New Steel Tooth Cutting Structure Breaks Multiple Records in Australasia
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Bibliographic record
Abstract
Abstract Approximately 90% of the large diameter holes in Australasia (Indonesia, Australia, PNG and New Zealand) are drilled with steel tooth roller cone bits. A new steel tooth bit design has proven to significantly improve the drilling economics in these applications. This paper describes the drilling challenges posed by these applications, details the new bit design features, and presents case studies showing the performance improvements these new bits provide when compared with conventional steel tooth bits. The new design bits feature a novel cutting structure with pyramid-shaped teeth, additional rows of teeth, wide grooves between rows, anti-tracking row(s) with tight pitches, thick hardfacing deposits, and a bar trimmer type gauge design. The result is a steel tooth bit that delivers significantly higher ROP and longer life than current designs, with high reliability, and predictable steering behavior for directional applications. Hole sections can often be completed with fewer bits, which further improves drilling economics. These bits achieve ROPs faster than even that of large diameter PDC bits in the Australasian applications, thus the reason that steel tooth bits are primarily used. An operator in Balikpapan, Indonesia drilled a long S-shaped hole with a new 17 1/2-in. steel tooth bit at 40% higher ROP than the best of nine direct offsets that were drilled with conventional steel tooth bits. Another operator offshore Western Australia conducted a head-to-head comparison of a new 16-in. steel tooth bit against a conventional steel tooth bit in identical hole sections. The new bit drilled over 70% faster and over 25% farther than the regular bit. A third operator in the Northwest Shelf area off Western Australia employed a new 17 ½-in. steel tooth bit to complete a section normally drilled with 12 ¼-in. PDC bits. The new steel tooth bit drilled over 25% faster than the fastest PDC offset run. Additional case studies will be presented further documenting these positive field results.
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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 | 0.001 | 0.001 |
| 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 it