When Will Low Sulphate Seawater No Longer Be Required on the Tiffany Field?
Bibliographic record
Abstract
Abstract Injection of sulphate rich seawater into reservoirs with formation brines rich in calcium, barium or strontium may result in the precipitation of sulphate scales. One technique for managing mineral scales in fields where scale inhibitor squeeze treatments may prove very difficult or ineffective is injection of low sulphate seawater. The CNR operated Tiffany field in the North Sea is one of the oilfields that has been swept with low sulphate seawater for the longest period (> 10 years) and from the start of water injection, and consequently yields useful information on brine mixing and brine-rock interactions during low sulphate seawater sweep. This paper presents the evolution of individual well brine chemistry data, backed up by reservoir simulation and reactive transport flow modelling, which demonstrates the effect that low sulphate seawater injection has had on the produced brine chemistry. The main impact is that scale inhibitor squeezes have only been required for carbonate scales. The modelling has been extended to predict future individual well brine compositions to identify potential barium and sulphate concentrations to end of field life, and hence identify any remaining potential barium sulphate scaling risk. However, the predictive modelling has also been used to study the sensitivity to timing of a switch from desulphated to full sulphate seawater injection towards the end of field life, to address the question of when will low sulphate seawater no longer be required on the Tiffany field? This study has significant implications for other basins around the world where desulphation projects are about to commence (Brazil and Angola).
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".