Rate of Penetration (ROP) is a dependent parameter predictable as a function of independent drilling parameters. The system conducts multiple regression analysis which is a statistical synthesis in real-time environment in order to find the regression coefficients of the pre-defined general ROP model in order to predict ROP. This gives the flexibility of ROP follow-up as a function of drilling parameters specifically for subject formation. Any diversion from the predicted value should indicate a change, either in formation or drilling condition that an action could be necessary to be taken. The modelled ROP prediction shows realistic match with the actual observations. The predicted ROP trend could be compared in real-time with what actually is occurring. The regression constants could be determined belonging to the specific formation for which they are calculated. With increased data volume, the accuracy of the constants is observed to improve. The accuracy of the predicted ROP is considered to increase with data that is more representative rather than spiky. This paper describes how a statistical synthesis of the past drilling data could be performed in real-time in order to predict what forthcoming drilling ROP performance to expect. This technique takes the advantage of today's communication and computer technology innovations. The system could become an important tool in terms of efficient drilling monitoring. The data belonging to a directionally drilled offshore well is used to present the introduced study
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