Automatic detection of UXO magnetic anomalies using extended Euler deconvolution

Geophysics ◽  
2010 ◽  
Vol 75 (3) ◽  
pp. G13-G20 ◽  
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.

Automatic determination of the magnetization–density ratio and magnetization inclination from the joint interpretation of 2D gravity and magnetic anomalies

Geophysics ◽  
2004 ◽  
Vol 69 (4) ◽  
pp. 938-948 ◽  
Author(s):  
Carlos Alberto Mendonça
Keyword(s):  
Vector Fields ◽  
Density Ratio ◽  
Magnetic Anomalies ◽  
Magnetic Data ◽  
Data Sets ◽  
Magnetization Direction ◽  
Gravity And Magnetic ◽  
Geophysical Surveys ◽  
Magnetization Density ◽  
Gravity And Magnetic Data

The Poisson theorem establishes a linear relationship between the gravity and magnetic potentials arising from common dense and magnetized bodies with constant magnetization–density ratio and magnetization direction. For geological formations satisfying such constraints (i.e., the Poisson conditions), this theorem provides suitable relationships between the gravity and magnetic anomalies that are useful in interpreting the related data sets. In such applications, both magnetization–density ratio (MDR) and magnetization direction can be estimated, thus helping the subsurface geological mapping from potential field data acquired on the earth's surface. However, no existing method is fully automatic, which has hampered extensive use in routine applications. Such a drawback follows the adoption of equations that, although obeying the Poisson theorem, relate particular components of the gravity and magnetic fields, thus requiring either a known magnetization direction or the implementation of iterative procedures to determine it. To allow one‐pass estimates for both MDR and magnetization direction (more precisely, its inclination projected on the plane normal to the source strike), this paper presents simple analytical solutions for these parameters by relating suitable gravity and magnetic vector fields that are derived from the gravity and magnetic data sets. Because current geophysical surveys usually provide only a single‐field component, a data processing scheme is developed to determine the required components in evaluating the desired vector fields. This is done by applying suitable linear transformations on the measured components according to well‐established filtering techniques in processing gravity and magnetic data. Except for distortions from noise, the proposed method automatically determines the MDR and the projected magnetization inclination for the underlying rocks everywhere the Poisson conditions are satisfied. Two‐dimensional sources are assumed, but no constraint upon their depth and cross‐section shape is required. Distorted estimates only appear close to the sources where at least one of the Poisson conditions is violated. In this case, the proposed technique furnishes apparent values for the rock properties. The abrupt changes of apparent values over contacts detect edges, thus facilitating the mapping of geological boundaries. The proposed technique is used to interpret two profiles across the Appalachian fold belt from the eastern portion of the State of Georgia, and the results are compared with some of the geological information available for the area.

scholarly journals An improved space domain algorithm for determining the 3-D structure of the magnetic basement

2019 ◽  
Vol 41 (1) ◽  
pp. 69-80
Author(s):  
Nguyen Thi Thu Hang ◽  
Erdinc Oksum ◽  
Le Huy Minh ◽  
Do Duc Thanh
Keyword(s):  
Magnetic Anomaly ◽  
Science And Technology ◽  
Three Dimensional ◽  
Magnetic Anomalies ◽  
Magnetic Data ◽  
Marine Science ◽  
Euler Deconvolution ◽  
The Earth ◽  
Magnetic Basement ◽  
Basement Structures

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.

scholarly journals MaGSoundDST — 3D automatic inversion of magnetic and gravity data based on the differential similarity transform

Geophysics ◽  
2010 ◽  
Vol 75 (1) ◽  
pp. L25-L38 ◽  
Author(s):  
Daniela Gerovska ◽  
Marcos J. Araúzo-Bravo ◽  
Petar Stavrev ◽  
Kathryn Whaler
Keyword(s):  
Gravity Data ◽  
Magnetization Vector ◽  
Singular Points ◽  
Magnetic Data ◽  
Moving Window ◽  
Euler Deconvolution ◽  
Grid Data ◽  
Similarity Transform ◽  
Window Method ◽  
Structural Indices

We present an automatic procedure — Magnetic And Gravity SOUNDing Differential Similarity Transform (MaGSoundDST) — for inversion of regular or irregular magnetic- and gravity-grid data measured on even or uneven surfaces. It solves for horizontal position, depth, and structural index of simple sources and is independent of a linear background. In addition, it estimates the shape of sources consisting of several singular points and lines. The method uses the property of the differential similarity transform (DST) of a magnetic or a gravity anomaly to become zero or linear at all observation points when the central point of similarity of the transform, which we refer to as the probing point, coincides with a source’s singular point. It uses a measured anomalous field and its calculated or measured (gradiometry) first-order derivatives. The method is independent of the magnetization-vector direction in the magnetic data case and does notrequire reduction-to-the-pole transformed data as input. With MaGSoundDST, we provide an important alternative interpretation technique to the Euler deconvolution procedures, combining a moving-window method, whereby the solutions are linked to singular points of causative bodies, with an approach in which the solutions are linked to the real sources. The procedure involves calculating a 3D function that evaluates the linearity of the DST for different integer or noninteger structural indices, using a moving window. We sound the subsurface along a vertical line under each window center. Then we combine the 3D results for different structural indices and present them in three easy-to-interpret maps, avoiding the need for clustering techniques. We deduce only one solution for location and type of simple sources, which is a major advantage over Euler deconvolution. Application to different cases of synthetic and real data shows the method’s applicability to various types of magnetic and gravity field investigations.

An assessment of long-wavelength magnetic anomalies over Canada

1996 ◽  
Vol 33 (1) ◽  
pp. 12-23 ◽  
Author(s):  
Mark Pilkington ◽  
Walter R. Roest
Keyword(s):  
Magnetic Field ◽  
Magnetic Anomalies ◽  
Time Span ◽  
Magnetic Data ◽  
Data Sets ◽  
Independent Data ◽  
Data Set ◽  
Long Wavelength ◽  
The Magnetic Field

The reliability of the long-wavelength portion (> 300 km) of the magnetic field over Canada, as represented by the national aeromagnetic anomaly database compiled by the Geological Survey of Canada (GSC), is assessed by comparison with two independent data sets: a high-altitude country-wide survey carried out by the former Earth Physics Branch (EPB) and data from the MAGSAT and POGO satellite missions. The different altitudes at which each data set was measured (300 m, ~4 km, and ~400 km), and their different resolution and time span of observations allow a determination of the integrity of selected wavelength bands in each data set. The (upward-continued) EPB and MAGSAT–POGO fields compare well for wavelengths of 300–2500 km. The GSC data show significant differences to the former, indicating that the levelling and merging of several hundred individual surveys has degraded the longer wavelength components of the magnetic field. Replacing the GSC wavelength components >300 km with those from the EPB field produces a magnetic data set containing more dependable information within the largest possible waveband.

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

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.

Comparison of grid Euler deconvolution with and without 2D constraints using a realistic 3D magnetic basement model

Geophysics ◽  
2005 ◽  
Vol 70 (3) ◽  
pp. L13-L21 ◽  
Author(s):  
Simon E. Williams ◽  
J. Derek Fairhead ◽  
Guy Flanagan
Keyword(s):  
Three Dimensional ◽  
Euler Method ◽  
Magnetic Data ◽  
Data Sets ◽  
Euler Deconvolution ◽  
Data Set ◽  
Distinct Source ◽  
Magnetic Basement ◽  
Modeling Strategy ◽  
Source Geometry

We describe the application of a 2D-constrained grid Euler deconvolution method which is able to determine for each solution window whether the source structure is two dimensional, three dimensional, or poorly defined and to estimate the source location and depth. In each solution window, eigenvalues and eigenvectors are derived from the Euler equations and compared to threshold levels. A single eigenvalue below the given threshold and lying in the x–y-plane is shown to indicate a 2D source, while the absence of such an eigenvalue indicates a 3D source geometry. Two small eigenvalues indicate the field in the window has no distinct source. Applying these criteria to each solution window allows us to generate a map of source-geometry distribution. We evaluate the effectiveness of 2D-constrained grid Euler deconvolution using synthetic magnetic data generated from a 3D basement model based on real topography from an area with surface-exposed faulting. This modeling strategy provides a complex, nonidealized data set that compares Euler depth estimates directly to the known basement surface depth. Our results indicate that noninteger structural indices can be the most appropriate choice for some data sets, and the 2D-constrained grid Euler method images magnetic basement structure more clearly and unambiguously than the conventional grid Euler method.

Correct structural index in Euler deconvolution via base-level estimates

Geophysics ◽  
2018 ◽  
Vol 83 (6) ◽  
pp. J87-J98 ◽  
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.

scholarly journals A Review of Geophysical Modeling Based on Particle Swarm Optimization

2021 ◽  
Author(s):  
Francesca Pace ◽  
Alessandro Santilano ◽  
Alberto Godio
Keyword(s):  
Particle Swarm Optimization ◽  
Inverse Modeling ◽  
Critical Evaluation ◽  
Particle Swarm ◽  
Geophysical Data ◽  
Magnetic Data ◽  
Data Sets ◽  
Swarm Optimization ◽  
Geophysical Modeling ◽  
Original Works

AbstractThis paper reviews the application of the algorithm particle swarm optimization (PSO) to perform stochastic inverse modeling of geophysical data. The main features of PSO are summarized, and the most important contributions in several geophysical fields are analyzed. The aim is to indicate the fundamental steps of the evolution of PSO methodologies that have been adopted to model the Earth’s subsurface and then to undertake a critical evaluation of their benefits and limitations. Original works have been selected from the existing geophysical literature to illustrate successful PSO applied to the interpretation of electromagnetic (magnetotelluric and time-domain) data, gravimetric and magnetic data, self-potential, direct current and seismic data. These case studies are critically described and compared. In addition, joint optimization of multiple geophysical data sets by means of multi-objective PSO is presented to highlight the advantage of using a single solver that deploys Pareto optimality to handle different data sets without conflicting solutions. Finally, we propose best practices for the implementation of a customized algorithm from scratch to perform stochastic inverse modeling of any kind of geophysical data sets for the benefit of PSO practitioners or inexperienced researchers.

Euler’s differential equation and the identification of the magnetic point‐pole and point‐dipole sources

Geophysics ◽  
1984 ◽  
Vol 49 (9) ◽  
pp. 1549-1553 ◽  
Author(s):  
J. O. Barongo
Keyword(s):  
Magnetic Field ◽  
Differential Equation ◽  
Magnetic Anomalies ◽  
Field Vector ◽  
Magnetic Data ◽  
Dipole Source ◽  
Point Dipole ◽  
Main Subject ◽  
Depth Extent ◽  
Dipole Sources

The concept of point‐pole and point‐dipole in interpretation of magnetic data is often employed in the analysis of magnetic anomalies (or their derivatives) caused by geologic bodies whose geometric shapes approach those of (1) narrow prisms of infinite depth extent aligned, more or less, in the direction of the inducing earth’s magnetic field, and (2) spheres, respectively. The two geologic bodies are assumed to be magnetically polarized in the direction of the Earth’s total magnetic field vector (Figure 1). One problem that perhaps is not realized when interpretations are carried out on such anomalies, especially in regions of high magnetic latitudes (45–90 degrees), is that of being unable to differentiate an anomaly due to a point‐pole from that due to a point‐dipole source. The two anomalies look more or less alike at those latitudes (Figure 2). Hood (1971) presented a graphical procedure of determining depth to the top/center of the point pole/dipole in which he assumed prior knowledge of the anomaly type. While it is essential and mandatory to make an assumption such as this, it is very important to go a step further and carry out a test on the anomaly to check whether the assumption made is correct. The procedure to do this is the main subject of this note. I start off by first using some method that does not involve Euler’s differential equation to determine depth to the top/center of the suspected causative body. Then I employ the determined depth to identify the causative body from the graphical diagram of Hood (1971, Figure 26).

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