xpertsystems/oil042-sample

OIL-042 是一个合成的集成油田数字孪生数据集，专注于石油上游领域。该数据集包含18个CSV表格，覆盖了从地下到地面的完整上游数字孪生，包括5个维度主表（油田/储层/井/设施/管道）、5个遥测流（储层/生产/举升/地面/管道/SCADA）和7个事件表（警报/工单/故障/环境/网络/操作员操作/标签）。数据集支持跨层因果建模，例如储层压力下降→人工举升退化→操作员干预→生产损失→备件需求。数据基于多个行业标准（如SPE、API、ISA、IEC等）进行校准，并包含验证记分卡以确保数据质量。数据集适用于储层到地面的因果建模、跨层异常检测、网络物理攻击建模、甲烷排放建模、操作员行为建模、人工举升优化等用例。OIL-042 is a synthetic integrated oilfield digital twin dataset focused on the upstream oil and gas sector. It includes 18 CSV tables covering the complete upstream digital twin: 5 dimensional masters (fields/reservoirs/wells/facilities/pipelines), 5 telemetry streams (reservoir/production/lift/surface/pipeline/SCADA), and 7 event tables (alarms/workorders/failures/environmental/cyber/operator actions/labels). The dataset supports cross-layer causal modeling, such as reservoir pressure decline → artificial lift degradation → operator intervention → production loss → spare parts demand. Data is calibrated to multiple industry standards (e.g., SPE, API, ISA, IEC) and includes a validation scorecard for quality assurance. Use cases include reservoir-to-surface causal modeling, cross-layer anomaly detection, cyber-physical attack modeling, methane emissions modeling, operator-action modeling, artificial lift optimization, and more.