The article presents a new approach to averaging water cut measurements in the process of oil production based on an automated algorithm using mathematical methods. The main goal of the research is to improve the accuracy and speed of water cut data analysis, which enables to minimize the influence of human factor, reduce labor costs and standardize the data processing process. The main objective of the method is to reduce the number of insignificant noise deviations caused by measurement errors and to highlight significant ones that require attention. The algorithm consists of two steps. At the first stage, the data are linearly approximated by the method of least squares and the corridors of acceptable deviations are constructed. At the second stage, the width of the corridors is refined using the standard deviation and the data are verified to identify only the most important outliers. This approach filters out non-physical outliers and automates the approximation of actual values, bringing analysis results closer to expert judgment. Automation of the analysis process facilitates the application of a systematic approach to monitoring well water cut parameters, prompt response to changes in oil flow rate, identification of problem wells, and elimination of the causes of deviations. Implementation of the proposed method improves the quality of data, standardizes the process of their processing and reduces the labor intensity of analysis, providing effective management of production processes.
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