Direct reconstruction of velocity and density profiles from scattered field data

A direct Born inversion algorithm is presented which separates the effects of stratified medium velocity and density gradients, thus facilitating the simultaneous reconstruction of the velocity and density profiles from scattered field data. A significant but not unexpected conclusion is that velocity and density variations cannot be separated and resolved from data acquired by a single source‐receiver configuration. Measurements at a minimum of two offset angles are required.

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

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.644-650.2670 ◽

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.

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Inversion of helicopter electromagnetic data to a magnetic conductive layered earth

Geophysics ◽

10.1190/1.1598113 ◽

2003 ◽

Vol 68 (4) ◽

pp. 1211-1223 ◽

Cited By ~ 50

Author(s):

Haoping Huang ◽

Douglas C. Fraser

Keyword(s):

Magnetic Permeability ◽

Field Data ◽

Model Parameters ◽

Relative Importance ◽

Magnetic Polarization ◽

Inversion Algorithm ◽

Layered Earth ◽

Electromagnetic Data ◽

Airborne Electromagnetic ◽

True Values

Inversion of airborne electromagnetic (EM) data for a layered earth has been commonly performed under the assumption that the magnetic permeability of the layers is the same as that of free space. The resistivity inverted from helicopter EM data in this way is not reliable in highly magnetic areas because magnetic polarization currents occur in addition to conduction currents, causing the inverted resistivity to be erroneously high. A new algorithm for inverting for the resistivity, magnetic permeability, and thickness of a layered model has been developed for a magnetic conductive layered earth. It is based on traditional inversion methodologies for solving nonlinear inverse problems and minimizes an objective function subject to fitting the data in a least‐squares sense. Studies using synthetic helicopter EM data indicate that the inversion technique is reasonably dependable and provides fast convergence. When six synthetic in‐phase and quadrature data from three frequencies are used, the model parameters for two‐ and three‐layer models are estimated to within a few percent of their true values after several iterations. The analysis of partial derivatives with respect to the model parameters contributes to a better understanding of the relative importance of the model parameters and the reliability of their determination. The inversion algorithm is tested on field data obtained with a Dighem helicopter EM system at Mt. Milligan, British Columbia, Canada. The output magnetic susceptibility‐depth section compares favorably with that of Zhang and Oldenburg who inverted for the susceptibility on the assumption that the resistivity distribution was known.

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Locally Perturbed Inaccessible Rough Surface Profile Reconstruction via Phaseless Scattered Field Data

IEEE Transactions on Geoscience and Remote Sensing ◽

10.1109/tgrs.2021.3105257 ◽

2021 ◽

pp. 1-8

Author(s):

Ahmet Sefer

Keyword(s):

Rough Surface ◽

Scattered Field ◽

Field Data ◽

Surface Profile ◽

Profile Reconstruction

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Bayesian Maximum Entropy Image Reconstruction from the Scattered Field Data

Maximum Entropy and Bayesian Methods ◽

10.1007/978-94-017-2217-9_32 ◽

1993 ◽

pp. 265-272

Author(s):

Maï Khuong Nguyen ◽

Ali Mohammad-Djafari

Keyword(s):

Image Reconstruction ◽

Maximum Entropy ◽

Scattered Field ◽

Field Data ◽

Bayesian Maximum Entropy

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Determination of the Behavior of Moving Human Body from the Scattered Field Data by using FDTD Method

2006 IEEE Antennas and Propagation Society International Symposium ◽

10.1109/aps.2006.1711444 ◽

2006 ◽

Author(s):

T. Sengor ◽

E. Ermisoglu

Keyword(s):

Human Body ◽

Scattered Field ◽

Field Data ◽

Fdtd Method

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Nonlinear waveform inversion of plane‐wave seismograms in stratified elastic media

Geophysics ◽

10.1190/1.1443083 ◽

1991 ◽

Vol 56 (5) ◽

pp. 664-674 ◽

Cited By ~ 56

Author(s):

F. Kormendi ◽

M. Dietrich

Keyword(s):

Plane Wave ◽

Least Squares ◽

Wave Velocity ◽

Generalized Least Squares ◽

P Wave ◽

Gradient Algorithm ◽

Stratified Medium ◽

Inversion Method ◽

Inversion Algorithm ◽

Frequency Wave

We present a method for determining the elastic parameters of a horizontally stratified medium from its plane‐wave reflectivity. The nonlinear inverse problem is iteratively solved by using a generalized least‐squares formalism. The proposed method uses the (relatively) fast convergence properties of the conjugate gradient algorithm and achieves computational efficiency through analytical solutions for calculating the reference and perturbational wavefields. The solution method is implemented in the frequency‐wave slowness domain and can be readily adapted to various source‐receiver configurations. The behavior of the algorithm conforms to the predictions of generalized least‐squares inverse theory: the inversion scheme yields satisfactory results as long as the correct velocity trends are introduced in the starting model. In practice, the inversion algorithm should be applied first in the precritical region because of the strong nonlinear behavior of postcritical data with respect to velocity perturbations. The suggested inversion strategy consists of first inverting for the density and P‐wave velocity (or P‐wave impedance) by considering plane waves in the low slowness region (near‐normal angles of incidence), then in optimizing for the S‐wave velocity by progressively including contributions from the high slowness region (steep angles of incidence). Numerical experiments performed with noise‐free synthetic data prove that the proposed inversion method satisfactorialy reconstructs the elastic properties of a stratified medium from a limited set of plane‐wave components, at a reasonable computing cost.

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