Log specification and intelligent analysis method based on oil and gas pipeline SCADA system

[1] Zeng, W., Xue, Y., Sun, Y., Zhao, J., Xie, H., & Ren, T. (2022). Sealing reliability assessment of deep-water oil and nature gas pipeline connector considering thermo-mechanical coupling: Proceedings of the Institution of Mechanical Engineers, Part M: Journal of Engineering for the Maritime Environment, 236(1), 196-208. Search in Google Scholar

[2] Hu, J., Chen, C., & Liu, Z. (2022). Early warning method for overseas natural gas pipeline accidents based on fdoobn under severe environmental conditions. Transactions of the Institution of Chemical Engineers. Process Safety and Environmental Protection, Part B(157-), 157. Search in Google Scholar

[3] Zhu, Y., Wang, P., Wang, Y., Tong, R., & Qu, Z. (2021). Assessment method for gas supply reliability of natural gas pipeline networks considering failure and repair. Journal of Natural Gas Science and Engineering (2), 103817. Search in Google Scholar

[4] Wang, W. C., Zhang, Y., Li, Y. X., Hu, Q., Liu, C., & Liu, C. (2022). Vulnerability analysis method based on risk assessment for gas transmission capabilities of natural gas pipeline networks. Reliability Engineering & System Safety, 218, 108150-. Search in Google Scholar

[5] Almaziad, F. (2022). Identifying and ranking the root causes of schedule delays in oil and gas pipeline construction projects. Energies, 16. Search in Google Scholar

[6] Zhu, X. X., Fu, C. M., Wang, Y. T., & Zhang, S. M. (2022). Experimental research on the contact force of the bi-directional pig in oil and gas pipeline. Petroleum Science. Search in Google Scholar

[7] Macintosh, A., Koppel, D. J., Johansen, M. P., Beresford, N. A., Copplestone, D., & Penrose, B., et al. (2022). Radiological risk assessment to marine biota from exposure to norm from a decommissioned offshore oil and gas pipeline. Journal of environmental radioactivity. Search in Google Scholar

[8] Yadav, G., & Paul, K. (2021). Architecture and security of scada systems: a review. International Journal of Critical Infrastructure Protection (Sgc), 100433. Search in Google Scholar

[9] Wang, D., Yan, Q. T. J., & Huang, D. (2022). New type of high-strength flexible cover plate to prevent engineering failure in oil and gas pipeline engineering. Engineering failure analysis (139-), 139. Search in Google Scholar

[10] Cui, W., Xiao, Z., Yang, J., Tian, M., Zhang, Q., & Feng, Z. (2022). Multi-crack dynamic interaction effect on oil and gas pipeline weld joints based on vcct. Energies, 15. Search in Google Scholar

[11] Kantyukov, I. K. R. (2021). The impact of internal stratifications on the performance of oil and gas pipes. Engineering failure analysis, 120(1). Search in Google Scholar

[12] Mao, L., Gan, L., Li, W., & Zhang, P. (2022). Failure analysis on weld joint of centrifugal pump diffuser for oil and gas pipeline transportation. Engineering failure analysis, 140. Search in Google Scholar

[13] Chen, Y., Zhang, L., Hu, J., Liu, Z., & Xu, K. (2022). Emergency response recommendation for long-distance oil and gas pipeline based on an accident case representation model. Journal of loss prevention in the process industries (77-), 77. Search in Google Scholar

[14] Malekpour, A., & She, Y. (2021). Real-time leak detection in oil pipelines using an inverse transient analysis model. Journal of Loss Prevention in the Process Industries, 70(11), 104411. Search in Google Scholar

[15] Yavasoglu, H. A. (2023). A comprehensive analysis of in-line inspection tools and technologies for steel oil and gas pipelines. Sustainability, 15. Search in Google Scholar

[16] Yang, D., Hou, N., Lu, J., & Ji, D. (2022). Novel leakage detection by ensemble 1dcnn-vapso-svm in oil and gas pipeline systems. Applied Soft Computing (115-), 115. Search in Google Scholar

[17] Yuan, C., Hu, Y., Zhang, Y., Zuo, T., Wang, J., & Fan, S. (2021). Evaluation on consequences prediction of fire accident in emergency processes for oil-gas storage and transportation by scenario deduction. Journal of Loss Prevention in the Process Industries, 72, 104570-. Search in Google Scholar

[18] Zhao, J., Liao, K., Li, X., He, G., Xia, F., & Zeng, Q. (2022). Collaborative detection and on-line monitoring of pipeline stress in oil and gas stations. Measurement Science & Technology. Search in Google Scholar

[19] Lamhour, K., & Tizliouine, A. (2021). Operation and approximation based on the history of failure modes recorded by scada system of amougdoul moroccan wind farm using fmeca maintenance model. Wind Engineering (9), 0309524X2199245. Search in Google Scholar

[20] Kermani, M., Adelmanesh, B., Shirdare, E., Sima, C. A., & Martirano, L. (2021). Intelligent energy management based on scada system in a real microgrid for smart building applications. Renewable Energy, 171(1). Search in Google Scholar

[21] Sheng, C., Yao, Y., Fu, Q., & Yang, W. (2021). A cyber-physical model for scada system and its intrusion detection. Computer networks (Feb.11), 185. Search in Google Scholar

[22] Zhang, K., Tang, B., Deng, L., Yu, X., & Wei, J. (2021). Fault source location of wind turbine based on heterogeneous nodes complex network. Engineering Applications of Artificial Intelligence, 103, 104300. Search in Google Scholar

[23] Hu, Y., Shi, P., Fang, C., Wang, Y., Liu, C., & Ding, G., et al. (2022). A health condition assessment method of wind turbine generator system based on multiple turbines cooperation. IET renewable power generation (1), 16. Search in Google Scholar

[24] Qu, B., Wang, Z., & Shen, B. (2021). Fusion estimation for a class of multi-rate power systems with randomly occurring scada measurement delays. Automatica, 125, 109408. Search in Google Scholar

[25] Hegazy, A., Blondel, Frédéric, Cathelain, M., & Aubrun, S. (2022). Lidar and scada data processing for interacting wind turbine wakes with comparison to analytical wake models. Renewable Energy, 181. Search in Google Scholar

[26] Parker, K. (2016). Scada addresses oil and gas field challenges. Control Engineering, 63(10app.1), 11-14. Search in Google Scholar

[27] Yang, Li, Cao, Xiedong, & Jie. (2016). A new cyber security risk evaluation method for oil and gas scada based on factor state space. Chaos, Solitons & Fractals. Search in Google Scholar

[28] Velandia-Cardenas, C., Vidal, Y., & Pozo, F. (2021). Wind turbine fault detection using highly imbalanced real scada data. Energies, 14(6), 1728. Search in Google Scholar

[29] Yu, C., Xiang, X., Maurelli, F., Zhang, Q., & Xu, G. (2019). Onboard system of hybrid underwater robotic vehicles: integrated software architecture and control algorithm. Ocean Engineering, 187, 106121. Search in Google Scholar

[30] Dobakhshari, A. S., Azizi, S., Abdolmaleki, M., & Terzija, V. (2020). Linear lav-based state estimation integrating hybrid scada/pmu measurements. IET Generation Transmission & Distribution, 14(8). Search in Google Scholar

[31] Larsen, K. R. (2016). Remote monitoring system tracks cathodic protection and sensor data. Materials performance. Search in Google Scholar

[32] Foster, C. (2016). Ensuring iiot connectivity for oil and gas process control. Control Engineering, 63(6suppl.2), 6-9. Search in Google Scholar