Numerical Modeling and Uncertainty Analysis of Downhole Low-Frequency Electromagnetic Transmission
DOI:
https://doi.org/10.13052/2026.ACES.J.410709Keywords:
Downhole signal transmission, low-frequency electromagnetic waves, sensitivity analysis, uncertainty analysisAbstract
As oil and gas resource development extends into increasingly complex geological conditions, reliable downhole signal transmission has become a critical challenge in drilling and measurement-while-drilling (MWD) operations. In engineering practice, downhole low-frequency electromagnetic wave (LF-EM) transmission is widely used as an important means of downhole data telemetry because of its low dependence on drilling fluid. However, uncertainties in formation properties and fluctuations in geological parameters can significantly affect electromagnetic signal transmission, making it difficult for surface systems to stably receive downhole information in practical applications. To address this issue, a transmission channel model for downhole LF-EM is established based on FEKO. First, sensitivity analysis is performed to identify the key uncertainty parameters that have the most significant influence on signal attenuation. Then, the Kriging method and the Stochastic Collocation Method (SCM) are employed to conduct uncertainty analysis and to obtain the probability density function (PDF) of the received magnetic-field strength within the parameter fluctuation range. To compare the reliability and applicability of the two methods, Monte Carlo Method (MCM) simulation is adopted as the benchmark, and the Mean Equivalent Area Method (MEAM) is introduced for comprehensive evaluation. Results show that the SCM exhibits overall better fitting accuracy and computational stability than the Kriging method, making it more suitable for probabilistic prediction and risk assessment of downhole low-frequency electromagnetic transmission.
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References
J. Sun, J. Yang, Y. Bai, K. Lyu, and F. Liu, “Research progress and development of deep and ultra-deep drilling fluid technology,” Petroleum Exploration and Development, vol. 51, no. 4, pp. 1022–1034, 2024.
A. E. Ibhaze, D. O. Akinola, A. L. Imoize, P. E. Orukpe, and F. O. Edeko, “A review of downhole communication technologies,” Journal of Telecommunication, Electronic and Computer Engineering, vol. 14, no. 4, pp. 1–10, 2022.
Y. Wu, F. Wang, J. Li, B. Wang, and D. Pang, “Wireless electromagnetic telemetry for metal cased wells: A novel approach with comprehensive channel analysis,” Geoenergy Science and Engineering, vol. 233, no. 212573, 2024.
Z. Li, J. Lin, S. Xing, X. Ji, M. Dang, and J. Wang, “A novel wireless electromagnetic wave transmission method applicable to water injection wells and analysis of the influence factors,” Scientific Reports, vol. 15, no. 17230, 2025.
C. Shao, L. Xu, X. Chen, Z. Chu, and B. Yang, “Factors affecting received signal intensity of electromagnetic measurement-while-drilling during underground in-seam horizontal drilling,” Journal of Natural Gas Science and Engineering, vol. 56, pp. 212–221, 2018.
Z. Wang, D. Jia, F. Sun, Z. Hao, and Q. Chen, “Network model and application in wellbore wireless communication of extremely low-frequency electromagnetic waves,” Journal of Geophysics and Engineering, vol. 22, no. 3, pp. 672–681, 2025.
H. Li, X. Chen, Y. Meng, Y. Chen, G. Li, and C. Xu, “A novel method for wireless telemetry during air drilling based on air pressure pulses,” Geoenergy Science and Engineering, vol. 234, no. 212669, 2024.
P. Sumithra and D. Thiripurasundari, “A review on computational electromagnetics methods,” Advanced Electromagnetics, vol. 6, no. 1, pp. 42–55, 2017.
R. Streich and A. Swidinsky, “On method-of-moments modelling of electromagnetic sources connected to metallic well casings,” Geophysical Journal International, vol. 234, no. 2, pp. 1476–1483, 2023.
Z. Wang, D. Jia, F. Sun, Q. Chen, S. Zhu, and Q. Wang, “Research on extremely low frequency electromagnetic wave model and simulation in wellbore communication,” Scientific Reports, vol. 14, no. 20093, 2024.
J. A. Luta, C. A. Castillo, D. C. Horvath, R. A. Howard, and S. D. Pekarek, “2-D method of moments formulations for nonlinear low-frequency electromagnetics,” Engineering Analysis with Boundary Elements, vol. 179, no. 106383, 2025.
Z. Fei, Y. Huang, J. Zhou, and Q. Xu, “Uncertainty quantification of crosstalk using stochastic reduced order models,” IEEE Transactions on Electromagnetic Compatibility, vol. 59, no. 1, pp. 228–239, 2016.
R. S. Edwards, A. C. Marvin, and S. J. Porter, “Uncertainty analyses in the finite-difference time-domain method,” IEEE Transactions on Electromagnetic Compatibility, vol. 52, no. 1, pp. 155–163, 2010.
S. A. Pignari, G. Spadacini, and F. Grassi, “Modeling field-to-wire coupling in random bundles of wires,” IEEE Electromagnetic Compatibility Magazine, vol. 6, no. 3, pp. 85–90, 2017.
H. Xie, J. F. Dawson, J. Yan, A. C. Marvin, and M. P. Robinson, “Numerical and analytical analysis of stochastic electromagnetic fields coupling to a printed circuit board trace,” IEEE Transactions on Electromagnetic Compatibility, vol. 62, no. 4, pp. 1128–1135, 2020.
H. You, M. Yang, D. Wang, and X. Jia, “Kriging model combined with Latin hypercube sampling for surrogate modeling of analog integrated circuit performance,” in Proc. 10th International Symposium on Quality Electronic Design (ISQED), San Jose, CA, USA, pp. 554–558, 2009.
J. Bai, G. Zhang, D. Wang, A. P. Duffy, and L. Wang, “Performance comparison of the SGM and the SCM in EMC simulation,” IEEE Transactions on Electromagnetic Compatibility, vol. 58, no. 6, pp. 1739–1746, 2016.
J. Bai, Y. Wan, M. Li, G. Zhang, and X. He, “Reduction of random variables in EMC uncertainty simulation model,” Applied Computational Electromagnetics Society (ACES) Journal, vol. 37, no. 9, pp. 941–947, 2022.
J. Bai, L. Wang, D. Wang, A. P. Duffy, and G. Zhang, “Validity evaluation of the uncertain EMC simulation results,” IEEE Transactions on Electromagnetic Compatibility, vol. 59, no. 3, pp. 797–804, 2017.
C. Zhang, H. Dong, J. Ge, and H. Liu, “Theoretical channel model and characteristics analysis of EM-MWD in the underground coal mine,” IEEE Access, vol. 9, pp. 142644–142652, 2021.
