xpertsystems/oil020-sample

OIL-020是一个合成产品收率数据集（样本），专注于石油和天然气下游炼油领域。该数据集是XpertSystems.ai企业炼油产品收率数据集的免费预览版，用于原油化验表征、常压/真空蒸馏建模、FCC/加氢裂化/重整/烷基化操作、产品混合优化、炼油经济学和排放跟踪的机器学习任务。样本包含8,000个原油化验记录，链接了常压和真空蒸馏切割点，以及17,500个操作记录，覆盖11个二级过程表，总计216,500行数据分布在14个表中。数据集通过行业标准（如UOP、Honeywell、ASTM、EPA等）进行校准，确保数据真实性。但请注意，这是一个样本版本，存在一些限制，如部分表之间缺乏连接性、质量平衡未强制实施等，适用于炼油收率机器学习研究，但不适用于实时操作决策。

OIL-020 is a synthetic product yield dataset (sample) focused on the oil and gas downstream refining sector. It is a free, schema-identical preview of XpertSystems.ais enterprise refinery product yield dataset for crude assay characterization, atmospheric/vacuum distillation modeling, FCC/hydrocracker/reformer/alkylation operations, product blending optimization, refinery economics, and emissions tracking ML. The sample covers 8,000 crude assays with linked atmospheric and vacuum distillation cuts, plus 17,500 operations records across 11 secondary process tables, with 216,500 rows linked across 14 tables. The dataset is calibrated using industry standards (e.g., UOP, Honeywell, ASTM, EPA) for authenticity. However, this is a sample version with limitations, such as lack of joinability between some tables and unenforced mass balance, making it suitable for refinery yield ML research but not for live operational decisions.