Successful Field Trial of a Shear-Resistant, High-Injectivity, Reservoir-Triggered Polymer
Bibliographic record
Abstract
Abstract This paper describes the successful execution of an inter-well field trial to test a novel reservoir-triggered polymer technology (the Polymer) which has been proven to mitigate two of the major operational and economic challenges facing polymer injection for enhanced oil recovery (EOR), particularly in the offshore environment. The challenges of shear degradation and reduced injectivity are overcome by delaying the development of viscosity until the Polymer is in the reservoir. The field trial was conducted in an onshore sandstone oil field in Texas. The 1,000 ppm Polymer solution was injected at rates of 500 to 900 bbl/d into a 10-ft interval of low water permeability (50-100 mD) under matrix conditions. To demonstrate development of its expected viscosity in the reservoir, the growing Polymer bank was sampled from an existing producer. Pressure Transient Analysis (PTA) was used to confirm the deep-reservoir behaviour of the Polymer. Field data demonstrates that the Polymer behaves as intended. The viscosity of the produced Polymer samples corresponds to the target viscosity as determined from surface activation of the Polymer at the same concentration. This confirms the shear-stability of the Polymer in its un-triggered form. In addition, the injection pressures were no greater than expected and significantly lower than the expected injection pressures, under matrix conditions, for an equivalent partially-hydrolysed polyacrylamide (HPAM). PTA indicates a bank of fluid of increased viscosity some distance from the injector, as designed.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".