Application of the curvelet transform for pipe detection in GPR images

International audienceThis paper is dedicated to the detection of buried pipeswith a ground penetrating radar (GPR). The imagesfrom GPR acquisitions also called B-scan are corruptedby clutter and noise. In order to remove these undesirableitems we propose to use the properties of the curvelettransform. Were using this method as a first step of theautomatic detection of hyperbola in a B-scan

Comparison Study For Stuck Pipe Detection Method. Statistical Method & Current Method

This report fundamentally discusses the preliminary research done and the basic understanding of the topic chosen, which is comparison study for stuck pipe detection method, current method and statistical method. Stuck pipe in the drilling industry results in hundreds of millions of dollars wasted because of the extra cost to ftx the problem and the time delay of the operation. The occurrence of stuck pipe consists of drill pipe, casing, tubing and coiled tubing getting stuck downhole. Amongst the reason why the pipe get stuck is because of mud sticking, sand sticking , key seat sticking, stuck packers, crooked pipe and foreign object in hole. Technology at the moment allows detection of stuck pipe through various method and the method which will be compared to the statistical method for this study is where readings from pressure while drilling tools are read in a flow pattern and then with the experience and the knowledge of the engineer, he or she is will determine whether such occurrences will happen or not. The scope of study for this project covers 3 important parts, literature review, data gathering and analysis of data. The study begins with familiarizing with the theory behind the statistical method, followed by case study of previous tested wells. The study then is continued with familiarizing with the current method used and the gathering of data in order to compare the efficiency of the statistical method with the current method. The data obtained then will be use for the statistical method calculation and the results will then be compared with the results given by the current method

Near-Surface Interface Detection for Coal Mining Applications Using Bispectral Features and GPR

The use of ground penetrating radar (GPR) for detecting the presence of near-surface interfaces is a scenario of special interest to the underground coal mining industry. The problem is difficult to solve in practice because the radar echo from the near-surface interface is often dominated by unwanted components such as antenna crosstalk and ringing, ground-bounce effects, clutter, and severe attenuation. These nuisance components are also highly sensitive to subtle variations in ground conditions, rendering the application of standard signal pre-processing techniques such as background subtraction largely ineffective in the unsupervised case. As a solution to this detection problem, we develop a novel pattern recognition-based algorithm which utilizes a neural network to classify features derived from the bispectrum of 1D early time radar data. The binary classifier is used to decide between two key cases, namely whether an interface is within, for example, 5 cm of the surface or not. This go/no-go detection capability is highly valuable for underground coal mining operations, such as longwall mining, where the need to leave a remnant coal section is essential for geological stability. The classifier was trained and tested using real GPR data with ground truth measurements. The real data was acquired from a testbed with coal-clay, coal-shale and shale-clay interfaces, which represents a test mine site. We show that, unlike traditional second order correlation based methods such as matched filtering which can fail even in known conditions, the new method reliably allows the detection of interfaces using GPR to be applied in the near-surface region. In this work, we are not addressing the problem of depth estimation, rather confining ourselves to detecting an interface within a particular depth range

Detection of soil pipes using ground penetrating radar

Soil piping leads to land degradation in almost all morphoclimatic regions. However, the detection of soil pipes is still a methodological challenge. Therefore, this study aims at testing ground penetrating radar (GPR) to identify soil pipes and to present the complexity of soil pipe networks. The GPR surveys were conducted at three sites in the Bieszczady Mountains (SE Poland), where pipes develop in Cambisols. In total, 36 GPR profiles longitudinal and transverse to piping systems were made and used to provide spatial visualization of pipe networks. Soil pipes were identified as reflection hyperbolas on radargrams, which were verified with the surface indicators of piping, i.e., sagging of the ground and the occurrence of pipe roof collapses. Antennas of 500 MHz and 800 MHz were tested, which made possible the penetration of the subsurface up to 3.2 m and 2 m, respectively. Concerning ground properties, antenna frequencies and processing techniques, there was a potential possibility to detect pipes with a minimum diameter of 3.5 cm (using the antenna of lower frequency), and 2.2 cm (with the antenna of higher frequency). The results have proved that soil pipes meander horizontally and vertically and their networks become more complicated and extensive down the slope. GPR is a useful method to detect soil pipes, although it requires field verification and the proper selection of antenna frequency

Remote pipeline assessment and condition monitoring using low-frequency axisymmetric waves: a theoretical study of torsional wave motion

Waves that propagate at low frequencies in buried pipes are of considerable interest in a variety of practical scenarios, for example leak detection, remote pipe detection, and pipeline condition assessment and monitoring. Particularly useful are the n=0, or axisymmetric, modes in which there is no displacement (or pressure) variation over the pipe cross section. Previous work has focused on two of the three axisymmetric wavetypes that can propagate: the s=1, fluid-dominated wave; and the s=2, shell-dominated wave. In this paper, the third axisymmetric wavetype, the s=0 torsional wave, is studied. Whilst there is a large body of research devoted to the study of torsional waves and their use for defect detection in pipes at ultrasonic frequencies, little is known about their behaviour and possible exploitation at lower frequencies. Here, a low-frequency analytical dispersion relationship is derived for the torsional wavenumber for a buried pipe from which both the wavespeed and wave attenuation can be obtained. How the torsional waves subsequently radiate to the ground surface is then investigated, with analytical expressions being presented for the ground surface displacement above the pipe resulting from torsional wave motion within the pipe wall. Example results are presented and, finally, how such waves might be exploited in practice is discussed

A comprehensive review of acoustic methods for locating underground pipelines

Underground pipelines are vital means of transporting fluid resources like water, oil and gas. The process of locating buried pipelines of interest is an essential prerequisite for pipeline maintenance and repair. Acoustic pipe localization methods, as effective trenchless detection techniques, have been implemented in locating underground utilities and shown to be very promising in plastic pipeline localization. This paper presents a comprehensive review of current acoustic methods and recent advances in the localization of buried pipelines. Investigations are conducted from multiple perspectives including the wave propagation mechanism in buried pipe systems, the principles behind each method along with advantages and limitations, representative acoustic locators in commercial markets, the condition of buried pipes, as well as selection of preferred methods for locating pipelines based on the applicability of existing localization techniques. In addition, the key features of each method are summarized and suggestions for future work are proposed. Acoustic methods for locating underground pipelines have proven to be useful and effective supplements to existing localization techniques. It has been highlighted that the ability of acoustic methods to locate non-metallic objects should be of particular practical value. While this paper focuses on a specific application associated with pipeline localization, many acoustic methods are feasible across a wide range of underground infrastructures

Analysing time series structure with hidden Markov models

This paper consides the problem of extracting the relationships between two time series in a non-linear non-stationary environment with Hidden Markov Models (HMMs). We describe an algorithm which is capable of identifying associations between variables. The method is applied both to synthetic data and real data. We show that HMMs are capable of modelling the oil drilling process and that they outperform existing methods