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Record W2326643986 · doi:10.1190/1.3255178

Load cell system test experience: Measuring the vibrator ground force on land seismic acquisition

2009· article· en· W2326643986 on OpenAlexaff
Shan Shan, Peter M. Eick, Joel Brewer, Xianhuai Zhu, Simon Shaw

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsConocoPhillips (Canada)
Fundersnot available
KeywordsVibrator (electronic)Load cellData acquisitionRemote sensingGeologyComputer scienceAcousticsSeismologyEngineeringElectrical engineeringPhysics

Abstract

fetched live from OpenAlex

Many methods have been developed in an attempt to expand the recorded bandwidth associated with Vibroseis surveys, particularly to boost the signal at high frequencies for improving seismic image resolution. However, the dominant frequency band still remains in the range of 10–60Hz and no significant improvement has been achieved at high frequencies in conventional 3D seismic surveys. Ground attenuation is one of possible limitations, and another is that during the course of the seismic acquisition, the vibrator may not actually be generating as much energy at high frequencies as expected. In this paper the letter possibility is addressed by using a Load Cell System to measure the force actually being generated by the servo hydraulic vibrator. We find that these measurements are not consistent with the drive signal from the vibrator electronic controller (weighted‐sum ground force estimate) therefore the conventional weighted‐sum ground force signal is deemed questionable.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.138
Threshold uncertainty score0.518

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 head0.179
Teacher spread0.174 · 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 designSimulation or modeling
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

Citations9
Published2009
Admission routes1
Has abstractyes

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