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Record W1155326440

Assimilation de données géophysiques pour la caractérisation hydrogéologique régionale: optimisation de la séquence.

2015· article· fr· W1155326440 on OpenAlex
Martin Blouin

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
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

VenueEspaceINRS Institutional Digital Repository (Institut National de la Recherche Scientifique) · 2015
Typearticle
Languagefr
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesGeologyPolitical scienceForestryGeographyArt
DOInot available

Abstract

fetched live from OpenAlex

Depuis plus d’une décennie, des groupes de chercheurs en hydrogéophysique comme
\ncelui de la Commission Géologique du Canada ont alimenté l’intérêt pour l’utilisation de
\nla sismique réflexion de proche surface en développant des outils tractables comme
\ndes sources vibrantes portables et des trains de géophones (landstreamer) à trois
\ncomposantes. Ces innovations technologiques, combinées à l’utilisation des ondes de
\ncisaillement pour l’imagerie à haute résolution de la stratigraphie des milieux
\nsédimentaires non-consolidés, ont rendus cette méthode géophysique plus versatile,
\nplus précise et surtout plus économique. En effet, la possibilité de couvrir en une
\njournée de grandes distances linéaires en fait un outil bien adapté pour la
\ncaractérisation à l’échelle régionale. À partir de ces travaux et dans un contexte de
\ncaractérisation hydrogéologique à l’échelle régionale dans les Basses-Terres du Saint-
\nLaurent, cette thèse propose des améliorations à la séquence de travail en assimilation
\nde données géophysiques. Ces avancées sont menées sur trois fronts : l’acquisition
\ndes données, leur traitement et leur intégration pour la construction de modèles de la
\nsous surface. Tout d’abord, comme la configuration des levés de sismique réflexion de
\nproche surface nécessite un faible espacement entre les capteurs et les points de tirs,
\nune quantité importante d’information sous forme brute est reçue lors de l’acquisition.
\nAinsi, il est difficile de procéder à un contrôle de qualité efficace (QC) et presque
\nimpossible de fournir une interprétation du milieu investigué en temps réel. Afin de
\nrégler ce problème, un algorithme de traitement de données « en direct » a donc été
\ndéveloppé. Ensuite, comme l’anisotropie sismique peut affecter le traitement des
\ndonnées, ces paramètres ont été mesurés dans les argiles de la mer de Champlain. Un
\nprofil sismique vertical à neuf composantes a identifié des écarts significatifs de la
\nvitesse des ondes sismiques en fonction de l’angle de propagation. Enfin, une
\nméthodologie a été mise de l’avant pour interpoler les interfaces stratigraphiques à
\nl’échelle régionale. L’approche développée tient compte de la résolution et de la fiabilité
\ndes mesures disponibles, extrait l’information statistique des interprétations de sismique
\nréflexion et peut même servir comme outil de réinterprétation de ces dernières.
\n<br /><br />
\nFor more than a decade, research groups such as the Geological Survey of Canada
\nbuilt the interest for near-surface reflection seismic by proposing small vibrating sources
\nand three components (3C) landstreamers. Developments in the instrumentation
\ncombined with extensive use of shear-wave profiling to image stratigraphy of
\nunconsolidated environments at high resolution have made this geophysical method
\nmore versatile, more accurate, increased cost effectiveness and allowed to cover
\ngreater distance per day. With those major upgrades as a starting point and in a context
\nof regional aquifer characterization in the Saint-Laurent Lowlands, the present study
\nproposes a workflow to further enhance the assimilation of geophysical data. First, as
\nhigh resolution near surface surveys require small shot intervals and multiple channels
\non three axis, a lot of the acquisition information is received under a raw format yielding
\nto unproductive quality control (QC). Hence, a tool was developed to process data “on
\nthe fly” and allow adequate real-time QC and on-site decision making. The algorithm
\nwas constructed in a Python environment and is accessible through a graphical user
\ninterface where the user is prompted for geometry parameters inputs and desired
\nprocessing flow steps. Second, at the scale of seismic wavelengths, fine grain and
\npoorly consolidated sediments such as marine clay of the St-Lawrence Lowlands can
\nbe viewed as a homogeneous medium presenting anisotropy. This section of the study
\nshowed that such geological settings yield to significant seismic velocity variations with
\nangle of propagation that should not be ignore for normal move-out correction, migration
\nor time to depth conversion. Finally, accurate delineation of stratigraphic horizons is an
\nimportant task of any environmental or hydrogeological characterization study. A
\nmethodology was put forward to help integrate geophysical measurements with
\ngeological knowledge in the construction of stratigraphic maps. The approach accounts
\nfor reliability and resolution of the measurements, extracts statistical information from
\nreflection seismic interpretations and can further serve as a tool for reinterpretation of
\nthe seismic 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.

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)0.009
metaresearch head score (Gemma)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Scholarly communication, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.775
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.003
Open science0.0010.000
Research integrity0.0020.002
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 head0.092
GPT teacher head0.315
Teacher spread0.224 · 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