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| Robust multi-scale seismic horizon detection and visualization |
| HUA Gang1,2, TAO Yu-bo1, LIN Hai1 |
1. State Key Laboratory of CAD & CG, Zhejiang University, Hangzhou 310058, China; 2. Electronic and
Information Engineering, Liaoning Technique University, Huludao 125105, China |
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Abstract A method of robust multi-scale seismic horizon detection and visualization was proposed for more complex horizon detection and classification. A seismic volume data enhancement algorithm based on trilateral filter was proposed in order to suppress the noise and enhance the continuity of horizon. Then a flatness-based multi-scale horizon detection method was proposed for the enhanced seismic volume data. The method adaptively adjusted the scale of detection by local flatness and achieved horizon classification. The multi-volume visualization technique was implemented and a method to visualize the processing of horizon detection was proposed in order to observe the detected horizons. A seismic horizon detection and visualization system was developed that integrated the seismic volume data enhancement algorithm, multi-scale horizon detection method and horizon visualization method. Experimental results demonstrated the efficiency of the method.
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Published: 01 October 2011
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鲁棒多尺度地震层位识别与可视化
提出鲁棒多尺度地震层位识别与可视化方法,解决复杂层位识别和分类难题.为了抑制噪声,增强层位连续性,提出基于三边滤波的地震体数据结构增强算法.对于结构增强的地震体数据,提出多尺度层位识别方法,根据层位平坦度在层位识别过程中自动调整识别尺度实现层位自动分类.为了观察所识别的层位,给出多体可视化与层位识别过程可视化方法.集成地震体数据结构增强算法、多尺度层位识别方法和层位可视化方法等新技术为一个地震层位识别与可视化系统.大量实验结果验证了该层位识别方法的有效性.
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