Edge enhancement of potential-field data using normalized statistics

Geophysics ◽  
2008 ◽  
Vol 73 (3) ◽  
pp. H1-H4 ◽  
Author(s):  
Gordon R. J. Cooper ◽  
Duncan R. Cowan
Keyword(s):  
Standard Deviation ◽  
Potential Field ◽  
Field Data ◽  
Gravity Data ◽  
Edge Enhancement ◽  
Potential Field Data ◽  
Geologic Interpretation ◽  
Derivatives Of ◽  
High Pass ◽  
Detection Filter

Edge enhancement in potential-field data helps geologic interpretation. There are many methods for enhancing edges, most of which are high-pass filters based on the horizontal or vertical derivatives of the field. Normalized standard deviation (NSTD), a new edge-detection filter, is based on ratios of the windowed standard deviation of derivatives of the field. NSTD is demonstrated using aeromagnetic data from Australia and gravity data from South Africa. Compared with other filters, the NSTD filter produces more detailed results.

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.

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>

A method for inversion of 1D vertical soundings of gravity anomalies

Geophysics ◽  
2018 ◽  
Vol 83 (2) ◽  
pp. G15-G23
Author(s):  
Andrea Vitale ◽  
Domenico Di Massa ◽  
Maurizio Fedi ◽  
Giovanni Florio
Keyword(s):  
Potential Field ◽  
Field Data ◽  
Gravity Data ◽  
Finite Size ◽  
Gravity Anomalies ◽  
Real Data ◽  
Gravity Inversion ◽  
Chain Process ◽  
Potential Field Data ◽  
Gamma Density

We have developed a method to interpret potential fields, which obtains 1D models by inverting vertical soundings of potential field data. The vertical soundings are built through upward continuation of potential field data, measured on either a profile or a surface. The method assumes a forward problem consisting of a volume partitioned in layers, each of them homogeneous and horizontally finite, but with the density changing versus depth. The continuation errors, increasing with the altitude, are automatically handled by determining the coefficients of a third-order polynomial function of the altitude. Due to the finite size of the source volume, we need a priori information about the total horizontal extent of the volume, which is estimated by boundary analysis and optimized by a Markov chain process. For each sounding, a 1D inverse problem is independently solved by a nonnegative least-squares algorithm. Merging of the several inverted models finally yields approximate 2D or 3D models that are, however, shown to generate a good fit to the measured data. The method is applied to synthetic models, producing good results for either perfect or continued data. Even for real data, i.e., the gravity data of a sedimentary basin in Nevada, the results are interesting, and they are consistent with previous interpretation, based on 3D gravity inversion constrained by two gamma-gamma density logs.

scholarly journals An edge-assisted smooth method for potential field data

2021 ◽  
Vol 18 (1) ◽  
pp. 113-123
Author(s):  
Shijing Zheng ◽  
Xiaohong Meng ◽  
Jun Wang
Keyword(s):  
Edge Detection ◽  
Potential Field ◽  
Field Data ◽  
Real Data ◽  
Linear Functions ◽  
Detection Methods ◽  
Edge Preserving ◽  
Potential Field Data ◽  
Tectonic Boundaries ◽  
Derivatives Of

Abstract Edge detection is one of the most commonly used methods for the interpretation of potential field data, because it can highlight the horizontal inhomogeneous of underground geological bodies (faults, tectonic boundaries, etc.). A variety of edge detection methods have been reported in the literature, most of which are based on the combined transformation results of horizontal and vertical derivatives of the observations. Consequently, these edge detection methods are sensitive to noise. Therefore, noise reduction is desirable ahead of applying edge detection methods. However, the application of conventional filters smears discontinuities in the data to a certain extent, which would inevitably induce unfavourable influence on subsequent edge detection. To solve this problem, a novel edge-preserving smooth method for potential field data is proposed, which is based on the concept of guided filter developed for image processing. The new method substitutes each data point by a combination of a series of coefficients of linear functions. It was tested on synthetic model and real data, and the results showed that it can effectively smooth potential field data while preserving major structural and stratigraphic discontinuities. The obtained data from the new filter contain more obvious features of existing faults, which brings advantageous to further geological interpretations.

Correction of topographic distortions in potential‐field data: A fast and accurate approach

Geophysics ◽  
1993 ◽  
Vol 58 (4) ◽  
pp. 515-523 ◽  
Author(s):  
Jianghai Xia ◽  
Donald R. Sprowl ◽  
Dana Adkins‐Heljeson
Keyword(s):  
Potential Field ◽  
Field Data ◽  
Gravity Data ◽  
Source Distribution ◽  
Potential Field Data ◽  
Equivalent Source ◽  
Horizontal Shift ◽  
Maximum Elevation ◽  
Rms Error ◽  
Forward Calculation

The equivalent source concept is used in the wavenumber domain to correct distortions in potential‐field data caused by topographic relief. The equivalent source distribution on a horizontal surface is determined iteratively through forward calculation of the anomaly on the topographic surface. Convergence of the solution is stable and rapid. The accuracy of the Fourier‐based approach is demonstrated by two synthetic examples. For the gravity example, the rms error between the corrected anomaly and the desired anomaly is 0.01 mGal, which is less than 0.5 percent of the maximum synthetic anomaly. For the magnetic example, the rms error is 0.7 nT, which is less than 1 percent of the maximum synthetic anomaly. The efficiency of the approach is shown by application to the gravity and aeromagnetic grids for Kansas. For gravity data, with a maximum elevation change of 500 m reducing to a horizontal datum results in a maximum correction in gravity anomaly amplitude of up to 2.6 mGal. For aeromagnetic data, the method results in a maximum horizontal shift of anomalies of 470 m with a maximum correction in aeromagnetic anomaly amplitudes up to 270 nT.

Edge enhancement of potential field data using an enhanced tilt angle

2015 ◽  
Vol 46 (3) ◽  
pp. 276-283 ◽  
Author(s):  
Xu Zhang ◽  
Peng Yu ◽  
Rui Tang ◽  
Yang Xiang ◽  
Chong-Jin Zhao
Keyword(s):  
Tilt Angle ◽  
Potential Field ◽  
Field Data ◽  
Edge Enhancement ◽  
Potential Field Data
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