Support Data and Code for: Physics-Informed Deep Learning for Resistivity Prediction in Hydrate-Bearing Sediments: An Efficient Pore Network Modeling Framework

This repository contains the source code, training datasets, and pre-trained models for the paper 'Physics-Informed Deep Learning for Resistivity Prediction in Hydrate-Bearing Sediments: An Efficient Pore Network Modeling Framework' published in JGR: Solid Earth."本代码仓库包含发表于《JGR：固体地球》的论文《面向含天然气水合物沉积物电阻率预测的物理驱动深度学习（Physics-Informed Deep Learning）：一种高效孔隙网络建模框架》的源代码、训练数据集与预训练模型。