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Record W3124868543 · doi:10.3997/2214-4609.2020603031

Rock Physics and Inversion Case Study of Lower Mannville Lithic Channel - An Interpreter Perspective

2020· article· en· W3124868543 on OpenAlexaffabout
Valentina Baranova, Azer Mustaqeem, Darren Kondrat

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Imaging and Inversion Techniques
Canadian institutionsPetro-Canada
Fundersnot available
KeywordsGeologyLithologyStructural basinCretaceousGeochemistryArcheanInversion (geology)Sedimentary rockGeomorphologyWorkflowPaleontology

Abstract

fetched live from OpenAlex

Summary Identifying Lower Mannville Lithic channels (Western Canada Sedimentary Basin) is challenging, it requires tight integration of geology and geophysics. Rock Physics interpretation yields insight into lithology and porosity changes that are essential to exploit oil and gas reserves within complex geological settings. Our workflow includes dynamic quantitative solution as a part of a complete interpretation. The Mannville Group comprise the oldest Cretaceous rocks over most of the Western Canada Sedimentary Basin and represent a major episode of subsidence and sedimentation following a long period of uplift, exposure and erosion of older strata. In this study, a Central Alberta Lower Mannville estuarine system is analyzed using Rock Physics in LMR crossplot space. Pre-stack Simultaneous Inversion is used to derive the Lamda and Shear moduli from 3D seismic data and a new interpretation integration workflow is applied.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.837
Threshold uncertainty score0.327

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.025
GPT teacher head0.240
Teacher spread0.215 · 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 designObservational
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
Published2020
Admission routes2
Has abstractyes

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