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• W1963616025 abstract "Abstract Pressure drop prediction in pipes is an old petroleum engineering problem. There is a long history of attempts to develop empirical correlations to predict the pressure drop in pipes. Some of these attempts have produced correlations that provide good prediction in some cases. However, their general applicability is question-able. Correlations that address only a specific class of problems exist. These types of correlation usually perform better than those which attempt to meet the need of av ariety of problems. Usually, the higher the_ number of variables in the model the lesser the reliability and general applicability of the correlations. This is the result of using methodologies such as conventional regression analysis. In such methodologies, the chances of correctly and completely captwing the relationship between variables decreases as the number of variables increases. Many parameters could be involved in these types of problems, such as gas-oil ratios in two phase systems, water flow in three phase systems, and inclination angles of the pipe, to name a few. In this paper, the authors introduce a new methodology for developing prediction models for pipes. This methodology, which has been named Virtual Measure-ment in Pipes (VMP), incorporates the cutting edge of infmmation technology, artificial neural networks (ANN), to address the development of tools to predict pressure drops in pipes and optimum design of pipelines under a variety of circumstances. The fimdamental problem with conventional approaches resides in the inherent sequential and point wise (as opposed to parallel and distributed) information processing methods used in development of such correlations. Because of this short coming, conventional methodologies are unable to address, defme, or unravel the highly complex relationships between many variables involved in the process. In this paper, artificial neural networks are used to develop a Virtual Measurement Tool to survey flowing bottom hole pressure in multi-phase systems using information such as oil, gas and water flow rates, temperature, oil and gas gravity, pipe length, swface pressure, and inclination angles of the pipe. The developed Virtual Measurement Tool has been applied to the published field data for flowing BHP predictions. VMP's predictions are com-pared to existing methods and the enhancement is clearly demon-strated. The developed VMP tool can be applied to wellbore hydraulic problems. It can address three-phase (oil, water, and gas) flow in well bores. This tool applies to a variety of wells, including vertical wells and those with various degrees of inclinations." @default.
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• W1963616025 date "1995-09-18" @default.
• W1963616025 modified "2023-10-01" @default.
• W1963616025 title "Virtual Measurement in Pipes: Part 1-Flowing Bottom Hole Pressure Under Multi-Phase Flow and Inclined Wellbore Conditions" @default.
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• W1963616025 doi "https://doi.org/10.2118/30975-ms" @default.
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