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Record W2152256688 · doi:10.1144/gsl.sp.2003.216.01.23

Pore pressure/stress coupling and its implications for rock failure

2003· article· en· W2152256688 on OpenAlexaboutno aff
Richard R. Hillis

Bibliographic record

VenueGeological Society London Special Publications · 2003
Typearticle
Languageen
FieldEngineering
TopicRock Mechanics and Modeling
Canadian institutionsnot available
Fundersnot available
KeywordsCoupling (piping)Stress (linguistics)Geotechnical engineeringPore water pressureMaterials scienceGeologyForensic engineeringComposite materialEngineeringPhilosophy

Abstract

fetched live from OpenAlex

Abstract Clastic dykes and sills witness that subsurface sediment mobilization is often controlled by the brittle failure of units ‘sealing’ overpressured and liquidized sediments. Brittle failure also imposes a limit on the buoyancy pressure that can be exerted by hydrocarbon columns. Conventional understanding of brittle failure induced by increasing pore pressure (P p ) assumes that total minimum horizontal stress (σ h ) is unaffected by changes in pore pressure. However, total minimum horizontal stress increases from shallow, normally pressured sequences to deeper, overpressured sequences. Data from the Canadian Scotian Shelf, the North Sea and the Australian North West Shelf demonstrate such P p /σ h coupling, with the minimum horizontal stress increasing at approximately 60–80% of the rate of pore pressure (i.e., Δσ h /ΔP p = 0.6–0.8). Hence, a greater increase in pore pressure can be sustained prior to brittle failure of units sealing overpressured compartments than would be predicted by conventional, uncoupled failure models. Furthermore, because total vertical stress is not similarly coupled to pore pressure, differential stress (σ 1 –σ 3 ) reduces as pore pressure increases in normal fault regime basins. Thus, the mode of rock failure can not be inferred from differential stress in the stable state and P p /σ h coupling promotes tensile over shear failure.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.906
Threshold uncertainty score0.661

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.024
GPT teacher head0.240
Teacher spread0.216 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations59
Published2003
Admission routes1
Has abstractyes

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