Coalbed Methane Content Research Articles

In Situ Gas Content and Extraction Potential of Ultra-Deep Coalbed Methane in the Sichuan Basin, China

In Situ Gas Content and Extraction Potential of Ultra-Deep Coalbed Methane in the Sichuan Basin, China

Experimental research on biogenic methane generation pathway and microflora constraints based on in-situ gas-water-microbe

Biogenic coalbed methane (CBM), generated through the biodegradation process of coal organic matter, is a relatively clean and environment-friendly unconventional natural gas resource. To investigate the differences in microbial communities (bacteria and archaea) as well as their environmental influencing factors between the Permian Shanxi Formation (P1s) and Taiyuan Formation (P1t), we systematically collected in-situ CBM samples along with coalbed water and microbial samples from a representative biogenic CBM field – the Baode block locked in the Ordos basin in China. The relative content of biogenic CBM was quantitatively calculated while analyzing gas composition, stable isotope, ion content, and high-throughput sequencing analysis to discuss the generation pathway for biogenic CBM and environmental control factors affecting microbial community structure. The results indicate that P1s and P1t are mixed with early thermogenic gas and secondary biogenic gas genetic types within their respective CBMs. The average proportion for biogenic gas within current coal seams is approximately 62.24 % for P1s, while it reaches around 64.37 % for P1t. Water quality type primarily consists of Na-HCO3 type with total dissolved solids (TDS) measuring at approximately 1015.86 mg/L for P1s, whereas P1t exhibits Na-Ca-HCO3-Cl water type with TDS content reaching about 2314.85 mg/L. Combining dominant Methanobacterium species, along with Δ13C(CO2-CH4) ratios and δD(CH4) versus δD(H2O) indexes, represents the biogenic CBM primarily generated through the hydrogenotrophic methanogenesis pathway. The in-situ bacterial communities of P1s are mainly influenced by Ni, pH, and TDS. The archaeal communities exhibit higher sensitivity to environmental factors (such as Co, pH, Ni, and dissolved organic carbon) than bacteria. These findings hold significant implications for understanding the generation process of biogenic CBM in middle and low-rank coal areas.

Optimized Random Forest Method for 3D Evaluation of Coalbed Methane Content Using Geophysical Logging Data.

Accurate evaluation of coalbed methane (CBM) content is crucial for effective exploration and development. Traditional gas content measurement methods based on laboratory analysis of drill core samples are costly, whereas geophysical logging methods offer a cost-effective alternative by providing continuous high-resolution profiles of rock layer physical properties. However, the relationship between CBM content and geophysical logging data is complex and nonlinear, necessitating an advanced prediction method. This study focuses on the No. 3 coal seam in the Shizhuang South Block of the Qinshui Basin, utilizing geophysical logging data and 148 sets of laboratory core samples. We employed the Random Forest (RF) method optimized with a simulated annealing-genetic algorithm (SA-GA) to develop the SA-GA-RF model for evaluating CBM content. The model's performance was validated using test data and new CBM well data, and it was applied to calculate the vertical gas content profiles of No. 3 coal seam across 128 wells. The SA-GA-RF model demonstrated an average relative error of 13.13% in the test data set, outperforming Backpropagation Neural Network (BPNN), Least Squares Support Vector Machine (LSSVM), Extreme Learning Machine (ELM), and multivariate regression (MR) methods. The model also exhibited strong generalizability in new wells and improved model-building efficiency compared to traditional cross-validation grid search methods. The construction of a three-dimensional CBM content model, incorporating well coordinates and elevation data, allowed for detailed identification of high gas content areas and layers. This three-dimensional model offers a more precise characterization than traditional two-dimensional isopleth maps, providing valuable insights for CBM exploration, reserve evaluation, and production optimization.

Gas desorption characteristics of coal particles under dynamic temperature changes: Implication for the lost gas estimation during borehole coal sampling

The estimation of lost gas during borehole coal sampling determines the accuracy of coalbed methane (CBM) content determination. The isothermal desorption data is used frequently for analyzing the estimation error of the lost gas, which is not consistent with the engineering practice that the gas desorption during borehole coal sampling is in dynamic temperature changing condition (i.e., DTC), thus resulting in the result of the lost gas estimation is not accurate. In this study, a DTC adsorption/desorption experimental system was set up to study the gas desorption characteristics of coal particles during borehole coal sampling, and the differences between isothermal desorption and DTC desorption were analyzed in detail. Furthermore, the isothermal desorption data and DTC desorption data were fitted using the unipore diffusion model (UDM) to discuss the influence of DTC desorption on the lost gas estimation. Finally, the fractional diffusion model (FDM) was applied to estimate the lost gas. The results showed that there is a significant difference between isothermal desorption and DTC desorption. For the case of DTC desorption, more gas will be lost at the same exposure time, resulting in the lost gas being underestimated in the CBM content determination. With the exposure time of 12 min, the average fitting errors of lost gas using the FDM with different coal particle sizes and gas pressures are less than 17.9%, while that using the UDM are greater than 57.5%, suggesting that the FDM could improve the fitting accuracy of lost gas estimation in the CBM content determination.

Gas desorption characteristics in different stages for retained water infiltration gas-bearing coal and its influence mechanism

Coal seam water injection (CSWI) can introduce additional water to form retained water. The migration of retained water will go through the stage from the end of CSWI to water migration equilibrium and the stage of water re-migration caused by the connection between the wetting area and the atmosphere. However, the gas desorption characteristics in two water migration stages reflect the effect of CSWI for gas control. To clarify the evolution characteristics of gas desorption, an experimental platform for simulating gas desorption characteristics of different stages was developed. The following results are obtained through the platform test and theoretical analysis. When the retained water transport equilibrium, the maximum replacement gas efficiency was inversely proportional to the gas pressure and proportional to the retained water content, respectively. The retained water infiltration gas-bearing coal can reduce the degree of water lock in the fractures and increase the wetting degree of pores. The interaction energy between coal molecules and water molecules was proportional to the number of water molecules added and inversely proportional to the gas pressure, respectively. The methane molecules interfered with the interaction between coal molecules and water molecules. After the water infiltration equilibrium was broken, the maximum gas desorption efficiency was inversely proportional to gas pressure and the retained water content, respectively. In a word, retained water can promote gas desorption and reduce coalbed methane content. The CSWI should be employed in advance to increase the wetting time, improve displacement gas efficiency, and delay gas emission when the working face mines. The research result provides some theoretical foundation for the rational use of CSWI for the gas control of coal mine.

Quantitative Prediction of Deep Coalbed Methane Content in Daning-Jixian Block, Ordos Basin, China

The potential of deep coalbed methane resources is substantial. Gas content is an important parameter for resource assessment. At present, the gas content test method commonly used for shallow coal reservoirs is not suitable for determining deep coalbed methane gas content. Therefore, it is urgent to establish a prediction method for deep coalbed methane gas content. This study aims to quantitatively predict the gas content of coalbed methane in deep coal reservoirs and uncover its influencing factors. For this purpose, we selected the Daning-Jixian area, a region in China with relatively advanced development of deep coalbed methane, as a case study. It established a prediction model for adsorbed gas and free gas content in deep coal reservoirs through a series of experimental tests, encompassing gas content, coal quality, isothermal adsorption, and nuclear magnetic resonance. The model sheds light on the impact of coal-rock characteristics, coal quality attributes, and pore characteristics on adsorbed gas and free gas content. The results show that adsorbed gas dominates in deep coal reservoirs with a high metamorphic degree and that the average proportion of adsorbed gas under reservoir burial depth is 80.15%. At a depth of approximately 1800~2000 m, a turning point is observed where adsorbed gas content begins to decline. Beyond this depth range, the detrimental effect of temperature on coalbed methane content surpasses the beneficial impact of pressure. Coal quality characteristics play a major role in controlling adsorbed gas content, and an increase in water content and ash yield significantly reduces the adsorption performance of coal reservoirs. The content of free gas increases with the increase in burial depth, with its controlling factors primarily being confining pressure and porosity. The increase in the proportion of micropores in the pores of deep coal reservoirs has an adverse effect on the content of free gas. The proportion of adsorbed gas in deep coal reservoirs gradually decreases with the increase in burial depth, while the proportion of free gas gradually rises with the increase in burial depth. The development potential of free gas cannot be overlooked in the exploration and development of deep coalbed methane.

Coalbed Methane Enrichment Regularity and Model in the Xishanyao Formation in the Santanghu Basin, NW China

The Santanghu Basin is a typical low-rank coal-bearing basin in northwest China, with abundant coalbed methane (CBM) resources. However, the understanding of the main controlling factors and reservoir formation models of CBM in low-rank coal is still insufficient, which has restricted the exploration and development of CBM in this region. In this paper, the CBM enrichment controlling factors and enrichment models are analyzed based on the aspects of sedimentary environment, reservoir characteristics, sealing conditions, and hydrogeological conditions after systematically analyzing the geological characteristics of coal measures. The research results indicate that the coal seams of the Xishanyao Formation in the Santanghu Basin are stably developed, with the main macerals being vitrinite and a lower degree of coalification belonging to low-rank coal; the highest content of CBM can reach 7.17 m3/t, and the methane is mainly composed of biogenic gas supplemented by thermogenic gas; the roof lithology of the coal seam is mainly mudstone and siltstone, with good sealing conditions. Finally, two enrichment modes of coalbed methane in slope zones are proposed, namely, the CBM enrichment in the slope zone and the CBM enrichment by fault-hydraulic plugging. The results of this study can serve as a guide for the exploration and development of the deep-buried coalbed methane in the low-rank coal areas.

New Data-Driven Method for In Situ Coalbed Methane Content Evolution: A BP Neural Network Prediction Model Optimized by Grey Relation Theory and Particle Swarm

New Data-Driven Method for In Situ Coalbed Methane Content Evolution: A BP Neural Network Prediction Model Optimized by Grey Relation Theory and Particle Swarm

South Anze Structure and Its Control on Coalbed Methane Aggregation in the Qinshui Basin and the Mechanism of Syncline Gas Enrichment in the Qinshui Basin

The phenomenon of coalbed-methane synclinal accumulation in the Qinshui Basin has been widely reported, but it has mainly been observed in the core block of the Qinshui Syncline. The questions arise: does this phenomenon exist in the wing of the Qinshui Syncline and, if so, what is the mechanism behind it? Further study is required to answer these questions. This paper focuses on the South Anze No. 3 coal seam in the Qinshui Basin as an example. It conducts a systematic sorting of coalbed-methane geological characteristics and an analysis of the effects of structural assemblage characteristics, genetic mechanisms, and structural control on coalbed-methane accumulation. Additionally, it examines the basin structure and evolution during the critical period of the Qinshui Basin, as well as the gas geological characteristics of adjacent areas, in order to discuss the gas-rich mechanism of the syncline in the Qinshui Basin. Key insights obtained from the study include the following: (i) The whole South Anze is a nosing structure that plunges from west to east and superposes secondary folds and faults in different directions. Four deformation zones can be identified based on the characteristics of structural assemblage, including NEN-oriented compressive structures, ENE-trend shear fractures, EW-trend compressive fractures, and EW-trend compressive folds. The formation of structural assemblage in the study area is attributed to the compression in the Indosinian and Yanshanian, and the fault inversion in the Himalayan period. (ii) The ENE-trend shear fracture deformation area located in the nosing uplift is a low CBM (coalbed methane) content area due to gas diffusion during the Himalayan extension. The syncline in the combination of NEN-trend and EW-trend “ejective folds” in the west and south of the study area is a high-value area of coalbed-methane content. It is further verified that the law of syncline gas accumulation in the Qinshui Basin is also applicable to the wing of the Qinshui Syncline. (iii) Since the formation of the Qinshui Syncline, the main coal seam has been in an extensional environment below the neutral plane, resulting in the main dissipation of coalbed methane. During its geological history, surface water penetrated the aquifer above the main coal seam through two channels: the extensional area above the neutral plane of the adjacent anticline and the shear fracture. A hydrostatic pressure seal is formed in the Qinshui Syncline and the secondary syncline is superimposed upon it, which is the cause of gas enrichment in the syncline of the Qinshui Basin. (iv) Weak deformation in the syncline basin is the focus of global coalbed-methane exploration and development. The mechanism proposed in this paper can provide ideas and references for further understanding of coalbed-methane enrichment in this type of basin.

Study on the Characteristics and Model Optimization of Coal Particle Gas Emission Law.

In order to further clarify the transport mechanism of coalbed methane and to study the gas diffusion law in coal, this paper conducted an experimental study on the desorption law of coal particle gas. On the basis of experiment, the time-varying characteristics of the diffusion coefficient in the process of coal particle gas desorption were analyzed, and the gas diffusion calculation model considering the time-varying diffusion coefficient was obtained by experimental fitting. On this basis, the influence of coal particles with different shapes on the gas desorption law is studied, and the gas diffusion equations of flat and cylindrical coal particles based on time-varying diffusion coefficients are established. The corresponding analytical solutions are obtained by using mathematical and physical methods, and the results are verified. The results show that the larger the adsorption equilibrium pressure is, the larger the gas desorption capacity is. At the initial stage of desorption, the larger the particle size is, the smaller the desorption capacity and desorption speed are. However, after reaching the "limit particle size", the particle size has little influence on the desorption capacity and desorption speed. Under different temperature conditions, the gas desorption amount monotonously increases with time. The higher the temperature is, the greater the desorption amount is. The adsorption constant a value slightly increases with the increase of temperature and then decreases. The adsorption constant b value has a trend of decreasing with the increase of temperature. The research results have very important practical significance for the optimization of the testing method of underground coalbed methane content and the prediction of coal and gas outburst risk.

Prediction of coalbed methane content based on seismic identification of key geological parameters: a case in a study area, Southern Qinshui Basin

Prediction of coalbed methane content based on seismic identification of key geological parameters: a case in a study area, Southern Qinshui Basin

Coalbed methane enrichment prediction and resource estimation for the areas with different tectonic complexities

Geological tectonic movement plays a controlling role in the distribution pattern of coalbed methane (CBM) resources. The traditional CBM resource estimation methods use the measured CBM as the overall CBM content and do not consider the influence of geological structure on the nonuniform distribution of CBM resources. In this paper, the geological structure of the Guojiahe coalfield in the northern Yonglong mining area, China, was used as the research background. Based on the precise three-dimensional (3D) seismic interpretation results of the coal seam geological structure and the tested CBM contents at sampling points, a fuzzy comprehensive evaluation method was used to classify the tectonic complexity of the study area, and the CBM contents of different tectonic locations in the tested coal seams and the results determined by the finite element method were analyzed. On this basis, a quantitative relationship between the tectonic complexity index and the amount of CBM resources was established, and finally, a CBM-enrichment prediction model and a CBM resource estimation method for areas with different tectonic complexities were proposed. The agreement between the amount of CBM resources obtained by the estimation method and the actual exploration result is 85.2%; therefore, the proposed method has a theoretical guidance and engineering application value for the exploration and precise development of CBM resources.

Coalbed Methane Reservoir Parameter Prediction and Sweet-Spot Comprehensive Evaluation Based on 3D Seismic Exploration: A Case Study in Western Guizhou Province, China

As a kind of clean energy, the exploration and development of coalbed methane (CBM) are of great importance and significance. In this paper, the CBM reservoir parameters of a working area in Western Guizhou Province, China, were predicted by using 3D seismic exploration technology, and the sweet-spot area was evaluated based on the prediction results. In terms of data interpretation, while the traditional technology is extended to the study of CBM, new technologies and methods suitable for CBM were also actively explored, especially in the quantitative prediction methods of parameters such as coal seam thickness, CBM content, coal body structure, in situ stress, etc., and a three-highs quantitative prediction technology of CBM sweet spots characterized by high precision, high resolution, and high coincidence was explored, which is based on logging evaluation and petrophysics. In addition, in the comprehensive evaluation of multiparameter sweet spots, the multiparameter weighted step-by-step evaluation method based on inversion was innovatively proposed, which made the prediction of CBM sweet spots more focused, effective, and practical, and the distribution law of sweet spots was more consistent with the geological law, providing enough basis for subsequent well location deployment. Based on this method, the C409 coal seam was selected as the sweet spot.

Selection of machine learning algorithms in coalbed methane content predictions

Selection of machine learning algorithms in coalbed methane content predictions

Evaluation of Coalbed Methane Content by Using Kernel Extreme Learning Machine and Geophysical Logging Data

Accurate evaluation of coalbed methane (CBM) content plays a momentous role in the identification and efficient development of favorable exploitation blocks of CBM resources, but there are still many technical challenges in the exploration and development of onshore CBM fields. With the development and application of geophysical logging technology, using geophysical logging data to predict the gas content of CBM reservoirs has been proven to be an effective and feasible solution. However, the complex logging response of the CBM reservoirs makes it difficult to characterize the relationship between the gas content and the logging curve response by a simple linear relationship. In this paper, kernel extreme learning machine (KELM), a machine learning method, is combined with the geophysical logging data to predict the vertical variation curve of gas content in CBM wells. In this paper, the laboratory data on coal rock gas content from 12 CBM wells in the Southern Shizhuang block are selected, and a CBM content prediction model based on the KELM method is constructed by selecting the log curves, combining cross-validation and grid-seeking to determine the hyperparameters, and validating the prediction model using the test dataset and a new well in the same block. The application of the model on the test dataset was remarkable, and the vertical variation of CBM content obtained by applying it to the new well was consistent with the laboratory results, which proved the correctness and generalizability of the model. The results of this paper show that the CBM content evaluation model based on the KELM method and geophysical logging data is applicable to the 3# coal seam in the target block and can be used to predict the vertical CBM content of CBM wells; compared with the extreme learning machine (ELM) method and the backpropagation neural network (BPNN) method, the KELM method requires fewer hyperparameters to be explored when constructing the CBM content evaluation model, and the model construction is simple and has high prediction accuracy. At the same time, the CBM content model constructed by the KELM method differs for different blocks, coal seams at different depths, and different response ranges of geophysical logging data. The construction of a CBM content prediction model using the KELM method and logging curves is an effective means of characterizing CBM resources, and the model construction process and evaluation criteria studied in this paper can be used to help other blocks evaluate the CBM content, providing guidance for further exploration and development of CBM fields with practical application.

Relationship between desorption amount and temperature variation in the process of coal gas desorption

Coal bed methane (CBM) is a clean energy source and its main component is methane, however, due to the complex conditions of its occurrence, its content detection is inaccurate and its utilization is not efficient. To further investigate the desorption and diffusion of methane in coal seams, this study uses an experimental system to investigate the desorption volume and temperature variations of gas desorption at different equilibrium pressures for three different particle sizes of coal samples. The results show that the desorption process is a heat absorption and cooling process, which is mainly influenced by the equilibrium pressure and the particle size of the coal samples. The amount of desorption and the absolute desorption temperature variation increases with increasing equilibrium pressure and increases with decreasing particle size of the coal sample. The desorption temperature variation at a desorption time of approximately 3000 s is close to the minimum. There is a linear relationship between the gas desorption volume and the absolute desorption temperature variation, which can be used to predict the desorption volume using the absolute desorption temperature variation. This will assist in the accurate measurement of coal bed methane content and the prevention and control of coal mine gas disasters.

Influence of geological structures on the occurrence of coalbed methane in Sima coal mine, China

Geological structures of Sima coal mine in Shanxi Province were analyzed to understand the control effect of the geological structures on the occurrence of coalbed methane (CBM) in coal seam #3 of Sima coal mine. The CBM contents in the districts #2 and #3 of Sima coal mine were tested, and the effects of buried depth, fault and collapse column on the distribution of coalbed methane content are studied. The research results showed that: 1) The average content of CBM has a linear relationship with buried depth and overburden thickness, but in the smallscale range of buried depth, the dispersion between CBM and buried depth is very large. 2) Faults and collapse columns significantly affect the content of local CBM nearby, but from the largescale range such as the whole mining area, the average value of CBM content at a certain buried depth will not be affected by faults and collapse columns. 3) In the hanging wall of F29 normal fault, it is roughly estimated that the average escape rate of CBM near the fault is 13.9%, while in the footwall of F29 normal fault, this value is 0.7%–1.1%. The results show that there is a significant difference in the influence of the fault on the CBM content in the hanging wall and footwall. 4) The control effect of collapse column on CBM occurrence is related to the development height of collapse column, the cementation degree of collapse column, groundwater runoff conditions and other factors. It can be divided into three categories: aggregation action, escape action (such as collapse column X8) and no obvious effect (such as collapse column DX7).

Inversion Study on Parameters of Cascade Coexisting Gas-Bearing Reservoirs in Huainan Coal Measures

The prediction and development of three gases, mainly coalbed methane, shale gas, and tight sandstone gas, in the Huainan coal measures of China, has been the focus of local coal mines. However, due to the overlapping and coexisting characteristics of the three gas reservoirs in Huainan coal measure strata, it is challenging to develop the three gas. The coal mine has been creating a single pool for a long time, resulting in the severe waste of other gas resources in developing the gas-bearing resources in the coal measure strata. The gas-containing reservoir is predicted based on geological, seismic, and logging in Huainan Mining. In addition, determining the excellent area for reference for the development of three gas resources. First, using logging data, mathematical–statistical methods are used to analyze the physical parameters of gas-bearing reservoirs in multi-layered stacked coal seams. Then, based on the theory of prestack seismic inversion, parameters, such as the impedance of P-wave, the ratio of P-wave velocity and S-wave, Lamé constant, Young’s modulus, and Poisson’s ratio and lithological distribution, are obtained for the whole area. The gas-bearing information of the reservoir is received by the statistics and equation of the parameter intersection diagram and is closely related to exploration and development. Finally, the paper synthetically predicts the most favorable area of the gas-bearing reservoir in the study area. The prediction results are compared with the actual results of coalbed methane content in the existing extraction wells, proving that the method is feasible and can provide the basis for the deployment and development of the well location.

Evaluation of lost gas in the borehole drilling stage: Implication for the direct method of coalbed methane content determination

The current direct method of coalbed methane (CBM) content determination may underestimate the CBM content due to the negligence of lost gas in the borehole drilling stage of coal sampling, thus causing inaccurate evaluation of CBM reserves. In this work, considering the gas flow in coal body around the borehole before the coal sample is drilled down and exposed to air, the advanced lost gas in the borehole drilling stage of coal sampling is quantitatively calculated. First, a dual-porosity model coupling coal deformation and gas flow in the coal matrix and fractures is proposed to describe the dynamical behavior of gas flow in the borehole drilling stage. The field logging data in previous references are used to verify the dual-porosity model. Then, the variations of advanced lost gas as well as gas pressure at the sampling location with the drilling depth and drilling time are numerically simulated and discussed in detail. Furthermore, the effects of model parameters such as permeability, drilling velocity and borehole diameter on the advanced lost gas are investigated. The results show that the advanced lost gas accounts for about 10% of the original CBM content. The relationship between the advanced lost gas and the drilling time can be well fitted by the exponential function. It is revealed that over 90% of advanced lost gas is lost within the last 5% of the drilling time. The borehole diameter cannot affect the drilling depth where the gas begins to lose, but largely affects the amount of the advanced lost gas. Finally, an improved method of CBM content determination is conceptualized, which regards the CBM content as the sum of the advanced lost gas in the borehole drilling stage, the lost gas in the sampling stage, the measured gas and the residual gas. The results contribute to improving the accuracy of CBM content determination.

Experimental and Numerical Simulation of Water Adsorption and Diffusion in Coals with Inorganic Minerals

The study on the adsorption and micropore filling of water vapor in coal is significant for predicting coalbed methane content in coal seams. The primary purpose of this study is to explain the effects of coal pore structure and its surface chemistry on water vapor monolayer adsorption, micropore filling, and diffusion coefficient. First, X-ray diffraction (XRD) and mercury intrusion porosimetry (MIP) analyzed inorganic mineral components of two kinds of coal samples and pore fissures structures. Then, we divide pores and fissures according to the theory of fractal dimensions. Furthermore, we carried out the water vapor adsorption and desorption experiments on two kinds of coal; in particular, we set 14 points of relative pressure between 0 and 0.2. Guggenheim–Anderson–de Boer (GAB), Frenkel–Halsey–Hill (FHH), and Freundlich models were used to analyze the data of water vapor adsorption to obtain the boundary pressure points of the monolayer, multilayer adsorption, and capillary condensation. Finally, the parameters of the models were obtained by fitting the adsorption data of water vapor according to the combined GAB, Freundlich, DA, and bidisperse adsorption (BDA) models to analyze the interaction mechanism between coal and water. We explain why the strongly adsorbed water minerals, such as pyrite, illite, and nacrite coal, can improve water vapor’s adsorption and diffusion capacity in coal pore fissures.