Particle roundness and sphericity detection method of proppant based on OpenCV image processing
Oil fracturing proppants are often used in hydraulic fracturing modification processes to increase oil and gas production,and roundness and sphericity are two important indicators commonly employed for assessing their performance.The existing prop-pant roundness and sphericity characterization recommended in the industry standard can only be achieved with the help of Krumbien template or sloss template,in which accurate results cannot be obtained.In order to improve the detection efficiency and detection accuracy,a proppant particle roundness and sphericity detection method based on OpenCV image processing is proposed.The OpenCV algorithm is employed to optimize the processing algorithm by comprehensively considering the influence of various factors such as the background color of the image and the diversity of the particles in the image,so as to improve the effectiveness of the detection and the efficiency of image processing.In the detection process,the algorithm can be optimized to adapt the emergence of new influencing factors,indicating a good adjustability.Comparation of the data of the detection results with the standard template proves that the detection method is feasible and effective,provides a new path for detecting the roundness and sphericity of the prop-pant particles.
万方数据
维普
