3D Simulation of Rock Breakage With Air Hammers in Gas-Well Drilling
Bibliographic record
Abstract
Abstract Air hammers have been used to drill gas wells in West Canada and Central USA since 1980s. Field evidence has demonstrated air drilling can be significantly improved with hammer bits in terms of Rate of Penetration (ROP), hole geometry, cost per foot, etc. However, inconsistent results in different formations, risks in operation, and economic uncertainties impede hammer acceptance and development. In an effort to improve understanding of drilling physics and predict hammer performance, a 3D numerical simulator of air hammer drilling is developed in this study. The main features include an elastoplastic material model for rock constitutive behavior, a rock damage model for strength reduction and damage accumulation because of cyclic hammer impacts, multiple rock failure criteria for initiation of rock breakage, rock dynamic characteristics for energy dissipation and non-reflective boundaries. The numerical tool is further calibrated with the results from a series of single impact tests. The simulation describes how rock behaves during the drilling, including stresses propagation inside the rock, deformation and damage evolvement, and breakage occurrence. It produces an estimation of ROP for different hammer energy and formation properties. The records of rock failure history indicate aggressive tensile failure may be primarily responsible for rock breakage in air hammer drilling, while compressive failure (or shear failure) may only contribute as a minor player. These developments advance the simulation technology of hammer drilling and improve fundamental understanding of the physics involved. More importantly, the simulator can serve as a new tool to achieve a more predictable hammer performance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| 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".