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Record W3178290791 · doi:10.5194/egusphere-egu21-8981

From seismic geomorphology to hydrostratigraphic units: spatial and temporal variations of deltaic to fluvial architecture, Pannonian Basin, Hungary

2021· article· en· W3178290791 on OpenAlexaff
Hana Ben Mahrez, Lilla Tőkés, John Molson, Judit Mádl‐Szőnyi, Orsolya Sztanó

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological Formations and Processes Exploration
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsSedimentary depositional environmentGeologyFluvialLithologyStructural basinGeomorphologyHydraulic conductivityPaleontologySoil science

Abstract

fetched live from OpenAlex

This study focuses on the stratigraphic architecture of deltaic and fluvial sand lithologies within the Late Neogene Pannonian basin-fill succession in Hungary, identified from seismic and well data, in order to develop a quantitative hydrostratigraphic classification of the sequence. Hydrostratigraphic divisions are based on the hydraulic conductivity of the rock bodies, which depends on their extent, i.e. the thickness and the spatial distribution, as well as the lateral and vertical connectivity of sand bodies embedded in various muddy lithologies. Thus, we are going to build a simplified 3D lithological model for the uppermost 1500 m of the basin fill succession, that can later be transformed into hydrostratigraphic units and hydraulic conductivity values applied in a numerical flow model. The depositional environments change from deltaic to fluvial and within the fluvial system, the environment alternates between meandering and anastomosing. These intervals will appear as different hydrostratigraphic units in the model. In our work-flow, a merged three-dimensional seismic cube covering an area of approximately 50 x 40 km2 was analyzed: 7 master horizons and several proportional slices were delineated in different attribute maps (e.g. amplitude, Root Mean Square amplitude, symmetry, similarity). These maps were generated to investigate the seismic geomorphological features and their associated depositional environments. Rock bodies were defined on the planform geometry of seismic attributes. Basic wireline logs (gamma, spontaneous potential, and resistivity) from 237 wells were interpreted simply in terms of sand, mud, and heterolithic muddy-sand, and finally were tied to the seismic cube. Lithology of rock bodies was determined with the help of well data. With this method, sandy deltaic lobes, sandy fluvial channel belts, and the muddy flood plains were identified. Based on the extension and density of sand bodies, percentages of sand vs clay (net-to-gross; N/G) as well as sand connectivity percentages were determined. Above the deltaic succession, the fluvial depositional setting can be divided into three minor units. These units start with a meandering system, with 500-3600 m wide channel belts and a relatively high N/G. For an interval in the Pliocene about 350 m thick, a transition into an anastomosing river system is observed. This unit is characterized by channels about 100-200 m wide, with significantly lower N/G ratios and less connectedness. In the uppermost part of the succession, large meandering channel belts returned to the area. These changes in river style and paleo-hydrography affect the sand and clay ratio and their connectivity; therefore, definition of previous hydrostratigraphic units must be reconsidered. This research is part of a project that has received funding from the European Union's Horizon 2020 research and innovation program under grant agreement No 810980.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.041
Threshold uncertainty score0.082

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.015
GPT teacher head0.208
Teacher spread0.192 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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".

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Citations1
Published2021
Admission routes1
Has abstractyes

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