Evaluación del uso de un compresor en cabeza de un Pozo con plunger lift para la optimización de producción de Gas en el campo Canadian Southwest
Bibliographic record
Abstract
The installation of compressors in head of wells in the United States has been one of the new technologies for the extraction of hydrocarbons in unconventional deposits allowing a recovery up to 50%, however, these compressors in many cases work in conjunction with lifting mechanisms . In the State of Colorado, most gas fields produce with compression technologies. This research makes a progressive compilation of different data such as the geology of the field, properties and characteristics of the well selected, in addition to the type of survey that works in conjunction with the compressor, allowing an analysis of the production curves. Production data were recorded during a period of five months with the lift system (plunger lift) compared to the installation of the compressor at the wellhead with the same time ranges, to determine the rate of gas produced with each of them.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.003 | 0.004 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.004 |
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; both teacher heads agree on what is shown here.
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".