Reactive Transport Modelling of a Carbonate Reservoir under Seawater Injection
Bibliographic record
Abstract
Abstract Produced water chemical compositional data are collected from a carbonate reservoir which had been flooded by North Seawater for more than 20 years, so there is an opportunity to analyse the large amount of produced water data collected, understand the brine/brine and brine/rock interactions and explore the impact factors behind them. In some publications, core flood experimental tests were performed with chalk cores or carbonate columns in order to make an understanding of possible chemical reactions occurring triggered by injected water with different composition (Seawater, low salinity water or any other brine). However, most of the time the laboratory conditions where core flooding experiments are implemented cannot fully simulate the real reservoir conditions. Therefore, in this study, with the help of the valuable produced water dataset and some basic reservoir properties, a one-dimensional reactive transport model is developed to identify what in situ reactions were taking place in the carbonate reservoir triggered by seawater injection. From the perspective of reservoir mineralogy, calcite, as the dominant mineral in the carbonate reservoir, is relatively more chemically reactive than quartz and feldspar which are usually found in sandstone. Whether calcite is initially and dominantly present in the carbonate reservoir rock is dissolved under seawater flooding or not is the first key issue we focused on. The effects of calcite dissolution on the sulphate scaling reactions due to incompatible brine mixing and the potential occurrence of carbonate mineral precipitation induced by calcite dissolution are investigated and discussed in detail. The comparison of simulation results from the isothermal model and the non-isothermal model show the important role of temperature during geochemical processes. The partitioning of CO2 from the hydrocarbon phase into injected brine was considered through calculation of the composition of reacted seawater equilibrated with the CO2 gas phase with fixed partial pressure (equivalent with CO2 content), then subsequently the impact of CO2 interactions on the calcite, dolomite and huntite mineral reactions are studied and explained. We also use calculation results from the model to match the observed field data to demonstrate the possibility of ion exchange occurring in the chalk reservoir.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".