Sulfur speciation in soured reservoirs: chemical equilibrium and kinetics
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Reservoir souring is a widespread phenomenon in reservoirs undergoing seawater injection. Sulfate in the injected seawater promotes the growth of sulfate-reducing bacteria (SRB) and archaea-generating hydrogen sulfide. However, as the reservoir fluid flows from injection well to topside facilities, reactions involving formation of different sulfur species with intermediate valence states such as elemental sulfur, sulfite, polysulfide ions, and polythionates can occur. A predictive reactive model was developed in this study to investigate the chemical reactivity of sulfur species and their partitioning behavior as a function of temperature, pressure, and pH in a seawater-flooded reservoir. The presence of sulfur species with different oxidation states impacts the amount and partitioning behavior of H 2 S and, therefore, the extent of reservoir souring. The injected sulfate is reduced to H 2 S microbially close to the injection well. The generated H 2 S partitions between phases depending on temperature, pressure, and pH. Without considering chemical reactivity and sulfur speciation, the gas phase under test separator conditions on the surface contains 1080 ppm H 2 S which is in equilibrium with the oil phase containing 295.7 ppm H 2 S and water phase with H 2 S content of 8.8 ppm. These values are higher than those obtained based on reactivity analysis, where sulfur speciation and chemical reactions are included. Under these conditions, the H 2 S content of the gas, oil, and aqueous phases are 487 ppm, 134 ppm, and 4 ppm, respectively.
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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 | 0.001 |
| 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) | 0.000 | 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 it