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    • A Comparison Of Data Preprocessing Strategies For Neural Network Modeling Of Oil Production Prediction

    Hh Nguyen,Cw Chan

    PROCEEDINGS OF THE THIRD IEEE INTERNATIONAL CONFERENCE ON COGNITIVE INFORMATICS（2004）

    Univ Regina

    Cited 18|Views5
    Abstract
    This paper presents a comparison of the different data preprocessing strategies for developing neural net-work models for prediction of oil production rate. Data processing is an important step in developing a neural network application, which could affect model accuracy and results. We considered the following three ways to pre-process monthly oil production data: (1) the sequential approach in which condition-decision records from all the wells in a reservoir are placed sequentially to form a data set, (2) the averaging approach in which a data set is formed by averaging data values from individual wells in a reservoir, and (3) the individual approach in which data for individual wells are used separately to build models tailored for individual wells. Some advantages and disadvantages, as well as results of each approach will be discussed.
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    Key words
    neural networks,data preprocessing,oil production prediction
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