Ultrasonic Monitoring System for Oil and Gas Pipeline Corrosion

2012 ◽  
Author(s):  
Bin Yang ◽  
Mingxing Li ◽  
Qiongwei Li ◽  
Yonghao Lu
Keyword(s):  
Monitoring System ◽  
Oil And Gas ◽  
Gas Pipeline ◽  
Ultrasonic Monitoring ◽  
Pipeline Corrosion

Gas Pipeline Corrosion Prediction Based on Modified Support Vector Machine and Unequal Interval Model

2013 ◽  
Vol 373-375 ◽  
pp. 1987-1994 ◽  
Author(s):  
Wei Dong Zhang ◽  
Bin Shen ◽  
Yi Bo Ai ◽  
Bin Yang
Keyword(s):  
Support Vector Machine ◽  
Oil And Gas ◽  
Prediction Method ◽  
Original Data ◽  
Gas Pipeline ◽  
Prediction Algorithm ◽  
Support Vector ◽  
Grey Prediction ◽  
Interval Model ◽  
Pipeline Corrosion

The corrosion is an important problem for the service safety of oil and gas pipeline. This research focuses. This paper proposed a new prediction algorithm on corrosion prediction of gathering gas pipeline, which combined modified Support Vector Machine (SVM) with unequal interval model. Firstly, grey prediction method with unequal interval model was used to pretreatment original data because there is unequal interval problem in actual collected data of pipeline. Secondly, improved Support Vector Regression (SVR) based on Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) has been proposed to resolve parameters selection problem for SVR. Finally, the corrosion prediction model of gas pipeline has been proposed which combined improved SVR and unequal interval grey prediction method. The experiment results show this algorithm could increase precision of the pipeline corrosion prediction compared with the traditional SVM. This research provides reliable basis for in-service pipeline life prediction and confirming inspecting cycle.

scholarly journals Research on the Intelligent Safety Monitoring System of Pipeline Corrosion in Acidic Oil and Gas Fields—II

2012 ◽  
Vol 27 ◽  
pp. 1664-1670 ◽  
Author(s):  
Xingpeng Guo ◽  
Zhehua Dong ◽  
Tan Gu ◽  
Xi Yuan ◽  
Xiankang Zhong ◽  
...  
Keyword(s):  
Monitoring System ◽  
Oil And Gas ◽  
Safety Monitoring ◽  
Oil And Gas Fields ◽  
Safety Monitoring System ◽  
Gas Fields ◽  
Pipeline Corrosion

Prediction of Residual Life of Oil and Gas Pipeline Corrosion Based on Deep Learning

2021 ◽  
pp. 105-114
Author(s):  
Wang Xinying ◽  
Zhang Huiran ◽  
Zhang Ruicheng ◽  
Zhao Bin ◽  
Huang Xuan ◽  
...  
Keyword(s):  
Deep Learning ◽  
Oil And Gas ◽  
Residual Life ◽  
Gas Pipeline ◽  
Pipeline Corrosion

Gas pipeline leakage detection in the presence of parameter uncertainty using robust extended Kalman filter

2021 ◽  
pp. 014233122198911
Author(s):  
Mohadese Jahanian ◽  
Amin Ramezani ◽  
Ali Moarefianpour ◽  
Mahdi Aliari Shouredeli
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Parameter Uncertainty ◽  
Oil And Gas ◽  
Estimation Error ◽  
Real Data ◽  
Gas Pipeline ◽  
Pipeline System ◽  
Parameter Uncertainties ◽  
Simulation Results

One of the most significant systems that can be expressed by partial differential equations (PDEs) is the transmission pipeline system. To avoid the accidents that originated from oil and gas pipeline leakage, the exact location and quantity of leakage are required to be recognized. The designed goal is a leakage diagnosis based on the system model and the use of real data provided by transmission line systems. Nonlinear equations of the system have been extracted employing continuity and momentum equations. In this paper, the extended Kalman filter (EKF) is used to detect and locate the leakage and to attenuate the negative effects of measurement and process noises. Besides, a robust extended Kalman filter (REKF) is applied to compensate for the effect of parameter uncertainty. The quantity and the location of the occurred leakage are estimated along the pipeline. Simulation results show that REKF has better estimations of the leak and its location as compared with that of EKF. This filter is robust against process noise, measurement noise, parameter uncertainties, and guarantees a higher limit for the covariance of state estimation error as well. It is remarkable that simulation results are evaluated by OLGA software.

Applying the Quantitative Risk Assessment (QRA) to Improve Safety Management of Oil and Gas Pipeline Stations in China

2012 ◽  
Author(s):  
Wenxing Feng ◽  
Xiaoqiang Xiang ◽  
Guangming Jia ◽  
Lianshuang Dai ◽  
Yulei Gu ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Environmental Protection ◽  
Oil And Gas ◽  
Hazard Identification ◽  
Gas Pipeline ◽  
Industrial Safety ◽  
Quantitative Risk Assessment ◽  
Chinese Government ◽  
Land Resource ◽  
Oil Pipeline

The oil and gas pipeline companies in China are facing unprecedented opportunities and challenges because of China’s increasing demand for oil and gas energy that is attributed to rapid economic and social development. Limitation of land resource and the fast urbanization lead to a determinate result that many pipelines have to go through or be adjacent to highly populated areas such as cities or towns. The increasing Chinese government regulation, and public concerns about industrial safety and environmental protection push the pipeline companies to enhance the safety, health and environmental protection management. In recent years, PetroChina Pipeline Company (PPC) pays a lot of attention and effort to improve employees and public safety around the pipeline facilities. A comprehensive, integrated HSE management system is continuously improved and effectively implemented in PPC. PPC conducts hazard identification, risk assessment, risk control and mitigation, risk monitoring. For the oil and gas stations in highly populated area or with numerous employees, PPC carries out quantitative risk assessment (QRA) to evaluate and manage the population risk. To make the assessment, “Guidelines for quantitative risk assessments” (purple book) published by Committee for the Prevention of Disasters of Netherlands is used along with a software package. The basic principles, process, and methods of QRA technology are introduced in this article. The process is to identify the station hazards, determinate the failure scenarios of the facilities, estimate the possibilities of leakage failures, calculate the consequences of failures and damages to population, demonstrate the individual risk and social risk, and evaluate whether the risk is acceptable. The process may involve the mathematical modeling of fluid and gas spill, dispersion, fire and explosion. One QRA case in an oil pipeline station is described in this article to illustrate the application process and discuss several key issues in the assessment. Using QRA technique, about 20 stations have been evaluated in PPC. On the basis of the results, managers have taken prevention and mitigation plans to control the risk. QRAs in the pipeline station can provide a quantitative basis and valuable reference for the company’s decision-making and land use planning. Also, QRA can play a role to make a better relationship between the pipeline companies and the local regulator and public. Finally, this article delivers limitations of QRA in Chinese pipeline stations and discusses issues of the solutions.

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