MétaCan
Menu
Back to cohort
Record W2052661097 · doi:10.1080/10916460701833889

Numerical Techniques Used for Predicting Subsidence Due to Gas Extraction in the North Adriatic Sea

2008· article· en· W2052661097 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePetroleum Science and Technology · 2008
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Imaging and Inversion Techniques
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsGeologySubsidenceAquiferCompactionInterpolation (computer graphics)Petroleum engineeringGeotechnical engineeringComputer scienceGeomorphologyGroundwaterStructural basin

Abstract

fetched live from OpenAlex

Abstract This article describes the assessment and application of numerical techniques required for predicting gas production induced subsidence in the North Adriatic. Due to the complexity of the reservoir description and compaction mechanisms, the subsidence modeling required the combined use of reservoir and geomechanical simulators. Extensive validation of the modeling techniques was undertaken, including the level of coupling between the fluid flow and geomechanical solution. It was shown that a fully coupled solution impacted only the aquifer area, and accurate results could be obtained by an explicitly coupled technique. Other issues of importance discussed include quality control of the mesh generation, mesh compatibility, and correct interpolation of variables between the two modules. Finally, we discuss the impact that small overconsolidation (threshold) effects may have on the extent of the subsidence bowl.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.252
Threshold uncertainty score0.411

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.015
GPT teacher head0.242
Teacher spread0.227 · 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