RA方法的扩展:稳定性分析

First EAGE/PESGB Workshop Machine Learning Pub Date : 2018-11-30 DOI:10.3997/2214-4609.201803029

E. V. Brazil, Reinaldo Silva, L. Farias

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引用次数: 0

摘要

我们对Perez-Valiente等人(2014)提出的方法进行了扩展，称为油藏类似物(RA)。该方法使用机器学习来完成数据集。我们担心的是，这种方法不能跟踪从缺失值的推算到类似物的排名列表所带来的错误。本研究旨在分析该步骤的固有不确定性，讨论如何在信息有限的情况下有利于获得准确的油藏信息。

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An Extension For The RA Methodology: Stability Analysis

We present an extension for a methodology proposed by Perez-Valiente et al (2014), known as Reservoirs Analogues (RA). This method finds analogues using machine learning to complete a dataset. Our concern is this methodology does not track error carried from the imputation of missing values until ranking lists of analogues. This study aims to analyze the inherent uncertainty of this step discussing how it can be beneficial to obtain accurate information for reservoirs with limited information.

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First EAGE/PESGB Workshop Machine Learning

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