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Record W2097514590 · doi:10.1785/0120110016

Resolution of Seismic-Moment Tensor Inversions from a Single Array of Receivers

2011· article· en· W2097514590 on OpenAlexaff
Ismael Vera Rodriguez, Yu Jeffrey Gu, Mauricio D. Sacchi

Bibliographic record

VenueBulletin of the Seismological Society of America · 2011
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Imaging and Inversion Techniques
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMoment tensorGeologyMoment (physics)Tensor (intrinsic definition)SeismologySeismic arrayGeodesyResolution (logic)MathematicsGeometryPhysicsComputer scienceClassical mechanicsArtificial intelligence

Abstract

fetched live from OpenAlex

Moment tensor inversion techniques are widely used in global and regional seismic applications. When the ray-path trajectories are confined in a single plane (e.g., in isotropic media using a vertical array of receivers or an array that deviates from the vertical in the direction of wave propagation) only five out of six elements of the moment tensor are resolvable. This study investigates the resolvability of the complete seismic moment tensor for single-well monitoring geometries. By analyzing the resolution matrix, we demonstrate that a correct representation of the five resolvable elements of the moment tensor is only possible in a local reference system. For a vertical array of receivers, a suitable choice of condition number can assist the acquisition design. For a non-vertical array, our numerical modeling experi- ments suggest that the required distance and orientation of receivers for a full moment tensor inversion can be satisfied in a deviated well. In this case, information embedded in the condition number is valuable for determining the required distribution of receivers along the well.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.131
Threshold uncertainty score0.998

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.195
Teacher spread0.164 · 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.

Study designNot applicable
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

Citations42
Published2011
Admission routes1
Has abstractyes

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