Assessment of Cold-Heavy-Oil Production With Sand CHOPS in Llanos Basin, Colombia
Bibliographic record
Abstract
Abstract Heavy Oil production has been subject of extended research and technological developments during the past 3 decades. These difficult resources have been economically produced by different methods thanks to new technologies and the adoption of best practices to achieve successful projects. However, other production methods have risen directly in the field by trial and error. This is the case of the cold heavy oil production with sands “CHOPS” which is an extended production practice mainly in Lloydminster, Canada. This method have make possible to produce thin sands at economical rates using big hole perforations in vertical wells without sand control. By letting the sand be produced in conjunction with the oil, the so called “wormholes” can be created within the reservoir. These wormholes are structures of about 1 inch diameter that can reach several meters of length beyond the producing well. These high conductive channels help supporting a sustained oil rate for several years using PCP pumps. The formation of wormholes has already been technically proved during cold production tests carried out in a thin heavy oil bearing sand located in Llanos basin, Colombia. During this test, there was observed communication with another well 25 meters apart from the tested well. Light weight ceramic proppant used to gravel packed the nearby well has migrated to the producing well after sand production. The migration throughout the porous medium of man-made ceramic whit a diameter higher than 1000 microns evidences the creation of high-conductive channels or wormholes. Since then, the potential for CHOPS in this reservoir has been analyzed. The production potential under cold production with sand is studied by analogs and numerical simulation. Factors affecting the operational model needed to achieve a successful project are analyzed.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".