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Record W2016233067 · doi:10.1190/int-2014-0105.1

Diffraction imaging of polygonal faults within a submarine volcanic terrain, Maverick Basin, south Texas

2015· article· en· W2016233067 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInterpretation · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Imaging and Inversion Techniques
Canadian institutionsnot available
FundersMcGill UniversityUniversity of Texas at Austin
KeywordsDiffractionCurvatureGeologyAmplitudeFault (geology)GeometryCoherence (philosophical gambling strategy)Envelope (radar)SeismologyPhysicsMathematicsOpticsComputer scienceStatistics

Abstract

fetched live from OpenAlex

Abstract Polygonal fault systems are common structural features of intracratonic continental margins. The map-view geometry of these faults became apparent with the use of powerful fault-imaging seismic attributes, such as coherence and curvature. However, these attributes lack the amplitude information necessary for lithological evaluation. We developed a 3D diffraction volume that not only imaged faults but also contained amplitude information. From the unmigrated stack volume, we extracted diffractions that were transformed into amplitude envelope and root-mean-square amplitude volumes. These attributes, together with clay volume (Vclay) data, were extracted along interpreted horizons and fault planes. Crossplots between seismic attributes and Vclay enabled linear relationships between the attributes and Vclay, which were used to infer lithological composition within fault zones. Our results found that, although the fault zones were clay filled, some subvertically inclined clay-poor zones that could serve as permeable pathways were present along the fault planes. In map view, images from diffraction volume were comparable with those obtained from coherence and curvature attributes; however, diffraction images appeared to be busy because of the huge number of diffracted waves embedded in the data. In addition, we found that, although Vclay increases with increasing diffraction energy, no systematic relationship exists between Vclay and curvature, or between Vclay and coherence. As such, curvature and coherence cannot be used to predict lithological distribution within fault zones. Furthermore, we observed that the higher the diffraction energies, the higher the fluid saturation, suggesting higher impedance contrast at the diffraction points. Therefore, we determined that by analyzing diffraction data, it was possible to infer likely sediment variations that largely control permeability within fault zones.

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.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.774
Threshold uncertainty score0.999

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 head0.013
GPT teacher head0.229
Teacher spread0.216 · 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