A texture-based interpretation workflow with application to delineating salt domes

Author:

Shafiq Muhammad Amir1,Wang Zhen1,AlRegib Ghassan1,Amin Asjad2,Deriche Mohamed2

Affiliation:

1. Georgia Institute of Technology, Atlanta, Georgia..

2. King Fahd University of Petroleum and Minerals, Dhahran, Saudia Arabia..

Abstract

We propose a texture-based interpretation workflow and apply it to delineate salt domes in 3D migrated seismic volumes. First, we compute an attribute map using a novel seismic attribute, 3D gradient of textures (3D-GoT), which measures the dissimilarity between neighboring cubes around each voxel in a seismic volume across the time or depth, crossline, and inline directions. To evaluate the texture dissimilarity, we introduce five 3D perceptual and nonperceptual dissimilarity functions. Second, we apply a global threshold on the 3D-GoT volume to yield a binary volume and demonstrate its effects on salt-dome delineation using objective evaluation measures such as receiver operating characteristic curves and the areas under the curves. Third, with an initial seed point selected inside the binary volume, we use a 3D region growing method to capture a salt body. For an automated 3D region growing, we adopt a tensor-based automatic seed point selection method. Finally, we apply morphological postprocessing to delineate the salt dome within the seismic volume. Furthermore, we also develop an objective evaluation measure based on the curvature and shape to compute the similarity between detected salt-dome boundaries and the reference interpreted by the geophysicist. Experimental results on a real data set from the North Sea show that the proposed method outperforms the state-of-the-art methods for salt-dome delineation.

Publisher

Society of Exploration Geophysicists

Subject

Geology,Geophysics

Cited by 42 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Salt3DNet: A Self-Supervised Learning Framework for 3-D Salt Segmentation;IEEE Transactions on Geoscience and Remote Sensing;2024

2. 3-D Salt Body Segmentation Method Based on Multiview Co-Regularization;IEEE Transactions on Geoscience and Remote Sensing;2024

3. Visual Attention-Guided Learning With Incomplete Labels for Seismic Fault Interpretation;IEEE Transactions on Geoscience and Remote Sensing;2024

4. Counterfactual uncertainty for high dimensional tabular dataset;Third International Meeting for Applied Geoscience & Energy Expanded Abstracts;2023-12-14

5. Proposing new seismic texture attributes based on novel gray level matrix with application to salt dome detection;Journal of Applied Geophysics;2023-11

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