数据缺失问题是油井生产记录中的常见问题。不完整的数据集通常通过省略所有缺失值的观察来简化，这可能会导致重大信息丢失。在完整的论文中，作者开发了一种有效的程序，可以快速重建整个生产数据集，并在不同变量中包含多个缺失部分。最终，完整的信息可以支持油藏历史匹配过程和产量分配，并可以开发油藏动态预测模型。
缺失值是压力瞬态分析中的一个普遍问题。
The problem of missing data is a common one in well-production records. An incomplete data set is commonly simplified by omitting all observations with missing values, which can lead to significant information loss. In the complete paper, the authors developed an efficient procedure that enables fast reconstruction of the entire production data set with multiple missing sections in different variables. Ultimately, the complete information can support the reservoir history-matching process and production allocation and can develop models for reservoir performance prediction.
Missing values are a prevalent issue in pressure transient analysis.
