5 papers
Multi-Condition Guided Diffusion Model for Controllable Elastic Parameter Synthesis
Hongling Chen, Qi Pang, Chuangji Meng +2
Prestack elastic parameter inversion is important for reservoir characterization and quantitative seismic interpretation. Most existing deep-learning-based methods have achieved pr…
GeoVolDiff: Taming 3D Geological Volumes with Latent Diffusion
Qi Pang, Hongling Chen, Jinghuai Gao
Deep learning has become a prevailing paradigm across a wide range of geophysical applications. Yet most existing studies concentrate on methodological refinements -- novel network…
Unsupervised Posterior Sampling for Seismic Data Recovery via Score-Based Generative Priors
Chuangji Meng, Jinghuai Gao, Zongben Xu
Seismic data restoration is a fundamental task in seismic exploration, yet remains challenging under complex and unknown degradations. Traditional model-driven or task-specific lea…
Generative modeling of seismic data using diffusion models and its application to multi-purpose posterior sampling for noisy inverse problems
Chuangji Meng, Jinghuai Gao, Wenting Shang +4
Geophysical inverse problems are often ill-posed and admit multiple solutions. Conventional discriminative methods typically yield a single deterministic solution, which fails to m…
Seismic Acoustic Impedance Inversion Framework Based on Conditional Latent Generative Diffusion Model
Jie Chen, Hongling Chen, Jinghuai Gao +3
Seismic acoustic impedance plays a crucial role in lithological identification and subsurface structure interpretation. However, due to the inherently ill-posed nature of the inver…