![]() ![]() These tested samples were drilled by diamond core bit using a fixed laboratory diamond drilling machine under conditions (4 rpm), and loads from 12 to 220 kg. Four types of rock were collected from different sites in the south of Egypt (Aswan sandstone, Isawya limestone, Assiut limestone, and Minya marble). The purpose of this research is to investigate the effect of weight on bit (WOB), rotary speed (RPM), and some rock properties on the rate of penetration (ROP). Our results indicate that the proposed model is able to predict the drilling ROP with an accuracy of more than 90%. The prediction performance of the proposed model is also evaluated in various formations for several test wells across an offshore gas field. The model can be incorporated in a framework to obtain an optimal well plan for a new well or for prescribing optimal operational parameters for well planning and real-time drilling operations. ![]() The importance of obtaining a formation-based ROP model is tested and verified with field data, and an algorithm to determine the parameters for new data is provided. The parameters of the model are obtained using multiple regression analysis with the field data. In particular, we incorporate the effect of equilibrium cuttings bed thickness and downhole cuttings concentration in the ROP model. On top of the factors included in the original B&Y model, our model accounts for parameters such as downhole motor, equivalent circulating density, mechanical weight on bit (WOB), and wellbore inclination. We extend the B&Y model to the PDC bits and discuss that a different predictive model should be obtained for each formation. Our model is inspired by the model of Bourgoyne and Young (B&Y) and follows an exponential form with 10 different drilling functions to account for various factors affecting ROP in drilling operations. ![]() In this paper, we present an accurate semiempirical rate of penetration (ROP) predictive model for polycrystalline diamond compact (PDC) bits. ![]()
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