Development of Forward and Inversion Schemes for Cross-Borehole Ground Penetrating Radar

Tomography is an imaging technique to develop a representation of the internal features of material using a penetrating wave, such as an electromagnetic wave. The calculation method used is an example of an inverse problem, which is a system where the input and the output are known but the internal parameters are not. These parameters can be estimated by understanding the responses of a penetrating wave as it passes through the unknown media. A forward problem is just the opposite; the internal structure and input penetrating wave is known and the output is determined. For both forward and inverse problems, raytracing is needed to define the raypath through the medium and inversion techniques are used to minimize the error for a discretized matrix of material properties. To assess various inversion techniques for use in shallow karst conditions, three synthetic karst geology models, each with increasing complexity, were generated. Each model was analyzed using forward modeling techniques to compare the calculated tomograms from known geometry and material properties. Gaussian Raytracing with LSQR inversion technique performed the best. This technique, Gaussian Raytracing with LSQR, was then applied to an inversion problem; cross-borehole ground penetrating radar data was collected at a karst geology field site and tomograms were produced. The resulting tomography confirmed information detailed in the driller\u27s logs and features between boreholes were identified. This confirmed that cross-borehole ground penetrating radar is an applicable technique for use in geotechnical site characterization activities in karst areas

3D stochastic inversion of gravity data using cokriging and cosimulation

Three-Dimensional gravity modeling -- Forward Modeling -- Geometry of domain -- Symmetry of kernel and less memory -- Geostatistics concept -- Theory and formulation of cokriging -- Inversion by Cokriging -- Inversion by Cokriging using Constraints -- Efficient calculation of the gravity-density covariance matrix and the gravity-gravity covariance matrix -- LU simulation -- Co-simulation bases on the FFT moving averag (FFT-MA) generator -- Application do Dipping Dyke -- Application to Synthetic Data generated by stochastic method -- Study area : Matagami region -- Preparing the gravity data for inversion

Inversion conjointe des données électriques et de radar en forage

RÉSUMÉ Dans le cadre de cette thèse, deux algorithmes d‘inversion conjointe des données électriques et de radar en forage ont été développés. Le premier algorithme combine une approche basée sur l‘échange de l‘information structurale entre deux inversions séparées et une régularisation dans le domaine des ondelettes qui force la solution à avoir une représentation creuse des coefficients en ondelettes. Cette régularisation consiste à appliquer un algorithme de seuillage doux à chaque itération d‘un algorithme de descente. L‘opération de seuillage nécessite le calcul de seuils qui sont déterminés dans notre cas en maximisant un critère de similarité structurale entre les modèles de résistivité et de lenteur. Comme la régularisation dans le domaine des ondelettes permet la reconstruction des discontinuités de contraste fort ainsi que les zones homogène, nous proposons d‘utiliser le détecteur de contours Canny pour extraire l‘information structurale de chaque modèle. Les contours ainsi détectés sont utilisés pour construire des matrices de pondération qui sont appliquées à la matrice de rugosité de chaque inversion séparée. Pour valider cet algorithme trois modèles synthétiques ont été utilisés. Les résultats montrent que celui-ci permet d‘améliorer la résolution spatiale, ainsi qu‘une meilleure estimation des propriétés physiques, en comparaison avec l‘inversion séparée. De plus, il présente l‘avantage d‘être très robuste lorsque le niveau du bruit est élevé. Dans le deuxième algorithme, on propose de combiner une inversion coopérative par zonation et une approche bayésienne hiérarchique. L‘inversion coopérative par zonation consiste à utiliser séquentiellement une approche de classification non-hiérarchique et un algorithme d‘inversion séparée. Dans un processus itératif, l‘algorithme de classification non-hiérarchique est appliqué sur les résultats obtenus par inversion séparée pour générer des modèles composés de plusieurs zones homogènes représentant chacune une certaine lithologie du milieu investigué. Les modèles ainsi construits sont ensuite utilisés comme modèles a priori dans une nouvelle étape d‘inversion séparée. La solution obtenue par une telle approche peut être biaisé vers le modèle a priori qui est fonction du nombre de classes dans l‘algorithme de classification non-hiérarchique.----------ABSTRACT We present two joint structural inversion algorithm for cross-hole electrical resistance tomography (ERT) and cross-hole radar travel time tomography (RTT). The first algorithm proceeds by combining the exchange of structural information and a regularization method that consists of imposing an L1-norm penalty in the wavelet domain. The minimization of the L1-norm penalty is carried out using an iterative soft-thresholding algorithm. The thresholds are estimated by maximizing a structural similarity criterion, which is a function of the two (ERT and RTT) inverted models. Besides, the regularization in the wavelet basis allows for the possibility of sharp discontinuities superimposed on a smoothly varying background. Hence the structural information is extracted from each model using a Canny edge detector. The detected edge serves to construct a weighting matrix that is used to alter the smoothness matrix constraint. To validate our methodology and its implementation, three synthetic models were created. Experiments demonstrate that the proposed approach improves the spatial resolution and quantitative estimation of physical parameters. In addition, it seems to be more robust in high noise level condition. In the second algorithm, we propose to combine a zonal cooperative inversion (ZCI) scheme with a hierarchical Bayesian approach, in order to invert cooperatively cross-hole ERT data and cross-hole radar travel time data. The basic idea of ZCI is to use cooperatively cluster analysis and separate inversion algorithm. For each iteration cluster analysis of separate inversion results is used to construct models that contain the parameter characteristics of dominant subsurface structures. These constructed models are then used as starting model in the next iteration of separate inversion. The resulting models are then biased to starting models which are a function of the number of clusters. To overcome this problem, we formulate the inverse problem within a hierarchical Bayesian framework where the hierarchical prior distribution is based on the a priori models constructed from cluster analysis

地中レーダによる地下環境の定量的性状評価

Tohoku University佐藤源之課

Three dimensional quantitative textural analysis of nickel sulphide ore using X-ray computed tomography and grey level co-occurrence matrices on drill core

Alongside the global trend to mine and process lower grade and more mineralogically complex ores, there has been an increased awareness of the prevalence of ore heterogeneity. Ore texture - the interrelationship of minerals comprising a rock, has been identified as one of the primary geometallurgical indicators of ore variability. It is well known that a relationship exists between ore texture and the resultant metallurgical performance (ore hardness, throughput, liberation, grade, recovery). Consequently, there exists a need to rapidly, routinely, cost effectively, and reliably quantify ore texture and its variability prior to mining. This information can thereafter be incorporated into the geometallurgical block model and used for decision making informing mine planning, plant operation and optimisation, forecasting, and mine closure. The ability to rapidly, routinely, cost effectively and reliably quantify ore texture remains an ongoing challenge. In this study, the use of 3D X-ray computed tomography (XCT) is proposed as an innovative solution to non-destructively image the internal structure of drill core. Thereafter, an established, discipline independent two dimensional (2D) image analysis technique known as grey level co-occurrence matrices (GLCM) is specially adapted into three dimensions (3D) to quantify ore texture using XCT grey level volumes of drill core

Wood Science for Conservation of Cultural Heritage – Braga 2008

COST Action IE0601 "Wood Science for Conservation of Cultural Heritage" (www.woodculther.org) aims to improve the conservation of European wooden cultural heritage objects, by fostering research and interaction between researchers in various fields of wood science, conservators of wooden artworks, scientists from related fields. These proceedings contain the papers presented in the 2nd International Conference held in Braga (Portugal) 5-7/11/2008, dealing with themes such as material properties, biological degradation, characterization and measurement techniques, conservation, structures. This conference was patronized by the European Society for Wood Mechanics (ESWM), an informal body promoting wood mechanics in Europe by regular organisation of meetings through running COST Actions