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Record W1975987839 · doi:10.3997/2214-4609.20140883

Interferometric Assessment of Borehole-geophone Clamping Quality

2014· article· en· W1975987839 on OpenAlexaff
Yoones Vaezi, Mirko van der Baan

Bibliographic record

VenueProceedings · 2014
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Waves and Analysis
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsGeophoneBoreholeMicroseismGeologyClampingSeismologyAcousticsVertical seismic profileNoise (video)InterferometrySeismic waveGeophysicsGeotechnical engineeringOpticsPhysicsEngineeringComputer science

Abstract

fetched live from OpenAlex

Summary Borehole arrays are often preferred over surface installations for hydraulic fracture monitoring of deep experiments due to proximity to the treatment zone. Borehole geophone strings are typically clamped to the observation wellbore wall using electromechanical or magnetic devices in order for them to be in close contact with the surrounding formations so as to record the background noise and propagating wavefields related to the microseismic experiments. This contact needs to be maintained throughout the recording time. We have used seismic interferometry to assess the clamping quality of borehole geophone arrays. We suggest that the characteristics of the reconstructed crosscorrelation functions between a reference receiver and other receivers in an array are indicative of the quality of clamping. The dominant contribution of tube waves in correlation functions and emergence of incoherent and fluctuating crosscorrelation functions indicate inadequate coupling while dominant appearance of clean body waves in the correlation gathers suggest a properly maintained coupling. We have applied this method to two different borehole microseismic datasets.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score0.606

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.022
GPT teacher head0.276
Teacher spread0.254 · 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 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
Published2014
Admission routes1
Has abstractyes

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