Correct structural index in Euler deconvolution via base-level estimates

In most applications, the Euler deconvolution aims to define the nature (type) of the geologic source (i.e., the structural index [SI]) and its depth position. However, Euler deconvolution also estimates the horizontal positions of the sources and the base level of the magnetic anomaly. To determine the correct SI, most authors take advantage of the clustering of depth estimates. We have analyzed Euler’s equation to indicate that random variables contaminating the magnetic observations and its gradients affect the base-level estimates if, and only if, the SI is not assumed correctly. Grounded on this theoretical analysis and assuming a set of tentative SIs, we have developed a new criterion for determining the correct SI by means of the minimum standard deviation of base-level estimates. We performed synthetic tests simulating multiple magnetic sources with different SIs. To produce mid and strongly interfering synthetic magnetic anomalies, we added constant and nonlinear backgrounds to the anomalies and approximated the simulated sources laterally. If the magnetic anomalies are weakly interfering, the minima standard deviations either of the depth or base-level estimates can be used to determine the correct SI. However, if the magnetic anomalies are strongly interfering, only the minimum standard deviation of the base-level estimates can determine the SI correctly. These tests also show that Euler deconvolution does not require that the magnetic data be corrected for the regional fields (e.g., International Geomagnetic Reference Field [IGRF]). Tests on real data from part of the Goiás Alkaline Province, Brazil, confirm the potential of the minimum standard deviation of base-level estimates in determining the SIs of the sources by applying Euler deconvolution either to total-field measurements or to total-field anomaly (corrected for IGRF). Our result suggests three plug intrusions giving rise to the Diorama anomaly and dipole-like sources yielding Arenópolis and Montes Claros de Goiás anomalies.

[1]  Henglei Zhang,et al.  GRAVITY AND MAGNETIC INTEGRATED DATA INTERPRETATION OF THE CORRÉGO DOS BOIS COMPLEX, GOIÁS ALKALINE PROVINCE, CENTRAL BRAZIL , 2016 .

[2]  M. Fedi,et al.  MHODE: a local-homogeneity theory for improved source-parameter estimation of potential fields , 2015 .

[3]  L. Uieda,et al.  Estimation of the total magnetization direction of approximately spherical bodies , 2014 .

[4]  J. Ebbing,et al.  Avoidable Euler Errors – the use and abuse of Euler deconvolution applied to potential fields , 2014 .

[5]  Vanderlei C. Oliveira,et al.  Geophysical tutorial: Euler deconvolution of potential-field data , 2014 .

[6]  M. Fedi,et al.  Multiridge Euler deconvolution , 2014 .

[7]  Felipe F. Melo,et al.  Estimating the nature and the horizontal and vertical positions of 3D magnetic sources using Euler deconvolution , 2013 .

[8]  A. Reid,et al.  The Structural Index in gravity and magnetic interpretation: errors, uses and abuses , 2012 .

[9]  A. Dutra,et al.  Investigation of the Goiás Alkaline Province, Central Brazil: Application of gravity and magnetic methods , 2012 .

[10]  João B. C. Silva,et al.  Reconstruction of geologic bodies in depth associated with a sedimentary basin using gravity and magnetic data , 2011 .

[11]  A. Reid,et al.  Euler deconvolution of gravity anomalies from thick contact/fault structures with extended negative structural index , 2010 .

[12]  J. Thurston Euler deconvolution in the presence of sheets with finite widths , 2010 .

[13]  W. Morris,et al.  Cluster analysis of Euler deconvolution solutions: New filtering techniques and geologic strike determination , 2010 .

[14]  A. Dutra,et al.  Gravity and magnetic 3D inversion of Morro do Engenho complex, Central Brazil , 2009 .

[15]  M. Fedi,et al.  Multiridge analysis of potential fields: Geometric method and reduced Euler deconvolution , 2009 .

[16]  M. Desa,et al.  Automatic Interpretation of Magnetic Data Using Euler Deconvolution with Nonlinear Background , 2007 .

[17]  J. A. Brod,et al.  Emplacement of kamafugite lavas from the Goiás alkaline province, Brazil: constraints from whole-rock simulations , 2005 .

[18]  Pierre Keating,et al.  Euler deconvolution of the analytic signal and its application to magnetic interpretation , 2004 .

[19]  João B. C. Silva,et al.  3D Euler deconvolution: Theoretical basis for automatically selecting good solutions , 2003 .

[20]  Marcos J. Araúzo-Bravo,et al.  Automatic interpretation of magnetic data based on Euler deconvolution with unprescribed structural index , 2003 .

[21]  P. R. Meneses,et al.  A Província Alcalina de Goiás e a extensão do seu vulcanismo kamafugítico , 2002 .

[22]  S. Hsu Imaging magnetic sources using Euler's equation , 2002 .

[23]  R. O. Hansen,et al.  Unification of Euler and Werner deconvolution in three dimensions via the generalized Hilbert transform , 2001 .

[24]  João B. C. Silva,et al.  Scattering, symmetry, and bias analysis of source-position estimates in Euler deconvolution and its practical implications , 2001 .

[25]  James Derek Fairhead,et al.  Magnetic source parameters of two-dimensional structures using extended Euler deconvolution , 2001 .

[26]  Valéria C. F. Barbosa,et al.  Stability analysis and improvement of structural index estimation in Euler deconvolution , 1999 .

[27]  Petar Stavrev,et al.  Euler deconvolution using differential similarity transformations of gravity or magnetic anomalies , 1997 .

[28]  D. Ravat Analysis of the Euler Method and Its Applicability in Environmental Magnetic Investigations , 1996 .

[29]  P. Hood Gradient measurements in aeromagnetic surveying , 1965 .

[30]  D. W. Smellie Elementary approximations in aeromagnetic interpretation , 1956 .

[31]  I. Zietz,et al.  ANALYSIS OF TOTAL MAGNETIC‐INTENSITY ANOMALIES PRODUCED BY POINT AND LINE SOURCES , 1948 .

[32]  M. Mantovani,et al.  Geophysical signatures of the alkaline intrusions bordering the Paraná Basin , 2013 .

[33]  A. Reid,et al.  Degrees of homogeneity of potential fields and structural indices of Euler deconvolution , 2007 .

[34]  Armand Galdeano,et al.  Application of artificial intelligence for Euler solutions clustering , 2003 .

[35]  J. Fairhead,et al.  Euler: Beyond the “Black Box” , 1994 .

[36]  I. W. Somerton,et al.  Magnetic interpretation in three dimensions using Euler deconvolution , 1990 .

[37]  D. T. Thompson,et al.  EULDPH: A new technique for making computer-assisted depth estimates from magnetic data , 1982 .