Coalbed Methane Production Research Articles

Optimising Neural Networks for Enhanced Fracture Density Prediction in Surrounding Rock of Coalbed Methane Reservoir

ABSTRACTFractures influence the mechanical strength of coal roof and floor, constraining the design of hydraulic fracturing for coalbed methane production. Currently, the predominant approach involves the integration of petrophysical logging with machine learning for fracture prediction. Nevertheless, challenges exist regarding the model's accuracy. In this study, we present a novel approach to predict fracture density. Our method optimises a back‐propagation (BP) neural network and utilises principal component analysis for feature extraction. We employ logging parameters (density, compensated neutron and acoustic time difference) obtained from Shouyang Block well SY‐1 and fracture density data from electrical imaging logging to construct the FVDC model's dataset. The BP neural network model is optimised using the Sparrow Search algorithm and Tent Chaotic Mapping. The results demonstrate a substantial enhancement over the BP neural network model, with reductions of 80.102% in mean absolute error, 94.182% in mean square error, 75.879% in root mean square error and 79.764% in mean absolute percentage error. When considering accuracy, the optimised model (97.098%) surpasses the support vector regression model (96.478%), the random forest model (94.404%) and the BP neural network model (85.657%). Scalability testing for the optimised model was conducted using data from well SY‐2, yielding a remarkable prediction accuracy of 96.775%. This performance exceeds that of the BP neural network (with an accuracy of 85.102%), as well as the random forest and support vector regression models (with accuracies of 91.234% and 90.384%, respectively). These results underscore the potential of well logging and machine learning in FVDC prediction.

Effects of surface tension and contact angle on pore structure development of coal samples under chemical solution erosion

To explore the influence of surfactant concentration on the pore structure and permeability of coal samples during the chemical enhancement of coalbed methane production, different kinds and different concentrations of surfactants were added to the chemical solution, and the coal samples were soaked. Methods such as low-field nuclear magnetic resonance testing (NMR), fractal theory, permeability testing, surface tension testing, and contact angle testing were employed to analyze the variation patterns of coal sample pore structure, fractal characteristics, and permeability, and to explore the correlation between surface tension, contact angle, and the degree of pore structure development. The results show that the increase in total porosity of coal samples, the increase in the seepage pore porosity, the decrease in Dt, and the growth rate of permeability increase with the increase in surfactant concentration, and are negatively correlated with the surface tension of the solution and the contact angle of the coal-solution interface, while the decrease in Ds is not significantly correlated with surfactant concentration, surface tension, or contact angle. In terms of the erosion effect of a chemical solution on coal samples, the influence of contact angle is greater than that of surface tension, while surface tension has the greatest impact on the development of adsorption pores. By adding different surfactants, the surface tension of the chemical solution and the contact angle of the coal-solution interface can be controlled, further promoting the erosion of coal samples, which is of positive significance for the chemical enhancement of coalbed methane production.

A thermodynamics-based coupled model for multi-phase flowback in deformable dual-porosity shale gas reservoirs

Over the past decades, there has been growing interest in modelling multi-phase flowback in shale gas reservoirs during hydraulic fracturing, primarily due to the significant risk of groundwater pollution. However, the lack of fully coupled simulations and a unified theoretical model has hindered the study of coupled adsorptive hydro-mechanical behaviour and its influence on fluid flowback prediction. In this paper, we have extended the non-equilibrium thermodynamics-based Mixture Coupling Theory to derive the constitutive relationship and governing equation for adsorptive multi-phase fluid flows in deformable dual-porosity media. Helmholtz free energy density has been used to establish the relationship between solids and fluids. The interaction of adsorptive fluids in the pore and fracture space has been fully considered, leading to a new form of constitutive equation, which obtained the molecular adsorptive effect on the rock by introducing adsorption entropy production. The proposed governing equations determine the fully coupled evolution of solid deformation and multi-phase flow, with the consideration of adsorption as well as pore and fracture porosity change. Numerical simulation is then performed to study the flowback of a real shale gas well and the influence of coupled behaviour on model prediction. The simulation shows that the flowback flux is mainly by the fracture (more than 99.9 %) and the overall cumulative volume is 2427.1 m3 within 225 h which accounts for about 5.3 % of the total injected fracturing fluid, and the sensitivity analysis reveals that the manual fracture porosity is the most sensitive factor to the cumulative flowback. This work provides new insights into the flowback process of shale reservoirs in a fully coupled view and the proposed theoretical tool should contribute to the modelling of other adsorptive multi-phase flow problem in deformable dual-porosity media such as carbon storage and coalbed methane production.

Effect of water occurrence in coal reservoirs on the production capacity of coalbed methane by using NMR simulation technology and production capacity simulation

The occurrence of gas and water is a critical factor affecting the production capacity of coalbed methane. Therefore, occurrence and dynamic interaction between gas and water in coal reservoirs need to be studied. T2 spectrum of all the samples were studied by NMR technique at 0, 5, 9, and 28 h of natural evaporation. Then, multifractal model was used to characterize water distribution heterogeneity, and a novel evaluation coefficient was proposed to characterize distribution heterogeneity of water content, the correlation among evaluation coefficient, water distribution heterogeneity and pore structure parameters was analyzed. The results are as follows. In the saturated state, the moisture distribution of three types is heterogeneous. Type A of adsorption pore-developed exhibits strong moisture variation heterogeneity of small pores, in contrast to the uniform moisture variation in large pores. Type B of fracture-developed has the highest coefficient of variation in moisture distribution. The coefficient of variation A1 for moisture content can determine the speed of moisture transport and evaporation in the pore structure. A lower A1 indicates a greater moisture transport volume and faster moisture transport rate over the same time. The coefficient of variation A2 for moisture distribution represents the heterogeneity of moisture content variation in the pore structure. That is, a smaller A2 indicates better heterogeneity in the distribution of moisture content in the pore structure. Numerical simulation indicates the average gas production and the peak gas production time increase and decrease with the initial moisture content (Sgrw) increases, respectively. These findings provide practical guidance for coalbed methane development, especially in optimizing coalbed methane production capacity prediction and improving recovery efficiency.

Low-rank coalbed methane production capacity prediction method based on time-series deep learning

Coalbed methane (CBM), a novel clean energy source, significantly contributes to reforming the energy supply structure, advancing carbon neutrality, and achieving peak carbon emissions. A precise production forecasting method is essential for understanding coalbed methane development and improving extraction efficiency. This paper proposes an improved multi-channel LSTM production forecasting model considering the influence of production dynamic factors, based on cutting-edge deep learning technology and widely applied production decline curve analysis methods. The model is experimentally tested on CBM wells in the Surat Basin of Australia. In the data processing segment of the model, we have improved the 3σ rule for handling outliers within a normal distribution. This enhancement maintains data integrity, achieves superior denoising, increases prediction accuracy, and significantly reduces model learning time. The test results demonstrate that the improved model exhibits excellent predictive performance for CBM wells, with 87.3 % of wells having a prediction accuracy exceeding 85 % overall. Additionally, the comprehensive multi-channel LSTM model identifies dynamic controlling factors in CBM production by analyzing variations in prediction accuracy with different dynamic factor combinations. This study provides new insights and scientifically rational references for production forecasting in CBM extraction. It's also crucial for effective production strategies and process optimization.

Aquifer Leakage Recharge Controls on CBM Production: A Case Study in the Sanjiao Block, Eastern Ordos Basin, China.

Aquifer leakage recharge poses a prevalent challenge in coalbed methane (CBM) development, severely impeding its efficient production. This study focuses on the Sanjiao Block, located on the eastern margin of the Ordos Basin, and provides a comprehensive evaluation of the impact of aquifer leakage recharge on CBM well productivity, employing hydrochemical characteristics and numerical simulation. Fisher's discriminant analysis reveals a close association between external water sources for CBM wells in the Taiyuan Formation and the hydrodynamic environment: in the western stagnant zone, hydrochemical characteristics resemble those from the Shanxi Formation; in the eastern strong runoff zone, water from the Taiyuan Formation directly contributes to CBM well development; in the central weak runoff zone, hydrochemical characteristics suggest mixed water sources from the Shanxi Formation and Taiyuan Formation. The numerical simulation employs orthogonal experiments to quantify the sensitivity of aquifer geological parameters to CBM production, ranked from strong to weak for aquifer types, leakage channel properties, and aquifer physical properties. The fundamental reason for disparities in the efficacy of leakage recharge lies in categorizing aquifers into finite and infinite recharges based on their water supply capacity. The properties of leakage channels, including the location and scale, manifest as effects on the magnitude and shape of gas production characteristics in infinite and finite recharge aquifers, respectively. Furthermore, a discriminant flowchart of CBM production is presented, delineating the production characteristics of CBM wells under the influence of aquifer leakage recharge into six patterns and illustrating their distribution in the study area. This discriminant process provides scientific guidance for analyzing CBM production characteristics and evaluating potential under the influence of aquifer leakage recharge.

Coal chemistry, utilization potential, and coalbed methane (CBM) assessment of some coal deposits in Central Benue Trough, north-central Nigeria

Coalbed methane (CBM), a current global legislative priority for climate change mitigation, is an unconventional and eco-friendly clean source of energy that is considered a veritable alternative to conventional fossil fuels. Despite its overwhelming advantages, CBM evaluation studies of Nigerian coals have received little or no attention. To bridge the gap in knowledge, we have for the first time in Jangwa-Shankodi and Lafia-Obi, described the potential of harnessing CBM for its gainful utilization in Nigeria using some coal deposits in its north-central region as a case study. The gas contents of the coals were determined empirically by taking account of their ultimate and proximate properties. Other coal parameters such as fuel ratio and vitrinite reflectance (Ro (%)) have also been computed and discussed. Proximate analyses of the studied coal samples show moisture contents that vary between 2.28 and 2.56%, whereas, volatile matter yield is placed in the range of 29.98–30.34%. Ash yield ranges from 7.83 to 8.64%. Fixed carbon content varies from 55.97 to 56.30%. Variation in fuel ratio shows a restricted range from 1.72 to 1.87. All the coal samples were found to be low in sulphur (< 1%) with H/C ratios that vary from 0.072 (LAF 2, 3 and 4) to 0.086 (JSK 3). Moreover, the coals were found to be of medium-volatile bituminous rank, with gas contents that range from 12.65 to 13.20 cc/g. In the current study, kerogen lies in the Type IV zone, which suggests the generation of methane gas by the studied coal samples. Also the estimated range of vitrinite reflectance (Ro) which varies between 1.073% and 1.086% indicates thermogenic gas expulsion in the coals. There is a noticeable increase in gas content with coal maturity and depth. These values are indicative of good quality coals that show antecedents for CBM production. However, considering that this work is a pilot study, we recommend that core drilling be employed in obtaining insitu measurements of the coal gas contents and thus, verify these empirical estimates. Also, detailed laboratory study on pore structure (and its distribution) and adsorption isotherm curve are recommended to better understand the coal reservoir properties and hence, consolidate the present study.

Multifractal Characteristics of Low-Field Nuclear Magnetic Resonance of Different Rank Coals and Its Permeability Predicting Method.

The permeability of methane in coal is a crucial factor in the production of coal-bed methane (CBM), which is dependent on the pore size distribution (PSD) of coal. The transverse relaxation time cutoff value (T2C) is a crucial parameter in nuclear magnetic resonance (NMR) techniques for converting NMR data into an absolute PSD. To investigate an appropriate approach for predicting the T2C and permeability of different rank coals, this study first revealed, through centrifuge experiments with a centrifugal force of 1.38 MPa, the T2C values of five coal samples: anthracite coal (3 ms), lean coal (8 ms), coking coal (12 ms), fat coal (11 ms), and lignite coal (13 ms). These T2C values were then employed to obtain the absolute PSD values of the coal samples. The results demonstrated that the pore structure characteristics of these coal samples are essentially identical, with micropores constituting the majority, varying between 63.47% and 93.74%. Subsequently, the multifractal analysis method was introduced to establish a new T2C value calculation model. A comparison of the model-calculated T2C values with those obtained from centrifugal experiments revealed an average deviation of only 5.26%. Finally, a new permeability model was developed by conducting multiple regressions on permeability and multifractal parameters. In comparison to classical models, such as the Timur-Coates (TC) model and the Schlumberger Dauer Research Center (SDR) model, the developed permeability model offers more accurate predictions. These results are applicable to pore structure characterization and methane permeability prediction in coal reservoirs of varying rank and other unconventional gas reservoirs.

Physical Properties of High-Rank Coal Reservoirs and the Impact on Coalbed Methane Production

The physical characteristics of coal reservoirs are important factors affecting the occurrence status of coalbed methane, as well as key factors restricting the production capacity. Therefore, taking 3# coal in Qinnan region of China as the research object, based on the actual production data of 200 coalbed methane wells in the research area, experimental testing combined with simulation analysis was used to explore the physical properties of medium and high-order reservoirs and their impact on the occurrence and production of coalbed methane. The characteristics of coalbed methane reservoir formation and production capacity changes in the research area were revealed, and the factors restricting the production capacity of coalbed methane wells were calculated using the gray correlation analysis method. The results indicate that the micropores in the coal reservoir in the study area are well-developed, while the macropores and mesopores (exogenous fractures) are underdeveloped, the surface of the micropores is complex, and the connectivity of the micropores is poor, resulting in reservoirs with high gas adsorption characteristics and low permeability. The fractal characteristics of pores and fractures can reflect the permeability characteristics of reservoirs. Permeability is positively correlated with macropores (exogenous fractures) and mesopores, and negatively correlated with micropores. There is a positive correlation between permeability and productivity, and the reservoir in the study area has a stress-sensitive boundary. The main factors restricting productivity under the complex pore and fracture system of high-rank coal reservoir were identified, and the gray relational analysis method was used to evaluate the development effect of the research area. This study provides guidance for the development of coalbed methane production in high-rank coal reservoirs.

Mitigation of Fracturing Fluid Leak-Off and Subsequent Formation Damage Caused by Coal Fine Invasion in Fractures: An Experimental Study

During the hydraulic fracturing process of coalbed methane (CBM) reservoirs, significant amounts of secondary coal fines are generated due to proppant grinding and crack propagation, which migrate with the fracturing fluid into surrounding fracture systems. To investigate whether coal fines can form plugs to reduce fluid leak-off during the hydraulic fracturing stage, we conducted physical simulation experiments on coal seam plugging and unplugging to demonstrate that coal fines indeed contribute to reducing fluid leak-off during hydraulic fracturing. We also explored the plugging mechanisms of coal fines under different concentrations and particle sizes in fracturing fluids, and revealed the damage law of coal fines of temporary plugging on reservoir permeability. Research results indicate the leak-off volume of fracturing fluids containing coal fines is lower than an order without coal fines, demonstrating a significant effect of coal fines in decreasing fluid leak-off. The temporary plugging rate of coal fines increases with higher concentrations and decreases with larger particle sizes, achieving rates exceeding 90%. The high temporary plugging effect of coal fines results from the superposition of internal and external filter cakes. Under conditions of small particle size and high concentration, the damage to fractures during the fine return process is minimized. Considering the potential damage of coal fines to propping fractures and wellbore, the concentration of coal fines in fracturing fluids should be kept relatively low while ensuring a high temporary plugging effect. Overall, these findings provide crucial insights into optimizing the temporary plugging performance of coal fines during the hydraulic fracturing stage and controlling their behavior during the fracturing fluid flow-back stage, thereby enhancing reservoir fracturing effectiveness and improving CBM production rates.

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.

Coalbed methane reservoir properties assessment and 3D static modeling for sweet-spot prediction in Dahebian block, Liupanshui Coal field, Guizhou Province, southwestern China

Guizhou Province has many multi-layer, thin-thick coal seams; however, complex geology, incomplete reservoir characterization, and sweet-spot selection technology prevent large-scale coalbed methane (CBM) development. This study evaluates the CBM reservoir properties within the Dahebian block using logging data, coal sample analysis, and well-testing data and develops a 3D static reservoir properties model to analyze their spatial and vertical propagation. A sweet spot evaluation model was established using a multi-level fuzzy method based on 9 parameters extracted from a 3D static reservoir properties model. The coal measure has 22 coal seams, and seams >2 m thick have 2 or 3 thin non-coal layers intercalated. Coal seams 1#, 7#, and 11# are thin to thick, deeply buried, widely distributed, and have high gas content and saturation. Undeformed and cataclastic coal predominates the coal seam 1# and 7#, whereas coal seam 11# is dominated by cataclastic and granulated coal. The southern and central parts of coal seam 7# and 11# have less tectonically deformed coal (TDC). Coal seams 1# and 7# have low permeability relative to seam 11# and are localized, while coal seams 11# have high permeability, are extensively distributed, and contain substantial gas concentrations. Comparative analysis of evaluation scores and CBM production statistics shows that high scores indicate sweet spots for CBM development. Sweet-spot potential was classified as high, medium, and low. Scattered sweet spots are found in single layers, while combined development (1# + 7#+11#) reveals a wider high-potential area in the south-central region. This area, featuring deep, thick coal seams, high permeability, gas saturation, reservoir pressure, and low TDC proportion, indicates significant development potential. This study validates CBM development statistics, identifies future development areas, and guides the development of geologically complex Guizhou CBM.

Effects of inorganic salt ions on the wettability of deep coal seams: Insights from experiments and molecular simulations

Coal wettability plays a significant role in the efficiency of coalbed methane (CBM) extraction since it determines fluid transport and distribution. Deep coal seam aqueous fluids have a high salinity. Consequently, coal wettability experiments utilizing fresh water are not representative for those coal seams. Therefore, the effect of aqueous fluids with inorganic salt ions on coal wettability needs to be investigated. In this study, both experiments and molecular simulations are conducted to unravel the wetting behaviour and mechanisms of saline fluids on coal surfaces, investigating different fluid salt concentrations, temperatures, valence states, and coal pore sizes. The results reveal that a more saline fluid displays a more hydrophobic behaviour on the coal surface. Microscopically, water molecules have a tendency to assemble around cations and anions as hydration shells and gradually detach from the coal surface, leading to a gradual transition from hydrophilicity to hydrophobicity. A change in wettability with fluid salinity can be caused by two mechanisms. On the one hand, an increase in ion concentration constrains the diffusion of water molecules through hydration, weakening the mobility of water molecules. On the other hand, a higher ion concentration weakens the interaction between water molecules and oxygen-containing functional groups, reducing the affinity of the water molecules with the pore wall. Moreover, at higher temperatures, ion valence states, and for coal with smaller pores, the impact of inorganic salt ions in fluids on the wetting behaviour of coal surfaces becomes more significant. The coal wettability influences the capillary pressure of coal pores. This study provides new insights on the effect of saline fluids on coal wettability which may help address challenges of fracturing fluid loss and water-blocking in CBM production activities.

Study on the Mechanical Parameters and Permeability of Coal Reservoirs at Different Temperatures.

Deep coal reservoirs, as opposed to their shallower counterparts, exhibit characteristics of higher temperatures and pressures. These conditions affect the fracture structure and mechanical properties of coal, which in turn controls permeability. Substantial studies have been conducted to determine the effects of overburden pressure on permeability, but the correlation between the temperature and mechanical parameters/permeability of coal remains unclear. This study focused on low-rank bituminous coal from the southern edge of the Junggar Basin in Xinjiang. Using experiments conducted on seepage and mechanics at different depths (considering effective stress and temperature), the study investigated how temperature affects the mechanical parameters and permeability of coal column samples. A permeability prediction model was established incorporating temperature, mechanical parameters, and effective stress. The results show that from 20 to 80 °C, the elastic modulus of coal column samples decreases by 31.0%, and the Poisson ratio increases by 72.0%. Permeability decreases between 48.37 and 90.12% under different depths. The stress sensitivity coefficient under various temperature conditions decreased exponentially as the effective stress increased, and the temperature sensitivity coefficient under various effective stress conditions decreased with increasing temperature. The permeability was more sensitive to a temperature below 40 °C. In the permeability prediction model, the fracture compressibility coefficient is bifurcated into two coefficients, each controlled by temperature and effective stress. The permeability prediction error of the model was 12.7% under constant effective stress and 17.2% under varying effective stress and temperature conditions. The study could provide guidance for fracturing and coalbed methane production in deep coal reservoirs.

A Semianalytical Model for Advanced Description of Pressure Drop Funnel during Coalbed Methane Production.

Advanced description of pressure drop funnel is crucial in coalbed methane (CBM) production because of dewatering and depressurization methods. Improving the precision of the pressure drop funnel description facilitates obtaining the actual production status and productivity potential, both pivotal for responsible development plans. The study presents a semianalytical model that integrates pressure profiles and material balance equations, incorporating inner and outer boundary conditions, and dynamic reservoir characteristics. The pressure propagation characteristics in undersaturated coal reservoirs are described during the production life of CBM wells, and the model is validated using two wells with different production characteristics. The results indicate that the effect of water saturation on the expansion of the drainage radius surpasses that of the desorption radius, demonstrating a more precise prediction of the production boundary when dynamic water saturation is considered. Additionally, a rapid drop rate of bottomhole flowing pressure triggers simultaneous propagation of the drainage and desorption radii, resulting in a smaller production boundary and fewer well-controlled resources. Conversely, an appropriate production strategy results in a larger drainage radius and lower boundary pressure before massive gas desorption, thereby facilitating efficient propagation of the pressure drop funnel. Moreover, the pressure drop funnel characterized by the model can compute the dynamic CBM resources and recovery efficiency of a single well, providing a valuable basis for assessing productivity potential. In summary, this model offers a time-saving and practical tool for describing the dynamic pressure drop funnel in various CBM production stages and promoting efficient development for undersaturated CBM reservoirs.

Quantitative Characterization of Pore–Fracture Structures in Coal Reservoirs by Using Mercury Injection–Removal Curves and Permeability Variation under Their Constraints

Pore and fracture structure heterogeneity is the basis for coalbed methane production capacity. In this paper, high-pressure mercury intrusion test curves of 16 coal samples from the Taiyuan Formation in the Linxing area are studied. Based on the fractal dimension values of mercury intrusion and retreat curves, the correlation between the two different fractal parameters is studied. Then, the permeability variation of different types of coal samples is studied using overlying pressure pore permeability tests. The correlation between the permeability variation of coal samples and dimension values is explored, and the results are as follows. (1) Based on porosity and mercury removal efficiency, all coal samples can be divided into three types, that is, types A, B, and C. Among them, Type A samples are characterized by lower total pore volume, with pore volume percentages ranging from 1000 to 10,000 nm not exceeding 15%. (2) During the mercury injection stage, both the M-model and S-model can reflect the heterogeneity of seepage pore distribution. In the mercury removal stage, the M-model cannot characterize the heterogeneity of pore size distribution in each stage, which is slightly different from the mercury injection stage. (3) The permeability of Type A samples is most sensitive to pressure, with a permeability loss rate of up to 96%. The original pore and fracture structure of this type of coal sample is relatively developed, resulting in a high initial permeability. (4) There is no significant relationship between compressibility and fractal dimension of mercury injection and mercury removal, which may be due to the comprehensive influence of pore structure on the compressibility of the sample.

An Innovative Experimental Methodology for Testing Anisotropic Permeabilities of Formation Rocks

Abstract The permeability of reservoir rocks is a typical anisotropic property. Accurate testing and characterization of reservoir in situ anisotropic permeability is crucial for geo-energy applications including geothermal energy extraction, hydrocarbon reservoir development, coalbed methane production, and carbon dioxide geological sequestration. In this work, a novel experimental apparatus was designed to more precisely determine the permeability tensor of reservoir rocks. The device can independently apply stresses in different directions to simulate in situ reservoir stress conditions and reservoir temperatures. The experiment can accurately measure the principal components of the permeability tensor in three directions for rock samples while effectively avoiding experimental errors caused by internal structure damage during disassembly. Using the self-developed apparatus, anisotropic permeability tests were conducted on sandstone, shale, and coal samples. The results show that the three-dimensional permeability of rock samples under in situ reservoir stress conditions is lower than under isotropic stress conditions. However, the variation magnitude of the three-dimensional permeability differs between the three rock types because of lithological differences. This confirms the difference in data between the proposed anisotropic permeability test method and other traditional methods. We also observed that for rocks without distinct oriented internal structures like sandstone, anisotropic permeability is more sensitive to (normal) stress changes. In contrast, for rocks with oriented pore structures such as shale and coal, the degree of anisotropic permeability is less sensitive to (normal) stress changes. The proposed novel anisotropic permeability test method obtains more accurate and realistic data under simulated in situ stress conditions compared with existing methods. It can evaluate rock properties and optimize geothermal or hydrocarbon production well designs to improve production efficiency.

Fracturing Construction Curves and Fracture Geometries of Coals in the Southern Qinshui Basin, China: Implication for Coalbed Methane Productivity.

Hydraulic fracturing technology has become a common practice to enhance the permeability of coal seams, and its effectiveness significantly impacts the productivity of coalbed methane (CBM) wells. In this study, multiple data sets, including fracturing reports, productivity data, and microseismic monitoring, were utilized to analyze the factors influencing fracturing effectiveness and gas well production at the southern margin of the Qinshui Basin, China, especially the Zhengzhuang and Fanzhuang blocks. Statistics revealed that the fracturing displacement, liquid consumption, and sand consumption were 8 m3/min, 17.69-1386.52 m3 (averaging 728.42 m3), and 28.5-46.1 m3 (averaging 40 m3), respectively. There were differences in the types of fracturing curves among blocks or well groups, and the natural fracture system was identified as the key factor affecting their characteristics. The coal seams with high density of microfractures in Zhengzhuang reduce the fracture threshold of reservoirs during hydraulic fracturing, resulting in a lower fracture response ratio than that of Fanzhuang (71.0 vs 80.3%). Well groups with higher microfracture width in coal seams (Group-ZC and DS) experienced a further reduction in fracture response (averaging 67.2 vs 80.3%), and the connection of hydraulic fractures (HFs) with these high-permeability microfractures lead to an increase in the proportion of fluctuating fracturing curves (averaging 52.2 vs 33.6%). Regional structural features and fracturing effectiveness jointly affected the production of CBM wells. The productivity in Zhengzhuang was lower than that in Fanzhuang due to the highly developed faults and deeply buried coal seams. Shallow coal seams with a high width of microfractures and a low-stress environment were easily supported by a proppant, forming a complex HF network and yielding a high productivity (Group-ZC and DS). For other deeper well groups, proppant migration became unfavorable once high-angle and complex branch HF clusters formed in coal seams, leading to local low-efficiency wells and fluctuating fracturing curves.

Research on the Interaction Mechanisms between ScCO2 and Low-Rank/High-Rank Coal with the ReaxFF-MD Force Field.

CO2 geological sequestration in coal seams can be carried out to achieve the dual objectives of CO2 emission reduction and enhanced coalbed methane production, making it a highly promising carbon capture and storage technology. However, the injection of CO2 into coal reservoirs in the form of supercritical fluid (ScCO2) leads to complex physicochemical reactions with the coal seam, altering the properties of the coal reservoir and impacting the effectiveness of CO2 sequestration and methane production enhancement. In this paper, theoretical calculations based on ReaxFF-MD were conducted to study the interaction mechanism between ScCO2 and the macromolecular structures of both low-rank and high-rank coal, to address the limitations of experimental methods. The reaction of ScCO2 with low-rank coal and high-rank coal exhibited significant differences. At the swelling stage, the low-rank coal experienced a decrease in aromatic structure and aliphatic structure, and high-rank coal showed an increase in aromatic structure and a decrease in aliphatic structure, while the swelling phenomenon was more pronounced in high-rank coal. At the dissolution stage, low-rank coal was initially decomposed into two secondary molecular fragments, and then these recombined to form a new molecular structure; the aromatic structure increased and the aliphatic structure decreased. In contrast, high-rank coal showed the occurrence of stretches-breakage-movement-reconnection, a reduction in aromatic structure, and an increase in aliphatic structure. The primary reasons for these variations lie in the distinct molecular structure compositions and the properties of ScCO2, leading to different reaction pathways of the functional group and aromatic structure. The reaction pathways of functional groups and aromatic structures in coal can be summarized as follows: the breakage of the O-H bond in hydroxyl groups, the breakage of the C-OH bond in carboxyl groups, the transformation of aliphatic structures into smaller hydrocarbon compounds or the formation of long-chain alkenes, and various pathways involving the breakage, rearrangement, and recombination of aromatic structures. In low-rank coal, there is a higher abundance of oxygen-containing functional groups and aliphatic structures. The breakage of O-H and C-OH chemical bonds results in the formation of free radical ions, while some aliphatic structures detach to produce hydrocarbons. Additionally, some of these aliphatic structures combine with carbonyl groups and free radical ions to generate new aromatic structures. Conversely, in high-rank coal, a lower content of oxygen-containing functional groups and aliphatic structures, along with stronger intramolecular forces, results in fewer chemical bond breakages and makes it less conducive to the formation of new aromatic structures. These results elucidate the specific deformations of different chemical groups, offering a molecular-level understanding of the interaction between CO2 and coal.

Metabolism mechanisms of biogenic methane production by synergistic biodegradation of lignite and guar gum

Coalbed methane (CBM) presents a promising energy source for addressing global energy shortages. Nonetheless, challenges such as low gas production from individual wells and difficulties in breaking gels at low temperatures during extraction hinder its efficient utilization. Addressing this, we explored native microorganisms within coal seams to degrade guar gum, thereby enhancing CBM production. However, the underlying mechanisms of biogenic methane production by synergistic biodegradation of lignite and guar gum remain unclear. Research results showed that the combined effect of lignite and guar gum enhanced the production, yield rate and concentration of biomethane. When the added guar gum content was 0.8 % (w/w), methane production of lignite and guar gum reached its maximum at 561.9 mL, which was 11.8 times that of single lignite (47.3 mL). Additionally, guar gum addition provided aromatic and tryptophan proteins and promoted the effective utilization of CC/CH and OCO groups on the coal surface. Moreover, the cooperation of lignite and guar gum accelerated the transformation of volatile fatty acids into methane and mitigated volatile fatty acid inhibition. Dominant bacteria such as Sphaerochaeta, Macellibacteroides and Petrimonas improved the efficiency of hydrolysis and acidification. Electroactive microorganisms such as Sphaerochaeta and Methanobacterium have been selectively enriched, enabling the establishment of direct interspecies electron transfer pathways. This study offers valuable insights for increasing the production of biogenic CBM and advancing the engineering application of microbial degradation of guar gum fracturing fluid. Future research will focus on exploring the methanogenic capabilities of lignite and guar gum in in-situ environments, as well as elucidating the specific metabolic pathways involved in their co-degradation.