Data for: A methodology for building a data-enclosing tunnel for automated online-feedback in simulator training

The data was generated randomly, based on different combinations of possible actions in the dynamic simulator K-Spice from Kongsberg Digital. In case study 1, the aim was to increase +10 % of the oil production with respect to the initial condition value. In case study 2, the aim was to decrease -10 % of the gas production with respect to the initial condition value. The data show examples of possible correct and incorrect paths that a trainee could follow trying to solve the scenarios.

该数据集系随机生成，基于Kongsberg Digital的动态模拟器K-Spice中可能采取的不同行动组合。在案例研究1中，旨在将相对于初始条件值的石油产量提升10%。在案例研究2中，旨在将相对于初始条件值的天然气产量降低10%。数据展示了学员在尝试解决这些场景时可能采取的正确与错误路径的示例。