English(EN) DualTCN: A Physics-Constrained Temporal Convolutional Network for 2 Time-Domain Marine CSEM Inversion

DualTCN框架利用AI提高海洋CSEM数据反演精度

作者 PulseAugur 编辑部 · [2 个来源] · 2026-05-06 14:58

研究人员开发了DualTCN，一个用于分析时域海洋可控源电磁（MCSEM）数据的新型深度学习框架。该框架通过直接重建电导率深度剖面，超越了传统方法，实现了25.3%的损耗降低和高预测精度。DualTCN在计算成本显著降低的同时，保持了对噪声的鲁棒性，显示出比传统优化技术有显著改进。 AI

影响引入了一种新颖的地球物理反演深度学习方法，有望加速海洋环境下的地下分析。

排序理由这是一篇详细介绍用于特定科学应用的新的深度学习框架的研究论文。

AI 生成摘要 · Google Gemini · 来自 2 个来源。我们如何撰写摘要 →

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arXiv cs.LG TIER_1 English(EN) · Khaled Ahmed, Ghada Omar · 2026-05-07 04:00

DualTCN：用于二维时域海洋可控源电磁法反演的物理约束时域卷积网络

arXiv:2605.04997v1 Announce Type: new Abstract: DualTCN is the first deep-learning framework for inverting time-domain marine controlled-source electromagnetic (MCSEM) transient data. Moving away from traditional subsurface discretization, the framework regresses four earth-model…
arXiv cs.LG TIER_1 English(EN) · Ghada Omar · 2026-05-06 14:58

DualTCN：用于二维时域海洋可控源电磁法反演的物理约束时域卷积网络

DualTCN is the first deep-learning framework for inverting time-domain marine controlled-source electromagnetic (MCSEM) transient data. Moving away from traditional subsurface discretization, the framework regresses four earth-model parameters -- $σ_1$, $σ_2$, $d_1$, $d_2$ -- and…