1887
Volume 66, Issue 2
  • E-ISSN: 1365-2478

Abstract

ABSTRACT

The ‘depth from extreme points’ method is an important tool to estimate the depth of sources of gravity and magnetic data. In order to interpret gravity gradient tensor data conveniently, formulas for the tensor data form regarding depth from the extreme points method were calculated in this paper. Then, all of the gradient tensor components were directly used to interpret the causative source. Beyond the component, also the and components can be used to obtain depth information. In addition, the total horizontal derivative of the depth from extreme points of the gradient tensor can be used to describe the edge information of geologic sources. In this paper, we investigated the consistency of the homogeneity degree calculated by using the different components, which leads to the calculated depth being confirmed. Therefore, a more integrated interpretation can be obtained by using the gradient tensor components. Different synthetic models were used with and without noise to test the new approach, showing stability, accuracy and speed. The proposed method proved to be a useful tool for gradient tensor data interpretation. Finally, the proposed method was applied to full tensor gradient data acquired over the Vinton Salt Dome, Louisiana, USA, and the results are in agreement with those obtained in previous research studies.

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/content/journals/10.1111/1365-2478.12512
2017-04-27
2020-04-10
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References

  1. AbbasM.A. and FediM.2014. Automatic DEXP imaging of potential fields independent of the structural index. Geophysical Journal International199, 1625–1632.
    [Google Scholar]
  2. AbbasM.A., FediM. and FlorioG.2014. Improving the local wavenumber method by automatic DEXP transformation. Journal of Applied Geophysics111, 250–255.
    [Google Scholar]
  3. BeikiM.2010. Analytic signals of gravity gradient tensor and their application to estimate source location. Geophysics75, I59–I74.
    [Google Scholar]
  4. BeikiM. and PedersenL.B.2010. Eigenvector analysis of gravity gradient tensor to locate geologic bodies. Geophysics75, I37–I49.
    [Google Scholar]
  5. CellaF., FediM. and FlorioG.2009. Toward a full multiscale approach to interpret potential fields. Geophysical Prospecting57, 543–557.
    [Google Scholar]
  6. CribbJ.1976. Application of the generalized linear inverse to the inversion of static potential data. Geophysics41, 1365–1369.
    [Google Scholar]
  7. ElysseievaI.S. and PastekaR.2009. Direct interpretation of 2D potential fields for deep structures by means of the quasi‐singular points method. Geophysical Prospecting57, 683–705.
    [Google Scholar]
  8. FediM.2007. DEXP: a fast method to determine the depth and the structural index of potential fields sources. Geophysics72, I1–I11.
    [Google Scholar]
  9. FediM. and FlorioG.2001. Detection of potential fields source boundaries by enhanced horizontal derivative method. Geophysical Prospecting49, 40–58.
    [Google Scholar]
  10. FediM. and FlorioG.2006. SCALFUN: 3D analysis of potential field scale function to determine independently or simultaneously structural index and depth to source. 76th SEG meeting, New Orleans, USA, Expanded Abstracts, 963–967.
  11. FediM. and FlorioG.2011. Normalized downward continuation of potential fields within the quasi‐harmonic region. Geophysical Prospecting59(6), 1087–1100.
    [Google Scholar]
  12. FediM. and PilkingtonM.2012. Understanding imaging methods for potential field data. Geophysics77, G13–G24.
    [Google Scholar]
  13. FediM. and AbbasM.A.2013. A fast interpretation of self‐potential data using the depth from extreme points method. Geophysics78, E107–E116.
    [Google Scholar]
  14. FediM. and FlorioG.2013. Determination of the maximum‐depth to potential field sources by a maximum structural index method. Journal of Applied Geophysics88, 154–160.
    [Google Scholar]
  15. FlorioG., FediM. and RapollaA.2009. Interpretation of regional aeromagnetic data by the scaling function method: the case of Southern Apennines (Italy). Geophysical Prospecting57, 479–489.
    [Google Scholar]
  16. GengM., HuangD., YangQ. and LiuY.2014. 3D inversion of airborne gravity‐gradiometry data using cokriging. Geophysics79, G37–G47.
    [Google Scholar]
  17. GuoL.H., MengX.H., ShiL. and LiS.L.2009. 3‐D correlation imaging for gravity and gravity gradiometry data. Chinese Journal of Geophysics‐Chinese Edition52, 1098–1106.
    [Google Scholar]
  18. MataragioJ. and KieleyJ.2009. Application of full tensor gradient invariants in detection of intrusion‐hosted sulphide mineralization: implications for deposition mechanisms. First Break27, 95–98.
    [Google Scholar]
  19. MaurielloP. and PatellaD.2001. Localization of maximum‐depth gravity anomaly sources by a distribution of equivalent point masses. Geophysics66, 1431–1437.
    [Google Scholar]
  20. MoreauF., GibertD., HolschneiderM. and SaraccoG.1999. Identification of sources of potential fields with the continuous wavelet transform: basic theory. Journal of Geophysical Research: Solid Earth104, 5003–5013.
    [Google Scholar]
  21. OliveiraJr. V.C. and BarbosaV.C.F.2013. 3‐D radial gravity gradient inversion. Geophysical Journal International195, 883–902.
    [Google Scholar]
  22. OrucB.2010. Depth estimation of simple causative sources from gravity gradient tensor invariants and vertical component. Pure and Applied Geophysics167, 1259–1272.
    [Google Scholar]
  23. PedersenL.B.1991. Relations between potential fields and some equivalent sources. Geophysics56, 961–971.
    [Google Scholar]
  24. SalemA., MastertonS., CampbellS., FairheadJ.D., DickinsonJ. and MurphyC.2013. Interpretation of tensor gravity data using an adaptive tilt angle method. Geophysical Prospecting61, 1065–1076.
    [Google Scholar]
  25. ThompsonD.T.1982. EULDPH—a new technique for making computer assisted depth estimates from magnetic data. Geophysics47, 31–37.
    [Google Scholar]
  26. WijnsC., PeresC. and KowalczykP.2005. Theta map: edge detection in magnetic data. Geophysics70, L39–L43.
    [Google Scholar]
  27. ZhangC.Y., MushayandebvuM.F., ReidA.B., FairheadJ.D. and OdegardM.E.2000. Euler deconvolution of gravity tensor gradient data. Geophysics65, 512–520.
    [Google Scholar]
  28. ZhdanovM.S., LiuX., WilsonG.A. and WanL.2011. Potential field migration for rapid imaging of gravity gradiometry data. Geophysical Prospecting59, 1052–1071
    [Google Scholar]
  29. ZhdanovM.S., LiuX., WilsonG.A. and WanL.2012. 3D migration for rapid imaging of total‐magnetic‐intensity data. Geophysics77, J1–J5.
    [Google Scholar]
  30. ZhouW.N.2015. Normalized full gradient of full tensor gravity gradient based on adaptive iterative Tikhonov regularization downward continuation. Journal of Applied Geophysics118, 75–83.
    [Google Scholar]
  31. ZhouW.N.2016. Depth estimation method based on the ratio of gravity and full tensor gradient invariant. Pure and Applied Geophysics173, 499–508.
    [Google Scholar]
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