MétaCan
Menu
Back to cohort
Record W2617328103 · doi:10.3997/2214-4609.201700626

Deterministic and Probabilistic Volumetric Evaluations of an Iranian Field in an Exploration Reservoir

2017· article· en· W2617328103 on OpenAlexaff
M. Ghoroori, Mohammad Mahdi Khalili, O. Neisarifam, J. Akhlaghi, L. Matin

Bibliographic record

VenueProceedings · 2017
Typearticle
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsPetro-Canada
Fundersnot available
KeywordsProbabilistic logicOil fieldPetroleum engineeringSensitivity (control systems)Volume (thermodynamics)DiagramComputer scienceField (mathematics)TornadoPorosityOil explorationKey (lock)GeologyAlgorithmMathematicsStatisticsGeotechnical engineeringEngineeringArtificial intelligencePhysics

Abstract

fetched live from OpenAlex

Summary Volumetric evaluation of exploration reservoirs is one of the most significant and key steps during field development. In this study, volumetric estimation was performed on the target formation and uncertainty analysis was done in two approaches while considering the variation of parameters such as contact, NTG, porosity, Sw and Bo. One should note that, the map-based approach is more accurate than considering a single average value. Sensitivity analysis was also done in order to determine the most effective parameter on the estimated oil in place. The Tornado diagram demonstrates that contact is the most effective parameter in volume calculation.

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)0.001
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 score0.073
Threshold uncertainty score0.413

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.080
GPT teacher head0.360
Teacher spread0.281 · 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

Citations1
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueProceedingsSame topicReservoir Engineering and Simulation MethodsFrench-language works237,207