3D modeling of geological anomalies based on segmentation of multiattribute fusion
Liu Zhi-Ning1, Song Cheng-Yun1, Li Zhi-Yong1, Cai Han-Peng2, Yao Xing-Miao2, and Hu Guang-Min1
1. School of Communication and Information Engineering, University of Electronic and Technology of China, Chengdu 611731, China.
2. School of Resources and Environment, University of Electronic and Technology of China, Chengdu 611731, China.
Abstract 3D modeling of geological bodies based on 3D seismic data is used to define the shape and volume of the bodies, which then can be directly applied to reservoir prediction, reserve estimation, and exploration. However, multiattributes are not effectively used in 3D modeling. To solve this problem, we propose a novel method for building of 3D model of geological anomalies based on the segmentation of multiattribute fusion. First, we divide the seismic attributes into edge- and region-based seismic attributes. Then, the segmentation model incorporating the edge- and region-based models is constructed within the levelset-based framework. Finally, the marching cubes algorithm is adopted to extract the zero level set based on the segmentation results and build the 3D model of the geological anomaly.Combining the edge-and region-based attributes to build the segmentation model, we satisfy the independence requirement and avoid the problem of insufficient data of single seismic attribute in capturing the boundaries of geological anomalies. We apply the proposed method to seismic data from the Sichuan Basin in southwestern China and obtain 3D models of caves and channels. Compared with 3D models obtained based on single seismic attributes, the results are better agreement with reality.
This work was supported by the National Natural Science Foundation of China (No. 41604107) and the Scientific Research Staring Foundation of University of Electronic Science and Technology of China (No. ZYGX2015KYQD049).
Cite this article:
. 3D modeling of geological anomalies based on segmentation of multiattribute fusion[J]. APPLIED GEOPHYSICS, 2016, 13(3): 519-528.
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2016, Vol. 13 
