The level to which data are aggregated or smoothed can impact analytical and predictive modeling results. This paper discusses findings regarding such impacts on estimating change points in production flow regimes of horizontal hydraulically fractured shale oil wells producing from the middle member of the Bakken Formation. Change points that signal transitions in flow regimes are important because they subsequently affect estimates of ultimate recovery from wells producing from shale plays. Extending our earlier work, we employ two different statistical approaches, Bacon–Watts Bayesian regression and nonlinear constrained least squares regression, and a designed computational experiment to estimate the time of transition from the transient to the boundary-dominated flow regime for 14 different wells using daily production data rather than aggregated monthly data, as previously considered. The daily data were also smoothed to reduce noise. Computational experiments suggest that both statistical approaches can lead to plausible estimates of the transition point under different data aggregation or smoothing regimes, but that daily data are likely too granular to produce credible estimates. Although the expected value of transition points using smoothed daily data and monthly disaggregated data are generally comparable, the confidence intervals bounding the estimates based on smoothed daily data are generally wider. Our results not only inform the operational practices of oil producers engaged in economic evaluation of their shale resources and additional play development activities, but also the activities of petroleum research groups, government agencies, and financial organizations seeking to improve the trustworthiness of resource projections.

数据汇总或平滑的水平可能会影响分析和预测建模结果。本文讨论了有关这样的发现，这些影响对估算从巴肯组中段开采的水平水力压裂页岩油井的生产流态中的变化点有影响。指示流动状态转变的变化点很重要，因为它们随后会影响页岩气开采井的最终采收率估算。在扩展我们之前的工作时，我们采用了两种不同的统计方法：Bacon–Watts贝叶斯回归和非线性约束最小二乘回归，以及设计的计算实验，它使用每日生产数据而不是先前考虑的每月汇总数据来估算14口井从瞬态过渡到边界为主的流动状态的时间。还对日常数据进行了平滑处理以减少噪音。计算实验表明，两种统计方法都可能导致在不同的数据汇总或平滑机制下对过渡点进行合理的估计，但是每日数据可能过于细化而无法产生可信的估计。尽管使用平滑的每日数据和月度分解数据的过渡点的预期值通常是可比较的，但以平滑的每日数据为基础的估计的置信区间通常较宽。