Morphological Segmentation Applied to 3D Seismic Data

Faucon, Timothée; Decencière, Étienne; Magneron, C.

doi:10.1007/1-4020-3443-1_43

Cited by 4 publications

(3 citation statements)

References 3 publications

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“…These voxels lead to a "leak" during the flooding step and as the two bordering basins merge earlier than they should, the final surface appears lower in the hierarchy. To restrict this problem to the leak location and pick the rest of the horizon we used a method described in [2], [12]. This method consists in dividing the original image into many subimages called cylinders and in computing a hierarchical segmentation inside each of them.…”

Section: Segmentation With Cylindersmentioning

confidence: 99%

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Application of Surface Topological Segmentation to Seismic Imaging

Faucon

Decencière

Magneron³

2006

Discrete Geometry for Computer Imagery

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Section: Segmentation With Cylindersmentioning

confidence: 99%

“…After briefly presenting seismic imaging in section 2, we proceed with the description of the picking method: in section 3 we describe briefly the horizon extraction part, which was presented in [2]. In section 4 we present the application of the surface segmentation method proposed by Malandain et al [1] to our data.…”

Section: Introductionmentioning

confidence: 99%

Application of Surface Topological Segmentation to Seismic Imaging

Faucon

Decencière

Magneron³

2006

Discrete Geometry for Computer Imagery

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“…The application of MM to the geosciences has also developed rapidly. At present, MM is employed mainly in the following regards: seismic signal de-noising [25], seismic crack detection [26], and gravity and magnetic data processing [27].…”

Section: Introductionmentioning

confidence: 99%

Multi-Scale Edge Detection Method for Potential Field Data Based on Two-Dimensional Variation Mode Decomposition and Mathematical Morphology

2020

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Using observational data to determine the edges of the sources is an important task in the interpretation of potential field data. Extracting the edges of deep and shallow bodies effectively is the key to correctly understanding the underground structure. Based on the good multi-scale decomposition ability of two-dimensional variational mode decomposition (2D-VMD) and the outstanding shape analysis capability of mathematical morphology (MM), a new multi-scale edge detection method for potential field data is proposed. We propose using the variance of this morphological filter as a basis for selecting the optimal structural element (SE) scale. By establishing theoretical models and comparing the results of our method with those of traditional edge detection methods, the proposed method is shown to be effective at detecting edges within potential field data. Taking the Hanmiao area of Chifeng city, Inner Mongolia, China, as an example, 1:50000 aeromagnetic data are processed and analysed by this method. The physical properties of the rocks in the study area are also discussed. The results of theoretical calculations and real data processing show that this method can accurately extract the edges of the sources at different scales. And the real data processing results show that this method is suitable for the identification of structural faults. INDEX TERMS Multi-scale edge detection, potential field data, two-dimensional variational mode decomposition (2D-VMD), mathematical morphology (MM)

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Balanced morphological filters for horizontal boundaries enhancement of the potential field sources

Zhang

Zeng

et al. 2020

Appl. Geophys.

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Morphological Segmentation Applied to 3D Seismic Data

Cited by 4 publications

References 3 publications

Application of Surface Topological Segmentation to Seismic Imaging

Application of Surface Topological Segmentation to Seismic Imaging

Multi-Scale Edge Detection Method for Potential Field Data Based on Two-Dimensional Variation Mode Decomposition and Mathematical Morphology

Balanced morphological filters for horizontal boundaries enhancement of the potential field sources

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