Ocean Science Journal

, Volume 53, Issue 2, pp 405–412 | Cite as

3D Focused Inversion of Near-bottom Magnetic Data from Autonomous Underwater Vehicle in Rough Seas

  • Zhou Fei
  • Tao ChunhuiEmail author
  • Wu Tao
  • Zeng Zhaofa
  • Liu Cai
Part of the following topical collections:
  1. Deep Seabed Mining Resources


The observation area of an autonomous underwater vehicle (AUV) often contains undulating terrain in which the shallow portions make a great contribution to near-bottom magnetic data. Magnetic information from varying terrain may be inadvertently removed when traditional topographic correction methods are used to reduce the effect of undulating terrain on inversion results. In this study, we introduce a terrain-weighting matrix into the focused inversion process to overcome this problem. To counteract the natural decay of the potential field, we used the focused inversion with a minimum support function to obtain focused results and depth-weighting function. We also used the interpolation-iteration method to mitigate the influence of the fluctuating observation surface on the inversion results. We verified the effectiveness of the proposed method by conducting model tests using near-bottom data measured along the Southwest Indian Ridge (SWIR) by the AUV, Qianlong II. We obtained the 3D magnetization structure of the oceanic core complex (OCC) area at the 28th segment along the SWIR and concluded that the OCC was primarily composed of gabbroic rock.


3D focused inversion undulating terrain fluctuating observation surface interpolation-iteration method oceanic core complex 


  1. Bhattacharyya BK (1964) Magnetic anomalies due to prism-shaped bodies with arbitrary polarization. Geophysics 29(4):517–531CrossRefGoogle Scholar
  2. Caratori Tontini F, De Ronde CEJ, Yoerger D, Kinsey J, Tivey M (2012) 3-D focused inversion of near-seafloor magnetic data with application to the Brothers volcano hydrothermal system, Southern Pacific Ocean, New Zealand. J Geophys Res-Sol Ea 117(B10):122–134CrossRefGoogle Scholar
  3. Chen B, Liang YY, Hu M, Hou B, Yu YS, Wang X, Wu GY (2013) Application of adaptive median filtering in logging processing. Comp Hydrocarb Reserv 6(2):23–25Google Scholar
  4. Hou ZL (2016) Research and application of the parallel inversion algorithms based on the full tensor gravity gradiometry data. Ph.D. Thesis, Jilin UniversityGoogle Scholar
  5. Kuang XT, Wu JS, Yang H, Zheng GR, Zhu XY (2016) Twodimensional inversion of magnetic anomaly and its application to undulating terrain. Geophys Geochem Explor 40(4):788–797Google Scholar
  6. Kumagai H, Okino K, Joshima Masato, Morishita T, Nakamura K, Neo N, Okada S, Sato T, Sawaguchi T, Shibuya T, Takaesu M, Takai K (2006) A field-work approach to investigate UltraH3-linkage hypothesis at two distinct hydrothermal fields, Indian Ocean. Eos T Am Geophys Un 87(Supplement 36): WP1319Google Scholar
  7. Last, BJ, Kubik K (1983) Compact gravity inversion. Geophysics 48(48):713–721CrossRefGoogle Scholar
  8. Li SL, Li YG (2014) Inversion of magnetic anomaly on rugged observation surface in the presence of strong remnant magnetization. Geophysics 79(2):502–514Google Scholar
  9. Li YG, Oldenburg DW (1996) 3-D inversion of magnetic data. Geophysics 61(2):394–408CrossRefGoogle Scholar
  10. Okuma S, Nakatsuka T, Ishizuka Y (2013) Aeromagnetic constraints on the subsurface structure of Usu Volcano, Hokkaido, Japan. Explor Geophys 45(1):24–36CrossRefGoogle Scholar
  11. Pilkington M (1997) 3-D magnetic imaging using conjugate gradients. Geophysics 62(4):1132–1142CrossRefGoogle Scholar
  12. Portniaguine O, Zhdanov MS (1999) Focusing geophysical inversion images. Geophysics 64(3):874–887CrossRefGoogle Scholar
  13. Sato T, Okino K, Kumagai H (2013) Magnetic structure of an oceanic core complex at the southernmost Central Indian Ridge: analysis of shipboard and deep-sea three-component magnetometer data. Geochem Geophy Geosy 10(6):329–332Google Scholar
  14. Tao CH, Wu T, Liu C, Li HM, Zhang JH (2017) Fault inference and boundary recognition based on near-bottom magnetic data in the Longqi hydrothermal field. Mar Geophys Res 38:1–9CrossRefGoogle Scholar
  15. Tikhonov AN, Arsenin VI (1977) Solutions of ill-posed problems. Halsted Press, New York, 258 pGoogle Scholar
  16. Wu T (2017) Near-bottom magnetic study of hydrothermal fields on the Southwest Indian Ridge: application to Longqi and Duanqiao hydrothermal fields. Ph.D. Thesis, Jilin UniversityGoogle Scholar
  17. Wu T, Tao CH, Zhang JH, Liu C (2018) Correction of tri-axial magnetometer interference caused by an autonomous underwater vehicle near-bottom platform. Ocean Eng 160:68–77CrossRefGoogle Scholar
  18. Xu SZ, Yu HL (2007) The interpolation iteration method for potential field continuation from undulating surface to plane. Chinese J Geophysics 50(6):1566–1570CrossRefGoogle Scholar
  19. Zhao MH, Qiu XL, Li JB, Sauter D, Ruan AG, Chen J, Cannat M, Singh S, Zhang JZ, Wu ZL, Niu XW (2013) Three-dimensional seismic structure of the Dragon Flag oceanic core complex at the ultraslow spreading Southwest Indian Ridge (49°39′E). Geochem Geophy Geosy 14(10):4544–4563CrossRefGoogle Scholar
  20. Zhdanov MS, Portniaguine O (2002) 3-D magnetic inversion with data compression and image focusing. Geophysics 67(5): 1532–1541CrossRefGoogle Scholar
  21. Zhu J, Lin J, Chen YJ, Tao CH, Christopher RG (2010) A reduced crustal magnetization zone near the first observed active hydrothermal vent field on the Southwest Indian Ridge. Geophys Res Lett 37(18):389–390CrossRefGoogle Scholar

Copyright information

© Korea Institute of Ocean Science & Technology (KIOST) and the Korean Society of Oceanography (KSO) and Springer Nature B.V. 2018

Authors and Affiliations

  • Zhou Fei
    • 1
    • 2
  • Tao Chunhui
    • 2
    Email author
  • Wu Tao
    • 2
  • Zeng Zhaofa
    • 1
  • Liu Cai
    • 1
  1. 1.College of Geo-exploration Science and TechnologyJilin UniversityChangchunChina
  2. 2.Key Laboratory of Submarine Geosciences, Second Institute of OceanographyState Oceanic AdministrationHangzhouChina

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