Derivative analysis of hyperspectral oceanographic data

22 pages, 12 figuresThis study was supported by the projects HIDRA (PIE06-301102) and ANERIS (PIF08-015) funded by the Spanish Ministry of Science and InnovationPeer Reviewe

Constraining potential field interpretation by geological data: examples from geophysical mapping, inverse and forward modelling

In this thesis three different strategies in potential field data interpretation were implemented and studied. The strategies are related to map transformation, inversion and forward problem. The thesis aims at obtaining geophysical outputs with geological-like features. These kinds of outputs are a significant key to make it easier the geological interpretation of the geophysical data modelling. In particular, the outputs obtained by the different strategies will tend to highlight different units with distinct boundaries and represented by fairly constant field or physical property values. A map transformation technique (terracing) is first proposed. It is based on the use of a cluster analysis technique applied to a gravity or pole-reduced magnetic map. The centre values of the clusters and the cluster number are selected by a statistical analysis of the data map. The use of cluster technique breaks the continuous function (potential field map) onto different areas characterized by piecewise constant values (terraces). The homogeneity within each area is preserved and this kind of feature allow an easy computation of an apparent physical property horizontal distribution map, directly comparable with a geological map. Tests on synthetic and real data are shown. The inversion is treated by applying a strategy made up by three steps. The first and the last steps are inversions with different constraints and associated weights, the second one is conducted by clustering the output of the first smooth inversion. The strategy allows obtaining, in the final step, a volume where the retrieved physical property is classified (by clustering technique) in different volumes of relatively constant values, easily relatable to different geological units. The number of the units, as well as the physical property values associated to each unit, it has to be fixed a priori according to the geological knowledge of the area. Tests on synthetic and real data show that the final obtained models are valid in both geophysical (honoring the data) and geological (understandable relationships among clearly-defined geological units) points of view. A forward problem solver procedure, based on iterative stochastic process is finally proposed. The solution is represented by surfaces that bound different layers having different physical properties. The anomaly field produced by the surfaces is computed by an algorithm working in a Fourier domain. According to the Markov chain simulation, at each iteration several surfaces are created and the best one is selected to be a starting model in the next iteration. The best model selection is performed according to the value of a goodness coefficient. A synthetic case is shown, and the final model obtained shows a possible shape of different bodies, with homogeneous physical property distribution, able to produce a field that adequately match an observed anomaly field

ATTRIBUTE ASSISTED SEISMIC FACIES, FAULTS, KARST, AND ANISOTROPY ANALYSIS

Seismic attributes provide quantitative measures of key statistical, geometric, or kinematic components of the 3D seismic volume. These measures can thus be subsequently used in 3D visualization, interactive crossplotting, or computer-assisted facies analysis. In this dissertation, I evaluate the attribute expression of seismic facies including karst collapse features, mass transport complexes, turbidites, and salt using 3D visualization and 3D pattern recognition. One of the more common and more important seismic facies is salt. Salt segmentation is critical for accelerating velocity modeling, which in turn is necessary for seismic depth migration. In general, geophysicists need to pick the high velocity salt interface manually. In the first chapter of the dissertation, I present a semi-supervised multiattribute clustering method, and apply it not only to salt segmentation, but also to mass transport complex, shale, and sand segmentation in the Gulf of Mexico. I develop a 3D Kuwahara filtering algorithm, and smooth the interior attribute response and sharpen the attribute contrast between one face with neighboring facies. Then, I manually paint target facies to evaluate the ability of candidate attributes to discriminate each seismic facies from the other. Crosscorrelating their histogram, candidate attributes with low correlation coefficients provide good facies discrimination. Kuwahara filtering significantly increases this discrimination. Kuwahara filtered attributes corresponding to interpreter-defined facies are then projected against a Generative Topological Mapping (GTM) manifold, resulting in a suite of n probability density functions (PDFs). The Bhattacharyya distance between the PDF of each unlabeled voxel to each facies PDF results in a probability volume of each interpreter-defined facies. In the second chapter, I introduce a 3D fault enhancement and skeletonization workflow. For large datasets, interpreter hand-picking of faults can be very time-consuming. This process can be accelerated by generating high resolution edge detecting attributes. Coherence is an algorithm that measures both stratigraphic and structural discontinuities. Application of a directional Laplacian of a Gaussian (LoG) filter to coherence volumes provides more continuous and sharper faults. To further increase fault resolution and preserve stratigraphic discontinuities, I skeletonize the filtered coherence volumes perpendicular to the discontinuities with the goal of providing subvoxel resolution. “Fault” points doesn’t fall on the geometric grid suggesting the distribution of the value onto eight neighboring grid points. I demonstrate this fault enhancement and skeletonization workflow through application to two datasets from New Zealand and the Gulf of Mexico. With the advent of shale resource plays, wide azimuth acquisition has become quite common. Migrating seismic gathers into different azimuthal bins provides a means to estimate horizontal stress and natural fractures. Different azimuths preferentially illustrate faults perpendicular to them. However, coherence applied to the lower fold azimuthally limited seismic volumes is contaminated by noise. In the third chapter, I improve the energy ratio coherence algorithm and extend it to map more subtle discontinuities, which can only be seen in different azimuthally limited seismic volumes. The main modification compared to the original energy ratio coherence algorithm is that I add the weighted covariance matrices of each azimuthal sectors together to form a single covariance matrix, thereby improving the signal-to-noise ratio. I apply this multi-azimuth coherence algorithm to two datasets from the Fort Worth Basin. In the fourth chapter, I summarize attribute-assisted interpretation in the Barnett Shale and the Ellenburger Group. Karst, faults, and joints are known to form geologic hazards for most Barnett Shale wells in the Fort Worth Basin. In the best cases, these drilling-related geohazards form conductive features that draw off expensive hydraulic fracturing fluid from the targeted shale formation. In the worst cases, the completed wells are hydraulically connected to the underlying Ellenburger aquifer and produce large amounts of water that must be disposed. Karst collapse generates a distinct morphologic pattern on 3D seismic data. I show that multiple attributes delineate different components of the same geologic features, thereby confirming my interpretation

Identification and tracking of marine objects for collision risk estimation.

With the advent of modem high-speed passenger ferries and the general increase in maritime traffic, both commercial and recreational, marine safety is becoming an increasingly important issue. From lightweight catamarans and fishing trawlers to container ships and cruise liners one question remains the same. Is anything in the way? This question is addressed in this thesis. Through the use of image processing techniques applied to video sequences of maritime scenes the images are segmented into two regions, sea and object. This is achieved using statistical measures taken from the histogram data of the images. Each segmented object has a feature vector built containing information including its size and previous centroid positions. The feature vectors are used to track the identified objects across many frames. With information recorded about an object's previous motion its future motion is predicted using a least squares method. Finally a high-level rule-based algorithm is applied in order to estimate the collision risk posed by each object present in the image. The result is an image with the objects identified by the placing of a white box around them. The predicted motion is shown and the estimated collision risk posed by that object is displayed. The algorithms developed in this work have been evaluated using two previously unseen maritime image sequences. These show that the algorithms developed here can be used to estimate the collision risk posed by maritime objects