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Applications of seismic pattern recognition and gravity inversion techniques to obtain enhanced subsurface images of the Earth's crust under the Central Metasedimentary Belt, Grenville Province, Ontario

2000· article· en· W1979155951 on OpenAlexaffabout
Baishali Roy, R. F. Mereu

Bibliographic record

VenueGeophysical Journal International · 2000
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Imaging and Inversion Techniques
Canadian institutionsUniversity of British ColumbiaWestern University
Fundersnot available
KeywordsGeologyCrustSeismologyInversion (geology)Reflection (computer programming)PrecambrianStackingGeophysicsTectonicsGeochemistry

Abstract

fetched live from OpenAlex

Project Lithoprobe's Abitibi–Grenville transect seismic reflection lines 32 and 33 traverse the exposed Central Metasedimentary Belt (CMB) located in the Grenville province of the Precambrian Shield of Canada in southern Ontario. These seismic lines image a zone with a protracted deformational history spanning more than 300 Myr. Detailed examination of the commercially processed stacked sections reveals a number of significant deficiencies in some important areas. The image quality in these zones of reduced coherency needs to be enhanced to examine specific features and their relation to the surface geology. Examination of near‐vertical seismic data from Lines 32 and 33 revealed that the signal‐to‐noise ratio was not improved by stacking, due to misalignment of signals even after static, normal moveout corrections and residual static corrections. The presumed reason is that reflected seismic energy following long ray paths in heterogeneous media suffers from relative advances and delays in its propagation, and hence arrives at slightly different times at the receivers, tending to be poorly aligned relative to its theoretical traveltime curves. A pattern recognition (PR) method for signal enhancement followed by energy stacking in moving time windows was used in this study to improve the images in spite of misalignments. Reprocessing has refined the geometry of the reflection profiles. The objective of this paper is to use enhanced images of the seismic reflection data obtained by using a PR approach together with gravity data, using 2.5‐D forward and 3‐D inversion routines, to give an improved model of subsurface structure in the vicinity of lines 32 and 33. Line 32 is dominated by southeast‐dipping reflectors soling into the lower crust. The listric geometry of the strong reflection packages of the CMB boundary thrust zone is interpreted to represent a crustal‐scale ramp–flat geometry that accommodated northwest‐directed tectonic transport of the CMB. This interpretation is also supported by the gravity data.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.973
Threshold uncertainty score1.000

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)0.0010.000

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 head0.009
GPT teacher head0.209
Teacher spread0.200 · 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 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

Citations4
Published2000
Admission routes2
Has abstractyes

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