FRACTAL EVIDENCE OF REACTIVE TRANSPORT IN GEOLOGIC SYSTEMS BASED ON MULTIPHASE FLOW HYDRAULIC MODELS PART II: THE BIOGEOCHEMICAL ASPECT
Bibliographic record
Abstract
In the petroleum and soil science literature, fractal models of porous systems abound. Consequently, any process, be it physicochemical or geomechanical, that imparts pore structure will equally impact the fractal nature of the system. Several studies have reported the effect of physicochemical processes, such as the water–rock interactions, on the fractal dimension of the porous system using different approaches involving sophisticated instrumentation. Others have also reported the effect of geomechanical processes such as compaction on fractal dimension using similar approaches. To the best of our knowledge, none or little has been reported regarding the use of multiphase flow hydraulic models for revealing the effect of water–rock interactions on the fractal dimension and pore size distribution of the porous system. Consequently, to fill the knowledge gap in this regard, data on two-phase flow of acid gas and brine in porous media have been used to show that the fractal dimension and pore size distribution of the porous system change in response to water–rock interactions. In view of the injection of acid gas, such as anthropogenic carbon dioxide, into saline aquifers being a feasible means for carbon immobilization by mineral carbonation and biogeochemical means, the effect of change in the fractal properties of the porous system on the microbial transport and distribution in porous system has also been reviewed in relationship to the principal findings of this paper. Most importantly, the results of this study show that data on two-phase flow in porous media involving acid gas and brine can be used to prove changes in the fractal nature of the porous system, and this change can also impact subsurface distribution of methanogens that have the potential to trap carbon by methanogenesis.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| 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".