PREDICTION OF DRILL-BIT PERFORMANCE USING MULTIVARIABLE LINEAR-REGRESSION ANALYSIS

Drill-bit performance is affected by a range of factors. However, the principal factors that require consideration in predicting drilling ra tes are the type of bit, the bit operating parameters and the characte ristics of the penetrated rock. A single index is not a sufficient bas is for predicting performance. A variety of rock types were drilled in the laboratory with polycrystalline diamond compact (PPC) and impregn ated diamond core bits using a fully instrumented drilling rig at diff erent rotational speeds and with a range of weights on the bit. Quanti tative determinations of a wide range of textural, mechanical and inta ct rock properties were also made. Multi-variable Linear regression an alysis was then used to develop predictive models of rates of penetrat ion from the operating and rock property data. The models have been ve rified by statistical tests. The analysis indicated that the models fo r the pin and hybrid PDC bits have potential for practical application . However, although the model for the impregnated diamond bit appears to be reasonable from a purely statistical point of view, it may not b e satisfactory for drilling uses as it is based on two measures of roc k hardness alone. The application of multiple regression analysis to P DC drilling performance is novel and the technique shows promise for t he prediction of rock drillability with PDC bits. The ability of the t echnique to provide a mathematical characterization of the performance of new drill bits in specific rocks may prove to be of value to drill manufacturers and users.