Investigation of drilling performance and penetration mechanism using passive vibration assisted rotary drilling technology
Bibliographic record
Abstract
Drilling performance is an essential goal in the petroleum and mining industry. Drilling Rate of Penetration (ROP) is influenced by the operating parameter: torque, Weight on Bit (WOB), fluid flow rate, Revolution per Minute (rpm), rock related parameters (rock type, rock homogeneousness, rock anisotropy orientation), and mechanical parameters (bit type, configuration of the Bottom Hole Assembly (BHA)). The Drilling Technology Laboratory (DTL) at Memorial University of Newfoundland has incorporated the passive Vibration Assisted Rotational Drilling Technology (pVARD) as a drilling tool. This tool includes three parts within a compliant part, a part that dampens and a torque transmitting unit that is inside the BHA of the drill string. This tool utilizes the natural vibrations of the drilling process to increase drilling efficiency and rate of penetration. In this thesis, laboratory and field drilling tests have been conducted by first and second generation pVARD tools respectively which could play a positive role in improving drilling penetration rate through modified bit-rock compliance from conventional drilling. This research aims to develop a fundamental guideline for rock strength measurement and to interlink mechanical tests for the purpose of evaluating drilling performance. The compressive rock strength has an inverse relationship with drilling efficiency. The average Unconfined Compressive Strength (UCS) and Indirect Tensile Strength (ITS) of the granite were obtained to be 168.4 MPa and 16.3 MPa respectively by the mechanical loading frame in the laboratory parameters following American Society for Testing and Materials (ASTM) standard. The pVARD operational details are important for optimal configuration and best drilling results. The study focused on designing pVARD to be consistent with a Large Drilling Simulator (LDS) selecting optimal Belleville springs. Compression tests and numerical studies have been carried out using a mechanical frame and simulation analysis respectively, for different Belleville Spring stacking scenarios. Mechanical and simulation studies with details of pre-planned drilling experiments can provide important guidelines for optimizing pVARD basics. The hysteresis effect analysis of LDS-pVARD springs also provided a coherent idea of energy dissipation during the cycle test. Depending on the rock type and drilling parameters can provide pre-settings and configurations of pVARD for optimal drilling performance. Finally, this dissertation focuses on the effects of vibration on the performance of a diamond coring bit when drilling on hard rock with a first-generation small lab scale vibration tool pVARD. Thereafter, Drill off Tests (DOTs) have been performed using a Small Drilling Simulator (SDS) with axial vibrations on the drill string in laboratory conditions. The vibration properties have been adjusted to various settings of spring compliance and dampening (rubber) material. The results of the evaluation of the experimental data show that the ROP increased by a maximum of 28% keeping WOB within the operational limits. The results and knowledge obtained from this study will help to design third generation pVARD tools.
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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".