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.

scholarly journals Three-dimensional interpretation of magnetic and gravity anomalies using the finite-difference similarity transform

Geophysics ◽  
2010 ◽  
Vol 75 (4) ◽  
pp. L79-L90 ◽  
Author(s):  
Daniela Gerovska ◽  
Marcos J. Araúzo-Bravo ◽  
Kathryn Whaler ◽  
Petar Stavrev ◽  
Alan Reid
Keyword(s):  
Finite Difference ◽  
Random Noise ◽  
Source Parameters ◽  
Magnetization Vector ◽  
Real Data ◽  
Index Formula ◽  
Magnetic Data ◽  
Horizontal Position ◽  
Structural Index ◽  
Similarity Transform

We present an automatic procedure for interpretation of magnetic or gravity gridded anomalies based on the finite-difference similarity transform (FDST). It is called MaGSoundFDST (magnetic and gravity sounding based on the finite-difference similarity transform) and uses a “focusing” principle in contrast to deriving multiple clusters of many solutions as in the widely used Euler deconvolution method. The source parameters are characterized by isolated solutions, and the interpreter obtains parallel images showing the horizontal position, depth, and structural index [Formula: see text] value. The underlying principle is that the FDST of a potential field anomaly becomes zero or linear at all observation points when the central point of similarity (CPS) of the transform coincides with a source field’s singular point and a correct [Formula: see text] value is used. The procedure involves calculating a 3D function that evaluates the linearity of the FDST for a series of [Formula: see text] values, using a moving window and sounding the subsurface along a verticalline under each window center. We then combine the 3D results for different [Formula: see text] values into a single map whose minima determine the horizontal position of the sources. The [Formula: see text] value and the CPS depth associated with each minimum determine the [Formula: see text] value and depth of the corresponding source. Only one estimate characterizes a simple source, which is a major advantage over other window-based procedures. MaGSoundFDST uses only the measured anomalous field and its upward continuation, thus avoiding the direct use of field derivatives. It is independent of the magnetization-vector direction in the magnetic data case. The procedure accounts for a linear background of local gravity or magnetic anomalies and has been applied effectively to several cases of synthetic and real data. MaGSoundFDST shares common features with the magnetic and gravity sounding based on the differential similarity transform (MaGSoundDST) but is more stable in estimating depth and structural index in the presence of random noise.

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.

scholarly journals Random Material Property Fields of 3D Concrete Microstructures Based on CT Image Reconstruction

Materials ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1423
Author(s):  
George Stefanou ◽  
Dimitrios Savvas ◽  
Panagiotis Metsis
Keyword(s):  
Random Fields ◽  
Volume Fraction ◽  
Concrete Specimen ◽  
Elasticity Tensor ◽  
Statistical Characteristics ◽  
Moving Window ◽  
Window Method ◽  
Ct Image Reconstruction ◽  
Random Material Property ◽  
Spatially Varying

The purpose of this paper is to determine the random spatially varying elastic properties of concrete at various scales taking into account its highly heterogeneous microstructure. The reconstruction of concrete microstructure is based on computed tomography (CT) images of a cubic concrete specimen. The variability of the local volume fraction of the constituents (pores, cement paste and aggregates) is quantified and mesoscale random fields of the elasticity tensor are computed from a number of statistical volume elements obtained by applying the moving window method on the specimen along with computational homogenization. Based on the statistical characteristics of the mesoscale random fields, it is possible to assess the effect of randomness in microstructure on the mechanical behavior of concrete.

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.

Application of gravity and magnetic methods to assess geological hazards and natural resource potential in the Mosida Hills, Utah County, Utah

Geophysics ◽  
2000 ◽  
Vol 65 (5) ◽  
pp. 1514-1526 ◽  
Author(s):  
Alvin K. Benson ◽  
Andrew R. Floyd
Keyword(s):  
Gravity Data ◽  
Magnetic Data ◽  
Geological Hazards ◽  
Mafic Lava ◽  
Subsurface Geology ◽  
Gravity And Magnetic ◽  
Geophysical Surveys ◽  
Utah County ◽  
Gravity And Magnetic Data ◽  
Hills Area

Gravity and magnetic data were collected in the Mosida Hills, Utah County, Utah, at over 1100 stations covering an area of approximately 58 km2 (150 mi2) in order to help define the subsurface geology and assess potential geological hazards for urban planning in an area where the population is rapidly increasing. In addition, potential hydrocarbon traps and mineral ore bodies may be associated with some of the interpreted subsurface structures. Standard processing techniques were applied to the data to remove known variations unrelated to the geology of the area. The residual data were used to generate gravity and magnetic contour maps, isometric projections, profiles, and subsurface models. Ambiguities in the geological models were reduced by (1) incorporating data from previous geophysical surveys, surface mapping, and aeromagnetic data, (2) integrating the gravity and magnetic data from our survey, and (3) correlating the modeled cross sections. Gravity highs and coincident magnetic highs delineate mafic lava flows, gravity lows and magnetic highs reflect tuffs, and gravity highs and magnetic lows spatially correlate with carbonates. These correlations help identify the subsurface geology and lead to new insights about the formation of the associated valleys. At least eight new faults (or fault segments) were identified from the gravity data, whereas the magnetic data indicate the existence of at least three concealed and/or poorly exposed igneous bodies, as well as a large ash‐flow tuff. The presence of low‐angle faults suggests that folding or downwarping, in addition to faulting, played a role in the formation of the valleys in the Mosida Hills area. The interpreted location and nature of concealed faults and volcanic flows in the Mosida Hills area are being used by policy makers to help develop mitigation procedures to protect life and property.

scholarly journals PPT-NS: Prioritized Progressive Trend Based Navigational System on GPS data with Artifacts

2019 ◽  
Vol 9 (2) ◽  
pp. 621-630
Keyword(s):  
Global Positioning System ◽  
Gps Data ◽  
Moving Window ◽  
Location Service ◽  
Window Method ◽  
Global Positioning ◽  
Trajectory Mapping ◽  
Coefficient Corrélation ◽  
Navigational System ◽  
Processing Techniques

The Global Positioning System is extensively used in the various context and location service-based applications. Any kind of abnormalities requires an efficient and suitable pre-processing algorithm to be implemented on the data which provides accurate results when used in the application synchronizations. This paper illustrates a framework for various pre-processing techniques applied to the real-time GPS data and its effect on trajectory mapping. The technique used includes Prioritized pattern-based, Savitzky-Golay filtering, outlier elimination, de-trending, and coefficient correlation. The performance assessment of methods discussed in this study is calculated in terms of accuracy with the original and re-created trajectory after the pre-processing and found that the best result is given by moving window method.

Magnetization vector imaging for borehole magnetic data based on magnitude magnetic anomaly

Geophysics ◽  
2013 ◽  
Vol 78 (6) ◽  
pp. D429-D444 ◽  
Author(s):  
Shuang Liu ◽  
Xiangyun Hu ◽  
Tianyou Liu ◽  
Jie Feng ◽  
Wenli Gao ◽  
...  
Keyword(s):  
Conjugate Gradient Method ◽  
Conjugate Gradient ◽  
Gradient Method ◽  
Magnetization Vector ◽  
Real Data ◽  
Magnetic Anomalies ◽  
Magnetic Data ◽  
Preconditioned Conjugate Gradient ◽  
Magnetization Direction ◽  
Magnetization Intensity

Remanent magnetization and self-demagnetization change the magnitude and direction of the magnetization vector, which complicates the interpretation of magnetic data. To deal with this problem, we evaluated a method for inverting the distributions of 2D magnetization vector or effective susceptibility using 3C borehole magnetic data. The basis for this method is the fact that 2D magnitude magnetic anomalies are not sensitive to the magnetization direction. We calculated magnitude anomalies from the measured borehole magnetic data in a spatial domain. The vector distributions of magnetization were inverted methodically in two steps. The distributions of magnetization magnitude were initially solved based on magnitude magnetic anomalies using the preconditioned conjugate gradient method. The preconditioner determined by the distances between the cells and the borehole observation points greatly improved the quality of the magnetization magnitude imaging. With the calculated magnetization magnitude, the distributions of magnetization direction were computed by fitting the component anomalies secondly using the conjugate gradient method. The two-step approach made full use of the amplitude and phase anomalies of the borehole magnetic data. We studied the influence of remanence and demagnetization based on the recovered magnetization intensity and direction distributions. Finally, we tested our method using synthetic and real data from scenarios that involved high susceptibility and complicated remanence, and all tests returned favorable results.

Integrated Geophysical Interpretation of Kerio Valley Basin Stratigraphy, Kenya Rift

2016 ◽  
Author(s):  
Godfred Osukuku ◽  
Abiud Masinde ◽  
Bernard Adero ◽  
Edmond Wanjala ◽  
John Ego
Keyword(s):  
Gravity Data ◽  
Gravity Anomalies ◽  
Fault System ◽  
Magnetic Data ◽  
Data Sets ◽  
Seismic Profiles ◽  
The West ◽  
Seismic Reflection Data ◽  
Basement Rocks ◽  
Western Side

Abstract This research work attempts to map out the stratigraphic sequence of the Kerio Valley Basin using magnetic, gravity and seismic data sets. Regional gravity data consisting of isotactic, free-air and Bouguer anomaly grids were obtained from the International Gravity Bureau (BGI). Magnetic data sets were sourced from the Earth Magnetic Anomaly grid (EMAG2). The seismic reflection data was acquired in 1989 using a vibrating source shot into inline geophones. Gravity Isostacy data shows low gravity anomalies that depict a deeper basement. Magnetic tilt and seismic profiles show sediment thickness of 2.5-3.5 Km above the basement. The Kerio Valley Basin towards the western side is underlain by a deeper basement which are overlain by succession of sandstones/shales and volcanoes. At the very top are the mid Miocene phonolites (Uasin Gishu) underlain by mid Miocene sandstones/shales (Tambach Formation). There are high gravity anomalies in the western and southern parts of the basin with the sedimentation being constrained by two normal faults. The Kerio Valley Basin is bounded to the west by the North-South easterly dipping fault system. Gravity data was significantly of help in delineating the basement, scanning the lithosphere and the upper mantle according to the relative densities. The basement rocks as well as the upper cover of volcanoes have distinctively higher densities than the infilled sedimentary sections within the basin. From the seismic profiles, the frequency of the shaley rocks and compact sandstones increases with depths. The western side of the basin is characterized by the absence of reflections and relatively higher frequency content. The termination of reflectors and the westward dip of reflectors represent a fault (Elgeyo fault). The reflectors dip towards the west, marking the basin as an asymmetrical syncline, indicating that the extension was towards the east. The basin floor is characterized by a nearly vertical fault which runs parallel to the Elgeyo fault. The seismic reflectors show marked discontinuities which may be due to lava flows. The deepest reflector shows deep sedimentation in the basin and is in reasonable agreement with basement depths delineated from potential methods (gravity and magnetic). Basement rocks are deeper at the top of the uplift footwall of the Elgeyo Escarpment. The sediments are likely of a thickness of about 800 M which is an interbed of sandstones and shales above the basement.

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