First Production Log Run in a Heavy-Oil Long-Horizontal Well Through a Y-Tool and Premium Screens
Bibliographic record
Abstract
Abstract The first production log ever run in a heavy oil, long horizontal well completed with premium screens in open hole and through a Y-tool was successfully executed by Petroregional del Lago S. A. (a joint venture between PDVSA and Shell) in the Urdaneta West Field (Lake Maracaibo, Western Venezuela). The purpose of the job was to identify the origin of water in a well that experienced water break-through from the first day of production. A specialized set of logging tools was run to detect both water and oil flow, as well as to determine any flow behaviors like cross-flow that would help understand the source of water in the formation, obtain sufficient data to prepare a water shut-off program, and establish basic productivity information from the well, being this also the first production log run in the heavy oil wells in the field, which require artificial lift to flow. The results of the production log indicate that a sand package is producing water from an unexpected zone, which will require a water shut-off workover. This paper describes the planning, operational and interpretation processes of the logging activity, and presents a number of lessons learnt and useful recommendations for similar activities in heavy oil wells.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".