Understanding Rock Multiphysics – Key Needs in Symbiotic Pursuit of Mining Critical Minerals and Transitioning Energy
Bibliographic record
Abstract
Both mining critical minerals and transitioning energy towards carbon neutrality draw heavily on fluids in the subsurface.For mining critical minerals, this involves the injection of specially designed fluids into and the recovery of pregnant fluids from ore deposits.For transitioning energy, this includes sequestering CO2, fuel switching to lower-carbon sources, such as from abundant gas shales and coal gas reservoirs, recovering deep geothermal energy via EGS (Enhanced Geothermal System), and diurnal and inter-seasonal storage of heat, H2 and energized fluids (CAES: Compressed Air Energy Storage).In all these endeavours, either maintaining the low permeability and integrity of caprocks or in controlling the growth of permeability in initially very-low-permeability shales/coals or geothermal reservoirs represent key desires.Injected volumes are necessarily enormous and anticipated processes complex.We assess these desires through advancing our understanding on fluid injection/extraction induced multiphysics in rocks/reservoirs.In rock multiphysics, all essential processes are coupled through the links between fluid injectivity/extractability and rock permeability.This lecture will cover rock multiphysics principles and how they can help in mining critical minerals and transitioning energy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".