| [1] |
Yang Y, Zeng X, Yang Y. Study on Erosion Wear Law and Anti-Erosion Ability Optimization of Wellhead Four-Way [J]. Journal of Failure Analysis and Prevention, 2022, 23(1).
|
| [2] |
N T M, S L K, G I A, et al. Influence of shock-vibration loads of drilling equipment on the drilling indicators of oil and gas wells [J]. Journal of Physics: Conference Series, 2022, 2176(1).
|
| [3] |
Habibov I, Abasova S, Huseynova V. Statistical analysis of the relative position of the rod hanger and the wellhead [J]. EUREKA: Physics and Engineering, 2022(2).
|
| [4] |
G. V E. Increasing the Reliability, Service Life, and Ecological Safety of the Stuffing Boxes of Wellhead Equipment of Wells that Operate by Means of Deep-Well Sucker-Rod Pumping Units [J]. Chemical and Petroleum Engineering, 2017, 53(7-8).
|
| [5] |
A V K, S A L, F Y K, et al. Automation of management and control system for wellhead equipment of a production well [J]. Journal of Physics: Conference Series, 2020, 1515(4).
|
| [6] |
Davydov A, Alekseeva E, Gaev A. Specificity to the choice of materials for wellhead equipment [J]. Materials Today: Proceedings, 2020, 30.
|
| [7] |
Farooqui, M. A. S. Z., Bitar, et al. Corrosion Problems in Below-Grade Wellhead Equipment and Surface Casings [J]. SPE Production & Facilities, 2005, 13(03).
|
| [8] |
Wang D H, Chen X G, Feng B, et al. Digital Integration for Wellhead Equipment of Gas Well and Its Intelligent Control Technology [J]. Inner Mongolia Petrochemical Industry, 2021, 47(02): 73-77.
|
| [9] |
Zhao M J. Research and Application of Fire and Explosion Prevention Technology and Equipment for Oilfield Gas Wells [J]. China Petroleum and Chemical Standard and Quality, 2023, 43(19): 86-88.
|
| [10] |
Kong C, Wang S Q, Zhang B, et al. Application of phased array detection technology in oil and gas wellhead device [J]. Machine Design and Manufacturing Engineering, 2019, 48(06): 113-116.
|
| [11] |
Chu X J, Sun W, Li F, et al. Simulation and experimental study on acoustic emission detection of dry wellhead christmas tree [J]. Construction Machinery and Equipment, 2019, 50(11): 46-54+8.
|
| [12] |
Wang Y W, Yang S Y, Chen Z H, et al. Analysis and Countermeasures of Common Faults in Wellhead Gas Tree of Sulige Gas Field [J]. Petro & Chemical Equipment, 2014, 17(07): 87-88+91.
|
| [13] |
H Chen. Failure Analysis for the Main Component Parts of Wellhead Equipment [J]. Journal of Southwest Petroleum Institute, 1998.
|
| [14] |
S Yang, J Zhuang. Failure Analysis for the Gas Production Wellhead Equipment [J]. Technology Supervision in Petrolevm Industry, 1999.
|
| [15] |
Chen H, Liang A W, Li Y X, et al. Analysis of Wellhead Facilities Failure [J]. Natural Gas Industry, 2004, 24(7): 65-67, 137-138.
|
| [16] |
Zhang B, Wang S Q, Peng J Y, et al. Application of Detection Technology for High Pressure Wellhead Equipment Service [J]. Journal of Beijing Institute of Petrochemical Technology, 2018, 26(04): 43-47.
|
| [17] |
Kuleshova S L, Kadyrov R R, Mukhametshin V V, et al. Design changes of injection and supply wellhead fittings operating in winter conditions [J]. IOP Conference Series: Materials Science and Engineering, 2019, 560(1).
|
| [18] |
J Wu, W Wu, E Li, et al. Magnetic Flux Leakage Course of Inner Defects and Its Detectable Depth [J]. Chinese Journal of Mechanical Engineering, 2021, 34(1), 1-11.
|
| [19] |
Y Chen, Z Xu, J Wu, et al. A Scanning Induction Thermography System for Thread Defects of Drill Pipes [J]. IEEE Transactions on Instrumentation & Measurement, 2022, 71, 3502509.
|
| [20] |
Yangyang Zhu, Luofeng Xie, Zhengfeng Xie, et al. FSConv: Flexible and Separable Convolution for Convolutional Neural Networks Compression [J]. Pattern Recognition, 140(2023) 109589.
|
| [21] |
Fei W, Hongxia W, Omid D R. Machine Learning Techniques and Big Data Analysis for Internet of Things Applications: A Review Study [J]. Cybernetics and Systems, 2024, 55(1).
|
| [22] |
Saurabh P, Kumar S J, Angappa G, et al. Optimizing the IoT and big data embedded smart supply chains for sustainable performance [J]. Computers & Industrial Engineering, 2024, 187.
|
| [23] |
Nan X, Zhaoshun W, Xiaoxue S, et al. A novel blockchain-based digital forensics framework for preserving evidence and enabling investigation in industrial Internet of Things [J]. Alexandria Engineering Journal, 2024, 86.
|
| [24] |
Martín G, P. R D, Manuel F, et al. Decentralized and collaborative machine learning framework for IoT [J]. Computer Networks, 2024, 239.
|
| [25] |
Zong Z B. Design and realization of data mining simulation and methodological models [J]. Journal of King Saud University - Science, 2023, 35(10).
|
| [26] |
Aszani A. Machine Learning for Knowledge Discovery with R: Methodologies for Modeling, Inference, and Prediction [J]. Technometrics, 2023, 65(4).
|