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English(EN) Depth-progressive 3D seismic velocity model building via 2D generative diffusion models

二维扩散模型赋能高效三维地震速度建模

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了一种新颖的深度渐进式框架，利用二维生成扩散模型构建三维地震速度模型。该方法将三维速度块的深度维度映射到二维 U-Net 的通道维度，从而能够从浅层到深层顺序合成块。该方法将更深层的预测条件化于浅层信息和地球物理约束，与传统的三维公式相比，显著降低了计算成本，同时在各种地质环境中保持了高精度。 AI

影响 该方法提供了一种计算效率更高的方法来构建三维地震速度模型，有望加速地球物理分析和地下勘探。

排序理由 详细介绍地震速度模型构建新方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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二维扩散模型赋能高效三维地震速度建模

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详细介绍地震速度模型构建新方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Shijun Cheng, Randy Harsuko, Mohammad H. Taufik, Tariq Alkhalifah ·

    通过二维生成扩散模型实现深度渐进三维地震速度建模

    arXiv:2610.14812v1 Announce Type: cross Abstract: Three-dimensional (3D) velocity model building (VMB) remains computationally challenging with conventional approaches and native 3D neural networks, largely due to the prohibitive memory and training cost of full 3D formulations. …

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