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.

中文翻译：

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嵌入式模型估计器在具有多个次要变量的合成非平稳油藏模型中的应用

将地质统计学与随机森林相结合的具有多个次要变量的非平稳空间建模方法 (Ember) 应用于三维 Reservoir 模型。它将随机森林方法扩展为插值算法，保留与地统计算法和随机森林相似的一致性属性。它允许将更简单的插值算法嵌入到过程中，并通过随机森林训练过程将它们组合起来。该算法估计每个目标位置的条件分布。这种分布的族称为模型包络。演示了一种从包络中产生随机模拟的算法。该算法允许次要变量的影响以及结果的可变性因模拟中的位置而异。