Geochemical Modeling of the Interplay Between Potential Determining Ions During Brine-Dependent Recovery in Carbonate Rocks
Bibliographic record
Abstract
Abstract Brine-dependent oil recovery in carbonate rocks has developed into an active area of research in the past two decades. It is well documented in the literature that wettability of carbonate rocks is altered due to desorption of oil acid groups from rock surfaces by the adsorbed sulfate, while the divalent cations co-adsorbed to maintain the surface charge balance as well as to reverse the oil-surface charge. Though the symbiotic interaction between active ions (Ca2+, Mg2+, and SO42−) and the rock surface has been established but how they systematically interplay at different conditions have not been well explored and available data seems inconsistent. In the present work, we develop a reactive transport model that includes various reaction sets like aqueous reactions, mineral reactions in terms of precipitation and dissolution, and surface sorption reactions in terms of adsorption and ion exchange to investigate and discuss the affinity of these active ions toward the rock surface. The important thermodynamic properties were obtained by using the model to interpret single-phase experiments. The model results were in remarkable agreement with the produced ion histories reported from the single-phase experiments. There were delays observed in the produced active ion concentrations because of retention at the rock surface. For two-phase experiments, the model excellently replicated the produced ion histories and oil recoveries obtained during various brines injections, using the same thermodynamic parameters. Although, the ion transports are impacted by the presence of oil because of reduced surface area accessible to the active ions. The established thermodynamic parameter can be applied to predict various brine-dependent recovery processes in different carbonate lithology as no significant difference was observed for the interplay between active ions and either chalk or limestone rocks.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".