MétaCan
Menu
Back to cohort
Record W1998559384 · doi:10.3997/2214-4609.20140686

Improved Prediction of Source Rock Maturity in Liquid-rich Unconventional Plays with 3D Basin Modeling

2014· article· en· W1998559384 on OpenAlexaff
Alexander Hartwig, David Jacobi, Gary Walters, Patrick J. Perfetta

Bibliographic record

VenueProceedings · 2014
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsConocoPhillips (Canada)
Fundersnot available
KeywordsSource rockKerogenStructural basinMaturity (psychological)GeologyBasin modellingEarth sciencePetroleum engineeringPaleontology

Abstract

fetched live from OpenAlex

Summary The recent unconventional exploration in North America has shown that the viable liquid-rich zone of most source rock plays is a narrow band. Accurate 3D basin modeling studies can be used to predict these in onshore basins with complex burial histories. This requires a rigorous quality checking of multiple thermal maturity indicators and the erosion estimates. The thermal maturity predictions and calibration to kerogen kinetics can be improved by integrating historic production data (API and GOR) and correcting erroneous thermal maturity measurements. This 3D basin modeling approach is shown on an example from the Permian Basin, USA.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.201
Threshold uncertainty score0.431

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 head0.009
GPT teacher head0.188
Teacher spread0.180 · 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 designSimulation or modeling
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

Citations0
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueProceedingsSame topicHydrocarbon exploration and reservoir analysisFrench-language works237,207