论文标题
将嵌入式模型估计器应用于具有多个辅助变量的合成非平稳储层模型
An application of an Embedded Model Estimator to a synthetic non-stationary reservoir model with multiple secondary variables
论文作者
论文摘要
通过将地统计学与随机森林相结合的非平稳空间建模的方法（Ember）应用于三维储层模型。它将随机森林方法扩展到插值算法，该算法保留了与地统计算法和随机森林相似的一致性。它允许将更简单的插值算法嵌入到该过程中，并通过随机的森林训练过程组合。该算法在每个目标位置估算一个条件分布。这种分布的家族称为模型信封。展示了一种从包膜中产生随机模拟的算法。该算法允许次级变量的影响以及结果在模拟中的位置变化。
A method (Ember) for non-stationary spatial modelling with multiple secondary variables by combining Geostatistics with Random Forests is applied to a three-dimensional Reservoir Model. It extends the Random Forest method to an interpolation algorithm retaining similar consistency properties to both Geostatistical algorithms and Random Forests. It allows embedding of simpler interpolation algorithms into the process, combining them through the Random Forest training process. The algorithm estimates a conditional distribution at each target location. The family of such distributions is called the model envelope. An algorithm to produce stochastic simulations from the envelope is demonstrated. This algorithm allows the influence of the secondary variables as well as the variability of the result to vary by location in the simulation.
