Sunjay Sunjay

Sunjay Sunjay

PhD Student

Banaras Hindu University, India

Mr Sunjay is a Ph.D. student in Geophysics at Banaras Hindu University, Varanasi, India. His current areas of Research are Geophysical Signal Processing, subsurface Imaging, Modeling & Simulation upstream hydrocarbon reservoir& energy resources (geothermal),etc./Energy sector leadership. He has experience in Geophysical Data Acquisition, Processing & Interpretation Petroleum Geoscience Softwares (Integrated Research Geoscientist) and is also the Chief Technology Officer-Hydrocarbon & Energy Sector/Primary Sector (Mines & Geology).


SESSION 24:  Mathematical Morphology 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. Application of multi-scale mathematical morphology which is a branch of mathematical morphology in seismic data processing. It mainly research on the seismic signal resolution improving and amplitude compensation. First, Multi-scale mathematical morphology is used to multi-scale decompose amplitude information of seismic signal, and make an analysis of the morphological characteristics of every scale, and make the choice of multi-scale structural elements. Because of less energy loss and higher resolution of the shallow seismic signal, information of shallow signal is used to simulate information of overall signal, to achieve improving resolution of overall signals. Multiple attenuation is a troublesome problem in many seismic exploration areas. Current multiple suppression technique include two kinds of method: filter-based method and prediction-based method. However, these methods are powerless when the energy of multiples and primaries are mixed. Mathematical morphology method to seismic exploration as a new method to solve this problem. Multiples have similar seismic wavelet with that of primary reflection, and also have distinct seismic event. These seismic events give us a chance to distinguish the multiples and the primary reflections. Morphological filter is based on multiscale decomposition method. It use different structuring element to separate the multiples and the primary reflection clearly, and thus making multiple attenuation as well as saving subtle signal of primary reflection. Seismic images are collected by seismic sensors. Containing the geological information of geological structures such as strata and crater, these images are of high significance. Image Enhancing  strata  and  crater of seismic images by  Using a highly-sensitive geophone, all  details  underground  are  displayed  in  the  3D  seismic  images. Due to the fact that seismic data have huge information, multiscale morphology methods such as opening and closing operation are exploited here. Mathematical morphology is an effective method to enhance images.  There  are  four  basic  operations  in  mathematical  morphology,  erosion,  dilation,  opening  and  closing.  By combining these four basic operations, geoscientists complete complicated tasks.  Image analysis techniques such as a tophat transformation (mathematical morphology) is applied for feature extraction, morphological approach to segmentation: the watershed transformation an efficient tool for image segmentation.