Development and Application of Methane Leakage Monitoring System for Gas Transmission Pipeline

Oil and gas pipeline transportation, as a relatively safe way of oil and gas transportation, undertakes most of the transportation tasks of crude oil and natural gas. Oil and gas pipeline accidents affect a wide range of consequences. Therefore, the oil and gas pipeline leakage detection is paid more and more attention. In this paper, ultra-low power methane gas sensor is selected to collect methane gas concentration in the air, and wireless network technology is used to build a wireless network sensor system with 4G function. Through the sensor distribution along the pipeline, it can intuitively and accurately judge whether there is a micro-leakage in the pipeline, and understand the diffusion situation after the leakage. The sensor system has high reliability and stability, and has high value of popularization and application.

Monitoring and Diagnosis System of Downhole Tubing Leakage

The downhole tubing in a gas well is affected by many factors such as high pressure erosion, gas lift operation, sand production at the bottom of the well and engineering construction, etc., which can easily lead to leakage of the threaded joints of the tubing and the pipe body, and the leaked natural gas will invade Annulus, making the annulus under pressure. The annular pressure caused by oil pipe leakage is a major safety hazard in oil and gas production. Therefore, the accurate diagnosis the degree of leakage of downhole tubing is of great significance to preventing the occurrence of production accidents effectively. To this end, a set of downhole tubing leak monitoring and diagnosis system has been developed by integrating fluid monitoring, acoustic wave detection and tracer detection technology, and the developed tubing leak monitoring and diagnosis system was used for leak detection tests on offshore platforms. The test results show that the developed tubing leakage monitoring and diagnosis system can meet the need of offshore gas well diagnosis, and realize the holographic diagnosis of the leakage degree of the downhole tubing without moving the downhole tubing string.

A normalized method for determining the influence on the fixed joints tightness using the technology of the sealing surface job

The existing approaches for determining and evaluating the sealing properties of seals for fixed sealants, as well as methods of leakage monitoring are considered. The description of a normalized method for leak-tightness assessment is given, which allows solving a sufficiently large number of evaluation tasks, for example, technological task: assessment of the influence of the technology sealing surfaced job; design: assessment of the influence of the seals surface layer quality of sealants and geometric parameters of them on sealing capacity (service property).

A novel wavelet threshold denoising and deep belief network fault detection algorithm

For oil pipeline leakage fault detection problems, a novel negative pressure wave (NPW) leak detection method based on wavelet threshold denoising and deep belief network (Wavelet-DBN) is proposed. Firstly, the wavelet threshold denoising method is used to deal with the sample pressure signal, and the results of wavelet denoising with different wavelet basis functions and different decomposition levels are compared. The optimal parameters are selected for wavelet denoising and the characteristic information of a pipeline pressure signal is extracted. Secondly, in order to improve the accuracy of the pipeline leakage monitoring method based on NPW, the deep belief network algorithms are proposed to classify and identify the NPW sample signals. Finally, the sample data are collected from the industrial oil pipeline leakage experiment. The simulation experimental results show that the proposed method has a higher accuracy rate than other traditional machine learning methods, such as support vector machines, and reduces the false alarm rate of oil pipeline leakage monitoring.