Forward Stratigraphic Modelling of Jezero Crater on Mars using Generative Adversarial Networks

使用生成对抗网络对火星 Jezero 陨石坑进行正向地层建模

• 批准号: 2755905
• 金额: --
• 依托单位: Imperial College London
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2755905
• 关键词: Forward; Stratigraphic; Modelling; Jezero; Crater

My project is investigating the potential use cases of Generative Adversarial Networks (GANs) in forward stratigraphic modelling, when combined with diffusion-based modelling techniques. The use of one-shot GANs (SinGAN) will be to rapidly provide uncertaintyquantification of diffusion models. I am researching the effectiveness of unconstrained GANs to provide 3D stratigraphic information. This can be combined with various forms of conditioning data, such as seismic data, borehole logs, and multi-spectral satellite imagery, with the aim of generating multiple stratigraphic models that are geologically feasible, in a short period of time.

我的项目是调查生成性对抗性网络(GANS)与基于扩散的建模技术相结合在正向地层建模中的潜在使用案例。一次性GAN(SinGAN)的使用将快速提供扩散模型的不确定量化。我正在研究不受约束的Gans提供3D地层信息的有效性。它可以与各种形式的条件数据相结合，例如地震数据、钻井记录和多光谱卫星图像，目的是在短时间内产生在地质上可行的多种地层模型。