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Record W2952098532 · doi:10.4236/jmp.2019.107055

Templates for Quantifying Clay Type and Clay Content from Magnetic Susceptibility and Standard Borehole Geophysical Measurements

2019· article· en· W2952098532 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Modern Physics · 2019
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBoreholeMagnetic susceptibilityPetrophysicsPermeability (electromagnetism)IlliteGeologyClay mineralsWell loggingMineralogyDrill cuttingsDrillDrillingDrilling fluidPorosityGeophysicsMaterials scienceGeotechnical engineeringChemistry

Abstract

fetched live from OpenAlex

This paper proposes a rapid means of identifying clay type and quantifying clay content from new template crossplots that compare magnetic susceptibility measurements with standard borehole well log data. The templates are similar in format to standard industry charts, but have a number of advantages over the commonly used charts. Laboratory measurements of magnetic susceptibility on core samples and drill cuttings have recently shown strong correlations with key petrophysical parameters, particularly clay content and fluid permeability [1] [2]. A new template crossplot between magnetic susceptibility and borehole spectral gamma ray log data can firstly help to quickly identify the types of clay present in the formation. Additional new template crossplots between magnetic susceptibility and borehole bulk density data allow the mineral contents and porosities of binary mixtures of clay minerals and matrix minerals (such as illite clay + quartz) to be rapidly quantified. The templates can use ambient (room temperature) magnetic susceptibility data from measurements on core samples or drill cuttings in the laboratory or at the wellsite. Furthermore, the paper shows how the templates can potentially be extended to utilize borehole magnetic susceptibility data for in situ estimations of the type and content of clay. This requires accounting for the temperature dependence of the magnetic susceptibility of paramagnetic minerals (such as illite clay), which varies with depth in a borehole. Whilst borehole magnetic susceptibility measurements are rarely part of standard well logging operations, they could be a potentially useful tool for in situ clay type and content quantification, which in turn can help predict fluid permeability.

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.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.843
Threshold uncertainty score0.433

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 head0.080
GPT teacher head0.274
Teacher spread0.194 · 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