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.本数据集数据基于康斯伯格数字（Kongsberg Digital）出品的动态模拟器K-Spice中各类可行操作的不同组合随机生成。在案例研究1中，目标为相较于初始工况值提升10%的原油产量；在案例研究2中，目标为相较于初始工况值降低10%的天然气产量。本数据集包含了受训人员在尝试解决上述两类场景时，可能采取的正确与错误操作路径示例。