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Rock drillability prediction from in situ determined unconfined compressive strength of rock

Kelesidis Vasilis

Πλήρης Εγγραφή

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Περίληψη

The interaction between rock and drill bit during drilling has been modeled for many years, but a complete understanding of the phenomena occurring has yet to materialize. Successful models will allow the prediction of rate of penetration in a given environment and optimal selection of drill bit and drilling parameters, thus minimizing exploration costs. In most rock-drilling models the value of the unconfined compressive strength of the rock (UCS) is used in the predictive equations, within the concept of specific energy, and the value of UCS is the percentage of the value of the stress applied on the drilling bit in order for the bit to advance. While the exact percentage depends on the model used and it is not known with certainty, good knowledge of UCS is never-theless required before any decent prediction can be made on rate of penetration. Determination of UCS, normally done via destructive testing, requires not only the availability of sound rock core samples but also expensive testing and significant time for the test, which frequently are not available for routine drillability predictions. Hence, a multitude of methods and techniques has been proposed for estimating UCS from various indirect and/or non-destructive measurements, or combination of measurements with neural networks, such as point load index, block punch index, unit weight, and apparent porosity, water absorption by weight, sonic velocity, and Schmidt hardness. The many proposed approaches are critically reviewed and the results are compared, and what becomes apparent is that after many years, not only in mining but also in oil-well drilling, accurate indirect determination of UCS is still an elusive goal. An equation to predict UCS from sonic velocity data is suggested based on several data sets reported in the literature. Use of the specific energy equation with UCS or sonic data and utilization of drilling data allows an estimation of the efficiency of energy transfer from the bit to the rock and of the friction coefficient. Analysis of data reported in the literature, both from laboratory and field studies, has shown that this approach is sound and enables the determination of energy transfer efficiencies and friction coefficients, which for the cases studied range between 15 and 30% and 0.15 and 0.30 respectively. Thus, the suggested data analysis approach allows drillers to focus on inefficiencies and optimize drilling practices in future campaigns.

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