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Coal Chemical Structure Evolution, Coal Molecule and Methane Adsorption

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A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Energy Systems".

Deadline for manuscript submissions: closed (10 January 2023) | Viewed by 7700

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Special Issue Editors

Dr. Wu Li

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Guest Editor

Key Laboratory of Coalbed Methane Resource & Reservoir Formation Process, Ministry of Education, China University of Mining and Technology, Xuzhou 221008, China
Interests: coal molecule; chemical structure; organic matter
Special Issues, Collections and Topics in MDPI journals

Dr. Junjian Zhang

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Guest Editor

College of Earth Sciences & Engineering, Shandong University of Science and Technology, Qingdao 266590, China
Interests: unconventional resource; methane adsorption; molecular structure
Special Issues, Collections and Topics in MDPI journals

Dr. Tim A. Moore

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Guest Editor

1. School of Earth, Environmental and Biological Sciences, Queensland University of Technology, Brisbane, Australia
2. International Research Center for Coal Geology, China University of Mining and Technology, Xuzhou 221000, China
3. Cipher Consulting Pty Ltd, Kenmore, QLD 4069, Australia
Interests: coal bed methane; coal sedimentology; plant evolution; trace elements

Special Issue Information

Dear Colleagues,

Coalbed methane, an unconventional clean energy, has been a topic of wide concern and been explored in mining safety, economic utilization, and greenhouse gas emission reduction. Methane in coal reservoirs is mainly stored in the pores of the coal matrix in the adsorption state. The molecular structure of coal is highly complex, and the methane adsorption capacity of different rank coals varies significantly. The evolution of the coal macromolecule structure may affect the nanopore structure and its spatial distribution, which affect methane adsorption behavior. Additionally, the distribution of various structural units/groups (e.g., aromatic, aliphatic, and oxygen-containing functional groups) in coal macromolecules may also directly promote/weaken methane adsorption capacity. For coal sorption science, researchers have focused extensively on the influence of coal macromolecular structure, pore morphology, and distribution on methane sorption potential. Frequently, the sorption capacity of various coals is investigated by means of physically experimental tests for pore characteristics (or combined with sorption models) and characterized analysis of macromolecular structures (and/or molecular sorption simulations). The molecular structure controlling mechanism in methane adsorption is an important link concerning basic science problem research and practical production applications. At the molecular level, further explorations are needed to more comprehensively understand the mechanisms controlling the methane adsorption properties of coal macromolecule structures with different degrees of evolution.

Topics include but are not limited to:

Differences and mechanisms of methane adsorption/desorption in coals for various coal ranks;
Molecular simulation of methane adsorption behavior;
The influence of coal chemical structure evolution on micro-nanopore structure;
Molecular structure of coal controlling methane adsorption capacity;
New methods, experiments, and theories for characterizing methane adsorption in coal.

Dr. Wu Li
Dr. Junjian Zhang
Dr. Tim A. Moore
Guest Editors

Manuscript Submission Information

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Keywords

methane adsorption/desorption
coalification/evolution
various rank coals
coal macromolecular structure
controlling mechanism
micro-nanopore

Published Papers (7 papers)

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Editorial

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3 pages, 149 KiB

Open AccessEditorial

Coal Molecular Structure Evolution for Methane Adsorption Molecular Mechanism

by Wu Li

Processes 2024, 12(1), 20; https://doi.org/10.3390/pr12010020 (registering DOI) - 21 Dec 2023

Viewed by 408

Abstract

Coal is complex as it includes organic matter (macerals) and inorganic matter (minerals) [...] Full article

(This article belongs to the Special Issue Coal Chemical Structure Evolution, Coal Molecule and Methane Adsorption)

Research

Jump to: Editorial

19 pages, 7561 KiB

Open AccessFeature PaperArticle

Research on Pore-Fracture Characteristics and Adsorption Performance of Main Coal Seams in Lvjiatuo Coal Mine

by Wu Li, Jin Li, Changqing Hu and Qianlong Xiao

Processes 2023, 11(6), 1700; https://doi.org/10.3390/pr11061700 - 02 Jun 2023

Viewed by 848

Abstract

Gas prevention and control have always been the focus of coal mine safety. The pore structure characteristics and gas adsorption characteristics of coal seams are the key factors affecting gas adsorption and diffusion in coal seams. Lvjiatuo Mine has the characteristics of a high gas content when it enters deep mining. In order to clarify the influence of the pore-fracture structure characteristics of main coal seams in the research area on coal seam gas adsorption and diffusion, and to study the differences in gas adsorption and diffusion ability in different coal seams, low-temperature nitrogen adsorption (LT-N₂GA), high-pressure mercury intrusion (MIP) and computerized tomography (μ-CT) were used as characterization methods, and methane isothermal adsorption experiments were carried out to systematically study the pore structure characteristics of five groups of coal samples, and the pore-fracture structure characteristics and gas adsorption characteristics of each main coal seam were obtained. The results show that: (1) in the LT-N₂GA experiment, the adsorption–desorption curves of all coal samples are of type III, and mainly develop cone-shaped pores or wedge-shaped semi-closed pores, with an average pore size of 1.84~4.84 nm, a total pore volume of 0.0010~0.0023 mL/g, a total specific surface area of 0.16~0.24 m²/g, and a fractal dimension D₁ of 1.39~1.87 and D₂ of 2.44~2.60. The micropores of L12 are more developed, and the mesopores and macropores of L9 are more developed. (2) In the MIP experiment, the porosity of coal samples is 3.79~6.94%. The porosity of L9 is the highest, the macropore ratio is the highest, and the gas diffusion ability is also the strongest. (3) In the μ-CT experiment, the porosity of L8-2 and L12 is 12.12% and 10.41%, the connectivity is 51.22% and 61.59%, and the D_f is 2.39 and 2.30, respectively. The fracture of L12 is more developed, the connectivity is better, and the heterogeneity of the pore of L8-2 is higher. (4) In the isothermal adsorption experiment of methane, the gas adsorption capacity basically increases with the increase in the buried depth of the coal seam, and the gas adsorption capacity of the No.12 coal seam is the highest. Based on the pore-fracture structure characteristics and gas adsorption characteristics of the main coal seams in the research area, the gas outburst risk of each coal seam is ranked as follows: No.12 coal seam > No.8 coal seam > No.7 coal seam > No.9 coal seam. The experimental results provide important help for researching the structural characteristics of coal seam pore fractures and preventing gas outbursts during deep coal seam mining. Full article

(This article belongs to the Special Issue Coal Chemical Structure Evolution, Coal Molecule and Methane Adsorption)

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18 pages, 11890 KiB

Open AccessArticle

CBM Gas Content Prediction Model Based on the Ensemble Tree Algorithm with Bayesian Hyper-Parameter Optimization Method: A Case Study of Zhengzhuang Block, Southern Qinshui Basin, North China

by Chao Yang, Feng Qiu, Fan Xiao, Siyu Chen and Yufeng Fang

Processes 2023, 11(2), 527; https://doi.org/10.3390/pr11020527 - 09 Feb 2023

Cited by 4 | Viewed by 1260

Abstract

Gas content is an important parameter for evaluating coalbed methane reservoirs, so it is an important prerequisite for coalbed methane resource evaluation and favorable area optimization to predict the gas content accurately. To improve the accuracy of CBM gas content prediction, the Bayesian hyper-parameter optimization method (BO) is introduced into the random forest algorithm (RF) and gradient boosting decision tree algorithm (GBDT) to establish CBM gas content prediction models using well-logging data in the Zhengzhuang block, south of Qinshui Basin, China. As a result, the GBDT model based on the BO method (BO-GBDT model) and the RF model based on the BO method (BO-RF model) were proposed. The results show that the mean-square-error (MSE) of the BO-RF model and the BO-GBDT model can be reduced by 8.83% and 37.94% on average less than that of the RF and GBDT modes, indicating that the accuracy of the models optimized by the BO method is improved. The prediction effect of the BO-GBDT model is better than that of the BO-RF model, especially in low gas content wells, and the R-squared (RSQ) of the BO-GBDT model and the BO-RF model is 0.82 and 0.66. The accuracy order of different models was BO-GBDT > GBDT > BO-RF > RF. Compared with other models, the gas content curve predicted by the BO-GBDT model has the best fitness with the measured gas content. The rule of gas distribution predicted by all four models is consistent with the measured gas content distribution. Full article

(This article belongs to the Special Issue Coal Chemical Structure Evolution, Coal Molecule and Methane Adsorption)

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18 pages, 6948 KiB

Open AccessArticle

Base-Level Fluctuation Controls on Migration of Delta Lobes: A Case Study from the Paleogene Shahejie Formation in the Huimin Depression, Bohai Bay Basin, NE China

by Renchao Yang, Yang Li, Xuepeng Wu, Jianqiang Di, Junjian Zhang and Nils Lenhardt

Processes 2023, 11(2), 378; https://doi.org/10.3390/pr11020378 - 25 Jan 2023

Viewed by 1026

Abstract

Sandbody distribution patterns and controls are the most important foundation for petroleum exploration and development, particularly in a lacustrine basin with rapid changes in the sedimentary environment. To provide sedimentologists and petroleum geologists around the world with an analogue for sandstone reservoir prediction, the sedimentary facies of the fourth member of the Shahejie Formation (Sha-4 Member) in the Huimin Depression of the Bohai Bay Basin were analyzed, and the sequence stratigraphic framework was established based on characteristics of spontaneous potential logs and lithology. According to the findings of this study, the Sha-4 Member’s sedimentary environment was dominated by delta front and shallow lake facies. Delta front sandbodies were discovered to retrograde before prograding again throughout the established profile. The Sha-4 Member in the Huimin Depression is divided into a third-order sequence (LSC1), which can be further divided into four fourth-order sequences (MSC1 to MSC4), corresponding to the four sub-members (S4-1 to S4-4). During the development of the MSC1 to MSC4 sequences, the delta depositional scale first decreased and then increased with the changing base level. The maximum flooding surface developed within the MSC3 sequence. The Sha-4 Member sequence model reveals that the deltas in the study area exhibit self-similarity, and delta sandbodies are primarily developed in the MSC1, MSC2, and MSC4, whereas mudstone is largely developed in the MSC3. Full article

(This article belongs to the Special Issue Coal Chemical Structure Evolution, Coal Molecule and Methane Adsorption)

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17 pages, 5023 KiB

Open AccessArticle

Pore Structure Multifractal Characteristics of Coal Reservoirs in the Central and Eastern Qinshui Basin and Influencing Factors

by Chaochao Duan, Xuehai Fu, Ze Deng, Junqiang Kang, Baoxin Zhang, Jielin Lu, Xing Hong, Ruirui Dai and Xiaogang Li

Processes 2023, 11(1), 286; https://doi.org/10.3390/pr11010286 - 16 Jan 2023

Viewed by 1336

Abstract

The heterogeneity of the pore structure of coal reservoirs affects the desorption and diffusion characteristics of coalbed methane, and determining its distribution law is conducive to improving the theory of coalbed methane development. The central and eastern parts of the Qinshui Basin are rich in coalbed methane resources, but the heterogeneity characteristics of the pore structure of coal reservoirs are not clear. NMR has the advantages of being fast, non-destructive and full-scale, and multifractal can describe the self-similarity of NMR T2 curve at different scales so as to analyze the complexity of pore distribution. Based on this, 15 samples with different coal ranks were collected from the central and eastern Qinshui Basin (R_o,max between 1.54 and 2.78%), and quantitative pore characterization experiments such as low-field nuclear magnetic resonance (LF-NMR) and low-temperature liquid nitrogen adsorption (LTN₂A) were conducted. Based on multifractal theory, the heterogeneity law of pore structure was quantitatively evaluated, and its influencing factors were elucidated. The results showed that the BJH pore volume of coal samples in the study area ranged from 0.0005–0.0028 cm³/g, with an average of 0.0014 cm³/g, and the BET specific surface area was 0.07–2.52 m²/g, with an average of 0.41 m²/g. The NMR T₂ spectrum peaked at 0.1–1, 10–100 and 100–1000 ms, and the spectrum was mostly bimodal or trimodal, indicating that pores of different pore sizes were developed. There were great differences in the pore structure of different coal ranks; high-rank coal was dominated by micropores, and the proportion of mesopores and macropores of medium-rank coal was higher. The pore structure of coal samples showed obvious multifractal characteristics, and the fractal characteristics of the sparse region (low-value information) were more significant; they dominated the pore distribution and had a stronger influence on the distribution of pore space. Pore structure heterogeneity is closely related to the degree of coalification, and with the increase in coalification, it is closely related to coal lithotype and quality, and high mineral and inertinite contents lead to the enhancement of pore structure heterogeneity in coal reservoirs, while R_o,max, M_ad and vitrinite group contents have opposite effects. The research results provide theoretical guidance for the subsequent exploration and development of coalbed methane in the region. Full article

(This article belongs to the Special Issue Coal Chemical Structure Evolution, Coal Molecule and Methane Adsorption)

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16 pages, 4818 KiB

Open AccessArticle

Interpretation Method for Lost Gas in Deep Coalbed and Its Application

by Ze Deng, Hongyan Wang, Zhenxue Jiang, Fenghua Tian, Rong Ding, Songyi Hou, Wuzhong Li, Yanan Li, Jiyue Zhu, Longfei Li and Xuefan Wang

Processes 2023, 11(1), 200; https://doi.org/10.3390/pr11010200 - 08 Jan 2023

Cited by 1 | Viewed by 1087

Abstract

The gas loss time during the deep coalbed coring process is long. The measured desorption curve does not meet the application conditions for the classical United States Bureau of Mines (USBM) method. However, the industry still lacks a reliable interpretation method, which affects identifying deep coalbed methane reserves and optimizing sweet spots. (Method) The classical double-porosity and double-permeability theoretical model was adopted, and the influence of reservoir permeability, water saturation, and temperature on gas output in the coalbed desorption process was considered. Based on the measured field desorption data of the P1 sample of the No. 8 coal in the Benxi Formation on the eastern margin of Ordos, the entire process for the deep coalbed gas content test was numerically simulated. (Results) The simulation results show that the lost gas in the P1 sample accounts for 24.7% of the total gas, reaching 8.64 m³/t, including 18.81% of loss in wellbore lifting and 5.88% of loss during surface exposure. The total gas content of the sample is 35.34 m³/t. The P1 sample contains free gas, with a content of 9.71 m³/t, and the ratio between adsorbed and free gas is close to 7:3. Matrix permeability, initial gas saturation, and lifting time are the key factors that determine the amount of lost gas. The results of deep coalbed gas loss calculated by the USBM method were excessively large, approximately twice that calculated using the new method. The total gas content calculated based on multiple parameters is consistent with the interpretation results of the new method, with an average error of approximately 7%. (Conclusion) The interpretation method of gas loss in deep coalbeds has acceptable reliability and can be applied in shale gas content testing. Full article

(This article belongs to the Special Issue Coal Chemical Structure Evolution, Coal Molecule and Methane Adsorption)

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20 pages, 4191 KiB

Open AccessArticle

The Role of Non-Covalent Bonds in the Deformation Process of Coal: An Experimental Study on Bituminous Coal

by Hewu Liu and Chenliang Hou

Processes 2022, 10(9), 1875; https://doi.org/10.3390/pr10091875 - 16 Sep 2022

Cited by 1 | Viewed by 1169

Abstract

The chemical structures of tectonically deformed coal are significantly altered by stress. However, the stress response of non-covalent bonds in deformation experiments and the role of non-covalent bonds in the deformation process of coal have not been studied yet. In this work, coals before and after simulative deformation experiments were systematically investigated to uncover the coal’s deformation mechanism and the variation of non-covalent bonds. The results indicate that differential stress and temperature can promote ductile deformation while confine pressure hinders the deformation process. Differential stress and temperature in the ranges of 100–150 MPa and 100–200 °C, respectively, are key transition conditions from brittle to ductile deformation for the selected bituminous coal. Furthermore, hydrogen bonds and π–π bonds crosslinking coal molecular networks determine the mechanical properties of the coal. The simulative deformation experiments indicate that, with an increase in the coal’s deformation intensity, hydrogen bonds and π–π bonds are inclined to be disrupted in the relaxation stage, which enhances the motion ability of the liberated molecular structures and reduces the brittleness of the coal. In the rearrangement stage, tighter and more ordered configurations are formed, accompanied by the formation of π–π bonds. Coals in the deformation experiments are inclined to undergo ductile deformation once sufficient non-covalent bonds are cleaved in the relaxation stage. Full article

(This article belongs to the Special Issue Coal Chemical Structure Evolution, Coal Molecule and Methane Adsorption)

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