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.

NAV-Edge: Edge detection of potential-field sources using normalized anisotropy variance

Geophysics ◽  
2014 ◽  
Vol 79 (3) ◽  
pp. J43-J53 ◽  
Author(s):  
Heng Lei Zhang ◽  
Dhananjay Ravat ◽  
Yára R. Marangoni ◽  
Xiang Yun Hu
Keyword(s):  
Edge Detection ◽  
Potential Field ◽  
Field Data ◽  
Gaussian Function ◽  
Magnetic Data ◽  
Horizontal Gradient ◽  
Potential Field Data ◽  
Variance Method ◽  
Detection Algorithms ◽  
Total Horizontal Derivative

Most existing edge-detection algorithms are based on the derivatives of potential-field data, and thus, enhance high wavenumber information and are sensitive to noise. The normalized anisotropy variance method (NAV-Edge) was proposed for detecting edges of potential-field anomaly sources based on the idea of normalized standard deviation (NSTD). The main improvement over the balanced, windowed normalized variance method (i.e., NSTD) used for similar purposes was the application of an anisotropic Gaussian function designed to detect directional edges and reduce sensitivity to noise. NAV-Edge did not directly use higher-order derivatives and was less sensitive to noise than the traditional methods that use derivatives in their calculation. The utility of NAV-Edge was demonstrated using synthetic potential-field data and real magnetic data. Compared with several existing methods (i.e., the curvature of horizontal gradient amplitude, tilt angle and its total-horizontal derivative, theta map, and NSTD), NAV-Edge produced superior results by locating edges closer to the true edges, resulting in better interpretive images.

Edge enhancement of potential field data using spectral moments

Geophysics ◽  
2016 ◽  
Vol 81 (1) ◽  
pp. G1-G11 ◽  
Author(s):  
Yanyun Sun ◽  
Wencai Yang ◽  
Xiangzhi Zeng ◽  
Zhiyong Zhang
Keyword(s):  
Potential Field ◽  
Moment Method ◽  
Field Data ◽  
Gravity Data ◽  
Magnetic Data ◽  
Horizontal Gradient ◽  
Spectral Moment ◽  
Edge Enhancement ◽  
Potential Field Data ◽  
Geologic Maps

Edge enhancement in potential-field data helps geologic interpretation, where the lineaments on the potential-field frequently indicate subsurface faults, contacts, and other tectonic features. Therefore, a variety of edge-enhancement methods have been proposed for locating edges, most of which are based on the horizontal or vertical derivatives of the field. However, these methods have several limitations, including thick detected boundaries, blurred response to low-amplitude anomalies, and sensitivity to noise. We have developed the spectral-moment method for detecting edges in potential-field anomalies based on the second spectral moment and its statistically invariable quantities. We evaluated the spectral-moment method using synthetic gravity data, EGM-2008 gravity data, and the total magnetic field reduced to the pole. Compared with other edge-enhancing filters, such as the total horizontal derivative (TDX), profile curvature, curvature of the total horizontal gradient amplitude, enhancement of the TDX using the tilt angle, theta map, and normalized standard deviation, this spectral-moment method was more effective in balancing the edges of different-amplitude anomalies, and the detected lineaments were sharper and more continuous. In addition, the method was also less sensitive to noise than were the other filters. Compared with geologic maps, the edges extracted by the spectral-moment method from gravity and the magnetic data corresponded well with the geologic structures.

Adaptive sampling of potential-field data: A direct approach to compressive inversion

Geophysics ◽  
2014 ◽  
Vol 79 (1) ◽  
pp. IM1-IM9 ◽  
Author(s):  
Nathan Leon Foks ◽  
Richard Krahenbuhl ◽  
Yaoguo Li
Keyword(s):  
Potential Field ◽  
Adaptive Sampling ◽  
Field Data ◽  
Computational Cost ◽  
Large Field ◽  
Magnetic Data ◽  
Data Sampling ◽  
Data Types ◽  
Data Set ◽  
Potential Field Data

Compressive inversion uses computational algorithms that decrease the time and storage needs of a traditional inverse problem. Most compression approaches focus on the model domain, and very few, other than traditional downsampling focus on the data domain for potential-field applications. To further the compression in the data domain, a direct and practical approach to the adaptive downsampling of potential-field data for large inversion problems has been developed. The approach is formulated to significantly reduce the quantity of data in relatively smooth or quiet regions of the data set, while preserving the signal anomalies that contain the relevant target information. Two major benefits arise from this form of compressive inversion. First, because the approach compresses the problem in the data domain, it can be applied immediately without the addition of, or modification to, existing inversion software. Second, as most industry software use some form of model or sensitivity compression, the addition of this adaptive data sampling creates a complete compressive inversion methodology whereby the reduction of computational cost is achieved simultaneously in the model and data domains. We applied the method to a synthetic magnetic data set and two large field magnetic data sets; however, the method is also applicable to other data types. Our results showed that the relevant model information is maintained after inversion despite using 1%–5% of the data.

Computer Application in Geosciences: Imaging of the Subsurface by Structural Coupled Inversion of Potential Field Data

2014 ◽  
Vol 644-650 ◽  
pp. 2670-2673
Author(s):  
Jun Wang ◽  
Xiao Hong Meng ◽  
Fang Li ◽  
Jun Jie Zhou
Keyword(s):  
Potential Field ◽  
Field Data ◽  
Gravity Data ◽  
Computer Application ◽  
Magnetic Data ◽  
Imaging Method ◽  
Inversion Algorithm ◽  
Constant Property ◽  
Near Surface ◽  
Potential Field Data

With the continuing growth in influence of near surface geophysics, the research of the subsurface structure is of great significance. Geophysical imaging is one of the efficient computer tools that can be applied. This paper utilize the inversion of potential field data to do the subsurface imaging. Here, gravity data and magnetic data are inverted together with structural coupled inversion algorithm. The subspace (model space) is divided into a set of rectangular cells by an orthogonal 2D mesh and assume a constant property (density and magnetic susceptibility) value within each cell. The inversion matrix equation is solved as an unconstrained optimization problem with conjugate gradient method (CG). This imaging method is applied to synthetic data for typical models of gravity and magnetic anomalies and is tested on field data.

Three-dimensional depth-to-basement modelling based on seismic and potential field data – basement configuration in the westernmost Polish Outer Carpathians

2020 ◽  
Author(s):  
Mateusz Mikołajczak ◽  
Jan Barmuta ◽  
Małgorzata Ponikowska ◽  
Stanislaw Mazur ◽  
Krzysztof Starzec
Keyword(s):  
Qualitative Analysis ◽  
Cross Sections ◽  
Potential Field ◽  
Field Data ◽  
Gravity Data ◽  
Three Dimensional ◽  
Magnetic Data ◽  
Gravity Inversion ◽  
Potential Field Data ◽  
Outer Carpathians

<p>The Silesian Nappe in the westernmost part of the Polish Outer Carpathians Fold and Thrust Belt exhibits simple, almost homoclinal character. Based on the field observations, a total stratigraphic thickness of this sequence equals to at least 5400 m. On the other hand, the published maps of the sub-Carpathian basement show its top at depths no greater than 3000 m b.s.l. or even 2000 m b.s.l. in the southern part of the Silesian Nappe. Assuming no drastic thickness variations within the sedimentary sequence of the Silesian Nappe, such estimates of the basement depth are inconsistent with the known thickness of the Silesian sedimentary succession. The rationale behind our work was to resolve this inconsistency and verify the actual depth and structure of the sub-Carpathian crystalline basement along two regional cross-sections. In order to achieve this goal, a joint 2D quantitative interpretation of gravity and magnetic data was performed along these regional cross-sections. The interpretation was supported by the qualitative analysis of magnetic and gravity maps and their derivatives to recognize structural features in the sub-Carpathian basement. The study was concluded with the 3D residual gravity inversion for the top of basement. The cross-sections along with the borehole data available from the area were applied to calibrate the inversion.</p><p>In the westernmost part of the Polish Outer Carpathians, the sub-Carpathian basement comprises part of the Brunovistulian Terrane. Because of great depths, the basement structure was investigated mainly by geophysical, usually non-seismic, methods. However, some deep boreholes managed to penetrate the basement that is composed of Neoproterozoic metamorphic and igneous rocks. The study area is located within the Upper Silesian block along the border between Poland and Czechia. There is a basement uplift as known mainly from boreholes, but the boundaries and architecture of this uplift are poorly recognized. Farther to the south, the top of the Neoproterozoic is buried under a thick cover of lower Palaeozoic sediments and Carpathian nappes.</p><p>Our integrative study allowed to construct a three-dimensional map for the top of basement the depth of which increases from about 1000 m to over 7000 m b.s.l. in the north and south of the study area, respectively. Qualitative analysis of magnetic and gravity data revealed the presence of some  basement-rooted faults delimiting the extent of the uplifted basement. The interpreted faults are oriented mainly towards NW-SE and NE-SW. Potential field data also document the correlation between the main basement steps and important thrust faults.</p><p> </p><p>This work has been funded by the Polish National Science Centre grant no UMO-2017/25/B/ST10/01348</p>

The monogenic signal of potential-field data: A Python implementation

Geophysics ◽  
2017 ◽  
Vol 82 (3) ◽  
pp. F9-F14 ◽  
Author(s):  
Marlon C. Hidalgo-Gato ◽  
Valéria C. F. Barbosa
Keyword(s):  
Potential Field ◽  
Field Data ◽  
Scale Space ◽  
Magnetic Data ◽  
Monogenic Signal ◽  
Potential Field Data ◽  
Source Program ◽  
Multiple Component ◽  
Ground Penetrating ◽  
Monogenic Signals

We have developed codes to calculate the local amplitude, the local phase, and the local orientation of the nonscale and the Poisson’s scale-space monogenic signals of potential-field data in version 1.0 of the open-source program Monogenic. The monogenic vector of a generic function is calculated in the wavenumber domain and then transformed back into the space domain to find the monogenic signal attributes. We compare the use of the nonscale monogenic signal with the Poisson’s scale-space monogenic signal in magnetic data. This comparison shows that the latter can produce better results as an edge detection filter. The implementation of the monogenic signal can be used to enhance other geophysical data, such as seismic, ground-penetrating radar, gravity, multiple-component gravity gradiometry, and magnetic gradient data.

Improved use of the local wavenumber in potential-field interpretation

Geophysics ◽  
2009 ◽  
Vol 74 (6) ◽  
pp. L75-L85 ◽  
Author(s):  
Pierre Keating
Keyword(s):  
Potential Field ◽  
Field Data ◽  
Thin Sheet ◽  
Homogeneous Magnetic Field ◽  
Horizontal Cylinder ◽  
Magnetic Data ◽  
Homogeneous Field ◽  
Potential Field Data ◽  
Local Wavenumber ◽  
Homogeneity Hypothesis

Fast interpretation of potential field data (magnetic data are a typical example) often uses simple geometries to describe a complex geologic reality. Many of these techniques assume that the potential field arising from the source body is homogeneous. The degree of homogeneity of a source is characteristic of its geometry. However, very few source geometries are known to generate a homogeneous field. The contact, thin sheet, horizontal cylinder, pole, and dipole all cause a homogeneous magnetic field. More complex geometries such as the thick dike or rectangular prism do not. Therefore, a major problem is to check for the validity of the homogeneity hypothesis when these types of interpretation techniques are used. The local wavenumber of a potential field calculated at a series of increasing heights above the measurement datum can be used to directly compute the depth to a source and its degree of homogeneity. In addition, the vertical derivative of the local wavenumber can provide an estimate of the depth to sources without knowledge of their degree of homogeneity. The proposed technique also allows us to test if the source is homogeneous or not, and it applies to any type of potential field data. The technique breaks down on synthetic magnetic data when anomalous sources are closer than about four times their depths. This behavior is expected from interpretation techniques that use upward continuation. The technique can be applied to profile and gridded data. Its main advantage is that it allows testing the homogeneity hypothesis and therefore the validity of the interpretation.

scholarly journals 3D Convolution Conjugate Gradient Inversion of Potential Fields in Acoculco Geothermal Prospect, Mexico

2022 ◽  
Vol 9 ◽  
Author(s):  
José P. Calderón ◽  
Luis A. Gallardo
Keyword(s):  
Conjugate Gradient ◽  
Potential Field ◽  
Field Data ◽  
Large Scale ◽  
Three Dimensional ◽  
Potential Fields ◽  
Magnetic Data ◽  
Geothermal System ◽  
Potential Field Data ◽  
Model Compression

Potential field data have long been used in geophysical exploration for archeological, mineral, and reservoir targets. For all these targets, the increased search of highly detailed three-dimensional subsurface volumes has also promoted the recollection of high-density contrast data sets. While there are several approaches to handle these large-scale inverse problems, most of them rely on either the extensive use of high-performance computing architectures or data-model compression strategies that may sacrifice some level of model resolution. We posit that the superposition and convolutional properties of the potential fields can be easily used to compress the information needed for data inversion and also to reduce significantly redundant mathematical computations. For this, we developed a convolution-based conjugate gradient 3D inversion algorithm for the most common types of potential field data. We demonstrate the performance of the algorithm using a resolution test and a synthetic experiment. We then apply our algorithm to gravity and magnetic data for a geothermal prospect in the Acoculco caldera in Mexico. The resulting three-dimensional model meaningfully determined the distribution of the existent volcanic infill in the caldera as well as the interrelation of various intrusions in the basement of the area. We propose that these intrusive bodies play an important role either as a low-permeability host of the heated fluid or as the heat source for the potential development of an enhanced geothermal system.

Sign in / Sign up

Export Citation Format

Share Document