Linearized least‐squares method for interpretation of potential‐field data from sources of simple geometry

Geophysics ◽  
2004 ◽  
Vol 69 (3) ◽  
pp. 783-788 ◽  
Author(s):  
Ahmed Salem ◽  
Dhananjay Ravat ◽  
Martin F. Mushayandebvu ◽  
Keisuke Ushijima
Keyword(s):  
Potential Field ◽  
Least Squares Method ◽  
Random Noise ◽  
The United States ◽  
Horizontal Gradient ◽  
Potential Field Data ◽  
Anomalous Field ◽  
Simple Geometry ◽  
Gravity And Magnetic ◽  
Gravity And Magnetic Anomaly

We present a new method for interpreting isolated potential‐field (gravity and magnetic) anomaly data. A linear equation, involving a symmetric anomalous field and its horizontal gradient, is derived to provide both the depth and nature of the buried sources. In many currently available methods, either higher order derivatives or postprocessing is necessary to extract both pieces of information; therefore, data must be of very high quality. In contrast, for gravity work with our method, only a first‐order horizontal derivative is needed and the traditional data quality is sufficient. Our proposed method is similar to the Euler technique; it uses a shape factor instead of a structural index to characterize the buried sources. The method is tested using theoretical anomaly data with and without random noise. In all cases, the method adequately estimates the location and the approximate shape of the source. The practical utility of the method is demonstrated using gravity and magnetic field examples from the United States and Zimbabwe.

scholarly journals Crustal structure in the Campanian region (Southern Apennines, Italy) from potential field modelling

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Y. Kelemework ◽  
M. Milano ◽  
M. La Manna ◽  
G. de Alteriis ◽  
M. Iorio ◽  
...  
Keyword(s):  
Potential Field ◽  
Carbonate Platform ◽  
Vertical Gradient ◽  
Magnetic Data ◽  
Potential Field Data ◽  
Gravity And Magnetic ◽  
Significant Depression ◽  
Mountain Chain ◽  
Surrounding Areas ◽  
Gravity And Magnetic Data

AbstractWe present a 3D model of the main crustal boundaries beneath the Campanian region and the onshore and offshore surrounding areas, based on high-resolution potential field data. Our main objective is the definition of the main structural interfaces in the whole Campanian region from gravity and magnetic data, thanks to their ability to define them on a regional and continuous way. The complex morphology of the Mesozoic carbonate platform, which is fundamental to constrain the top of geothermal reservoir, was reconstructed by inverting the vertical gradient of gravity. We assumed local information from seismic models and boreholes to improve the model. We modeled the deep crustal structures by spectral analysis of Bouguer gravity and magnetic data. The inferred depth estimates indicate a shallow crystalline basement below the Tyrrhenian crust and the Apulian foreland and a significant depression beneath the Bradanic foredeep. The map of the Moho boundary shows a NE-SE verging trough below the Southern Apennine chain and two pronounced uplifts beneath the foreland and the Tyrrhenian crust. We also estimated the depth to the magnetic bottom, showing a thick magnetic crust below the mountain chain and shallow depths where the crustal heat flow is high. The models were compared with seismic sections along selected profiles; a good agreement was observed, despite of some inherent lower resolution for the gravity modelling from spectral methods. The regional covering and the continuity of our estimated crustal interfaces make it a new and valid reference for further geological, geophysical and geothermal studies, especially in areas such as northern and eastern Campania, where there is an incomplete geophysical and geological information.

Gravity and magnetic data analysis based on Poisson wavelet-transforms

2020 ◽  
Author(s):  
Kirill Kuznetsov ◽  
Bulychev Andrey ◽  
Ivan Lygin
Keyword(s):  
Data Analysis ◽  
Magnetic Fields ◽  
Potential Field ◽  
Wavelet Transforms ◽  
Geophysical Methods ◽  
Magnetic Data ◽  
Potential Field Data ◽  
Gravity And Magnetic ◽  
Gravity And Magnetic Data ◽  
Poisson Wavelets

<p>Studies of the Earth’s interior structure are one of the most complex topics in modern science. Integration of different geophysical methods plays a key role in effectively tackling the problem. In the last decade capabilities of potential field geophysical methods have been increasing due to development of advanced digital technologies. Improved resolution and accuracy of gravity and magnetic fields measurements made by modern equipment makes it possible to build more detailed geological models. Different tectonic and structural elements being interpreted in such models produce potential field signals with different spectral characteristics. Like any geophysical signals, potential fields can be described as a spatially non-stationary signal. This means its frequency content may change depending on a given signal sample, in particular with different spatial location of a sample. In this case, approaches of gravity and magnetic fields analysis based on Fourier transform or signal decomposition into a number of harmonic functions can lead to incorrect results. One of the ways to solve this challenge involves using wavelet transform based algorithms, since these transforms do not assume stationary signals and each function of a wavelet-based basis is localized in space domain.</p><p>In gravity and magnetic data analysis it is beneficial to use wavelets based on partial derivatives of the Poisson kernel, which correspond to derivatives of a point source gravity potential. Application of Poisson wavelets in potential field data analysis has begun in the 1990's and is predominantly aimed at studying gravity and magnetic fields singularity points during data interpretation.</p><p>Similar to Fourier-based potential field techniques, it is possible to construct a number of data filtering algorithms based on Poisson wavelets. Current work demonstrates that it is possible to construct algorithms based on Poisson wavelets for transforming profile and spatially gridded gravity and magnetic data, e.g. for calculation of equivalent density and magnetization distributions, upward and downward continuations, reduction to pole and many other filters that take into account spatial distribution of the signal.</p><p>Wavelet-transforms allow to account for spatially non-stationary nature of geophysical signals. Use of wavelet based techniques allows to effectively carry out potential field data interpretation in a variety of different geologic and tectonic settings in a consistent fashion.</p>

A new source location and attribute recognition method based on correlation analysis of gravity and magnetic anomaly

2020 ◽  
Author(s):  
Baoliang Lu ◽  
Tao Ma ◽  
Shengqing Xiong ◽  
Wanyin Wang
Keyword(s):  
Potential Field ◽  
Source Area ◽  
High Density ◽  
Low Density ◽  
Field Source ◽  
Geological Body ◽  
Gravity And Magnetic ◽  
Attribute Recognition ◽  
Parameter Values ◽  
Gravity And Magnetic Anomaly

<p>The traditional gravity and magnetic correspondence analysis tends to have high correlation outside the field source area. In order to overcome the disadvantage, we propose a new method for identify the source position and attribute, which is based on similarity and vertical derivative of potential field. In this method, we put forward a new gravity and magnetic correlation parameter (GMCP), which can effectively reduce the range of potential field source and indicate the field intensity information. The distribution of the non-zero areas of GMCP reflects the size of the source. GMCP discriminant parameter values of positive and negative reflect the source attribute. When GMCP is greater than zero, it is a positive correlation indicating that there are high-density and high-magnetization or low-density and low-magnetization homologous bodies in this region; When GMCP is less than zero, it is negative correlation indicating that there are high-density and low-magnetic or low-density and high-magnetic density homologous bodies in this region. GMCP goes to zero, which means no gravity-magnetic homologous geological body. Complex models test results with different noise level and actual data processing of South China Sea Basin show the correctness and validity of identification of the proposed methods.</p>

3-D inversion of gravity and magnetic data with depth resolution

Geophysics ◽  
1999 ◽  
Vol 64 (2) ◽  
pp. 452-460 ◽  
Author(s):  
Maurizio Fedi ◽  
Antonio Rapolla
Keyword(s):  
Potential Field ◽  
Field Data ◽  
Vertical Direction ◽  
Depth Resolution ◽  
Magnetic Data ◽  
Data Set ◽  
Potential Field Data ◽  
Magnetic Methods ◽  
Level Data ◽  
Gravity And Magnetic

Magnetization and density models with depth resolution are obtained by solving an inverse problem based on a 3-D set of potential field data. Such a data set is built from information on vertical and horizontal variations of the magnetic or gravity field. The a priori information consists of delimiting a source region and subdividing it in a set of blocks. In this case, the information related to a set of field data along the vertical direction is not generally redundant and is decisive in giving a depth resolution to the gravity and magnetic methods. Because of this depth resolution, which derives solely from the potential field data, an unconstrained and joint inversion of a multiobservation‐level data set is shown to provide surprising results for error‐free synthetic data. On the contrary, a single‐observation level data inversion produces an incorrect and too shallow model. Hence, a good depth resolution is likely to occur for the gravity and magnetic methods when based on the information along the vertical direction. This is also evidenced by an analysis of the kernel function versus the field altitude level and by a singular value analysis of the inversion operators for both the single and multilevel cases. Errors connected to numerical upward continuation do not affect the quality of the solution, provided that the data set extent is larger than that of the anomaly field. Application of the method to a 3-D magnetic data set relative to Vesuvius indicates that the method may significantly improve interpretation of potential fields.

On: “Geophysical Analysis in Central Indiana using Potential Field Continuation,” by A. J. Rudman, Judson Mead, Joseph F. Whaley, and Robert F. Blakely (GEOPHYSICS, October 1971, p. 878–890)

Geophysics ◽  
1972 ◽  
Vol 37 (6) ◽  
pp. 1047-1047
Author(s):  
Douglas J. Guion
Keyword(s):  
Gravity Anomaly ◽  
Magnetic Anomaly ◽  
Potential Field ◽  
Downward Continuation ◽  
Gravity Effect ◽  
Gravity And Magnetic ◽  
Gravity And Magnetic Anomaly ◽  
Field Continuation ◽  
Hamilton County

I read with interest the article concerning modeling the Hamilton County, Indiana, gravity and magnetic anomaly. The authors’ method for outlining the igneous body by downward continuation aroused my curiosity to the point that I decided to study the results in detail. My investigation revealed that the calculated gravity effect of the model did not satisfy the observed gravity anomaly. In fact, the amount of mismatch is quite serious.

RECURSION FILTERS FOR DIGITAL PROCESSING OF POTENTIAL FIELD DATA

Geophysics ◽  
1976 ◽  
Vol 41 (4) ◽  
pp. 712-726 ◽  
Author(s):  
B. K. Bhattacharyya
Keyword(s):  
Frequency Domain ◽  
Potential Field ◽  
Field Data ◽  
Least Squares Method ◽  
Vertical Gradient ◽  
Two Dimensional ◽  
Single Variable ◽  
Potential Field Data ◽  
Recursive Filter ◽  
Rational Expression

Zero‐phase two‐dimensional recursive filters, with a specified frequency domain response, have been designed for processing potential field data. In the case of second vertical derivative filters, it is possible to use the rational approximation of symmetrical functions of a single variable for the design of a short recursive filter. The filter so designed has an excellent response in the frequency domain. For vertical gradient and continuation filters, a method is developed for obtaining, by the least‐squares method, a rational expression for a two‐dimensional symmetrical function. In order to ensure the stability of the recursive filter, the denominator of the rational expression is approximated by a product of two factors, each being a function of a single variable. Finally, to keep the error of the filter response as small as possible, an iterative procedure is used for adjusting the zeros of the denominator and then determining the coefficients of the numerator of the rational expression.

Combination of horizontal gradient ratio and Euler methods for the interpretation of potential field data

Geophysics ◽  
2013 ◽  
Vol 78 (5) ◽  
pp. J53-J60 ◽  
Author(s):  
Guoqing Ma
Keyword(s):  
Potential Field ◽  
Field Data ◽  
Magnetic Data ◽  
Horizontal Gradient ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Potential Field Data ◽  
Free Data ◽  
Location Parameters ◽  
Gradient Ratio

The horizontal gradient ratio has been widely used to enhance the linear features of potential field data. I explore a combination of the horizontal gradient ratio and Euler method to interpret gridded potential field data, called HGR-EUL method. A linear equation derived for the Euler equation and expressing the fields as horizontal gradient ratio can be used to estimate the horizontal location and the depth of the source without any priori information about the nature (structural index) of the source. After obtaining the source location parameters, the nature of the source can be determined. The HGR-EUL method is tested on synthetic magnetic anomalies, and the inversion results show that the method can accurately provide the location parameters for noise-free data, and also obtain reasonable results for noise-corrupted data by applying a low pass filter to smooth the data. I also applied the HGR-EUL method to real magnetic data, and the results are compared with results from the standard Euler deconvolution method. The results obtained by the HGR-EUL method show less unjustified variability and are more useful for geologists.

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