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Record W3185663823 · doi:10.3968/12102

Research on One Novel Logging Interpretation Method of CBM Reservoir

2020· article· en· W3185663823 on OpenAlexvenueno aff
Qing Feng, Shengsheng Li, Sun Yan-ni, M. Zeng, Xiaonan Li, Xuxing Wang

Bibliographic record

VenueAdvances in petroleum exploration and development · 2020
Typearticle
Languageen
FieldEngineering
TopicCoal Properties and Utilization
Canadian institutionsnot available
Fundersnot available
KeywordsCoalbed methanePetroleum engineeringCoalMethaneCoal miningWell loggingNatural gasVolume (thermodynamics)LoggingMining engineeringEnvironmental scienceGeologyEngineeringWaste managementChemistry

Abstract

fetched live from OpenAlex

Coalbed methane (CBM) is a kind of natural gas which is stored in the micropores and fractures of the “coal seam” and has not been transported out of the source rock. Conventional logging technology plays an important role in coalbed methane exploration and development. By analyzing the response characteristics of conventional logging of coalbed methane, coal bearing strata are accurately determined. Two methods of statistical model and volume model are established to analyze and calculate industrial components. Based on the study of adsorption isotherm and correlation between logging parameters and coal core gas content, the calculation method of coal seam gas content is determined In practices, the calculation accuracy of industrial components and gas content of coal seam has been significantly improved. Abstract: coalbed methane (CBM) is a kind of natural gas which is stored in the micropores and fractures of “coal seam” and has not been transported out of the source rock. Conventional logging technology plays an important role in coalbed methane exploration and development. By analyzing the response characteristics of conventional logging of coalbed methane, coal bearing strata are accurately determined. Two methods of statistical model and volume model are established to analyze and calculate industrial components. Based on the study of adsorption isotherm and correlation between logging parameters and coal core gas content, the calculation method of coal seam gas content is determined In practice, the calculation accuracy of industrial components and gas content of coal seam has been significantly improved.

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: Methods · Consensus signal: none
Teacher disagreement score0.961
Threshold uncertainty score0.300

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 head0.114
GPT teacher head0.347
Teacher spread0.234 · 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
GenreMethods

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
Published2020
Admission routes1
Has abstractyes

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