Colorado Drill Cuttings Injection Pilot Results
Bibliographic record
Abstract
Abstract From December 2007 through April 2011, the operator conducted a two-phase drill cuttings injection pilot at the Piceance Field in Western Colorado in an effort to reduce the environmental footprint of drilling operations. This was the first subsurface injection of drill cuttings in Colorado and utilized a lost circulation zone in the Wasatch G formation as the injection interval. The first phase of the pilot was to assess the technical feasibility and formation response to injection. During this phase, water-based mud and drill cuttings from four wells were injected into a fifth well that was temporarily suspended at the intermediate casing and perforated in the Wasatch G formation. Over 40,000 bbl of fluid were injected under vacuum conditions with confirmed confinement to the target zone. Based on the injection results, the pilot progressed to a second phase to assess the logistical requirements of transporting cuttings from multiple drilling locations to a central processing and injection site. The injection well selected had experienced lost returns in the Wasatch G when originally drilled and was completed as a dedicated injector. The pilot processed cuttings from three active rigs, and demonstrated capacity to process cuttings from over six rigs. The operator proved injection as a technically feasible option for drilling waste disposal during full-field development at Piceance.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".