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Record W4401480269 · doi:10.56952/arma-2024-0409

Determination of Thermo-Mechanical Coal Deformations and Implication for CO2 Storage in Deep Coal Formations

2024· article· en· W4401480269 on OpenAlexaboutno aff
Kunming Zhang, Shimin Liu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicGeotechnical and Geomechanical Engineering
Canadian institutionsnot available
Fundersnot available
KeywordsCoalPetroleum engineeringGeologyEnvironmental scienceWaste managementEngineering

Abstract

fetched live from OpenAlex

ABSTRACT: CO2 sequestration along with enhanced coalbed methane (ECBM) has received considerable attention for energy recovery and CO2 storage. CO2 injection not only reduces permeability due to the swelling effect but modifies the temperature field, resulting in coupled thermo-mechanical coal deformations. Limited efforts have been devoted towards the understanding of thermo-mechanical deformations in the coalbed methane (CBM) industry. This study proposed a theoretical model of thermal expansion coefficients through energy principle. Direct measurements of coal deformations with variations in temperature and pressure were carried out. The results indicate that thermo-induced deformation linearly correlates with temperature variations with estimated thermo-deformative coefficients between 8×10-5/K to 10×10-5/K, falling within the theoretical bounds. Additionally, the coal matrix retains its elastic properties after thermal cycling. The mechanical compression at different temperatures exhibits similar trends, increasing linearly with pressure. The matrix bulk modulus increases with pressure cycles at elevated temperatures, indicating that the coal becomes stiffer due to residual strain and gradually increases with pressure depletion. Anisotropic matrix deformation was observed when the temperature was above 273.15 K. The deformation of the coal can have significant implications on the evolution of effective stress, permeability, and localized failure, ultimately controlling CO2 sequestration and long-term CBM production. 1. INTRODUCTION CBM is an unconventional natural gas resource stored within coal seams. Over the past four decades, CBM has developed rapidly and become an important energy source in the United States, Canada, Australia, China, et al. (Yang & Liu, 2021). CBM is known for its relatively low risk associated with low costs due to the maturity of CBM exploration, drilling, completion, and stimulation processes (Flores, 2013). In the United States, CBM production peaked at 1.97 trillion cubic feet (TCF) in 2008, and as of 2022, it still contributes 0.72 TCF, accounting for 2% of the overall U.S. natural gas production (U.S. Department of Energy, 2022, 2023). ECBM was first proposed by Puri (Puri & Yee, 1990) to address the inefficiencies resulting from the reservoir pressure reduction during the late time reservoir depletion. More recent attention has focused on the CO2-ECBM technology and CO2 storage, as depicted in Figure 1 (a) (Jessen, Tang, & Kovscek, 2008; Lin, Ren, Cheng, & Nemcik, 2021; Mazzotti, Pini, & Storti, 2009). CO2 can displace methane attributed to its higher affinity for coal, effectively enhancing methane recovery, particularly in low-permeability CBM reservoirs (White, Strazisar, Granite, Hoffman, & Pennline, 2003). Furthermore, this innovative process has a long-term environmental benefit of sequestering and storing CO2 within underground coal seams. The storage potential of CO2 in unminable coal seams is considerable, with estimated capacities ranging from 3 to 200 GtCO2, making it a relevant option for mitigating anthropogenic CO2 emissions (Mazzotti et al., 2009; Metz, Davidson, De Coninck, Loos, & Meyer, 2005). Many researchers have considered that during the CO2 injection process, CO2 adsorption can induce a significant matrix swelling (Figure 1 (b)), resulting in cleat closure and reduction in permeability (Pekot & Reeves, 2002; J.-Q. Shi & Durucan, 2005; Siriwardane, Gondle, & Smith, 2009; G. X. Wang, Wei, Wang, Massarotto, & Rudolph, 2010; White et al., 2005). This reduction in permeability limits the CO2 injection rate, which is critical for the success of CO2-ECBM (Bai et al., 2022; Lu & Connell, 2008; Zhang & Ranjith, 2019). Indeed, in addition to sorption-induced strain, the coal deformation can also be influenced by fluid composition, temperature, and water saturation, as demonstrated in Figure 1 (c), (d), and (e).

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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: Empirical · Consensus signal: none
Teacher disagreement score0.966
Threshold uncertainty score0.312

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 head0.008
GPT teacher head0.221
Teacher spread0.213 · 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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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