Simulation of Dissolution Front Propagation During Acid Injection Into Porous Media: A CFD Approach
Bibliographic record
Abstract
Acid is often injected into porous media to dissolve rock material and enhance flow capability of the rock. Most simulation studies on the propagation of the dissolution front are based on constant injection rate (CIR). Therefore, the objective of this work is to develop numerical model to study acid dissolution front under constant injection pressure (CIP) and also incorporate the effect of fluid temperature on acid–rock interaction. Commercial computational Fluid Dynamics (CFD) software (ANSYS Fluent) is used to solve three-dimensional acid-rock interaction model in cylindrical coordinates. In this work, correlated porosity and permeability distributions are generated. Effect of heat transfer between the injected fluid and the formation on fluid properties and surface reaction rate are accounted for in the model. The study confirmed that all types of acid dissolution patterns exist during constant injection pressure. CIP technique requires lower acid volume to achieve breakthrough in the conical and branched dissolution regimes, than that is required for CIR technique. In dominant wormhole pattern, both techniques require nearly the same acid volume to breakthrough. Thermal interaction between the injected fluid and the formation leads to change of surface reaction rate and physical properties of the fluid, such as viscosity, density, and diffusivity. Injection of cold fluid into heated formation leads to a higher wormhole density as found from experimental studies due to retardation of surface reaction rate. The model developed in this work accurately captures different dissolution patterns. The model shows that the acid volume required for wormhole breakthrough depends on the inlet conditions (CIR or CIP) and the thermal interaction between the injected fluid and formation. This modeling study attempts to answer the critical questions pertaining to the effect of temperature and injection conditions on acid-rock interaction.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".