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A Method for the Full Automation of Euler Deconvolution for the Interpretation of Magnetic Data

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Abstract

The conventional Euler deconvolution methodology requires the user to choose appropriate structural index (SI) in order to compute the source parameters, and this makes the operation tedious and time consuming. To solve the mentioned problem, a method based on Euler’s homogeneity relation for full automation of magnetic data interpretation is presented in this paper. The technique uses multiple linear regression (MLR) methodology to estimate background, horizontal coordinate (x0 and y0), depth and structural index (SI) simultaneously is prepared and used for this task. The technique involves the use of first-order derivatives, independent of analytic signal (AS) and the derivatives are computed directly from the total field grid. It is fast means of magnetic data interpretation and easy to implement.

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Correspondence to Nuraddeen Usman .

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Usman, N., Abdullah, K., Nawawi, M. (2018). A Method for the Full Automation of Euler Deconvolution for the Interpretation of Magnetic Data. In: Saian, R., Abbas, M. (eds) Proceedings of the Second International Conference on the Future of ASEAN (ICoFA) 2017 – Volume 2. Springer, Singapore. https://doi.org/10.1007/978-981-10-8471-3_80

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  • DOI: https://doi.org/10.1007/978-981-10-8471-3_80

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-8470-6

  • Online ISBN: 978-981-10-8471-3

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