Complex fuzzy-probabilistic analysis of information on drilling mud losses
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Abstract
Abstract
In recent years, classification and clustering have been widely used for processing and analyzing information for the purpose of structuring, ordering, summarizing, and sorting. Classification and clustering are used when working with information processes both in enterprises (large and medium-sized) and in various fields of scientific activity, which is especially important in the context of the constant growth of processed information.
At the same time, during cluster analysis, an important task is to assess its quality. In this work, cluster analysis was used to identify loss circulation zones when drilling wells and classify them by severity (intensity). To determine the quality of the cluster analysis, the entropy value was calculated, which should tend to a minimum. In our case, it was 0.23, which allows us to judge the fairly high quality of the cluster solution.
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