MétaCan
Menu
Back to cohort
Record W2032137395 · doi:10.2118/2008-142

The Stress and Gas Adsorptive Effect on Coal Densities in Laboratory CBM/ECBM Processes

2008· article· en· W2032137395 on OpenAlexaffabout
Rong Guo, Apostolos Kantzas

Bibliographic record

VenueCanadian International Petroleum Conference · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicMinerals Flotation and Separation Techniques
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsStress (linguistics)CoalMaterials scienceEnvironmental scienceWaste managementEngineering

Abstract

fetched live from OpenAlex

Abstract Density is an important coal property that determines the potential of gas resources in CBM reservoir. This paper aims to investigate coal density and structure variation during primary CBM and CO2-ECBM experiments. A coal core sample from Alberta Mannville formation with the rank of SubB was used to conduct the core flooding experiments covering the stages of inert gas flow, methane production, methane displacement by CO2 and inert gas flow after CO2 desorption. The x-ray CT experiments were carried out parallel to the core flooding experiment to provide x-ray images of coal core saturated with different gases at different stress conditions. The x-ray techniques were used for visualization and mapping of larger fractures and mineral streaks, as well as identification of flow paths. The coal density and density distribution changed with the gas adsorptive capacity and the stress condition were obtained. The results show that net stress, gas adsorption capacity, and the production history are all key factors affecting coal core structure, leading coal density and density distribution variations. Hence, the core flow path, which contributes to the coal permeability, changes with those factors during CBM/ECBM processes. The results from this study provide laboratory coal characterization techniques using x-ray imaging analysis. Introduction Coalbed methane (CBM) is a new energy source and has the potential to contribute a significant portion of Canadian natural gas production. Coal reservoir characterization is one of the important steps to successfully develop CBM reservoirs. Coal seams are heterogeneous in terms of lithotypes and morphologies. This creates a challenge in understanding the subsurface behavior of the coal and injected gas during primary and enhanced gas recovery processes. As an organic rock, coal structure is easily deformed by the net stress imposed on it. Besides, adsorption of gases causes the coal matrix to swell and desorption of gases causes the coal matrix to shrink(1, 2). Therefore, coal experiences many changes in stress conditions uring the production life of the CBM reservoir. Because the network of natural fractures and cleats in a coal determines to a large extent the mechanical properties of the coal. Coal is very soft and has low elastic modulus compared to the rock formation. The stress and time dependent deformation of the coal porous structure is expected to change the behavior of the most important properties of the coal, such as porosity and permeability, which in turn change the reservoir production profiles. Coal physical properties such as density are therefore dynamically changed with the coal structure deformation. Coal bulk densities are highly useful for determination of the ash content of the coal. Because of the excellent correlation between core ash and gas content and the excellent correlation between core ash and open-hole bulk density data, it is possible to accurately estimate the gas content from the high resolution bulk density log data(3). Coal bulk density is also used in the estimation of the total gas content in a given drainage area(4).

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.380
Threshold uncertainty score0.991

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 head0.011
GPT teacher head0.230
Teacher spread0.219 · 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 designObservational
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
Published2008
Admission routes2
Has abstractyes

Explore more

Same venueCanadian International Petroleum ConferenceSame topicMinerals Flotation and Separation TechniquesFrench-language works237,207