MétaCan
Menu
Back to cohort
Record W4256269871 · doi:10.2118/2007-042

Laboratory Investigation on the Permeability of Coal During Primary and Enhanced Coalbed Methane Production

2007· article· en· W4256269871 on OpenAlexafffund
R. Guo, K. Mannhardt, A. Kantzas

Bibliographic record

VenueCanadian International Petroleum Conference · 2007
Typearticle
Languageen
FieldEngineering
TopicCoal Properties and Utilization
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsCoalbed methanePetroleum engineeringPermeability (electromagnetism)CoalEnvironmental scienceMethaneGeologyWaste managementCoal miningEngineeringChemistry

Abstract

fetched live from OpenAlex

Abstract Coalbed Methane (CBM) has grown into an important natural gas resource in North America in recent decades. The economical development of CBM heavily relies on coal permeability. The coal permeability is provided through a network of coal cleats and natural fractures. It is greatly affected by the confining stresses and the coal matrix response during gas adsorption and desorption in primary and enhanced recovery processes. This paper is focused on a laboratory investigation of coal permeability variability with different operating parameters. Core flood experiments in coal have been conducted with methane production and methane displacement by CO2. The permeability to different gases (CH4, CO2) under equilibrium conditions was measured at different confining stresses. The coal permeability to helium, which was reported in previous work, provides a comparison baseline. The permeability of a coal core to gases shows a strong dependence on net confining pressure, and exhibits strong hysteresis. The CH4 permeability is relatively smaller than the corresponding He permeability demonstrating a swelling effect of coal by CH4. The adverse effect of CO2 on coal permeability is also shown. The paper focuses on the experimental results obtained to date. Introduction Coalbed methane (CBM) is an unconventional natural gas resource that gains increasing worldwide attention. Using CO2 for enhanced CBM production or using coal beds for CO2 sequestration has also received intense research interest in recent years. CO2 has been proven to have more than twice the affinity to coal than CH4(1). Limited studies have shown the concept of CO2-ECBM to be technically viable. However the mechanisms have not been studied in detail. Permeability of coal is recognized as the most important parameter controlling CBM and ECBM (enhanced CBM) production. Coal cleats are responsible for the permeability of coal. Flow through the cleats is dominated by Darcy flow that relates flow rate to permeability and pressure gradient(2). Methane is the major component of the coalbed gas. Measuring coal permeability to methane is crucial for evaluating CBM production rate. When injecting CO2 into the coalbeds in the ECBM production, the interaction of coal with dense CO2 can be inferred from the permeability changes. Measuring coal permeability to CO2 is the fundamental step to investigate the CO2-ECBM process and potential of CO2 sequestration. Measuring meaningful coal permeability is more difficult than measuring reservoir rock permeability. Only a limited number of research groups have measured the permeability of coal by core flooding, and have pointed out some of the associated difficulties(3), (4), (5). Permeability is provided to coal by the cleats and depends on cleat orientation, spacing, and aperture. The coal matrix swells and shrinks during adsorption and desorption of gases(6), (7). As reservoir pressure is depleted, the net stress due to overburden increases, leading to closure of the cleats. At the same time, gas desorption causes coal matrix shrinkage, which leads to cleat opening. Different gases adsorb on coal to different degrees and are expected to cause different degrees of swelling or shrinkage.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.396
Threshold uncertainty score0.998

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 head0.017
GPT teacher head0.199
Teacher spread0.183 · 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 designBench or experimental
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

Citations9
Published2007
Admission routes2
Has abstractyes

Explore more

Same venueCanadian International Petroleum ConferenceSame topicCoal Properties and UtilizationFrench-language works237,207