scholarly journals A new method for interpolating linear features in aeromagnetic data

Geophysics ◽  
2019 ◽  
Vol 84 (3) ◽  
pp. JM15-JM24 ◽  
Author(s):  
Tomas Naprstek ◽  
Richard S. Smith
Keyword(s):  
Field Data ◽  
Interpolation Method ◽  
Source Code ◽  
Synthetic Data ◽  
Aeromagnetic Data ◽  
Derivative Expansion ◽  
Linear Features ◽  
Interpolation Methods ◽  
Minimum Curvature ◽  
Linear Nature

When aeromagnetic data are interpolated to make a gridded image, thin linear features can result in “boudinage” or “string of beads” artifacts if the anomalies are at acute angles to the traverse lines. These artifacts are due to the undersampling of these types of features across the flight lines, making it difficult for most interpolation methods to effectively maintain the linear nature of the features without user guidance. The magnetic responses of dikes and dike swarms are typical examples of the type of geologic feature that can cause these artifacts; thus, these features are often difficult to interpret. Many interpretation methods use various enhancements of the gridded data, such as horizontal or vertical derivatives, and these artifacts are often exacerbated by the processing. Therefore, interpolation methods that are free of these artifacts are necessary for advanced interpretation and analysis of thin, linear features. We have developed a new interpolation method that iteratively enhances linear trends across flight lines, ensuring that linear features are evident on the interpolated grid. Using a Taylor derivative expansion and structure tensors allows the method to continually analyze and interpolate data along anisotropic trends, while honoring the original flight line data. We applied this method to synthetic data and field data, which both show improvement over standard bidirectional gridding, minimum curvature, and kriging methods for interpolating thin, linear features at acute angles to the flight lines. These improved results are also apparent in the vertical derivative enhancement of field data. The source code for this method has been made publicly available.

scholarly journals Cross-streamer wavefield reconstruction through wavelet domain learning

Geophysics ◽  
2020 ◽  
Vol 85 (6) ◽  
pp. V457-V471
Author(s):  
Thomas Andre Larsen Greiner ◽  
Volodya Hlebnikov ◽  
Jan Erik Lie ◽  
Odd Kolbjørnsen ◽  
Andreas Kjelsrud Evensen ◽  
...  
Keyword(s):  
Field Data ◽  
Barents Sea ◽  
Interpolation Method ◽  
Synthetic Data ◽  
Seismic Exploration ◽  
Wavelet Domain ◽  
Spatial Aliasing ◽  
Industry Standard ◽  
Marine Source ◽  
Marine Seismic

Seismic exploration in complex geologic settings and shallow geologic targets has led to a demand for higher spatial and temporal resolution in the final migrated image. Conventional marine seismic and wide-azimuth data acquisition lack near-offset coverage, which limits imaging in these settings. A new marine source-over-cable survey, with split-spread configuration, known as TopSeis, was introduced in 2017 to address the shallow-target problem. However, wavefield reconstruction in the near offsets is challenging in the shallow part of the seismic record due to the high temporal frequencies and coarse sampling that leads to severe spatial aliasing. We have investigated deep learning as a tool for the reconstruction problem, beyond spatial aliasing. Our method is based on a convolutional neural network (CNN) approach trained in the wavelet domain that is used to reconstruct the wavefield across the streamers. We determine the performance of the proposed method on broadband synthetic data and TopSeis field data from the Barents Sea. From our synthetic example, we find that the CNN can be learned in the inline direction and applied in the crossline direction, and that the approach preserves the characteristics of the geologic model in the migrated section. In addition, we compare our method to an industry-standard Fourier-based interpolation method, in which the CNN approach shows an improvement in the root-mean-square (rms) error close to a factor of two. In our field data example, we find that the approach reconstructs the wavefield across the streamers in the shot domain, and it displays promising characteristics of a reconstructed 3D wavefield.

Interpretive gridding by anisotropic kriging

Geophysics ◽  
1993 ◽  
Vol 58 (10) ◽  
pp. 1491-1497 ◽  
Author(s):  
R. O. Hansen
Keyword(s):  
A Priori ◽  
Juan De Fuca Ridge ◽  
Aeromagnetic Data ◽  
Covariance Model ◽  
A Priori Information ◽  
Linear Features ◽  
Additional Information ◽  
Juan De Fuca ◽  
Priori Information ◽  
Minimum Curvature

Most interpolation algorithms perform poorly on data sampled along profiles crossing features whose length scales are small along the profiles but large transverse to them, such as lineaments. Rather than reproducing the linear features, these algorithms create a series of closures around the profiles. By introducing additional information into the algorithm, in particular by using an anisotropic covariance model for kriging that contains a priori information about the lineations, more realistic results can be obtained. An algorithm of this type produces a much more reasonable map of aeromagnetic data from the Cobb Offset zone of the Juan de Fuca Ridge than either minimum curvature gridding or isotropic kriging.

ENHANCING LINEAR FEATURES IN AEROMAGNETIC DATA USING DIRECTIONAL HORIZONTAL GRADIENT AT WADI HAIMUR AREA, SOUTH EASTERN DESERT, EGYPT,

2020 ◽  
Vol 15 (2) ◽  
pp. 323-326
Author(s):  
Ahmed Mohammed ELDOSOUKY ◽  
◽  
Sayed Omar ELKHATEEB ◽  
Abeer ALI ◽  
Sherif KHARBISH
Keyword(s):  
Eastern Desert ◽  
Horizontal Gradient ◽  
Aeromagnetic Data ◽  
Linear Features ◽  
South Eastern

Research about Influencing Factor on Interpolation Accuracy in Data Exchange of Fluid-Structure Interaction

2013 ◽  
Vol 318 ◽  
pp. 100-107
Author(s):  
Zhen Shen ◽  
Biao Wang ◽  
Hui Yang ◽  
Yun Zheng
Keyword(s):  
Data Exchange ◽  
Shape Function ◽  
Interpolation Method ◽  
Matching Condition ◽  
Optimal Interpolation ◽  
Complex Interpolation ◽  
Interpolation Function ◽  
Interpolation Methods ◽  
Interpolation Accuracy ◽  
Lower Accuracy

Six kinds of interpolation methods, including projection-shape function method, three-dimensional linear interpolation method, optimal interpolation method, constant volume transformation method and so on, were adoped in the study of interpolation accuracy. From the point of view about the characterization of matching condition of two different grids and interpolation function, the infuencing factor on the interpolation accuracy was studied. The results revealed that different interpolation methods had different interpolation accuracy. The projection-shape function interpolation method had the best effect and the more complex interpolation function had lower accuracy. In many cases, the matching condition of two grids had much greater impact on the interpolation accuracy than the method itself. The error of interpolation method is inevitable, but the error caused by the grid quality could be reduced through efforts.

scholarly journals Coupled hydrogeophysical parameter estimation using a sequential Bayesian approach

2010 ◽  
Vol 14 (3) ◽  
pp. 545-556 ◽  
Author(s):  
J. Rings ◽  
J. A. Huisman ◽  
H. Vereecken
Keyword(s):  
Water Content ◽  
Particle Filtering ◽  
Field Data ◽  
Synthetic Data ◽  
Time Domain Reflectometry ◽  
Second Step ◽  
Parameter Estimates ◽  
Posterior Distributions ◽  
Data Set ◽  
Resistivity Tomography

Abstract. Coupled hydrogeophysical methods infer hydrological and petrophysical parameters directly from geophysical measurements. Widespread methods do not explicitly recognize uncertainty in parameter estimates. Therefore, we apply a sequential Bayesian framework that provides updates of state, parameters and their uncertainty whenever measurements become available. We have coupled a hydrological and an electrical resistivity tomography (ERT) forward code in a particle filtering framework. First, we analyze a synthetic data set of lysimeter infiltration monitored with ERT. In a second step, we apply the approach to field data measured during an infiltration event on a full-scale dike model. For the synthetic data, the water content distribution and the hydraulic conductivity are accurately estimated after a few time steps. For the field data, hydraulic parameters are successfully estimated from water content measurements made with spatial time domain reflectometry and ERT, and the development of their posterior distributions is shown.

Balancing images of potential-field data

Geophysics ◽  
2009 ◽  
Vol 74 (3) ◽  
pp. L17-L20 ◽  
Author(s):  
G. R. Cooper
Keyword(s):  
Potential Field ◽  
Field Data ◽  
Large Range ◽  
Signal Amplitude ◽  
Analytic Signal ◽  
Aeromagnetic Data ◽  
Hilbert Transforms ◽  
Potential Field Data ◽  
Total Gradient ◽  
Data Source

Horizontal and vertical gradients, and filters based on them (such as the analytic signal), are used routinely to enhance detail in aeromagnetic data. However, when the data contain anomalies with a large range of amplitudes, the filtered data also will contain large and small amplitude responses, making the latter hard to see. This study suggests balancing the analytic signal amplitude (sometimes called the total gradient) by the use of its orthogonal Hilbert transforms, and shows that the balanced profile curvature can be an effective method of enhancing potential-field data. Source code is available from the author on request.

A new method for absolute underground positioning based on transient electromagnetics

2019 ◽  
Vol 221 (1) ◽  
pp. 87-96
Author(s):  
S Malecki ◽  
R-U Börner ◽  
K Spitzer
Keyword(s):  
Field Data ◽  
Synthetic Data ◽  
Trust Region ◽  
Trust Region Algorithm ◽  
Location Data ◽  
The Earth ◽  
Time Regime ◽  
Em Method ◽  
Em Field ◽  
Confidence Ellipses

SUMMARY We present a procedure for localizing underground positions using a time-domain inductive electromagnetic (EM) method. The position to be localized is associated with an EM receiver placed inside the Earth. An EM field is generated by one or more transmitters located at known positions at the Earth’s surface. We then invert the EM field data for the receiver positions using a trust-region algorithm. For any given time regime and source–receiver geometry, the propagation of the electromagnetic fields is determined by the electrical conductivity distribution within the Earth. We show that it is sufficient to use a simple 1-D model to recover the receiver positions with reasonable accuracy. Generally, we demonstrate the robustness of the presented approach. Using confidence ellipses and confidence intervals we assess the accuracy of the recovered location data. The proposed method has been extensively tested against synthetic data obtained by numerical experiments. Furthermore, we have successfully carried out a location recovery using field data. The field data were recorded within a borehole in Alberta (Canada) at 101.4 m depth. The recovered location of the borehole receiver differs from the actual location by 0.70 m in the horizontal plane and by 0.82 m in depth.

Signal leakage in f-x deconvolution algorithms

Geophysics ◽  
2017 ◽  
Vol 82 (5) ◽  
pp. W31-W45 ◽  
Author(s):  
Necati Gülünay
Keyword(s):  
Field Data ◽  
New Technologies ◽  
Filter Design ◽  
Synthetic Data ◽  
Data Sets ◽  
Amplitude Variation ◽  
Amplitude Variation With Offset ◽  
Backward Design ◽  
Use Of Data ◽  
Domain Prediction

The old technology [Formula: see text]-[Formula: see text] deconvolution stands for [Formula: see text]-[Formula: see text] domain prediction filtering. Early versions of it are known to create signal leakage during their application. There have been recent papers in geophysical publications comparing [Formula: see text]-[Formula: see text] deconvolution results with the new technologies being proposed. These comparisons will be most effective if the best existing [Formula: see text]-[Formula: see text] deconvolution algorithms are used. This paper describes common [Formula: see text]-[Formula: see text] deconvolution algorithms and studies signal leakage occurring during their application on simple models, which will hopefully provide a benchmark for the readers in choosing [Formula: see text]-[Formula: see text] algorithms for comparison. The [Formula: see text]-[Formula: see text] deconvolution algorithms can be classified by their use of data which lead to transient or transient-free matrices and hence windowed or nonwindowed autocorrelations, respectively. They can also be classified by the direction they are predicting: forward design and apply; forward design and apply followed by backward design and apply; forward design and apply followed by application of a conjugated forward filter in the backward direction; and simultaneously forward and backward design and apply, which is known as noncausal filter design. All of the algorithm types mentioned above are tested, and the results of their analysis are provided in this paper on noise free and noisy synthetic data sets: a single dipping event, a single dipping event with a simple amplitude variation with offset, and three dipping events. Finally, the results of applying the selected algorithms on field data are provided.

Image Interpolation Algorithm Based on Edge Features

2011 ◽  
Vol 50-51 ◽  
pp. 564-567
Author(s):  
Yun Feng Yang ◽  
Xiao Guang Wei ◽  
Zhi Xun Su
Keyword(s):  
Interpolation Method ◽  
Spline Interpolation ◽  
Weighted Average ◽  
Image Interpolation ◽  
Interpolation Process ◽  
Edge Information ◽  
B Spline ◽  
Interpolation Methods ◽  
Distance Weighted ◽  
Edge Features

Image interpolation is used widely in the computer vision. Holding edge information is main problem in the image interpolation. By using bilinear and bicubic B-spline interpolation methods, a novel image interpolation approach was proposed in this paper. Firstly, inverse distance weighted average method was used to reduce image’s noise. Secondly, edge detection operator was used to extract image's edges information. It can help us to select different interpolation methods in the image interpolation process. Finally, we selected bilinear interpolation approach at non-edge regions, and bicubic B-spline interpolation method was used near edges regions. Further more, control vertexes were computed from pixels with calculation formula which has been simplified in the B-spline interpolation process. Experiments showed the interpolated image by the proposed method had good vision results for it could hold image's edge information effectively.

The IDQ curve: A tool for evaluating the direction of remanent magnetization from magnetic anomalies

Geophysics ◽  
2020 ◽  
Vol 85 (5) ◽  
pp. J85-J98
Author(s):  
Shuang Liu ◽  
Xiangyun Hu ◽  
Dalian Zhang ◽  
Bangshun Wei ◽  
Meixia Geng ◽  
...  
Keyword(s):  
Remanent Magnetization ◽  
Field Data ◽  
Eastern China ◽  
Synthetic Data ◽  
Magnetic Anomalies ◽  
Natural Remanent Magnetization ◽  
Magma Intrusion ◽  
Magnetization Direction ◽  
Ore Bodies ◽  
Using Data

Natural remanent magnetization acts as a record of the previous orientations of the earth’s magnetic field, and it is an important feature when studying geologic phenomena. The so-called IDQ curve is used to describe the relationship between the inclination ( I) and declination ( D) of remanent magnetization and the Köenigsberger ratio ( Q). Here, we construct the IDQ curve using data on ground and airborne magnetic anomalies. The curve is devised using modified approaches for estimating the total magnetization direction, e.g., identifying the maximal position of minimal reduced-to-the-pole fields or identifying correlations between total and vertical reduced-to-the-pole field gradients. The method is tested using synthetic data, and the results indicate that the IDQ curve can provide valuable information on the remanent magnetization direction based on available data on the Köenigsberger ratio. Then, the method is used to interpret field data from the Yeshan region in eastern China, where ground anomalies have been produced by igneous rocks, including diorite and basalt, which occur along with magnetite and hematite ore bodies. The IDQ curves for 24 subanomalies are constructed, and these curves indicate two main distribution clusters of remanent magnetization directions corresponding to different structural units of magma intrusion and help identify the lithologies of the magnetic sources in areas covered by Quaternary sediments. The estimated remanent magnetization directions for Cenozoic basalt are consistent with measurements made in paleomagnetism studies. The synthetic and field data indicate that the IDQ curve can be used to efficiently estimate the remanent magnetization direction from a magnetic anomaly, which could help with our understanding of geologic processes in an area.

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