Heavy Oil Polymer Pilot with Active Bottom Water Drive – A Success Story
Bibliographic record
Abstract
Abstract Bechraji is one of the major fields of heavy oil belt of Mehsana Asset in Western India. It contains heavy oil with average viscosity of ~270cp at reservoir temperature. During the early phase of production, high viscosity led to viscous fingering which resulted in sharp rise in field water cut to ~80%. Polymer flood in heavy oil has received significant attention after the numerous success across the globe namely, Marmul Oman, Bohai Bay offshore China and Pelican lake Canada fields. Screening studies were conducted followed by comprehensive laboratory evaluations of chemical flood potential which identified it as suitable process. Thus, a normal five spot pattern pilot testing was planned to understand the role of chemical EOR methods in the ultimate development strategy for the Bechraji. Comprehensive monitoring and quality control procedures were being followed to ensure smooth operations. Pressure surveys, tracer surveys, detailed produced fluid analyses and tests for monitoring the quality of injected fluids were all performed routinely. This paper deliberates the operational aspects of polymer flood, quality control and monitoring program followed, challenges faced and results of polymer flooding.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".