Use of Euler deconvolution in recognizing magnetic anomalies of pipelike bodies

The paper presents an improved algorithm based on Bhaskara Rao and Ramesh Babu’s algorithm to invert magnetic anomalies of three-dimensional basement structures. The magnetic basement is approximated by an ensemble of juxtaposed vertical prisms whose bottom surface coincides with Curie surface with the known depth. The computer program operating with the proposed algorithm is built in Matlab environment. Test applications show that the proposed method can perform computations with fast and stable convergence rate where the results also coincide well with the actual model structure. The effectiveness of the method is demonstrated by inverting magnetic anomalies of the southeast part of Vietnam continental shelf. The calculated magnetic basement relief of the study area provides useful additional information for studies in the aim of dealing with the geological structure of the area.References Beiki M., 2010. Analytic signals of gravity gradient tensor and their application to estimate source location, Geophysics, 75(6), i59–i74.Bui C.Q. (chief author), Le T., Tran T. D., Nguyen T. H., Phi T.T., 2007. Map of deep structure of the Earth’s crust, Atlas of the characteristics of natural conditions and environment in Vietnam’s waters and adjacent region. Publisher of Science and Technology, Ha Noi. Do D.T., Nguyen T.T.H., 2011. Atempt the improvement of inversion of magnetic anomalies of two dimensional polygonal cross sections to determine the depth of magnetic basement in some data profile of middle off shelf of Vietnam. Journal of Science and Technology, Vietnam Academy of Science and Technology, 49(2), 125–132.Do D.T., 2013. Study for application of 3D magnetic and gravity method to determine density contribution of basement rock and depth of magnetic basement on Vietnam’s shelf for oil research and prospecting Vietnam National University, Hanoi, Project code QG-11-04. Keating P. and Pilkington M., 2000, Euler deconvolution of the analytic signal, 62nd Annual International Meeting, EAGE, Session P0193.Keating P., Zerbo L., 1996. An improved technique for reduction to the pole at low latitudes, Geophysics, 61, 131–137.Le H.M., Luu V.H., 2003. Preliminary interpretation of the magnetic anomalies of the Eastern Vietnam sea and adiacent regions. J. Sci. of the Earth, 25(2), 173–181. Mai T.T., Pham V.T., Dang V.B., Le D.B., Nguyen B., Le V.D., 2011. Characteristics of Pliocene - Quaternary geology and Geoengineering in the Center and Southeast parts of Continental Shelf of Vietnam. J. Sci. of the Earth, 33(2), 109-118.Mushayandebvu M.F., Lesur V., Reid A.B., Fairhead J.D., 2004. Grid Euler deconvolution with constraints for 2D structures, Geophysics, 69, 489–496.Nguyen N.T., Bui V.N., Nguyen T.T.H., Than D.L., 2014a. Application of power density spectrum of magnetic anomaly to estimate the structure of magnetic layer of the earth crust in the Bac Bo gulf. Journal of Marine Science and Technology, 14(4A), 137–148.Nguyen N.T., Bui V.N., Nguyen T.T.H., 2014b. Determining the depth to the magnetic basementand fault systems in Tu Chinh - Vung May area by magnetic data interpretation. Journal of Marine Science and Technology, 14(4A), 16–25.Nguyen T.T.H., Pham T.L., Do D.T., Le H.M., 2018. Improving algorithm of determining the coordinates of the vertices of the polygon to invert magnetic anomalies of two-dimensional basement structures in space domain, Journal of Marine Science and Technology (preparing to print).Parker R.L., 1973. The rapid calculation of potential anomalies, Geophys. J. Roy. Astron. Soc, 31, 447–455. Pilkington M., Gregotski M.E., Todoeschuck J.P., 1994. Using fractal crustal magnetization models in magnetic interpretation, Geophysical Prospecting, 42, 677–692.Pilkington M., 2006. Joint inversion of gravity and magnetic data for two-layer models, Geophysics, 71, L35–L42.Rao D.B., Babu N.R., 1993. A fortran 77 computer program for three dimensional inversion of magnetic anomalies resulting from multiple prismatic bodies, Computer & Geosciences, 19(8), 781–801.Tanaka A., Okubo Y., Matsubayashi O., 1999. Curie point depth based on spectrum analysis of the magnetic anomaly data in East and Southeast Asia, Tectonic Pphysics, 306, 461–470.Thompson D.T., 1982. EULDTH – A new technique for marking computer-assisted depth estimates from magnetic data, Geophysics, 47, 31–37.Vo T.S., Le H.M., Luu V.H., 2005. Determining the horizontal position and depth of the density discontinuties in Red River Delta by using the vertical derivative and Euler deconvolution for the gravity anomaly data, Vietnam. Journal of Geology, Series A, 287(3–4), 39–52. Werner S., 1955. Interpretation of magnetic anomalies of sheet-like bodies, Sveriges Geologiska Undersokning, Series C, Arsbok, 43, 6.Xu S.Z., 2006. The integral-iteration method for continuation of potential ﬁelds, Chinese journal of geophysics (in Chinese), 49(4), 1176–1182.Zhang C., Huang D.N., Zhang K., Pu Y.T., Yu P., 2016. Magnetic interface forward and inversion method based on Padé approximation, Applied Geophysics, 13(4), 712–720.CCOP, 1996. Magnetic anomaly map of East Asia, scale 1:4.000.000, Geological survey of Japan and Committee for co-ordination of joint prospecting for mineral resources in asian offshore areas.

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Euler deconvolution and similar transformations of gravity or magnetic anomalies

56th EAEG Meeting ◽

10.3997/2214-4609.201409958 ◽

1994 ◽

Author(s):

P. Stavrev

Keyword(s):

Magnetic Anomalies ◽

Euler Deconvolution

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Continuous wavelet transform and the Euler deconvolution method and their application to magnetic field data of Jharia coal field, India

10.5194/gi-2016-22 ◽

2016 ◽

Author(s):

Arvind Singh ◽

Upendra Kumar Singh

Keyword(s):

Wavelet Transform ◽

Field Data ◽

Magnetic Anomalies ◽

Magnetic Data ◽

Deconvolution Method ◽

Euler Deconvolution ◽

Coal Field ◽

Potential Field Data ◽

Gravity And Magnetic ◽

Jharia Coal

Abstract. This paper deals the application of Continuous Wavelet Transform (CWT) and Euler deconvolution methods to estimate the source depth using magnetic anomalies. These methods are utilised mainly to focus on the fundamental issue for mapping the major coal seam and locating magnetic lineaments. These methods are tested and demonstrated on synthetic data and finally applied on field data from Jharia coal field. Prepared magnetic anomaly map that reflects clear tectonics control and nature of the underlying basement, demarcation of the basin, geological faults by steep gradients of magnetic anomaly. Analysis suggests that the CWT have a great utility in the magnetic data interpretation and the correlation between magnetic anomalies and geological features such as faults/joints and intrusive bodies over the basin. The CWT provides the consistent and reliable depth of the underlying basement with the results of Euler deconvolution and Tiltdepth methods without any priory information that is correlated well with borehole samples (Raja Rao, 1987). One of the fundamental issues is to detect differences in susceptibility and density between rocks that contain ore deposits or hydrocarbons or coal. These differences are reflected in the gravity and magnetic anomalies and also delineation of structural features, which are interpreted using several techniques (Blakely and Simpson, 1986). One of the most important objective in the interpretation of potential field data is to improve the resolution of underlying source, delineating lateral change in magnetic susceptibilities that provides information not only on lithological changes but also on structural trends. Especially, mapping the edges of causative bodies is fundamental to the application of potential field data to geological mapping. The edge detection techniques are used to distinguish between different sizes and different depths of the geological discontinuities (Cooper and Cowan 2006, 2008; Perez et al. 2005; Ardestani 2010; Hsu et al. 1996, 2002; Holschneider et al., 2003). The derivatives of magnetic data are used to enhance the edges of anomalies and improve significantly the visibility of such features. Sedimentary layer dominates the gravity and magnetic signature over Jharia Coal field (Verma et al., 1973, 1976, 1979). Thus the difference between the depths estimated using Euler deconvolution method (EDM) (Thompson 1982; Reid et al. 1990) and Tilt Depth Method (TDM) technique (Salem et al., 2007; Cooper 2004, 2011) may help to detect the thickness of the coalbed. Wavelet transform and Euler deconvolution method has been theoretically demonstrated on magnetic data. These methods provide source parameters such as the location, depth, geometry of geological bodies and interfaces in an easy and effective way. However, it may be more difficult to characterize the source properties in cases of extended sources (Sailhac et al., 2009). These methods executed over Jharia coal field, Dhanbad, India. This area forms an east west trending belt of Gondwana basin of Damodar valley at the north eastern part of India. This study region is mostly coal rich area of Gondwana basin. Analysis on Jharia coal field suggests that the magnetic anomalies provide encouraging results which are well correlated with available gravity data and some borehole informations.

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Automatic detection of UXO magnetic anomalies using extended Euler deconvolution

Geophysics ◽

10.1190/1.3375235 ◽

2010 ◽

Vol 75 (3) ◽

pp. G13-G20 ◽

Cited By ~ 30

Author(s):

Kristofer Davis ◽

Yaoguo Li ◽

Misac Nabighian

Keyword(s):

Direct Detection ◽

Automatic Detection ◽

Spatial Location ◽

Magnetic Anomalies ◽

Magnetic Data ◽

Data Sets ◽

Euler Deconvolution ◽

Amplitude Analysis ◽

The Hilbert Transform ◽

Structural Indices

We have developed an algorithm for the automatic detection of prospective unexploded ordnance (UXO) anomalies in total-field or gradient magnetic data based on the concept of the structural index (SI) of a magnetic anomaly. Identifying magnetic anomalies having specific structural indices enables the direct detection of potential UXO targets. The total magnetic field produced by a dipolelike source, such as a UXO, decays with inverse distance cubed and therefore has an SI of three, whereas the gradient data have an SI of four. The developed extended Euler deconvolution method based on the Hilbert transform provides a reliable means for calculating the spatial location, depth, and SI of compact and isolated anomalies; it has enabled us to perform automatic anomaly selection for further analysis. Our method first examines the anomaly decay and selects possible UXO anomalies based on the expected SI. We refine the result further by post-Euler amplitude analysis using the relative source strength of the anomalies selected in the first stage. The amplitude analysis statistically identifies weak anomalies that are due to noise in the data. This enhances the final result and eliminates automatic picks that fall within the noise level. We have demonstrated the effectiveness of the method using synthetic and field data sets.

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Correct structural index in Euler deconvolution via base-level estimates

Geophysics ◽

10.1190/geo2017-0774.1 ◽

2018 ◽

Vol 83 (6) ◽

pp. J87-J98 ◽

Cited By ~ 5

Author(s):

Felipe F. Melo ◽

Valéria C. F. Barbosa

Keyword(s):

Standard Deviation ◽

Field Measurements ◽

Real Data ◽

Magnetic Anomalies ◽

Magnetic Data ◽

Total Field ◽

Minimum Standard ◽

Euler Deconvolution ◽

Structural Index ◽

Base Level

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.

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