In quest of the grid

Geophysics ◽  
1999 ◽  
Vol 64 (4) ◽  
pp. 1116-1125 ◽  
Author(s):  
Gualtiero Böhm ◽  
Aldo L. Vesnaver

The possible nonuniqueness and inaccuracy of tomographic inversion solutions may be the result of an inadequate discretization of the model space with respect to the acquisition geometry and the velocity field sought. Void pixels and linearly dependent equations are introduced if the grid shape does not match the spatial distribution of rays, originating the well‐known null space. This is a common drawback when using regular pixels. By definition, the null space does not depend on the picked traveltimes, and so we cannot eliminate it by minimising the traveltime residuals. We show that the inversion quality can be improved by following a trial and error approach, that is, by adapting the pixels’ shape and distribution to the layer interfaces and velocity field. The resolution can be increased or decreased locally to search for an optimal grid, although this introduces a personal bias. On the other hand, we can so decide where, why, and which a priori information is introduced in the sought velocity field, which is hardly feasible by managing other stabilising tools such as damping factors and smoothing filters.

1997 ◽  
Vol 40 (1) ◽  
Author(s):  
G. Böhm ◽  
G. Rossi ◽  
A. Vesnaver

3D reflection tomography allows the macro-model of complex geological structures to be reconstructed. In the usual approach, the spatial distribution of the velocity field is discretized by regular grids. This choice simplifies the development of the related software, but introduces two serious drawbacks: various domains of the model may be poorly covered, and a relevant mismatch between the grid and a complex velocity field may occur. So the tomographic inversion becomes unstable, unreliable and necessarily blurred. In this paper we introduce an algorithm to adapt the grid to the available ray paths and to the velocity field in sequence: so we get irregular grids with a locally variable resolution. We can guide the grid fitting procedure interactively, if we are going to introduce some geological a priori information; otherwise, we define a fully automatic approach, which exploits the Delauny triangles and Voronoi polygons.


Geophysics ◽  
2006 ◽  
Vol 71 (6) ◽  
pp. R101-R111 ◽  
Author(s):  
Thomas Mejer Hansen ◽  
Andre G. Journel ◽  
Albert Tarantola ◽  
Klaus Mosegaard

Inverse problems in geophysics require the introduction of complex a priori information and are solved using computationally expensive Monte Carlo techniques (where large portions of the model space are explored). The geostatistical method allows for fast integration of complex a priori information in the form of covariance functions and training images. We combine geostatistical methods and inverse problem theory to generate realizations of the posterior probability density function of any Gaussian linear inverse problem, honoring a priori information in the form of a covariance function describing the spatial connectivity of the model space parameters. This is achieved using sequential Gaussian simulation, a well-known, noniterative geostatisticalmethod for generating samples of a Gaussian random field with a given covariance function. This work is a contribution to both linear inverse problem theory and geostatistics. Our main result is an efficient method to generate realizations, actual solutions rather than the conventional least-squares-based approach, to any Gaussian linear inverse problem using a noniterative method. The sequential approach to solving linear and weakly nonlinear problems is computationally efficient compared with traditional least-squares-based inversion. The sequential approach also allows one to solve the inverse problem in only a small part of the model space while conditioned to all available data. From a geostatistical point of view, the method can be used to condition realizations of Gaussian random fields to the possibly noisy linear average observations of the model space.


2016 ◽  
Vol 33 (3) ◽  
Author(s):  
Danian Steinkirch de Oliveira ◽  
Milton José Porsani ◽  
Paulo Eduardo Miranda Cunha

ABSTRACT. We developed a strategy for automatic Semblance panels pick, that uses Genetic Algorithm optimization method. In conjunction with restrictions and penalties set from a priori information... RESUMO. Foi desenvolvida uma estratégia de pick automático dos painéis de Semblance , que usa método de otimização Algorítmo Genético. Em conjunto com restrições...


Geophysics ◽  
1997 ◽  
Vol 62 (3) ◽  
pp. 869-883 ◽  
Author(s):  
Peter S. Rowbotham ◽  
R. Gerhard Pratt

Standard least‐squares traveltime inversion techniques tend to produce smoothed estimates of the velocity field. More complete results can be obtained by incorporating into the inversion scheme a priori information about the media to be imaged, derived from well logs, core data, and surface geology. A promising technique for achieving this involves projecting this information onto the null space model singular vectors of the inverse problem and including this projection with the non‐null space contribution in order to produce a solution. The method, demonstrated with both field and synthetic crosshole traveltime data acquired through layered, anisotropic media, successfully produces improved inversion solutions with lower traveltime residuals, layers that are more homogeneous, sharper interfaces, and better correlated anisotropy parameters than solutions obtained with standard techniques.


Aviation ◽  
2004 ◽  
Vol 8 (2) ◽  
pp. 21-24
Author(s):  
Darius Mariūnas ◽  
Vytautas Giniotis

The analysis performed in the paper shows that the effectiveness of discretization methods depends on the accuracy of the evaluation of the parameters of local surface errors and on the characteristics of the regression polynomial describing them. It is evident from the expressions derived that the wavelength of the distribution errors depends on the number of members of the regression polynomial. By increasing the number of members of the regression polynomial, the wavelength of errors of the surface form will be not evaluated. On the other hand, reducing the number of polynomial members, the accuracy of the description of local surface errors will be lost. This is why a priori information is needed about the surface to be measured before choosing the order of the polynomial equation.


Geophysics ◽  
2000 ◽  
Vol 65 (1) ◽  
pp. 102-112 ◽  
Author(s):  
João B. C. Silva ◽  
Walter E. Medeiros ◽  
Valéria C. F. Barbosa

We present a constraint which incorporates in the geophysical inverse problem a priori information about the source convexity. Two kinds of convexity are considered: directional convexity, defined as the attribute of a body being intersected at most at two points by a straight line with a fixed spatial orientation, and global convexity, defined as the attribute of a body being intersected at most at two points by any arbitrarily oriented straight line. The interpretation model consists of several juxtaposed 2-D prisms whose positions, widths, and physical property are established by the interpreter. The depth to the top and the thickness of each prism are the parameters to be determined. The directional convexity is incorporated by minimizing a functional which expresses the number of times that several lines, parallel to a given direction and spaced at regular intervals, intersect the interpretation model. On the other hand, the global convexity is introduced in an algorithmic way by constraining the depths to the top and to the bottom of each prism to be, respectively, smaller or greater than the average of the depths to the top or to the bottom of the adjacent prisms. The use of the presented convexity contraint is demonstrated using synthetic gravity data produced by an isolated source. We found that convexity constraints (either directional along the horizontal axis or global) alone are insufficient to produce strongly stable solutions, although they reduce substantially the solution instability. Despite the “slight” instability, the directional convexity constraint leads to a reasonable delineation of the source shape and produces a better resolution of its base as compared with the inverse method imposing smoothness constraints on the top and bottom surfaces of the anomalous source. The potential use of the convexity constraint is the possibility of combining it with other constraints to produce geologically meaningful solutions. As an example, the global convexity was combined with the minimum moment of inertia of the anomalous masses about a vertical axis passing through its center of mass. This combination allowed introducing a priori information about a diapir shape. This is important because a maximum spread at the diapir middle portion indicates that it ascended like a viscous bubble in an isotropic medium. On the other hand, a spread located at its top indicates that the host medium is mechanically anisotropic, exhibiting horizontal planes of weakness where the mobile material was forced into. So, this combination of constraints alows introducing a priori information about the diapir emplacement. The combination of global convexity and minimum moment of inertia may also be applied to isolated intrusions, as illustrated with the real gravity anomaly produced by the granitic body of Castelsarrasin, in the Aquitaine Basin, France. The estimated source has its top located between 0.45 and 0.57 km from the surface, a base 6.4 km deep, and center of mass at a depth of 3.5 km, which agree reasonably with a priori geological and geophysical information about the body.


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