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The Statistical Eigenvector Analysis Technique (SEAT) for Image Log-Based Directional Measurements


Directional measurements, or Previous HitdipNext Hit data, gathered from image logs (i.e. the Previous HitdipNext Hit/azimuth of planar features) are widely used in the oil and gas industry to interpret a variety of subsurface features relating to both structural and sedimentary geology. Gradual and/or abrupt variations in Previous HitdipNext Hit data over Previous HitdepthNext Hit typically indicate major structural features (e.g. faults, folds, etc.) or sedimentological breaks (i.e. unconformity). The orientation and geometry of geologic structures can be precisely calculated Previous HitusingNext Hit stereogram plots and the statistical eigenvector analysis technique. Although this method is widely utilized by field and academic geologists, it is not typically applied in the oil and gas industry to subsurface Previous HitdipNext Hit data. Poles to planes are plotted onto a stereographic projection over a given Previous HitdepthNext Hit interval and are interactively analyzed Previous HitusingNext Hit statistical distribution Previous HitfunctionsNext Hit on the unit sphere. The maximum of the distribution function is achieved when a quadratic form is maximized. The quadratic form acquires its maximum in the eigenvector related to the largest eigenvalue of the corresponding 3×3 symmetry matrix. The pole associated to the eigenvector with the smallest eigenvalue is the axis of the best-fit great circle for a spread of poles. A series of interactively calculated axes over a given Previous HitdepthNext Hit interval can accurately inform the geometry and orientation of a variety of subsurface features (e.g. upright and plunging folds, coaxial fault drag deformation, fault block rotation, etc.). The application of the statistical eigenvector analysis technique to subsurface Previous HitdipTop data will improve the quality of subsurface structural and sedimentological interpretations.