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Field Data Sets (field + data_set)
Selected AbstractsFast velocity analysis by wave path migrationGEOPHYSICAL PROSPECTING, Issue 2 2010Yike Liu ABSTRACT Iterative migration velocity analysis is computationally expensive, where most of the computation time is used for generating prestack depth images. By using a reduced form of Kirchhoff migration, denoted as wave path migration, we can significantly speed up the depth imaging process and reduce the entire velocity analysis expense accordingly. Our results with 2D synthetic and field data show that wave path migration velocity analysis can efficiently improve the velocity model and the wave path migration velocity analysis updated velocity correlates well with that from the Kirchhoff migration velocity analysis. The central processing unit comparison shows that, for a 2D synthetic and field data set, wave path migration velocity analysis is six times faster than Kirchhoff migration velocity analysis. This efficiency should be even greater for 3D data. [source] Simple preconditioners for the conjugate gradient method: experience with test day modelsJOURNAL OF ANIMAL BREEDING AND GENETICS, Issue 3 2002I. STRANDÉN Preconditioned conjugate gradient method can be used to solve large mixed model equations quickly. Convergence of the method depends on the quality of the preconditioner. Here, the effect of simple preconditioners on the number of iterations until convergence was studied by solving breeding values for several test day models. The test day records were from a field data set, and several simulated data sets with low and high correlations among regression coefficients. The preconditioner matrices had diagonal or block diagonal parts. Transformation of the mixed model equations by diagonalization of the genetic covariance matrix was studied as well. Preconditioner having the whole block of the fixed effects was found to be advantageous. A block diagonal preconditioner for the animal effects reduced the number of iterations the higher the correlations among animal effects, but increased memory usage of the preconditioner. Diagonalization of the animal genetic covariance matrix often reduced the number of iterations considerably without increased memory usage. Einfache Preconditioners für die `Conjugate Gradient Method': Erfahrungen mit Testtagsmodellen Die `Preconditioned Conjugate Gradient Methode' kann benutzt werden um große `Mixed Model' Gleichungssysteme schnell zu lösen. In diesem Beitrag wurde der Einfluss von einfachen Preconditioners auf die Anzahl an Iterationen bis zur Konvergenz bei der Schätzung von Zuchtwerten bei verschiedenen Testtagsmodellen untersucht. Die Testtagsdaten stammen aus einem Felddatensatz und mehreren simulierten Datensätzen mit unterschiedlichen Korrelationen zwischen den Regressionskoeffizienten. Die Preconditioner Matrix bestand aus Diagonalen oder Blockdiagonalen Teilen. Eine Transformation der Mixed Modell Gleichungen durch Diagonalisierung der genetischen Kovarianzmatrix wurde ebenfalls untersucht. Preconditioners mit dem Block der fixen Effekte zeigten sich immer überlegen. Ein Blockdiagonaler Preconditioner für den Tiereffekt reduzierte die Anzahl an Iterationen mit höher werden Korrelationen zwischen den Tiereffekten, aber erhöhte den Speicherbedarf. Eine Diagonalisierung der genetischen Kovarianzmatrix reduzierte sehr oft die Anzahl an Iterationen erheblich ohne den Speicherbedarf zu erhöhen. [source] Ecological boundary detection using Carlin,Chib Bayesian model selectionDIVERSITY AND DISTRIBUTIONS, Issue 6 2005Ralph Mac Nally ABSTRACT Sharp ecological transitions in space (ecotones, edges, boundaries) often are where ecologically important events occur, such as elevated or reduced biodiversity or altered ecological functions (e.g. changes in productivity, pollination rates or parasitism loads, nesting success). While human observers often identify these transitions by using intuitive or gestalt assignments (e.g. the boundary between a remnant woodland patch and the surrounding farm paddock seems obvious), it is clearly desirable to make statistical assessments based on measurements. These assessments often are straightforward to make if the data are univariate, but identifying boundaries or transitions using compositional or multivariate data sets is more difficult. There is a need for an intermediate step in which pairwise similarities between points or temporal samples are computed. Here, I describe an approach that treats points along a transect as alternative hypotheses (models) about the location of the boundary. Carlin and Chib (1995) introduced a Bayesian technique for comparing non-hierarchical models, which I adapted to compute the probabilities of each boundary location (i.e. a model) relative to the ensemble of models constituting the set of possible points of the boundary along the transect. Several artificial data sets and two field data sets (on vegetation and soils and on cave-dwelling invertebrates and microclimates) are used to illustrate the approach. The method can be extended to cases in with several boundaries along a gradient, such as where there is an ecotone of non-zero thickness. [source] The influence of fluid-sensitive dispersion and attenuation on AVO analysisGEOPHYSICAL JOURNAL INTERNATIONAL, Issue 1 2006Mark Chapman SUMMARY Analysis of seismic data suggests that hydrocarbon deposits are often associated with higher than usual values of attenuation, but this is generally ignored during amplitude-versus-offset (AVO) analysis. The effect can be modelled with equivalent medium theory based on the squirt flow concept, but the excess attenuation is associated with strong velocity dispersion. Consequently, when we study reflections from the interface between such an equivalent medium and an elastic overburden we find that the reflection coefficient varies with frequency. The impact of this variation depends on the AVO behaviour at the interface; class I reflections tend to be shifted to higher frequency while class III reflections have their lower frequencies amplified. We calculate synthetic seismograms for typical models using the reflectivity method for materials with frequency dependent velocities and attenuations, and find that these effects are predicted to be detectable on stacked data. Two field data sets show frequency anomalies similar to those predicted by the analysis, and we suggest that our modelling provides a plausible explanation of the observations. [source] A comparison of automatic techniques for estimating the regularization parameter in non-linear inverse problemsGEOPHYSICAL JOURNAL INTERNATIONAL, Issue 3 2004Colin G. Farquharson SUMMARY Two automatic ways of estimating the regularization parameter in underdetermined, minimum-structure-type solutions to non-linear inverse problems are compared: the generalized cross-validation and L-curve criteria. Both criteria provide a means of estimating the regularization parameter when only the relative sizes of the measurement uncertainties in a set of observations are known. The criteria, which are established components of linear inverse theory, are applied to the linearized inverse problem at each iteration in a typical iterative, linearized solution to the non-linear problem. The particular inverse problem considered here is the simultaneous inversion of electromagnetic loop,loop data for 1-D models of both electrical conductivity and magnetic susceptibility. The performance of each criteria is illustrated with inversions of a variety of synthetic and field data sets. In the great majority of examples tested, both criteria successfully determined suitable values of the regularization parameter, and hence credible models of the subsurface. [source] Support vector machines-based modelling of seismic liquefaction potentialINTERNATIONAL JOURNAL FOR NUMERICAL AND ANALYTICAL METHODS IN GEOMECHANICS, Issue 10 2006Mahesh Pal Abstract This paper investigates the potential of support vector machines (SVM)-based classification approach to assess the liquefaction potential from actual standard penetration test (SPT) and cone penetration test (CPT) field data. SVMs are based on statistical learning theory and found to work well in comparison to neural networks in several other applications. Both CPT and SPT field data sets is used with SVMs for predicting the occurrence and non-occurrence of liquefaction based on different input parameter combination. With SPT and CPT test data sets, highest accuracy of 96 and 97%, respectively, was achieved with SVMs. This suggests that SVMs can effectively be used to model the complex relationship between different soil parameter and the liquefaction potential. Several other combinations of input variable were used to assess the influence of different input parameters on liquefaction potential. Proposed approach suggest that neither normalized cone resistance value with CPT data nor the calculation of standardized SPT value is required with SPT data. Further, SVMs required few user-defined parameters and provide better performance in comparison to neural network approach. Copyright © 2006 John Wiley & Sons, Ltd. [source] Enhancing a regional vegetation map with predictive models of dominant plant species in chaparralAPPLIED VEGETATION SCIENCE, Issue 1 2002Janet Franklin Abstract. Data from more than 900 vegetation plots surveyed in the evergreen shrublands of southern California were used to develop predictions of the distributions of eight dominant shrub species for a 3880 km2 region. The predictions, based on classification tree (CT) models, were validated using independent field data collected during a vegetation survey conducted in the 1930s. Presence and absence were correctly predicted an average of 75% of the time for the eight species. At the same time, these models minimized false positives, so that presence was predicted in the correct proportion of the cases for most species. The areal proportion of the landscape on which the species were predicted to occur was in the same rank order, and of the same magnitude, as their frequency (proportion of plots in which they occurred) within the field data sets. Predictive maps of species presence were overlaid and combined with an existing regional vegetation map. The shrub species ,assemblages' that resulted from this procedure had analogs with vegetation series defined using field data in previous studies. The resulting multiple species map will be used in a landscape simulation model of fire disturbance and succession. [source] | ||||||||||