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Communication Dans Un Congrès Année : 2018

Automatic Fault Detection for 2D Seismic Data Based on the Seismic Coherence of Mutative Scale Analysis Window

Wenli Zheng
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  • PersonId : 1046670
Jinwen Ma
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  • PersonId : 1046618

Résumé

Fault detection is a very challenging problem on seismic interpretation. In fact, the process of fault detection contains seismic attribute extraction, seismic attribute enhancement and fault line detection. It is clear that the extracted seismic attributes are key to the fault detection process. Traditionally, as an important seismic attribute, the seismic coherence is generally employed in the fault detection process, but the size of the analysis window often effects the value of the seismic coherence, and there is a trade-off between the vertical resolution and the lateral resolution. In order to overcome this problem, we propose a new kind of seismic coherence with a mutative scale analysis window, and utilize it to locate the fault lines. It is demonstrated by the experimental results that our proposed seismic coherence is more suitable for the fault line detection in comparison with the traditional seismic coherence.
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hal-02118843 , version 1 (03-05-2019)

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Wenli Zheng, Jinwen Ma. Automatic Fault Detection for 2D Seismic Data Based on the Seismic Coherence of Mutative Scale Analysis Window. 2nd International Conference on Intelligence Science (ICIS), Nov 2018, Beijing, China. pp.391-400, ⟨10.1007/978-3-030-01313-4_42⟩. ⟨hal-02118843⟩
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