Concentric Coiled Tubing Well Vacuuming Technology for Complex Horizontal Wells in Eastern Venezuela
Bibliographic record
Abstract
Abstract Recent activity in developing the heavy oil reserves of the Orinoco belt has required that operators there utilize cutting edge oil field technologies. The latest in pumping technology and horizontal, multi-lateral well completions are being employed and enhanced. Additionally, operators are looking at new approaches to collect and evaluate well and reservoir data. Coiled tubing is also being used to help with some of the well performance issues. To optimize the performance of long, and/or multi-branch horizontal wells, post drilling clean-up is very important. Historically, this issue has often been overlooked or dealt with ineffectively. Not only is this step important for the resulting production performance, an effective system for accomplishing this can have additional benefits for the downstream facilities during start-up. The zones of interest in the Orinoco belt are typically poorly consolidated sands, requiring some form of retaining completion. As slotted liners are most common, an effective method of removing solids from inside the slotted liner may also become a requirement. This paper will discuss the technology of combining concentric coiled tubing with a jet pump to be able to do both the post drilling fluid clean-up and sand removal operations. It will detail the type of equipment used in this application. The paper will also go into specifics of the need for the service in this operation and the corresponding results. Future developments for this technology will also be covered.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".