Hydromechanical Modeling of Stress, Pore Pressure, and Porosity Evolution in Fold‐and‐Thrust Belt Systems
Bibliographic record
Abstract
Abstract We present coupled, critical state, geomechanical‐fluid flow simulations of the evolution of a fold‐and‐thrust belt in NW Borneo. Our modeling is the first to include the effects of both syntectonic sedimentation and transient pore pressure on the development of a fold‐and‐thrust belt. The present‐day structure predicted by the model contains the key first‐order structural features observed in the field in terms of thrust fault and anticline architectures. Stress predictions in the sediments show two compressive zones aligned with the shortening direction located at the thrust front and back limb. Between the compressive zones, near to the axial plane of the anticline, the modeled stress field represents an extensional regime. The predicted overpressure distribution is strongly influenced by tectonic compaction, with the maximum values located in the two laterally compressive regions. We compared the results at three notional well locations with their corresponding uniaxial strain models: the 2‐D thrust model predicted porosities which are as much as 7.5% lower at 2.5 km depth and overpressures which are up to 6.4 MPa higher at 3 km depth. These results show that one‐dimensional methods are not sufficient to model the evolution of pore pressure and porosity in contractional settings. Finally, we performed a drained simulation during which pore pressures were kept hydrostatic. The predicted geological structures differ substantially from those of the coupled simulation, with no thrust faulting. These results demonstrate that pore pressure is a key control on structural development.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".