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Record W4408429181 · doi:10.5194/egusphere-egu25-14435

Combining P-Wave  and Tube Wave Attenuation for Mechanical and Hydrogeological Fracture Characterization  

2025· preprint· en· W4408429181 on OpenAlexaffabout
Hamidreza Dannak, P. Pehme, Jonathan Munn, Beth L. Parker

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Imaging and Inversion Techniques
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsAttenuationHydrogeologyFracture (geology)Tube (container)Characterization (materials science)GeologyPhysicsGeotechnical engineeringMaterials scienceComposite materialOptics

Abstract

fetched live from OpenAlex

Fractured bedrock aquifers pose unique challenges due to heterogeneity attributed to variability in fracture network characteristics where fractures serve as primary pathways for water flow and contaminant transport. Bedrock mechanical properties control fracture frequency and connectivity that influence hydrologic unit boundaries and hydraulic conductivity variations. Understanding these properties and boundaries is therefore essential for science-based groundwater management and source protection. This study focuses on the use of Full Waveform Sonic (FWS) with other advanced borehole geophysical and hydraulic datasets to investigate the relationship between inhole-derived fracture characteristics with vertical hydraulic head and gradient profiles to evaluate the influence of mechanical units on hydrogeological unit (HGU) boundaries. This study utilizes downhole data collected in three cored holes within a regionally significant dolostone aquifer near the town of Elora and in the City of Guelph, Ontario, Canada. In such aquifers, HGU boundaries are often associated with zones of poor vertical fracture connectivity, caused by the termination of vertical joints at changes in rock mechanical properties often associated with bedding. Fractures alter seismic wave characteristics such as propagation velocity due to phase-change induced time delay, and reduce amplitude (e.g., Pyrak-Nolte et al., 1990). The transmission coefficient derived from both a displacement discontinuity model (Crouch & Starfield, 1983; Pyrak-Nolte 1990) and linear slip model (Schoenberg,1980) yields fracture mechanical compliance, that can be used to distinguish between terminating bed-parallel fractures positioned at HGU boundaries to non-boundary ones. Following Barbosa et al (2019), estimations of normal fracture mechanical compliance together with tube wave attenuation under continuous (non-conventional slow logging speeds of 0.2-0.3 m/min) and static (4cm steps) acquisition modes are used with several complementary high resolution borehole methods to delineate vertical hydraulic conductivity contrasts and HGU boundaries. These other datasets include depth discrete temperature, transmissivity, Nuclear Magnetic Resonance (NMR) and hydraulic head profiles from numerous, temporary deployed pressure transducers sealed behind flexible fabric borehole liners. By linking fracture mechanical and hydraulic properties, the study aims to improve the understanding of aquifer and aquitard unit boundaries to better inform hydrogeologic conceptual models in fractured sedimentary rocks and the design of conventional and multilevel monitoring wells for source water management

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.047
GPT teacher head0.255
Teacher spread0.208 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations0
Published2025
Admission routes2
Has abstractyes

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