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Record W4378230996 · doi:10.3997/2214-4609.2023101080

Characterising regional evaporite seal for hydrocarbon and CO2 storage — Upper Jurassic, Arab-Hith formations, Saudi Arabia

2023· article· en· W4378230996 on OpenAlexaff
N. Boehm, Frans van Buchem, Thomas Finkbeiner

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicCO2 Sequestration and Geologic Interactions
Canadian institutionsKootenay Association for Science & Technology
Fundersnot available
KeywordsEvaporiteSedimentologyGeologyCretaceousPetroleumGeochemistrySeal (emblem)Abu dhabiPetroleum engineeringPaleontologyArchaeologySedimentary rockGeography

Abstract

fetched live from OpenAlex

Summary At KAUST in the Fall of 2022 we drilled 390 m of core that spans the Upper Jurassic-Lower Cretaceous. The formations include: the Sulaiy, Hith, Arab and top of the Jubaila Formation. The Hith and Arab formations consist and contain important evaporite deposits that act as regional seals. Many of the world’s largest hydrocarbon accumulations in Saudi Arabia and the region (such as the Ghawar field) are contained within these seals. As the energy transition is becoming increasingly significant, the importance of these seals for CO2 storage is also being considered. Characterising these evaporite seals based on their sedimentology, geochemistry and geomechanical properties is essential in order to assess their lateral continuity and sealing capacity, and thus their ability to act as seals for CO2 storage sites. This presentation will present the results obtained from the core regarding the formation thickness and sedimentology, as well as additional geochemical and rock mechanical properties from experimental lab analysis carried out at the ANPERC research lab for Petroleum Engineering at KAUST.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.369
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 head0.023
GPT teacher head0.268
Teacher spread0.245 · 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 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

Citations1
Published2023
Admission routes1
Has abstractyes

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