The rapid growth of deep learning research, including within the field of computational
mechanics, has resulted in an extensive and diverse body of literature. To help researchers …

Seismic inversion is a fundamental tool in geophysical analysis, providing a window into
Earth. In particular, it enables the reconstruction of large-scale subsurface Earth models for …

高效高精度的反演算法在重力大数据时代背景下显得尤为重要, 受深度学习卓越的非线性映射
能力的启发, 本文提出了一种基于深度学习的重力异常及重力梯度异常的联合反演方法 …

Full waveform inversion (FWI) is widely used in geophysics to reconstruct high-resolution
velocity maps from seismic data. The recent success of data-driven FWI methods results in a …

Seismic impedance inversion is essential to characterize hydrocarbon reservoir and detect
fluids in field of geophysics. However, it is nonlinear and ill-posed due to unknown seismic …

Seismic inversion is one of the most commonly used methods in the oil and gas industry for
reservoir characterization from observed seismic data. Deep learning (DL) is emerging as a …

Machine learning, and specifically deep-learning (DL) techniques applied to geophysical
inverse problems, is an attractive subject, which has promising potential and, at the same …

基于全卷积神经网络的磁异常及磁梯度异常反演 Page 1 2021 年第36 卷第1 期 2021,36( 1) :
0325-0337 地球物理学进展Progress in Geophysics http: //www.progeophys.cn ISSN 1004-2903 …

Deep learning is applied to assist the joint inversion for audio-magnetotelluric and seismic
travel time data. More specifically, deep residual convolutional neural networks (DRCNNs) …

边界识别是位场数据处理中极为重要的一种技术, 现有的边界识别方法属于无监督式机器运算,
其识别精度与地质体的空间分布存在很大关系, 尤其是对深部复杂异常体的识别存在边界模糊的 …