Dataset of MCF-NET

Dataset in "Multiple-condition fusion network for characterizing complex subsurface structures based on sparse measurements and auxiliary variable". The data set includes two-dimensional experimental case data and three-dimensional experimental case data. All data used in this study are available at Github repository (https://github.com/GS-3DMG/mcf-net-data) and have been published on Zenodo (https://doi.org/10.5281/zenodo.8260600). Accurately inferring realistic subsurface structures according to different types of geophysical observations and interpretations remains a significant challenge as the morphology controls the subsurface flow and transport behavior. Hard data and soft data are most commonly used in subsurface characterization. Among them, hard data are observations obtained from subsurface measurements. Soft data areremotely sensed geophysical information and interpretations.本数据集对应论文《基于稀疏测量与辅助变量的多条件融合网络表征复杂地下结构》（Multiple-condition fusion network for characterizing complex subsurface structures based on sparse measurements and auxiliary variable）。本数据集包含二维实验案例数据与三维实验案例数据。本研究使用的全部数据均可在Github仓库（https://github.com/GS-3DMG/mcf-net-data）获取，且已在Zenodo平台（https://doi.org/10.5281/zenodo.8260600）发布。由于地下形态控制着地下流体流动与运移行为，基于不同类型的地球物理观测与解译结果精准反演真实地下结构仍是一项极具挑战性的任务。硬数据（hard data）与软数据（soft data）是地下结构表征中最常用的两类数据。其中，硬数据指通过地下测量获取的观测结果；软数据则指遥感获取的地球物理信息及其解译结果。