Passive Super-Low Frequency electromagnetic prospecting technique

Abstract

The Super-Low Frequency (SLF) electromagnetic prospecting technique, adopted as a non-imaging remote sensing tool for depth sounding, is systematically proposed for subsurface geological survey. In this paper, we propose and theoretically illustrate natural source magnetic amplitudes as SLF responses for the first step. In order to directly calculate multi-dimensional theoretical SLF responses, modeling algorithms were developed and evaluated using the finite difference method. The theoretical results of three-dimensional (3-D) models show that the average normalized SLF magnetic amplitude responses were numerically stable and appropriate for practical interpretation. To explore the depth resolution, three-layer models were configured. The modeling results prove that the SLF technique is more sensitive to conductive objective layers than high resistive ones, with the SLF responses of conductive objective layers obviously showing uprising amplitudes in the low frequency range. Afterwards, we proposed an improved Frequency-Depth transformation based on Bostick inversion to realize the depth sounding by empirically adjusting two parameters. The SLF technique has already been successfully applied in geothermal exploration and coalbed methane (CBM) reservoir interpretation, which demonstrates that the proposed methodology is effective in revealing low resistive distributions. Furthermore, it siginificantly contributes to reservoir identification with electromagnetic radiation anomaly extraction. Meanwhile, the SLF interpretation results are in accordance with dynamic production status of CBM reservoirs, which means it could provide an economical, convenient and promising method for exploring and monitoring subsurface geo-objects.

Keywords

Super-Low Frequency (SLF) / three-dimensional modeling / frequency-depth transformation / geothermal exploration / coalbed methane (CBM) / electromagnetic radiation (EMR)

References

[1] Aprea C, Booker J, Smith J (1997). The forward problem of electromagnetic induction: accurate finite-difference approximations for two-dimensional discrete boundaries with arbitrary geometry. Geophys J Int, 129(1): 29–40

[2] Atzberger C (2013). Advances in remote sensing of agriculture: context description, existing operational monitoring systems and major information needs. Remote Sens, 5(2): 949–981

[3] Avdeev D B (2005). Three-dimensional electromagnetic modelling and inversion from theory to application. Surv Geophys, 26(6): 767–799

[4] Berdichevsky M N, Dmitriev V I, Zhdanov M S (2010). Possibilities and problems of modern magnetotellurics. Izv Phys Solid Earth, 46(8): 648–654 doi:10.1134/S1069351310080021

[5] Börner R U (2010). Numerical modelling in geo-electromagnetics: advances and challenges. Surv Geophys, 31(2): 225–245 doi:10.1007/s10712-009-9087-x

[7] Congalton R, Gu J, Yadav K, Thenkabail P, Ozdogan M (2014). Global land cover mapping: a review and uncertainty analysis. Remote Sens, 6(12): 12070–12093 doi:10.3390/rs61212070

[8] Cui R B, Qin Q M, Li B S, Wang Q P (2009). Design and development of passive super low frequency electromagnetic data processing software. In: 2009 IEEE International Geoscience And Remote Sensing Symposium, Vols 1-5 IEEE International Symposium on Geoscience and Remote Sensing IGARSS. (345 E 47TH ST, New York, NY 10017 USA: IEEE), 627–630

[9] Frid V, Rabinovitch A, Bahat D (2003). Fracture induced electromagnetic radiation. J Phys D Appl Phys, 36(13): 1620–1628

[10] Frid V, Vozoff K (2005). Electromagnetic radiation induced by mining rock failure. Int J Coal Geol, 64(1‒2): 57–65

[11] Gomez-Treviño E (1996). Approximate depth averages of electrical conductivity from surface magnetotelluric data. Geophys J Int, 127(3): 762–772 doi:10.1111/j.1365-246X.1996.tb04055.x

[12] Greiling R O, Obermeyer H (2010). Natural electromagnetic radiation (EMR) and its application in structural geology and neotectonics. J Geol Soc India, 75(1): 278–288

[13] He X Q, Nie B S, Chen W X, Wang E Y, Dou L M, Wang Y H, Liu M J, Hani M (2012). Research progress on electromagnetic radiation in gas-containing coal and rock fracture and its applications. Saf Sci, 50(4): 728–735

[14] Heise W, Caldwell T G, Bibby H M, Bannister S C (2008). Three-dimensional modelling of magnetotelluric data from the Rotokawa geothermal field, Taupo Volcanic Zone, New Zealand. Geophys J Int, 173(2): 740–750

[15] Huang H P, Won I J (2003). Detecting metal objects in magnetic environments using a broadband electromagnetic method. Geophysics, 68(6): 1877–1887 doi:10.1190/1.1635040

[16] Liu H, Sang S, Wang G, Li M, Xu H, Liu S, Li J, Ren B, Zhao Z, Xie Y (2014). Block scale investigation on gas content of coalbed methane reservoirs in southern Qinshui basin with statistical model and visual map. J Petrol Sci Eng, 114: 1–14

[17] Liu M J, He X Q (2001). Electromagnetic response of outburst-prone coal. Int J Coal Geol, 45(2-3): 155–162

[18] Mackie R L, Madden T R, Wannamaker P E (1993). Three-dimensional magnetotelluric modeling using difference equations—Theory and comparisons to integral equation solutions. Geophysics, 58(2): 215–226

[19] Meju M A (2002). Geoelectromagnetic exploration for natural resources: Models, case studies and challenges. Surv Geophys, 23(2‒3): 133–206 doi:10.1023/A:1015052419222

[20] Melesse A M, Weng Q, Thenkabail P S, Senay G B (2007). Remote sensing sensors and applications in environmental resources mapping and modelling. Sensors (Basel Switzerland), 7(12): 3209–3241

[21] Moore T A (2012). Coalbed methane: a review. Int J Coal Geol, 101: 36–81

[22] Ouchi K (2013). Recent trend and advance of synthetic aperture radar with selected topics. Remote Sens, 5(2): 716–807

[23] Qin  Q M, Li  B S, Cui  R B, Jiang  H B, Wang  Q P, Zhang  Z X (2010). Analysis of factors affecting natural source SLF electromagnetic exploration at geothermal wells. Chinese Journal of Geophysics, 53(3): 685–694doi: 10.3969/j.issn.0001-5733.2010.03.023(in Chinese)

[24] Rodríguez J, Esparza F J, Gómez-Treviño E (2010). 2-D Niblett-Bostick magnetotelluric inversion. Geologica Acta, 8(1): 15–30 doi: 10.1344/105.000001513

[25] Schmucker U (1987). Substitute conductors for electromagnetic response estimates. Pure Appl Geophys, 125(2‒3): 341–367

[26] Shan Z, Qi Q, Nan W, Li C, Yan B, Cheng Y (2014). Analysis and design of passive super low frequency detection system. In: 2014 IEEE Geoscience and Remote Sensing Symposium. (IGARSS). Proceedings (Piscataway, NJ, USA: IEEE), 5056–5059

[27] Siripunvaraporn W, Egbert G, Lenbury Y (2002). Numerical accuracy of magnetotelluric modeling: a comparison of finite difference approximations. Earth Planets Space, 54(6): 721–725 doi:10.1186/BF03351724

[28] Slonecker T, Fisher G B, Aiello D P, Haack B (2010). Visible and infrared remote imaging of hazardous waste: a review. Remote Sens, 2(11): 2474–2508

[29] Spichak V, Manzella A (2009). Electromagnetic sounding of geothermal zones. J Appl Geophys, 68(4): 459–478

[30] Su X B, Lin X, Liu S, Zhao M, Song Y (2005). Geology of coalbed methane reservoirs in the Southeast Qinshui Basin of China. Int J Coal Geol, 62(4): 197–210

[31] van Genderen J L (2011). Advances in environmental remote sensing: sensors, algorithms, and applications. Int J Digit Earth, 4(5): 446–447

[32] Wang E Y, He X Q, Liu X, Li Z, Wang C, Xiao D (2011). A non-contact mine pressure evaluation method by electromagnetic radiation. J Appl Geophys, 75(2): 338–344

[33] Wang E Y, Jia H L, Song D Z, Li N, Qian W H (2014). Use of ultra-low-frequency electromagnetic emission to monitor stress and failure in coal mines. Int J Rock Mech Min Sci, 70: 16–25

[34] Wang N, Qin Q M, Chen L, Bai Y B, Zhao S S, Zhang C Y (2014a). Dynamic monitoring of coalbed methane reservoirs using Super-Low Frequency electromagnetic prospecting. Int J Coal Geol, 127: 24–41

[35] Wang N, Qin Q M, Chen L, Bai Y B, Zhao S S, Zhang C Y (2014b). Passive Super-Low Frequency Remote Sensing Technique For Monitoring Coal-Bed Methane Reservoirs. In: 2014 IEEE International Geoscience And Remote Sensing Symposium (IGARSS) IEEE International Symposium on Geoscience and Remote Sensing IGARSS. (345 E 47TH ST, NEW YORK, NY 10017 USA: IEEE), 867–870

[36] Wang N, Qin Q M, Xie C, Chen L, Bai Y B (2013). Coal-Bed Methane Reservoir Identification Using The Natural Source Super-Low Frequency Remote Sensing. In: 2013 IEEE International Geoscience And Remote Sensing Symposium (IGARSS) IEEE International Symposium on Geoscience and Remote Sensing IGARSS. (345 E 47TH ST, NEW YORK, NY 10017 USA: IEEE), 4022–4025

[37] Yavuz M E, Teixeira F L (2009). Ultrawideband microwave sensing and imaging using time-reversal techniques: a review. Remote Sens, 1(3): 466–495

[38] Zhdanov M S, Varentsov I M, Weaver J T, Golubev N G, Krylov V A (1997). Methods for modelling electromagnetic fields Results from COMMEMI—the international project on the comparison of modelling methods for electromagnetic induction. J Appl Geophys, 37(3‒4): 133–271 doi:10.1016/S0926-9851(97)00013-X

Acknowledgments

This work is financially supported by the National Science and Technology Major Project of China (2011ZX05034-002) and China Scholarship Council (CSC). Resources of Peking University (PKU), Institute of Electronics (Chinese Academy of Sciences) and other coalbed methane companies are utilized and much appreciated. Meanwhile, we also express our thanks for constructive comments from Prof. Gary Egbert in Oregon State University, USA. Content embellishments were provided by Dr. Ebeer and Dr. Hamed in Peking University, and we are grateful for their efforts. We also thank editors and anonymous reviewers for their constructive comments and suggestions.

RIGHTS & PERMISSIONS

2017 Higher Education Press and Springer-Verlag Berlin Heidelberg