摘要
为提升检测效率和检测精度,提出了基于OpenCV图像处理的支撑剂颗粒圆度和球度检测方法。该方法使用OpenCV算法,综合考虑图像的背景颜色和图像中颗粒的多样性等各种因素的影响,优化处理算法,提高检测有效性和图像处理效率。在检测过程中,新出现的影响因素还可对算法进行优化,具有很好的可调节性。将检测数据与标准模板相比较,结果证明该检测方法具有可行性和有效性,为支撑剂颗粒的圆度和球度检测提供了新路径。
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.
作者
曹磊
纪国法
彭超
陈海建
CAO Lei;JI Guofa;PENG Chao;CHEN Haijian(Cooperative Innovation Center of Unconventional Oil and Gas(Yangtze University),Ministry of Education&Hubei Province,Wuhan 430100,China;Key Laboratory of Drilling and Production Engineering for Oil and Gas(Yangtze University),Wuhan 430100,China;Exploration,Development and Construction Branch,China National Petroleum Corporation Coalbed Methane Limited Liability Company,Xi’an 710082,China;Xi’an Changqing Petrochemical Corporation Co.,Ltd.,Xi’an 710299,China)
出处
《中国科技论文》
CAS
2024年第1期85-91,共7页
China Sciencepaper
基金
国家自然科学基金资助项目(51804042)
油气资源勘探技术教育部重点实验室(长江大学)青年创新团队项目(PI2021-04)
非常规油气省部共建创新中心(长江大学)开放基金资助项目(UOG2022-38)。
