Using Thermodynamics to Predict the Outcomes of Nitrate-Based Oil Reservoir Souring Control Interventions
Bibliographic record
Abstract
Souring is the undesirable production of hydrogen sulphide (H2S) in oil reservoirs by sulphate-reducing bacteria (SRB). Souring is a common problem during secondary oil recovery via water flooding, especially when seawater with its high sulphate concentration is introduced. Nitrate injection into these oil reservoirs can prevent and remediate souring by stimulating nitrate-reducing bacteria (NRB). Two conceptually different mechanisms for NRB-facilitated souring control have been proposed: nitrate-sulphate competition for electron donors (oil-derived organics or H2) and nitrate driven sulphide oxidation. Thermodynamics can facilitate predictions about which nitrate-driven mechanism is most likely to occur in different scenarios. From a thermodynamic perspective the question “Which reaction yields more energy, nitrate driven oxidation of sulphide or nitrate driven oxidation of organic compounds?” can be rephrased as: “What is the equilibrium constant for the acetate driven sulphate reduction to sulphide?” or more precisely: “Is acetate driven sulphate reduction to sulphide exergonic or endergonic?” Our analysis indicates that under conditions encountered in oil fields, sulphate driven oxidation of acetate (or other SRB organic electron donors) is always more favourable than sulphide oxidation to sulphate: the change in Gibbs free energy (ΔGo') for the reaction CH3COO- + SO42- + 2H+ " 2CO2 + HS- + 2H2O is -57.3 kJ, i.e., the equilibrium for this reaction is strongly to the right. That predicts that organotrophic NRB that oxidize acetate would outcompete lithotrophic NRB that oxidize sulphide. However, sulphide oxidation to elemental sulphur is different; ΔGo' for the reaction CH3COO- + 4S0 + 2H2O " 2CO2 + 4HS- + 3H+ is -16.3 kJ under standard conditions at pH 7. Low acetate levels drive this reaction to the left, i.e., make HS- oxidation more favourable than acetate oxidation. Incomplete oxidation of sulphide to S0 is likely to occur when nitrate levels are low, and is favoured by low temperatures; conditions that can be encountered at oil field above-ground facilities where intermediate sulphur compounds like S0 may cause corrosion. These findings have implications for reservoir management strategies and for assessing the success and progress of nitrate-based souring control strategies and the attendant risks of corrosion associated with souring and nitrate injection.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".