Experimental Investigation of Induced Low Frequency Axial Vibration on Drilling Response of a PDC Bit
Bibliographic record
Abstract
Abstract This study investigates the impact of induced low frequency axial excitations on drilling actions of Polycrystalline Diamond Compact (PDC) bits. Variations in drilling efficiency have been documented through a series of experiments at different intensities (frequency and amplitude) of axial excitations. Prior work has identified the challenges of bit wear due to high frequency oscillations and an experimental validation is conducted to incorporate vibration related force changes into mechanical specific energy (MSE) to allow for identification while drilling. Axial vibrations were induced using a controlled linear actuator at the cutter-rock interface, in low frequency regime (up to 5 Hz) using a rotary experimental setup, based on state-of-the-art modified lathe machine. Through imposition of bit kinematics of angular velocity and rate of penetration (ROP), a PDC cutter was used to drill several cores of donnybrook sandstone, at a constant angular velocity of 100 revolutions per minute (RPM). A piezoelectric triaxial sensor measured the cutting forces: normal (weight) and shear (torque) force, at the cutter-rock interface. The results quantify variation of drilling response under several combinations of frequency, amplitude and cutting speed. It was observed that forces required to penetrate through rock were reduced with minimum effect on degree of wear on the cutter, mainly due to lower intensity of induced oscillations. This shows that once periodic axial oscillations are imposed, a lesser amount of energy is required to achieve same rate of penetration (ROP), thereby indicating improvement in cutting efficiency of the drilling process. The results from this study also provides experimental evidence for the need to incorporate vibration induced force losses into the equation of drilling efficiency for correct estimations of rock strength downhole.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".