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Record W2093615691 · doi:10.1190/1.3068426

Measuring velocity dispersion and attenuation in the exploration seismic frequency band

2009· article· en· W2093615691 on OpenAlexaff
Langqiu Sun, B. Milkereit, Douglas R. Schmitt

Bibliographic record

VenueGeophysics · 2009
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Imaging and Inversion Techniques
Canadian institutionsUniversity of TorontoUniversity of Alberta
Fundersnot available
KeywordsDispersion (optics)Velocity dispersionGeologyAttenuationSeismic waveFrequency bandSeismologyVertical seismic profilePhase velocityUncorrelatedAcousticsGeophysicsPhysicsOpticsMathematicsStatisticsTelecommunications

Abstract

fetched live from OpenAlex

Abstract No perfectly elastic medium exists in the earth. In an anelastic medium, seismic waves are distorted by attenuation and velocity dispersion. Velocity dispersion depends on the petrophysical properties of reservoir rocks, such as porosity, fractures, fluid mobility, and the scale of heterogeneities. However, velocity dispersion usually is neglected in seismic data processing partly because of the insufficiency of observations in the exploration seismic frequency band (∼5 through 200Hz). The feasibility of determining velocity dispersion in this band is investigated. Four methods are used in measuring velocity dispersion from uncorrelated vibrator vertical seismic profile (VSP) data: the moving window crosscorrelation (MWCC) method, instantaneous phase method, time-frequency spectral decomposition method, and cross-spectrum method. The MWCC method is a new method that is satisfactorily robust, accurate, and efficient in measuring the frequency-dependent traveltime in uncorrelated vibrator records. The MWCC method is applied to the uncorrelated vibrator VSP data acquired in the Mallik gas hydrate research well. For the first time, continuous velocity dispersion is observed in the exploration seismic frequency band using uncorrelated vibrator VSP data. The observed velocity dispersion is fitted to a straight line with respect to log frequency to calculate Q. This provides an alternative method for Q measurement.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.935
Threshold uncertainty score0.253

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 head0.030
GPT teacher head0.210
Teacher spread0.180 · 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 designOther design
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

Citations46
Published2009
Admission routes1
Has abstractyes

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