成品油上倾管道油水两相流相分布识别方法

1. 中国石油新疆油田油气储运公司;2. 西南石油大学石油与天然气工程学院

上倾管道;油水两相流;图像处理;中值滤波;边缘检测

Phase distribution identification method for oil-water two-phase flow in updip products pipelines
WEN Songqing1,2, ZHANG Tao2, ZHANG Qichao2

1. Oil & Gas Storage and Transportation Company, PetroChina Xinjiang Oilfield Company;2. College of Oil and Gas Engineering, Southwest Petroleum University

updip pipelines, oil-water two-phase flow, image processing, median filtering, edge detection

备注

成品油携水沿上倾管道流动会产生复杂的流动型态,准确识别油水两相在上倾管道中的分布特征是深入认识油携水规律的基础。针对实验中采集的上倾管油水两相流图像,提出一种基于图像处理的上倾管道油水两相分布特征识别方法:将原始图像转化为灰度图像,剔除图像中的无用信息;调整图像的灰度,以提升对比度,凸显图像细节;对图像进行中值滤波处理,消除图像拍摄过程中的随机噪声;对图像进行边缘检测,分割出油水两相边界,识别出相分布特征。该方法可以分割出清晰的油水两相边界,从而识别出管道中油水两相流的相分布特征。研究成果适用于各种工况下油水两相相分布特征识别,为多相流图像处理特别是流型识别提供了指导。(图 13,参[21]

The flow of refined oil carrying water along updip pipelines will lead to complex flow patterns. The base for understanding the law of oil carrying water is to accurately identify the distribution characteristics of oil-water two-phase flow in updip pipelines. In this paper, an oil-water two-phase flow distribution characteristic identification method based on image processing was proposed to analyze the images of oil-water two-phase flow in the updip pipeline acquired in the experiment. In this method, the original image is firstly transformed into the gray-scale image to remove the useless information in the image. Secondly, the gray scale of the gray image is adjusted to enhance the contrast and highlight the details of the image. Thirdly, the gray-scale image is processed by means of median filtering to eliminate the random noise in the process of image shooting. Finally, edge detection is carried out on the image to demarcate the oil-water boundary and identify the phase distribution characteristics. It is indicated that this method can demarcate the oil-water boundary clearly so as to identify the phase distribution characteristics of the oil-water two-phase flow in the pipelines. The research results are applicable to identify the phase distribution characteristics of oil-water two-phase flow in various working conditions, and provide the guidance for multiphase flow image processing, especially flow pattern recognition. (13 Figures, 21 References)