New Quantitative, Analytical Approach Provides Rapid Identification and Diagnosis of Dysfunctional Bit Performance

Abstract

Abstract A complete analytical model for the penetration rate performance of polycrystalline diamond compact (PDC) bits has been developed to support a more rapid identification of drilling dysfunctions and allow more accurate efficiency calculations. The model predicts both rate of penetration (ROP) and torque based on the rock properties, pressure environment, PDC cutter and bit geometry, applied weight on bit (WOB), and rotary speed. The model has been used to identify and diagnose bit balling in full scale pressurized laboratory tests, as well as excessive drillstring torque and drag in the field. Evidence of global bit balling and cutter balling was found in full-scale drilling tests in Catoosa and Mancos shales using both water base and oil base drilling fluids. Reduction in ROP with increasing WOB was confirmed as a symptom of severe balling, but typically time is required to identify the trend, at which point it is often too late, as severe bit balling is generally irreversible. The model was applied to identify global balling before the onset of irreversible global balling, using specific force ratio signatures. The symptoms were similar in both mud types and were observed to be completely reversible by a applying a timely adjustment of drilling parameters. A sample application of the model to a southern U.S. shale play has been presented where both surface and downhole drilling measurements were used to evaluate the model. Overall, the model's predictions are in agreement with field data, as the model clearly identifies the occurrence of a dysfunction from change in formation properties and depth. The data also confirms that surface torque can be significantly different from downhole torque, though surface WOB is much closer to downhole WOB. The proposed model can be used as a diagnostic tool for real-time monitoring of drilling efficiency to identify and diagnose dysfunctions. Because the prediction is based on applied WOB, which can be accurately measured in real time even from surface data, identification is faster than with torque-based equations such as mechanical specific energy (MSE). This provides the opportunity for the rapid mitigation of drilling dysfunctions and reduced ROP.