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Record W2159380541 · doi:10.3997/2214-4609-pdb.177.53

VSP And Well Logs From A Shallow Test Well

2008· article· en· W2159380541 on OpenAlexaffabout
Joe Wong, Soo K. Miong, L. R. Bentley, Robert R. Stewart

Bibliographic record

Venue21st EEGS Symposium on the Application of Geophysics to Engineering and Environmental Problems · 2008
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Imaging and Inversion Techniques
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsGeologyGeophoneWell loggingDrillingVertical seismic profileOil shaleSeismologyHydrogeologyCasingGeophysicsGeotechnical engineeringPaleontology

Abstract

fetched live from OpenAlex

Shallow VSP and geophysical well logging surveys were undertaken in a 127 m-deep well drilled at the Rothney Astrophysical Observatory site near Priddis, Alberta. The well was drilled through interbedded sands and shales of the Tertiary Paskapoo formation. A suite of geophysical well logs (including natural gamma-ray, single-point resistance, focused-beam resistivity, density, neutronneutron, caliper, temperature, and SP) was acquired in the open hole immediately after drilling. After PVC casing was inserted into the well and grouted to the formation rocks, we obtained natural gammaray and full-waveform sonic logs. The logs were useful for delineating the sandstone and shale beds, and for providing hydrogeological information at the well site. For the VSP surveys, we used a 5.5 kg sledge hammer source with a downhole clamping 3C geophone. From the full-waveform sonic logs and VSP data, we determined P-wave velocities to lie between 1.7 to 3.0 km/s. Standard VSP processing resulted in a corridor stack of up-going reflections that correlate reasonably well with a 1-D synthetic seismogram constructed from the density and P-wave velocity logs.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.546
Threshold uncertainty score0.443

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 head0.005
GPT teacher head0.150
Teacher spread0.145 · 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

Citations4
Published2008
Admission routes2
Has abstractyes

Explore more

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