构建了用于模拟孔隙尺度二氧化碳-水相互作用的基准数据集
A Benchmark Dataset for Machine Learning Surrogates of Pore-Scale CO2-Water Interaction
- 基于高保真数值模拟生成624个2D孔隙样本
- 每张图512x512分辨率，覆盖100个时间步，支持动态建模
- 适用于碳捕集与封存领域机器学习模型的性能评估
准确模拟孔隙尺度下二氧化碳与水的复杂相互作用对碳捕集与封存（CCS）等地球科学应用至关重要。本文通过高保真数值模拟，构建了一个综合性数据集，涵盖624个2D孔隙样本，每个样本尺寸为512×512，分辨率35 μm，覆盖100个时间步，注射速率恒定。数据集包含不同粒径及随机间距带来的多级异质性，为发展预测模型提供了可靠测试平台。该数据集提供高时空分辨率信息，可用于机器学习模型的基准测试。
原文摘要 · Abstract (English)
Accurately capturing the complex interaction between CO2 and water in porous media at the pore scale is essential for various geoscience applications, including carbon capture and storage (CCS). We introduce a comprehensive dataset generated from high-fidelity numerical simulations to capture the intricate interaction between CO2 and water at the pore scale. The dataset consists of 624 2D samples, each of size 512x512 with a resolution of 35 μm, covering 100 time steps under a constant CO2 injection rate. It includes various levels of heterogeneity, represented by different grain sizes with random variation in spacing, offering a robust testbed for developing predictive models. This dataset provides high-resolution temporal and spatial information crucial for benchmarking machine learning models.
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