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Record W2003357484 · doi:10.1130/b26078.1

Quantifying heterogeneity in variably fractured sedimentary rock using a hydrostructural domain

2007· article· en· W2003357484 on OpenAlexaffabout
Megan J. Surrette, D. M. Allen

Bibliographic record

VenueGeological Society of America Bulletin · 2007
Typearticle
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsSimon Fraser University
FundersU.S. Geological Survey
KeywordsCitationGeologySedimentary rockLibrary scienceDownloadArchaeologyPaleontologyWorld Wide WebHistoryComputer science

Abstract

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Other| January 01, 2008 Quantifying heterogeneity in variably fractured sedimentary rock using a hydrostructural domain Megan J. Surrette; Megan J. Surrette 1Department of Earth Sciences, Simon Fraser University, Burnaby, British Columbia V5A 1S6, Canada Search for other works by this author on: GSW Google Scholar Diana M. Allen Diana M. Allen 1Department of Earth Sciences, Simon Fraser University, Burnaby, British Columbia V5A 1S6, Canada Search for other works by this author on: GSW Google Scholar Author and Article Information Megan J. Surrette 1Department of Earth Sciences, Simon Fraser University, Burnaby, British Columbia V5A 1S6, Canada Diana M. Allen 1Department of Earth Sciences, Simon Fraser University, Burnaby, British Columbia V5A 1S6, Canada Publisher: Geological Society of America Received: 19 Jul 2006 Revision Received: 07 Apr 2007 Accepted: 09 Jul 2007 First Online: 08 Mar 2017 Online ISSN: 1943-2674 Print ISSN: 0016-7606 The Geological Society of America, Inc. GSA Bulletin (2008) 120 (1-2): 225–237. https://doi.org/10.1130/B26078.1 Article history Received: 19 Jul 2006 Revision Received: 07 Apr 2007 Accepted: 09 Jul 2007 First Online: 08 Mar 2017 Cite View This Citation Add to Citation Manager Share Icon Share Facebook Twitter LinkedIn Email Permissions Search Site Citation Megan J. Surrette, Diana M. Allen; Quantifying heterogeneity in variably fractured sedimentary rock using a hydrostructural domain. GSA Bulletin 2008;; 120 (1-2): 225–237. doi: https://doi.org/10.1130/B26078.1 Download citation file: Ris (Zotero) Refmanager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentBy SocietyGSA Bulletin Search Advanced Search Abstract Characterizing permeability at a regional scale where fracture distributions are heterogeneous can be aided by defining hydrostructural domains. A hydrostructural domain approach is applied to a fracture data set for Mayne Island, one of the Gulf Islands in British Columbia, Canada. Fracture domains were defined using changes in fracture intensity, and are represented and modeled using a stochastic, discrete fracture-network approach. Models that statistically honor field data were constructed for representative stations for three hydraulically distinct, hydrostructural domains: "highly" fractured, interbedded mudstone and sandstone (IBMS-SS) (<10-cm spacing), "less" fractured sandstone (LFSS) (>1.0-m spacing), and fault and fracture zones (FZ). The highly fractured IBMS-SS and FZ domains have a greater potential porosity compared to the LFSS domain due largely to greater fracture intensities. The two highly fractured domains (IBMS-SS and FZ) have an average permeability, on the order of 10−13 m2, due to enhanced fracture-network connectivity. In contrast, the LFSS domain has an average permeability of 10−14 m2. The possibility of increased infiltration rates within FZ domains, coupled with a high-storage potential relative to the other domains suggests that fault zones with similar characteristics are likely zones of recharge. As a result, these recharge zones have an increased capacity to store and transmit infiltrated water throughout the interconnected fracture network. This study demonstrates that hydrostructural domain modeling provides a good foundation upon which to simulate flow and transport in regional groundwater resource studies. You do not have access to this content, please speak to your institutional administrator if you feel you should have access.

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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)0.001
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.435
Threshold uncertainty score0.874

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.023
GPT teacher head0.261
Teacher spread0.237 · 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 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

Citations26
Published2007
Admission routes2
Has abstractyes

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