Evaluation of Drag Reducing Agent (DRA) for Seawater Injection System: Lab and Field Cases
Bibliographic record
Abstract
Abstract Thorough experimental studies were conducted to assess the effectiveness of a drag reducing agent (DRA) to increase the flow capacity of transfer line that supplies treated seawater to power water injectors in carbonate reservoirs and ensure it has no adverse impact on water wells injectivity. These studies included: compatibility tests, corrosion rate measurements, flow through tube tests, and coreflood experiments. Experimental results showed that the examined DRA is compatible with the currently used biocides in seawater. Corrosion tests implied that the DRA decreased the corrosivity of seawater by 50%. Flow through tube tests confirmed that the DRA reduced frictional (drag) pressure drop in the tube and increase the flow capacity. The DRA was found to be sensitive to shear where its effectiveness decreased with high shear due to polymer chains degradation. Permeability reduction was observed at higher DRA concentrations. However, degraded DRA gave less damage compared to a fresh batch. The extent of permeability damage increased in low permeability (tight) cores. The DRA caused an external damage on the face of the core, where it was removed by reversing flow direction. The examined treatments (polymer oxidizers) degraded the DRA and restored core permeability. This paper summarizes three successful field cases of this DRA in seawater injection systems. Injection rates of six wells increased up to 34% after the DRA injection in the Brent Alpha offshore field. Injection of a DRA, up to 80 ppm, increased the total volume of seawater injected by 65% in the Gyda oil field, Norway. The use of a DRA in the seawater system of the Galley offshore field resulted in re-pressurizing the reservoir and maintained oil production. Based on the obtained promised results and successful field cases, field application guidelines for using DRA seawater system were summarized.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".