Development and Optimization of Polymer Conformance Control Technology in Mature Reservoirs: Laboratory Experiments vs. Field Scale Simulation
Bibliographic record
Abstract
Abstract Water shutoff in mature reservoirs is traditionally achieved with cross-linked gels. By blocking the areas already swept by water, subsequently injected water can sweep an unswept area of the reservoir and thereby increase the oil recovery. However, it is a complicated process and the performance of polymer gel flood in complex reservoirs requires an accurate model that represents the reservoir features, chemical properties, and displacement mechanisms. This paper presents a successful investigation of polymer gel behavior from laboratory to full field scales. First, a series of laboratory experiments were conducted to achieve a deep understanding of polymer gel behavior. The results show that the polymer viscosity, gelation time, and gel strength strongly depend on reservoir temperature, polymer type, polymer concentration, cross-linker concentration, pH and salt concentration, which are the successful keys of a polymer conformance control process. The optimal values of these parameters are proposed for applying in a pilot test. A series of numerical simulations are performed to history match with experiment data and generate parameters for field scale simulation. The adsorption phenomenon is fully integrated into the reservoir model for controlling and reducing this effect during the polymer flooding process. According to the laboratory results, polymer gel flooding was applied for White Tiger which is the biggest oil field in Viet Nam. After a long time of waterflooding, water production becomes a serious problem in this field. Polymer gel treatment is simulated in full field scale and the results show that it is an excellent candidate for conformance control. Water production decreases from 4,800m3/d to slightly less than 2,000m3/d, while a significant increase in oil production has been achieved from unswept zones. That is a really successful evidence of the polymer conformance control technology in heterogeneous reservoirs.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".