Seismic Signal Processing and Image Analysis

Mathematical morphology has its applications in both optical and acoustic image analysis and is useful in image cleaning, image enhancement, feature selection and extraction, quantitative analysis, etc. Morphology has the capabilities of performing quantitative analysis of images using morphological operation. Partial differential equation(PDE) is employed for Anisotropic Diffusion filtering techniques where the filtering is guided by the local structures in the image. seismic processing image for an example. Another example is fingerprint enhancement where smooth the image along the direction of the texture in the image(adaptive filtering for image analysis), while the edges are sharpened in the other direction, giving a high contrast image of the fingerprint. Image analysis follows three steps: image processing (image-> image), Analysis(imageattributes), Understanding and interpretation(attributes->attributes).3D seismic image filtering, the method of 3D anisotropic diffusion filtering is applied and the relationship between the eigenvalues of structure tensor and the stratum structure has been analyzed in detail. By using structure tensor, extracted the local structure of 3D seismic image, and using the improved coherent enhancement diffusion method, designed eigenvalues of diffusion tensor ,and constructed the diffusion tensor to control the diffusion rate of three main orientation. Extracting fault, unconformity, and horizon surfaces from a seismic image is useful for interpretation of geologic structures and stratigraphic features. Although interpretation of these surfaces has been automated to some extent by others, significant manual effort is still required for extracting each type of these geologic surfaces. automatically extract all the fault, unconformity, and horizon surfaces from a 3D seismic image. To a large degree, just involve image processing or array processing which is achieved by efficiently solving partial differential equations.Geophysical interpretation is closely related to geologic interpretation, i.e., the task of inferring from a description of a region the sequence of events which formed that region. The description of the region can be a diagram representing a cross-section of the region, which comes e.g. from the geophysical interpretation of a seismic cross-section, together with an identification of the rock types. Geologic interpretation is not static. It attempts to reconstruct the sequence of events which occurred, i.e., it converts the signal data from a spatial domain to the temporal domain of geologic processes.Seismic interpretation is a difficult task, because the seismic data are usually fuzzy and noisy. Furthermore, it is heavily based on the available geological and geophysical knowledge of the region and on the expertise of the interpreter. The most common approaches are the following:-Seismic pattern recognition;Seismic image processing; Graphics-visualization(GPU graphic processing unit-sobel filter/gradient filter);.Geophysical and geologic expert systems-cognitive geoscience.