Magnetic interpretation of two-dimensional dikes using integration-nomograms

The magnetic anomaly caused by a buried dike is separated into its even and odd components, which have a simple symmetry with respect to the origin. These values are integrated up to the half-maximum abscissa for the even component, and the maximum abscissa for the odd component. The integration nomograms are generated using various values to the half-width and depth in the theoretical anomaly equations. These nomograms are used to determine the half-width and depth to the top of the dike for the field anomaly. The method also includes the determination of the index parameter (Q) and the amplitude coefficient (P). An example using theoretical data shows the effectiveness of the present method.     

Interpretation of magnetic anomalies of dikes using correlation factors

The magnetic anomaly due to a buried dike consists of the sum of two easily separated elementary functions. These functions, which have simple symmetry, are called even and odd functions. The correlation factors (r _0,1 for the even andr _0,2 for the odd function) between least-squares residual anomalies from even and odd functions are computed. Correlation values are used to determine the depth to the top and the half-width of the dike. The method also includes the determination of the index parameter and the amplitude coefficient. The validity of the method is tested against a theoretical and a field example where the parameters of the latter were determined by other investigators in comparing the results.     

A Least-Squares Standard Deviation Method to Interpret Gravity Data due to Finite Vertical Cylinders and Sheets

We have developed a least-squares approach to determine simultaneously the depth to both the top and base of a buried finite vertical cylinder (vertical line element approximation) and a 2-D vertical thin sheet from moving average residual anomaly profiles obtained from gravity data using filters of successive window lengths. The method involves using a relationship between the depth to the top, and base of the source and a combination of windowed observations. The method is based on computing the standard deviation of the depths to the top, determined from all moving average residual anomalies for each value of the depth to the base. The standard deviation may generally be considered a criterion for determining the correct depth to the top and base of the buried structure. When the correct depth to the base value is used, the standard deviation of the depths to the top is less than the standard deviation using incorrect values of the depth to the base. This method can be applied to residuals as well as to the observed gravity data. The method is applied to synthetic examples with and without random errors and tested on two field examples from the USA and Canada.     

Least-squares Minimization Approaches to Interpret Total Magnetic Anomalies Due to Spheres

We have developed three different least-squares approaches to determine successively: the depth, magnetic angle, and amplitude coefficient of a buried sphere from a total magnetic anomaly. By defining the anomaly value at the origin and the nearest zero-anomaly distance from the origin on the profile, the problem of depth determination is transformed into the problem of finding a solution of a nonlinear equation of the form f(z)=0. Knowing the depth and applying the least-squares method, the magnetic angle and amplitude coefficient are determined using two simple linear equations. In this way, the depth, magnetic angle, and amplitude coefficient are determined individually from all observed total magnetic data. The method is applied to synthetic examples with and without random errors and tested on a field example from Senegal, West Africa. In all cases, the depth solutions are in good agreement with the actual ones.     

A new least-squares minimization approach to depth and shape determination from magnetic data

We have developed a least‐squares minimization approach to depth determination using numerical second horizontal derivative anomalies obtained from magnetic data with filters of successive window lengths (graticule spacings). The problem of depth determination from second‐derivative magnetic anomalies has been transformed into finding a solution to a non‐linear equation of the form, f(z) = 0. Formulae have been derived for a sphere, a horizontal cylinder, a dike and a geological contact. Procedures are also formulated to estimate the magnetic angle and the amplitude coefficient. We have also developed a simple method to define simultaneously the shape (shape factor) and the depth of a buried structure from magnetic data. The method is based on computing the variance of depths determined from all second‐derivative anomaly profiles using the above method. The variance is considered a criterion for determining the correct shape and depth of the buried structure. When the correct shape factor is used, the variance of depths is less than the variances computed using incorrect shape factors. The method is applied to synthetic data with and without random errors, complicated regionals, and interference from neighbouring magnetic rocks. Finally, the method is tested on a field example from India. In all the cases examined, the depth and the shape parameters are found to be in good agreement with the actual parameters.     

Interpretation of Self-potential Anomalies over Two-dimensional Plates by Gradient Analysis

—Numerical horizontal self-potential gradients obtained from self-potential data using filters of successive window lengths can be used to determine the depth and width of a 2-D plate. For a fixed window length the depth is determined iteratively using a simple formula for each half width value. The computed depths are plotted against the half width values representing a continuous window curve. The solution for the depth and the half width of the buried structure is read at the common intersection of the window curves. The method is applied to synthetic data with and without random errors.     

A Least-squares Approach to Depth Determination from Numerical Horizontal Self-potential Gradients

We have developed a least-squares minimization approach to depth determination of a buried ore deposit from numerical horizontal gradients obtained from self-potential (SP) data using filters of successive window lengths (graticule spacings). The problem of depth determination from SP gradients has been transformed into the problem of finding a solution to a nonlinear equation of the form f(z)=0. Formulas have been derived for vertical and horizontal cylinders and spheres. Procedures are also formulated to estimate the electrical dipole moment and the polarization angle. The method is applied to synthetic data with and without random noise. Finally, the validity of the method is tested on two field examples. In both cases, the depth obtained is found to be in a very good agreement with that obtained from drilling information.     

Estimating magnetic dike parameters using a non‐linear constrained inversion technique: an example from the Särna area,west central Sweden

In this paper, we describe a non‐linear constrained inversion technique for 2D interpretation of high resolution magnetic field data along flight lines using a simple dike model. We first estimate the strike direction of a quasi 2D structure based on the eigenvector corresponding to the minimum eigenvalue of the pseudogravity gradient tensor derived from gridded, low‐pass filtered magnetic field anomalies, assuming that the magnetization direction is known. Then the measured magnetic field can be transformed into the strike coordinate system and all magnetic dike parameters – horizontal position, depth to the top, dip angle, width and susceptibility contrast – can be estimated by non‐linear least squares inversion of the high resolution magnetic field data along the flight lines. We use the Levenberg‐Marquardt algorithm together with the trust‐region‐reflective method enabling users to define inequality constraints on model parameters such that the estimated parameters are always in a trust region. Assuming that the maximum of the calculated g_zz (vertical gradient of the pseudogravity field) is approximately located above the causative body, data points enclosed by a window, along the profile, centred at the maximum of g_zz are used in the inversion scheme for estimating the dike parameters. The size of the window is increased until it exceeds a predefined limit. Then the solution corresponding to the minimum data fit error is chosen as the most reliable one. Using synthetic data we study the effect of random noise and interfering sources on the estimated models and we apply our method to a new aeromagnetic data set from the Särna area, west central Sweden including constraints from laboratory measurements on rock samples from the area.     

A New Algorithm for Depth Determination from Total Magnetic Anomalies due to Spheres

We have developed an automatic method to determine the depth of a buried sphere from numerical second horizontal derivative anomalies obtained from total field magnetic data. The method is based on using a relationship between the depth and a combination of observations at symmetric points with respect to the coordinate of the projection of the center of the source in the plane of the measurement points with a free parameter (graticule spacing). The problem of depth determination has been transformed into the problem of finding a solution of a nonlinear equation of f(z) = 0. Procedures are also formulated to determine the magnetic moment and the effective angle of magnetization. The method is applied to synthetic examples with and without random errors and tested on a field example from Senegal. In all cases, the depth solutions are in good agreement with the actual ones.     

Interpretation of magnetic anomalies using a genetic algorithm

A genetic algorithm (GA) is an artificial intelligence method used for optimization. We applied a GA to the inversion of magnetic anomalies over a thick dike. Inversion of nonlinear geophysical problems using a GA has advantages because it does not require model gradients or well-defined initial model parameters. The evolution process consists of selection, crossover, and mutation genetic operators that look for the best fit to the observed data and a solution consisting of plausible compact sources. The efficiency of a GA on both synthetic and real magnetic anomalies of dikes by estimating model parameters, such as depth to the top of the dike (H), the half-width of the dike (B), the distance from the origin to the reference point (D), the dip of the thick dike (δ), and the susceptibility contrast (k), has been shown. For the synthetic anomaly case, it has been considered for both noise-free and noisy magnetic data. In the real case, the vertical magnetic anomaly from the Pima copper mine in Arizona, USA, and the vertical magnetic anomaly in the Bayburt–Sar?han skarn zone in northeastern Turkey have been inverted and interpreted. We compared the estimated parameters with the results of conventional inversion methods used in previous studies. We can conclude that the GA method used in this study is a useful tool for evaluating magnetic anomalies for dike models.     

Interpretation of potential fields from inclined dikes in the wavenumber domain

The interpretation of the gravity and magnetic fields from inclined dikes has been studied with artifical data contaminated by various noise components: base level, linear trend, and random noise. A Gaussian window was applied to the data prior to transformation to reduce the influence of noise as demonstrated by an analysis of the horizontal cylinder. The case of the dike is more complicated due to the fact that its spectrum has a number of zeroes at wavenumbers which are inversely related to the width of the dike. Around these wavenumbers, especially the random noise distorts the spectrum making interpretation ambiguous.     

Fair function minimization for interpretation of magnetic anomalies due to thin dikes, spheres and faults

A new method is proposed to interpret magnetic anomalies due to a thin dike, a sphere, and a fault like structure, where depth, horizontal location, effective magnetization intensity and effective magnetization inclination of a buried structure are simultaneously obtained. The proposed method is based on Fair function minimization and also on stochastic optimization modeling. This new technique was firstly tested on a theoretical synthetic data randomly generated by a chosen statistical distribution from a known model with different random noises components. This mathematical simulation shows a very close agreement between the assumed and the estimated parameters. The applicability and validity of this method are thereafter applied to magnetic anomaly data taken from United States, Australia, India, and Brazil. The agreement between the results obtained by the new method and those obtained by other interpretative methods is good and comparable. Moreover, the depth obtained by such a method is found to be in high accordance with that obtained from drilling information.     

A Least-squares Minimization Approach to Depth Determination from Magnetic Data

—We have developed a least-squares minimization approach to depth determination from magnetic data. By defining the anomaly value T(0) at the origin and the anomaly value T(N) at any other distance (N) on the profile, the problem of depth determination from magnetic data has been transformed into finding a solution to a nonlinear equation of the form f(z)=0. Formulas have been derived for a sphere, horizontal cylinder, dike, and for a geologic contact. Procedures are also formulated to estimate the effective magnetization intensity and the effective magnetization inclination. A scheme for analyzing the magnetic data has been formulated for determining the model parameters of the causative sources. The method is applied to synthetic data with and without random errors. Finally, the method is applied to two field examples from Canada and Arizona. In all cases examined, the estimated depths are found to be in goodagreement with actual values.     

Analysis of a vertical dike,infinitely deep,striking north by fourier transform

Summary The present work deals with the analysis of the frequency spectrum of a vertical magnetic dike like body, infinitely deep, striking north to determine its width and depth from the surface. Fourier transform of the functional representative of the theoretical magnetic anomaly for such a body has been obtained. By framing amplitude response curves, the parameters were estimated.     

Magnetic interpretation of long horizontal cylinders using correlation factors between successive least-squares residual anomaly profiles

Procedures are formulated using the correlation factors between successive least-squares residual magnetic anomaly profiles due to long horizontal cylinders for interpreting the three principal anomalies (vertical, horizontal, and total). It is demonstrated that correlation values can be used to determine the depth to the center of the buried structure and the index parameter. Procedures are also formulated to estimate the amplitude coefficient. Two worked examples using theoretical data show the effectiveness of the present method.     

Horizontal-loop electromagnetic signature of a buried dike, Al Quweira area, southwest Jordan

During 1999, horizontal-loop electromagnetic (HLEM) measurements were made over a buried dike in the Al Quweira area, southwest Jordan, using the APEX MAX MIN III instrument, as part of a mineral exploration project. The objectives of the study were (i) to evaluate the resolution of the HLEM technique in field work in detecting and locating anomalies caused by vein-like bodies, and (ii) to assess the capability of HLEM surveys for detecting targets in other locations throughout our geophysical survey programme. In-phase and quadrature anomalies were recorded with 50 m and 100 m coil separations and multiple frequencies across the strike of the buried dike. Data recorded at 43 locations, spaced 10 m apart along the survey line, were interpreted quantitatively. For a 50 m separation, corresponding to shallow depths of investigation, the results do not show any recognizable response from the buried dike. The HLEM data were modelled using a three-layer structure in order to estimate the thickness of the weathering layer along the survey line. Conversely, data obtained with a 100 m separation, corresponding to moderate depths of investigation, reveal significant anomalies from the buried dike at high frequencies. A phasor or vector diagram was used to calculate the response parameter, depth and dip of the buried dike.     

A simple formula for shape and depth determination from residual gravity anomalies

This paper presents a simple method for shape and depth determination of a buried structure from residual gravity anomalies along profile. The method utilizes the anomaly values of the origin and characteristic points of the profile to construct a relationship between the shape factor and depth of the causative source. For fixed points, the depth is determined for each shape factor. The computed depths are then plotted against the shape factor representing a continuous monotonically increasing curve. The solution for the shape and depth of the buried structure is then read at the common intersection point of the depth curves. This method is applied to synthetic data with and without random errors. Finally, the validity of the method is tested on two field examples from the USA.     

A New Best-Estimate Methodology for Determining Magnetic Parameters Related to Field Anomalies Produced by Buried Thin Dikes and Horizontal Cylinder-like Structures

A new best estimate methodology is proposed and oriented towards the determination of parameters related to a magnetic field anomaly produced by a simple geometric-shaped model or body such as a thin dike and horizontal cylinder. This approach is mainly based on solving a system of algebraic linear equations for estimating the three model parameters, e.g., the depth to the top (center) of the body (z), the index parameter or the effective magnetization angle (θ) and the amplitude coefficient or the effective magnetization intensity (k). The utility and validity of this method is demonstrated by analyzing two synthetic magnetic anomalies, using simulated data generated from a known model with different random errors components and a known statistical distribution. This approach was also examined and applied to two real field magnetic anomalies from the United States and Brazil. The agreement between the results obtained by the proposed method and those obtained by other interpretation methods is good and comparable. Moreover, the depth obtained by such an approach is found to be in high accordance with that obtained from drilling information. The advantages of such a proposed method over other existing interpretative techniques are clarified, where it can be generalized to be automatically applicable for interpreting other geological structures described by mathematical formulations.     

A Robust Nonlinear Inversion for the Interpretation of Magnetic Anomalies Caused by Faults,Thin Dikes and Spheres Like Structure Using Stochastic Algorithms

A geophysical interpretative method is proposed to depth, amplitude coefficient (effective magnetization intensity), and index parameter (effective magnetization inclination) determination of a buried structure from magnetic field data anomaly due to a fault, a thin dike or a sphere-like structure. The method is based on the nonlinearly constrained mathematical modelling and also on the stochastic optimization approaches. The proposed interpretative method was first tested on a theoretical synthetic model with different random errors, where a very close agreement was obtained between the assumed and the evaluated parameters. The validity of this method was also tested on practical field data taken from United States, Australia, India and Brazil, where available magnetic data existed and were previously analyzed by different interpretative methods. The agreement between the results obtained by our developed method and those obtained by the other geophysical methods is good.     

iSPITM— the improved source parameter imaging method

Interpretation of an anomalous magnetic response involves determining the parameters that characterize the source of the anomaly. The depth to the top of the structure is a parameter that is commonly sought, and the Source Parameter Imaging^TM (SPI^TM) method is one way of determining this depth estimate. One advantage of the SPI method is that the depths can be displayed on an image. Typically there can be one image for an assumed contact (fault) model and another image for an assumed dipping thin sheet (dike) model. The depth estimate obtained will depend on the model assumed. An improvement to the source parameter imaging method extends the method to horizontal cylinders and at the same time allows the most appropriate model to be determined automatically. This model can be displayed on an image and the correct depth estimate for each anomaly can also be determined. The depth estimates can therefore be summarized on one map independent of an assumed model. The images generated from synthetic and field data show that the improved SPI method makes the task of interpreting magnetic data significantly easier.