Hydrodynamic Modeling of CO2-Saturated Brine Injection in Geologic Formations for Carbon Sequestration Using the Lattice Boltzmann Method
Bibliographic record
Abstract
We present the implementation of the conventional lattice Boltzmann method (LBM) with single-relaxation time (SRT) to model the injection of CO2-saturated brine into underground porous rocks. The aim is to describe the “surface dissolution” technique of carbon sequestration, whereby CO2 is dissolved in brine extracted from the designated storage site and this CO2-brine solution is pumped back into underground formations. In the two-dimensional numerical model here, a small subsection of underground porous rock formation is represented as a staggered periodic array of disks. From a single unit cell of the porous structure, we have determined the domain size and lattice spacing required to reach a stable solution. By modeling single-phase flow, the permeability k could be calculated and compared over various lattice sizes to determine a mesh size-independent solution. A constant pressure gradient was imposed across the length of the domain to simulate the injection of the incompressible CO2-saturated brine solution into the domain. From these simulations, velocity fields within the pore structure were obtained, and the effects of porosity on the permeability were explored. Such porosity effects may prove important at the transition between different rock layers within a storage site.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".