Leakage simulation and acoustic characteristics based on acoustic logging by ultrasonic detection

Jingcui Li, Jifang Wan, Tingting Wang, Guangjie Yuan, Maria Jose Jurado, Qing He

Abstract view|3|times       PDF download|0|times

Abstract


The detection of casing leakage in oil and gas wells or water injection wells is an important element of wellbore integrity management. Ultrasonic technology is suitable to detect and identify the position of leakage in oil and gas well shafts, providing engineering guidance for subsequent treatment. In this paper, the finite element calculation model of casing leakage in oil and gas wells is established by using the computational fluid dynamics method, and the large eddy simulation model and Ffowcs Williams-Hawkings acoustic model are utilized to simulate the casing leakage condition. The acoustic pressure signals of each monitoring point on the inner axis of the pipeline are obtained, and the influences of the pipeline pressure difference, the leakage hole diameter and the pipeline fluid on the leakage acoustic field are analyzed. The simulation results indicate that the acoustic pressure level measured on the pipeline axis rises with the increase of pipeline pressure difference and leakage hole diameter. The size and variation rule of acoustic pressure level also vary with the type of pipeline fluid. Overall, the results obtained show that ultrasonic logging can accurately locate and detect tubing leakage, and they provide theoretical guidance for practical casing leakage detection, assisting with wellbore integrity management.

Cited as: Li, J., Wan, J., Wang, T., Yuan, G., Jurado, M. J., He, Q. Leakage simulation and acoustic characteristics based on acoustic logging by ultrasonic detection. Advances in Geo-Energy Research, 2022, 6(3): 181-191. https://doi.org/10.46690/ager.2022.03.02


Keywords


Acoustic logging, well logging, leakage, ultrasound, simulation, numerical modelling

Full Text:

PDF

References


Adegboye, M. A., Karnik, A., Fung, W. K. Numerical study of pipeline leak detection for gas-liquid stratified flow. Journal of Natural Gas Science and Engineering, 2021, 94: 104054.

Cao, J., Zhang, J., Yu, X., et al. Detection of pressure relief valve leakage by tuning generated sound characteristics. Process Safety and Environmental Protection, 2021, 148: 664-675.

Datta, S., Sarkar, S. A review on different pipeline fault detection methods. Journal of Loss Prevention in the Process Industries, 2016, 41: 97-106.

Doshmanziari, R., Khaloozadeh, H., Nikoofard, A. Gas pipeline leakage detection based on sensor fusion under model-based fault detection framework. Journal of Petroleum Science and Engineering, 2020, 184: 106581.

Fedotov, Y. V., Belov, M. L., Kravtsov, D. A., et al. Selecting laser fluorosensor detection band to monitor oil pipeline leaks. IOP Conference Series: Materials Science and Engineering, 2021, 1155: 012074.

Fu, H., Yang, L., Liang, H., et al. Diagnosis of the single leakage in the fluid pipeline through experimental study and CFD simulation. Journal of Petroleum Science and Engineering, 2020, 193: 107437.

Ghosh, S., Saha, S. K. Modeling and simulation of subcooled coolant loss through circumferential pipe leakage. Journal of Nuclear Engineering and Radiation Science, 2021, 7(3): 034503.

Hudson, T. B., Follis, P. J., Pinakidis, J. J., et al. Porosity detection and localization during composite cure inside an autoclave using ultrasonic inspection. Composites Part A: Applied Science and Manufacturing, 2021, 147: 106337.

Jahanian, M., Ramezani, A., Moarefianpour, A., et al. Gas pipeline leakage detection in the presence of parameter uncertainty using robust extended Kalman filter. Transactions of the Institute of Measurement and Control, 2021, 43(9): 2044-2057.

Karthik, K., Jeyakumar, S., Sarathkumar, J. S. Optimization of wavy cylinder for aerodynamic drag and aeroacoustic sound reduction using computational fluid dynamics analysis. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 2021, 235(11): 1979-1991.

Keramat, A., Duan, H. F. Spectral based pipeline leak detection using a single spatial measurement. Mechanical Systems and Signal Processing, 2021, 161: 107940.

Lalitha, K., Balakumar, V., Yogesh, S., et al. IOT enabled pipeline leakage detection and real time alert system in oil and gas industry. International Journal of Recent Technology and Engineering, 2020, 8(5): 2582-2586.

Lu, H., Iseley, T., Behbahani, S., et al. Leakage detection techniques for oil and gas pipelines: State-of-the-art. Tunnelling and Underground Space Technology, 2020, 98: 103249.

Mahmutoglu, Y., Turk, K. Received signal strength difference based leakage localization for the underwater natural gas pipelines. Applied Acoustics, 2019, 153: 14-19.

Mei, Z., Yang, X., Liu, Z., et al. Study of pipeline leak detection and location method based on acoustic emission technology. Pipeline Technique and Equipment, 2021, 5: 17-21. (in Chinese)

Moosavi, S. R., Vaferi, B., Wood, D. A. Auto-detection interpretation model for horizontal oil wells using pressure transient responses. Advances in Geo-Energy Research, 2020, 4(3): 305-316.

Ning, F., Cheng, Z., Di, M., et al. A framework combining acoustic features extraction method and random forest algorithm for gas pipeline leak detection and classification. Applied Acoustics, 2021, 182: 108255.

Piltan, F., Kim, J. M. Advanced fuzzy-based leak detection and size estimation for pipelines. Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology, 2020, 38(1): 947-961.

Quy, T. B., Kim, J. M. Leak detection in a gas pipeline using spectral portrait of acoustic emission signals. Measurement, 2020, 152: 107403.

Rai, A., Kim, J. M. A novel pipeline leak detection approach independent of prior failure information. Measurement, 2021, 167: 108284.

Sarallah, A., Mohammad, S. On the passive control of aeroacoustics noise behind a square cylinder. Journal of the Brazilian Society of Mechanical Sciences and Engineering, 2021, 43: 58.

Shahmirzaee, M., Hemmati-Sarapardeh, A., Husein, M. M., et al. A review on zeolitic imidazolate frameworks use for crude oil spills cleanup. Advances in Geo-Energy Research, 2019, 3(3): 320-342.

Shan, L., Liu, Y., Tang, M., et al. CNN-BiLSTM hybrid neural networks with attention mechanism for well log prediction. Journal of Petroleum Science and Engineering, 2021, 205: 108838.

Shi, M., Ye, T., Zhou, B., et al. Design and experimental research of internal leakage detection device of buried pipeline ball valve based on valve cavity pressure detection. Flow Measurement and Instrumentation, 2022, 83: 102112.

Xu, C., Liu, P., Li, Z., et al. Leakage identification method of gas-liquid two-phase flow pipeline based on acoustic emission signal. Oil & Gas Storage and Transportation, 2021, 40(10): 1131-1137. (in Chinese)

Yuan, F., Zeng, Y., Luo, R., et al. Numerical and experimental study on the generation and propagation of negative wave in high-pressure gas pipeline leakage. Journal of Loss Prevention in the Process Industries, 2020, 65: 104129.

Zadkarami, M., Shahbazian, M., Salahshoor, K. Pipeline leak diagnosis based on wavelet and statistical features using Dempster-Shafer classifier fusion technique. Process Safety and Environmental Protection, 2017, 105: 156-163.

Zeng, Y., Luo, R. Numerical analysis on pipeline leakage characteristics for incompressible flow. Journal of Applied Fluid Mechanics, 2019, 12(2): 485-494.

Zhang, H., Yuan, G., Li, G., et al. Numerical simulation of leakage flow field for tubing and casing in gas wells. China Petroleum Machinery, 2020, 48(12): 123-129. (in Chinese)

Zhang, J., Lian, Z., Zhou, Z., et al. Acoustic method of high-pressure natural gas pipelines leakage detection: Numerical and applications. International Journal of Pressure Vessels and Piping, 2021a, 194: 104540.

Zhang, K., Tan, B., Zhang, W., et al. Design of a new acoustic logging while drilling tool. Sensors, 2021b, 21(13): 4385.

Zhang, M., Chen, X., Li, W. A hybrid hidden Markov model for pipeline leakage detection. Applied Sciences, 2021c, 11(7): 3138.

Zhang, T., Kou, J., Sun, S. Review on dynamic Van der Waals theory in two-phase flow. Advances in Geo-Energy Research, 2017, 1(2): 124-134.




DOI: https://doi.org/10.46690/ager.2022.03.02

Refbacks

  • There are currently no refbacks.


Copyright (c) 2022 The Author(s)

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Copyright ©2018. All Rights Reserved