MétaCan
Menu
Back to cohort

Low Resistivity Contrast Gas Bearing Formation Identification from Conventional Logs in Tight Gas Sandstones

2013· article· en· W1960821003 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueAdvances in petroleum exploration and development · 2013
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsnot available
Fundersnot available
KeywordsPorosityWater saturationElectrical resistivity and conductivityNeutronNatural gas fieldTight gasSaturation (graph theory)MineralogyBearing (navigation)GeologyGeotechnical engineeringNatural gasChemistryMathematicsNuclear physicsPhysics

Abstract

fetched live from OpenAlex

It’s a great challenge in identifying gas bearing formation from conventional logs in tight gas sandstones due to the low resistivity contrast caused by high irreducible water saturation. Based on the difference of the principles of three kinds of porosity logs (density, neutron and acoustic logs), three porosities difference method, three porosities ratio method, correlation of neutron and density logs and the overlap method of water-filled porosity and total porosity are introduced to identify tight gas bearing reservoirs. In gas bearing formations, the difference of three porosities is higher than 0.0, the ratio of three porosities is higher than 1.0, the correlation between density and neutron logs is negative, and the water filled porosities are lower than total porosities. On the contrary, in water saturated formations, the difference of three porosities is lower than 0.0, the ratio of three porosities is lower than 1.0, the correlation between density and neutron logs is positive, and the water filled porosities are overlapped with total porosities. Considering the complexity of in-suit formation, when the proposed identification criterion are mainly meet, the pore fluid should be determined, field examples show that the proposed techniques are applicable in tight gas formation identification. Key words : Low resistivity contrast gas bearing formation; Tight gas sandstones;  Identification; Difference of three porosities; Ratio of three porosities; Correlation of neutron and density logs

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)0.000
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 score0.333
Threshold uncertainty score0.653

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 communication0.0000.003
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 head0.011
GPT teacher head0.222
Teacher spread0.211 · 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