MétaCan
Menu
Back to cohort
Record W2787478749 · doi:10.1155/2018/4931307

3D Seismic Structural Analysis and Basin Modeling of the Matruh Basin, Western Desert, Egypt

2018· article· en· W2787478749 on OpenAlexaff
Farouk I. Metwalli, El Arabi H. Shendi, Bruce S. Hart, Waleed M. Osman

Bibliographic record

VenueInternational Journal of Geophysics · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Imaging and Inversion Techniques
Canadian institutionsMcGill University
Fundersnot available
KeywordsGeologyCenomanianStructural basinCretaceousPaleontologyMaturity (psychological)Basin modellingSource rockTectonicsSubsidence

Abstract

fetched live from OpenAlex

In order to evaluate the hydrocarbon potential of the Matruh Basin, North Western Desert of Egypt, the tectonic history, basin analysis, and maturity modeling of the Albian-Cenomanian Formations of the Matruh Basin were investigated using well logs and 3D seismic data. Structural analysis of the tops of the Bahariya, Kharita, and Alamein Dolomite Formations reveals them to dip to the southeast. Burial history and subsidence curves show that the basin experienced a tectonic subsidence through the Middle-Late Jurassic and Early Cretaceous times. Thermal maturity models indicated that Cenomanian clastics of the Bahariya Formation are in the early mature stage in the east portions of the area, increasing to the mid maturity level in the southwestern parts. On the other hand, the Albian Kharita Formation exhibits a mid maturation level in the most parts of the area. The petroleum system of the Matruh Basin includes a generative (charge) subsystem with Middle Jurassic and Cenomanian sources (for oil/gas) and Turonian sources (for oil), with peak generation from Turonian to Eocene, and a migration-entrapment subsystem including expulsion and migration during Early Tertiary to Miocene into structures formed from Late Cretaceous to Eocene.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.770
Threshold uncertainty score0.437

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 head0.010
GPT teacher head0.236
Teacher spread0.226 · 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.

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".

Quick stats

Citations11
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of GeophysicsSame topicSeismic Imaging and Inversion TechniquesFrench-language works237,207