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METHOD FOR PREDICTING PERMEABILITY AND OIL CONTENT IN A GEOLOGICAL FORMATION

机译:预测地层渗透率和含油量的方法

摘要

Systems, methods, and apparatuses are provided for permeability prediction. The method acquires data associated with one or more geological formations, calculates, using processing circuitry and a trained Hidden Markov model, log-likelihood values to group the data into a plurality of clusters, and trains an artificial neural network for each of the plurality of clusters when the mode of operation is training mode. Further, the method acquires one or more formation properties corresponding to a geological formation, determines using the trained Hidden Markov model, a log-likelihood score associated with the one or more formation properties, identifies a cluster associated with the one or more formation properties as a function of the log-likelihood score, and predicts a permeability based at least in part on the one or more formation properties and a trained artificial neural network associated with the identified cluster when the mode of operation is forecasting mode.
机译:提供用于渗透率预测的系统,方法和装置。该方法获取与一个或多个地质构造相关的数据,使用处理电路和训练有素的隐马尔可夫模型计算对数似然值,以将数据分组为多个簇,并为多个模型中的每一个训练一个人工神经网络。当操作模式为训练模式时会聚类。此外,该方法获取与地质地层相对应的一个或多个地层性质,使用训练后的隐马尔可夫模型确定与一个或多个地层性质相关的对数似然分数,将与一个或多个地层性质相关的聚类识别为当对数模式为预测模式时,至少部分地基于一个或多个地层特性以及与所识别的聚类相关联的受过训练的人工神经网络来预测渗透率。

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