipes and sewers. The challenges that said infrastructures pose with respect to oil and natural gas pipeline networks will be discussed. Finally, the methodologies that can be translated into SHM approaches are highlighted

Design and Construction of Smartball for Oil & Gas Pipeline Inspection

After the commissioning of an oil or gas pipeline, it is vital that it is inspected periodically to maintain its integrity. Traditional detection equipment which is the pipeline inspection gauges or pigs has a high risk of blocking a pipeline. The objectives of the project are to design a free swimming inspection device which can run freely in a pipeline with minimum risk of blocking a pipeline, and to develop a sensitive leak detection system that can detect small leaks in oil and gas pipelines. The scope of the project will involve mainly on the designing of the Smartball and also the testing of the product. For this project, in order to detect leaks, an acoustic sensor and a pressure sensor are used. Based on previous studies and literature reviews, when pressurized product leaks from a pipe, it creates a distinctive acoustic signal that is transmitted through the product flowing in the pipeline, and this signal can be received by using an acoustic sensor, on board the Smartball. In order to achieve the objectives of the project, the project was conducted starting from literature review, followed by the designing of the Smartball, material and equipment selection, fabrication and testing, and finally result analysis. The sensors need to be programmed to the microprocessor in order to allow the sensors to detect the acoustic wave and pressure difference. The fabrication of the Smartball was divided into two, which are fabrication of the cores, and fabrication of the inner components. However, due to some difficulties, the design of the Smartball needs to be modified. After fabrication, the product needs to be tested in a pipeline in order to test the mobility of the Smartball, and to test the functionality of the sensors. However, due to lack of availability of pipeline facilities, the Smartball was not able to be run in a pipeline. Thus, an indirect test was performed by submerging the product in bucket of water, and heated with a heating coil. This was done in order to proof that the onboard sensors can detect the changes in temperature and pressure of the surrounding, the microprocessor can process the data obtained from the sensors, and the data can be stored in a memory storage. From the indirect tests performed, if the temperature and pressure were able to be detected by the sensors, processed by the microprocessor, and stored in the memory storage, it can be concluded that the acoustic sensor will be able to detect, and be stored in an actual test runs that will be performed in the future

Small unmanned airborne systems to support oil and gas pipeline monitoring and mapping

Acknowledgments We thank Johan Havelaar, Aeryon Labs Inc., AeronVironment Inc. and Aeronautics Inc. for kindly permitting the use of materials in Fig. 1.Peer reviewedPublisher PD

Pipeline leak detection

In the present research two techniques are applied for leak detection in pipelines. The first method is a hardware-based technique which uses ultrasonic wave\u27s emission for pipeline inspection. Ultrasonic waves are propagated in the pipe walls and reflected signal from leakage will be used for pipe analysis. Several Pipes with various dimensions and characteristics are modeled by finite element method using ANSYS. Second order longitudinal modes of ultrasonic waves are emitted in their walls. For this purpose, excited frequency is calculated such that it excites the second order longitude mode. In order to investigate the behavior of emitted wave in contact with leakage, four sensors are used in outer surface of pipe. Waves are reflected when encountering leakage and the leak location is recognized knowing the wave emission speed and flight time of backscattered signals. Wavelet transform is used for processing these signals and recognizing leak location. This method is tested on several pipe models and it presents satisfactory results for short pipes. The second approach is a software-based method which works based on the transient model of the pipeline. In this method the outputs from simulated pipeline are compared to those measured from flow meters and if their difference goes beyond a threshold value, leak is detected. For leak localization a gradient pressure technique is applied which needs pressure slope measurements at inlet and outlet of the pipeline. Several cases with leak at various positions are studied. This method works well with high accuracy for long pipelines. --Abstract, page iii