xpertsystems/oil005-sample

OIL-005 — 合成钻井勘探前景数据集（样本）是一个免费的、模式相同的预览版本，源自XpertSystems.ai的企业级钻井勘探数据集，专为上游勘探分析、地质风险建模和勘探经济机器学习设计。该样本包含5,000个勘探前景，分布在9个相互关联的表格中，覆盖了从勘探前景到结果的全流程。数据集包括主表、地质风险因素、碳氢化合物概率模型、体积估算、钻井程序、钻井成本模型、勘探经济、钻井结果和勘探标签，总计130,000行数据。它经过行业基准校准，如IHS Markit、Wood Mackenzie、Rystad Energy等，并验证了地质成功率、干井率、钻井成本等指标。数据集适用于勘探前景排名与筛选模型、地质概率估计、钻井成本回归、发现结果分类、体积蒙特卡洛工作流和多表关系机器学习等用例。

OIL-005 — Synthetic Drilling Prospect Dataset (Sample) is a free, schema-identical preview of XpertSystems.ais enterprise drilling-prospect dataset for upstream exploration analytics, geological risk modeling, and exploration-economics ML. The sample contains 5,000 prospects across 9 linked tables covering the full prospect-to-outcome pipeline. It includes master tables, geological risk factors, hydrocarbon probability models, volumetric estimates, drilling programs, drilling cost models, exploration economics, drilling outcomes, and exploration labels, totaling 130,000 rows. The dataset is calibrated to industry benchmarks such as IHS Markit, Wood Mackenzie, Rystad Energy, etc., and validates metrics like geological probability of success, dry-hole rate, drilling cost, etc. It is suitable for use cases such as prospect ranking and screening models, geological POS estimators, drilling-cost regression, discovery-outcome classification, volumetric Monte Carlo workflows, and multi-table relational ML.