PREDICTION OF FACIES DISTRIBUTION IN A CLASTIC RESERVOIR USING A HIDDEN MARKOV MODEL COMBINED WITH AN EXPECTATION-MAXIMIZATION ALGORITHM

机译：隐马尔可夫模型结合期望最大化算法预测碎屑岩储层分布

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This study determines facies distribution in a clastic reservoir using a hidden Markov model combined with an Expectation-Maximization algorithm. Iterating expectation and maximisation steps of the algorithm builds the hidden Markov model by tuning the model parameters including initial state distribution, state transition probability distribution, and observable symbol probability distribution. Optimized model parameters contribute to improving the predictability of facies distribution along the well trajectory using core and logging data.

机译：这项研究使用隐马尔可夫模型结合期望最大化算法确定碎屑岩储层中的相分布。该算法的迭代期望和最大化步骤通过调整模型参数（包括初始状态分布，状态转换概率分布和可观察符号概率分布）来构建隐马尔可夫模型。优化的模型参数有助于使用岩心和测井数据来改善沿井眼轨迹的岩相分布的可预测性。

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《ASME international conference on ocean, offshore and arctic engineering》|2016年|V008T11A012.1-V008T11A012.7|共7页
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Hwasoo Suk; Joe M. Kang; Baehyun Min; Cheolkyun Jeong;
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PREDICTION OF FACIES DISTRIBUTION IN A CLASTIC RESERVOIR USING A HIDDEN MARKOV MODEL COMBINED WITH AN EXPECTATION-MAXIMIZATION ALGORITHM

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