Investigation of Enhancing Drill cuttings Cleaning and Penetration Rate Using Cavitating Pressure Pulses
Bibliographic record
Abstract
Drilling efficiency is governed by rock cuttings removal by hydraulic forces. The mechanical force introduced by the drill bit removes the rock chips from the parent rock. The chips will be held down until the downward forces due to overburden pressure are overcome. The turbulent jet that flushes away these chips consists of static impingement and dynamic pressure fluctuations. Instead of providing high pressure and hence enhancing the pressure fluctuations of the turbulent jet by rig pumps, the existing fluid pressure can be used more effectively. A fluid passing a Convergent-Divergent venturi demonstrates significant pressure fluctuations due to the cavitation phenomenon. As the fluid passes the vena-contracta, according to the Bernoulli’s principle, the fluid velocity increases and hence the pressure decreases. If pressure drops below the fluid vapor pressure, cavitation occurs and bubbles are created. Different prototypes were designed to investigate the probability of cavitation occurrence by using CFD simulations. The successful designs were venturis with diameters of 4 mm and 12 mm. Simulation software applies tetrahedral meshing to the prototype geometry for robust simulation results when geometry of the tool is complex. The results obtained confirmed the pressure pulses and occurrence of cavitation. An experimental setup consisting of a 12 mm venturi, two pressure sensors at upstream and downstream, and 3 load cells in a triangular combination, and a flow meter was used. The flow rate range was from 10 USGPM to 70 USGPM. The cavitation started at 25 USGPM with a shear noise that is the characteristics of a iii cavitating flow and the sensors recorded the pressure pulses at this point. The magnitude of pressure peaks ranged from 150 psi up to 600 psi. The second stage of the experiments was to investigate the effect of venturi and axial compliance in drilling. Compliant element used in these experiments consists of two plates with rubber mounts embedded between these two plates in an equilateral configuration. The rubber mounts enable the displacement of the upper plate on the base plate. An 8 mm venturi was also mounted on the drill string behind the bit as the vibration source. The experimental results show that the tool starts to cavitate and produce vibrations. The tool was tested with compliance and without compliance to seek the effects of the compliant element. Results show that when rigid (no compliance), the vibrations produced, did not have any significant effect on the rate of penetration (ROP). However, with integration of the compliant element, the vibrations produced by the tool intensified the natural vibration of the compliant element and the penetration rate increased.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".