Abstract
Euler deconvolution is a standard tool of geophysical prospection. In the early 1980s, the beginning of its development, it was used for the evaluation of magnetic field data. However, since the 1990s, together with the increasing power of computers, research was intensified on the aspect that Euler deconvolution is also applicable to gravity gradiometry data. Now we are in the position that gravity gradiometry data with near global coverage from a single source are available, namely the satellite mission GOCE (Gravity field and steady-state Ocean Circulation Explorer), launched on 17 March 2009.In this project we investigate the benefit of Euler deconvolution to geodesy, e.g. to retrieve global gravity models. We also assess whether geodetic methodology can contribute to enhance Euler deconvolution. Until now our project is still in preparatory stage, mainly, because the GOCE gradiometry data need to be preprocessed extensively.
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References
Blakely RJ (1995), “Potential Theory in Gravity and Magnetic Applications”, Cambridge University Press.
CODATA (2010). Recommended values. Ed. by National Institute of Standards and Technology. URL: http://physics.nist.gov/cgi-bin/cuu/Value?bg, retrieved: 10 April 2012.
ESA (2011) GOCE website: http://www.esa.int/goce, retrieved: 10 April 2012.
Mantyla M (1988), “An introduction to solid modeling”, Principles of computer science series Vol. 13, Computer Science Press.
Marson I and Klingelé EE (1993), “Advantages of using the vertical gradient of gravity for 3-D interpretation”, Geophysics. Vol. 58(11), pp. 1588–1595.
Mushayandebvu MF, Lesur V, Reid AB and Fairhead JD (2004), “Grid Euler deconvolution with constraints for 2D structures”, Geophysics. Vol. 69(2), pp. 489–496.
Peil R, Bruinsma S, Migliaccio F, Förste C, Goiginger H, Schuh WD, Höck E, Reguzzoni M, Brockmann JM, Abrikosov O, Veicherts M, Fecher T, Mayrhofer R, Krasbutter I, Sansò F, Tscherning CC (2011), “First GOCE gravity field models derived by three different approaches”, Journal of Geodesy. Vol. 85, pp. 819–843.
Reid AB, Allsop JM, Granser H, Millett AJ and Somerton IW (1990), “Magnetic interpretation in three dimensions using Euler deconvolution”, Geophysics. Vol. 55(1), pp. 80–91.
Roth M (2009), “Marine full tensor gravity gradiometry data analysis and Euler deconvolution”, study thesis, Intstitute of Geodesy, University of Stuttgart.
Thompson DT (1982), “EULDPH: A new technique for making computer-assisted depth estimates from magnetic data”, Geophysics. Vol. 47(1), pp. 31–37.
Wu P (2002), “Euler Deconvolution”. URL: http://www.geo.ucalgary.ca/~wu/Goph547/EulerDeconvolution.pdf, retrieved: 10 April 2012.
Zhang C, Mushayandebvu MF, Reid AB, Fairhead JD and Odegard ME (2000), “Euler deconvolution of gravity tensor gradient data”, Geophysics. Vol. 65(2), pp. 512–520.
Acknowledgements
The authors thank the High Performance Computing Center Stuttgart (HLRS) for the opportunity to use their computing facilities; furthermore, we gratefully acknowledge the helpful technical support. This work was supported by the European Space Agency (ESA) within the project UWB/GOCE-GDC – ITT AO/1-6367/10/NL/AF, STSE-GOCE + , Theme2.
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Roth, M., Sneeuw, N., Keller, W. (2013). Euler Deconvolution of GOCE Gravity Gradiometry Data. In: Nagel, W., Kröner, D., Resch, M. (eds) High Performance Computing in Science and Engineering ‘12. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33374-3_36
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DOI: https://doi.org/10.1007/978-3-642-33374-3_36
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