Biotechnology Applications to EOR in Talara Off-shore Oil Fields, Northwest Peru
Bibliographic record
Abstract
Abstract Seven producer wells (oils between 32-36 °API) from Basal Salina fm. in Providencia and Lobitos areas of Z-2B Block (Talara basin, Northwest Peru) were selected to evaluate a biotechnology approach for Enhanced Oil Recovery. The MEOR candidates are vertical and high-angle slanted wells. They produce from faulted reservoirs through intermittent gas lift methods under an off-shore operative environment. The oils are paraffinic and hence with positive bio-treatability. The treated wells exhibited a typical MEOR response in two consecutive stages: 1) Clean-up effects by the removal of organic damage occurring in the near wellbore of the perforated interval, opening non-productive zones bearing oils with a more segregated, pseudoplastic behavior. The typical signature is a high pulse in oil rate but only lasting a short time. 2) Radial-Colonizing response, by generation of light-end solvents (biocracking on N-alkanes present in the oil) which cause a permanent rheological effects by the compositional alteration that occurat deeper colonization radius, in drainage zones with extremely low shear rate values (low fluid velocity). The MEOR pilot stage in PG-U9 and PG-9 of Providencia and LO16-14 and LO16-24 of Lobitos fields resulted in 3,086 M[3] (19,410 bbls.) and 2,211 M[3] (13,907bbls.) of Incremental Oil respectively. MEOR Increments of36.5% in Providencia and 46.5% in Lobitos were assumed as conservative (non optimized) MEOR performance indexes. Note: Due to operative reasons not directly related to MEOR, the complete inoculation program was concluded in only four of the original seven candidate wells. The pilot project was considered profitable and economically feasible of further expansion. Z-2B block possess 430 producers as excellent MEOR prospect and waterflooding schemes as potential targets for biotechnology (MEOR[2]). [Ref. 7 to 14].
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".