Coalbed Methane Reservoirs Research Articles

Damage Mechanism of Deep Coalbed Methane Reservoir and Novel Anti-Waterblocking Protection Technology

Coalbed Methane (CBM) accounts for about 5% of China’s domestic gas supply, which has been regarded as one of the most promising energies for alleviating the energy supply–demand imbalance. Deep CBM reservoirs have the characteristics of low permeability, low porosity, and low water saturation, which easily experience reservoir damage during the drilling process, further affecting the gas productivity. Based on the analysis of coal mineral composition, pore structure distribution, and the surface micromorphology change in coal surface before and after hydration, a possible mechanism for CBM formation damage was revealed. It was found that the damage caused by drilling fluid intrusion can be divided into three stages: stripping, migration, and plugging. Based on the water-sensitive, acid-sensitive, and stress-sensitive evaluation tests, a novel anti-waterblocking agent with both wettability alteration and surface tension reduction was developed; then a reservoir protection drilling fluid for deep coal formation in Daning-Jixian block was constructed; then the reservoir protection performance of drilling fluid was evaluated. The results show that as the concentration of the anti-waterblocking agent FSS increases from 0% to 1%, the surface tension of the water phase is significantly reduced from 72.15 mN/m to 26.58 mN/m, while the maximum contact angle of water on the surface reaches 117°. This enhancement in wettability leads to an improvement in the permeability recovery rate from 56.6% to 80.0%, indicating a substantial reduction in waterblocking effects and better fluid mobility within the reservoir. These findings highlight the efficacy of FSS in mitigating formation damage and optimizing gas production in coalbed methane reservoirs. The drilling fluid has good wettability alteration, inhibition, and sealing performance, which is of great significance for protecting gas well productivity.

Tectonically deformed coal: Focus on microstructures & implications for basin evolution

Traditionally, the Gondwana basins of India were believed to have formed primarily through extensional tectonics that created rift basins. However, recent models propose that strike-slip movements along deep-seated crustal fractures also contributed to their development. This article investigates this theory through a comprehensive structural analysis of the Bokaro Basin, located in the Damodar Valley of eastern India. This study deciphers tectonic history and evolutionary mechanisms of the Bokaro Basin by analyzing its coal samples, especially their structures—a relatively unexplored aspect in Indian coal research. We investigate maceral types, deformation manifestations, and fracture patterns at various scales. This led us to refine the structural classification of (Indian) coals. Deformation imprints were identified using remote sensing for regional features, geological fieldwork for megascopic observations, and petrographic analysis for micro-scale studies. The study utilized ArcGIS for lithology and fault mapping in conjunction with fieldwork in the highly deformed southwestern Bokaro Basin. Petrographic analysis revealed coal macerals and deformation signs. This research confirms that the Bokaro Basin's tectonic evolution involved uneven fault distribution, with significant rift and pull-apart mechanism. Coal seams show diverse deformation patterns, from ductile in fusinite to brittle in collotelinite, indicating multiple deformation stages under varying stress regimes. The East Bokaro Basin, with deeper seams, shows stronger deformation than the West. Shear stress, alongside extension, played a role in shaping the basin, with sigmoidal tension gashes from the coals of Barakar Formation, confirming active shearing through or afterwards coalification during or/and after the Early Permian time. The structural classification aids in coal bed methane (CBM) reservoir characterization, highlighting promising potential in cataclastic/tectonically deformed coal reservoirs. Tectonic deformation has affected the coals from the Bokaro Basin, resulting in structures that range from blocky to cataclastic, with some instances of granulation.

Study on the Influence of Deep Coalbed Methane Horizontal Well Deployment Orientation on Production

The development of deep coalbed methane has become an important way to obtain natural gas in China. The development of deep CBM mainly depends on horizontal well technology. The different orientations of horizontal wells will have an important impact on the productivity of coalbed methane wells. The angle grid geological model of coalbed methane reservoirs with different inclination angles is established, and the deployment orientation of horizontal wells is changed to study the optimal deployment orientation of deep-saturated coalbed methane reservoirs. When CBM horizontal wells in deep saturated CBM reservoirs are deployed upward along the dip, well-controlled reserves, peak daily gas production, and cumulative gas production increase as the dip decreases. When deploying down the dip, with the increase in dip angle, the well-controlled reserves increase, and the peak daily gas production and cumulative gas production first increase and then decrease. In the low-dip reservoir, the development effect of horizontal wells deployed in different directions is better than that in the up-dip direction. In the high-dip reservoir, the development effect of horizontal wells deployed along the strike is better than that in the up-dip and down-dip directions. The development effect of horizontal wells is controlled by both well-controlled reserves and reservoir pressure drop. Because this method is targeted at different geological conditions, it can be used to guide the horizontal well optimization of other coalbed methane blocks and has very important significance for the development and optimization of coalbed methane reservoirs.

Gas content, geochemical characteristics and implications of coalbed methane from the Deep Area of Qi’Nan Coalmine in Huaibei Coalfield

The objective of this work is to investigate the implications of geological influence factors on gas content and geochemical characteristics of deep-buried (> 800 m) coalbed methane (CBM) reservoirs. Results show that bituminous coal accounts for the majority, which exhibits similar maturity but differ in maceral and chemical constituents. CBM reservoirs show low porosity, low permeability and moderate temperature, with thickness of 0.85–4.15 m. In addition, the total gas content is 4.58–12.33 m3/t (average of 8.83 m3/t). CH4 is the main component with concentration of 92.83−99.22% (average of 96.68%), and the δ13CCH4 and δ13DCH4 is − 53.78‰–−44.62‰ (average of − 48.82‰) and − 223.93‰––−4.49‰ (average of − 215.37‰), respectively. All CBM samples are the mixtures of thermogenic gases and secondary biogenic gases with CO2 reduction. In addition, gas content characteristic at the critical point of burial depth is the result by positive and negative geological effects. CH4 concentration shows a wide range with the increases of buried depth, while the numerical values of which for the selected samples display complex variation characteristics. Furthermore, the values of δ13CCH4 and δ13DCH4 become heavier with the increases of buried depth. Besides, the above two geochemical parameters are related to Ro, max and reservoir temperature.

Fracture prediction method for deep coalbed methane reservoirs based on seismic texture attributes

Fracture prediction method for deep coalbed methane reservoirs based on seismic texture attributes

The influence of lamination and fracture on the velocity anisotropy of tectonic coals

The elastic anisotropy of coal formations is important for the prediction of unconventional coalbed methane reservoir performance and hydraulic fracturing. Although essential for several geophysical applications, the elastic anisotropy of coals is still poorly understood. Therefore, three sets of cylindrical coal samples are drilled parallel and perpendicular to the bedding plane, and the ultrasonic velocities under different confining pressures are measured in the laboratory. We combine experimental observations and modeling analysis to evaluate the elastic anisotropy of the coals. The results suggest that the velocity of coals parallel to the bedding plane is less sensitive to confining pressure than those perpendicular to the bedding plane. The fracture densities of coals parallel to the bedding plane are much lower than those perpendicular to the bedding plane, and most of the fractures are closed when the pressure is higher than 15 MPa. The organic matter (OM), clay content, and their preferred orientation play dominant roles in velocity anisotropy, and the fracture effect can significantly enhance it. The velocity anisotropy parameters of coals are positively correlated with the OM and clay content, and the preferred orientation of OM and clay plays a significant role in coal anisotropy. The results in this study are helpful in the characterization of the fractures of coals and can provide an important rock-physics basis for microseismic fracture monitoring and reservoir prediction.

Analytical Model for Rate Transient Behavior of Co-Production between Coalbed Methane and Tight Gas Reservoirs

Analytical Model for Rate Transient Behavior of Co-Production between Coalbed Methane and Tight Gas Reservoirs

Robotics and artificial intelligence in unconventional reservoirs: Enhancing efficiency and reducing environmental impact.

Shale, tight gas, and coal bed methane reservoirs are unconventional reservoirs that have geometrically complicated geological formations with low permeability, rendering their extraction operations difficult, expensive, and environmentally sensitive. On the other hand, recent developments in Robotics and Artificial Intelligence continue to transform how exploration, production, and maintenance activities are carried out in these reservoirs. This review paper encompasses how Robotics and AI technologies are applied to these unconventional reservoirs, improving operation efficiency, increasing the recovery rate and minimizing environmental damage. It updates on the latest status of autonomous drilling, AI-driven reservoir characterization and robotic fracturing. The paper also discusses future opportunities: emerging technologies, integration of AI with predictive analytics, and innovations toward sustainability. These are the challenges that come with possible solutions discussed in the paper: high costs, technical integration, and data quality. The review thereby presents the thought that robotics and AI will take a transformative role in the unconventional reservoir sector during the next few years, both in economic performance and environmental sustainability.

Microscopic adsorption study from coal rank comparison on the feasibility of CO2-rich industrial waste gas injection enhanced coal bed methane recovery

A new method of injecting CO2-rich industrial waste gas (CO2-rich IWG) to displace coal bed methane (CBM) is proposed for energy conservation and green growth. In this study, theadsorption mechanisms of this method were studied by the Giant canonical Monte Carlo and molecular dynamics methods in macromolecular coal models with three ranks (brown, bituminous, and anthracite coal). It is found that the proportion of gas molecules in the adsorbed state is higher in the anthracite coal slit than in the brown and bituminous slits, indicating that anthracite coal seams are more appropriate for waste gas sequestration. The adsorption selectivity of NO and CO2 is consistent among the three coal ranks, with the order of brown > bituminous > anthracite > 1.0, and that of N2 orders as 1.0 > bituminous > anthracite > brown.This is due to the different dominant factors affecting the competitive adsorption between different waste gas components and CBM, namely competition for adsorption sites in the NO and CO2 systems and thefilling effect in the N2 system. There is a positive correlation between the number of major competitive adsorption sites and the adsorption selectivity of theCO2(NO) system. CO2 and CH4 compete for COC structures in brown and bituminous coal and OH structures in anthracite coal, and OH structures in the three coals are the major adsorption sites for NO systems. Our work advances the understanding of the microscopic adsorption mechanisms of CO2-rich IWG in the CBM reservoirs, which provides a theoretical basis for CO2-rich injection-enhanced CBM recovery technology.

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.

Geological and hydrological controls on the pressure regime of coalbed methane reservoir in the Yanchuannan field: Implications for deep coalbed methane exploitation in the eastern Ordos Basin, China

The pressure regimes of the No. 2 coalbed methane (CBM) reservoir in the Yanchuannan field located in the southeastern Ordos Basin are highly variable and divided into overpressured (pressure gradient >9.80 kPa/m), slightly underpressured (pressure gradient of 8–9.80 kPa/m), and moderately underpressured (pressure gradient of 5–8 kPa/m). The controlling factors for the variable pressure regimes were investigated through the analysis of geological and hydrological characteristics. The pressure regimes are controlled by different mechanisms in different hydrodynamic environments. In the closed hydrodynamic environment characterized by TDS > 10,000 mg/L and NaCl type of groundwater, the pressure regime is dominated by overpressured to slightly underpressured and is controlled by CBM migration. Overpressure was developed by thermogenic CBM generation during the coalification process and is maintained by thermogenic CBM migration from the extended northwestward and deeply buried CBM reservoir during tectonic uplift. The transition from overpressure to slight underpressure and then to moderate underpressure towards the southeast is the result of the progressively weakened migrated thermogenic CBM with increasing migration distance. In the open hydrodynamic environment characterized by TDS < 10,000 mg/L and NaHCO3 type of groundwater, the pressure regime is dominated by slightly to moderately underpressured and is governed by hydrodynamics. Groundwater is fed by meteoric recharge along the structurally upturned basin margin and creates the hydrodynamic framework during tectonic uplift. The transition from moderate to slight underpressure towards the southwest is associated with the minor decrease range in ground elevation from basin margin to basin interior and the gradually weakened runoff intensity of groundwater with increasing distance to meteoric recharge. The idealized models for the pressure regimes are established, which can provide guidance to deep CBM sweet spot identification in CBM fields in the eastern Ordos Basin and elsewhere.

Moisture dependence of responses in physical–chemical property and CH4 ad-/desorption capability of coals to microwave radiation

For purpose of understanding feasibility of coalbed methane (CBM) production in practical water (H2O)-containing reservoirs by using microwave radiation, the dielectric property highly associated with microwave-absorbing and resultant temperature-rising capabilities of coals were addressed primarily; afterward, the temperature-rising rule of coals and its dependence on moisture were examined; finally, the impacts of moisture on changes about main physical–chemical property and resultant CH4 ad-/desorption performance of coals were investigated under microwave field. Results indicated that the coals display microwave-absorbing potential to raise temperature. The moisture initially increases the temperature-rising rate owing to its strong microwave-absorbing capability while decreases the final bulk temperature because of its endothermal evaporation. The resultant rising temperature decomposes and transforms minerals. Moreover, the temperature rise upgrades crystallite structure of the dried coals. As for the wetted coals, the rapid temperature rise disorders crystallite structure of the Sihe and Yima coals due to potential steam explosion. Furthermore, the radiation decreases the aromaticity and the total surface oxygenic groups of the dried coals; the moisture whittles down these decreasing trends. In general, the micro- and mesopore surface area and volume of the coals drops after radiation. The microwave radiation smooths pore surface of the wetted coals while roughens that of the dried coals. The complexity of the coal pore structure almost reduces after radiation. Besides, the microwave radiation significantly reduces the CH4 adsorption capability of the dried coals by 6.74–36.69 %; the moisture further reduces the CH4 adsorption capability by 20.48–43.03 %. Ultimately, the microwave radiation almost enhances the ad-/desorption hysteresis of CH4 on the dried coals while weakens that of the wetted coals. Such alterations depend on the responses of pore abundance and pore surface roughness to microwave. These findings confirm that microwave radiation is a promising option to produce CBM, particularly for H2O-bearing CBM reservoirs.

Clumped isotopes constrain thermogenic and secondary microbial methane origins in coal bed methane

Methane is an economic energy resource and potent greenhouse gas. Distinguishing secondary microbial methane from thermogenic gas is important for natural gas exploration and consideration of subsurface microbial activity in the global carbon cycle, but remains challenging. To understand controls on methane origins in natural gas systems, we investigated the methane clumped isotopologue distributions in the Qinshui Basin high-thermal maturity coal bed methane (CBM) reservoir. Here, near-equilibrium clumped isotopologues distribution (Δ13CH3D and Δ12CH2D2) inferred a temperature interval of 21.6–252.3 °C. The high-temperature thermodynamic equilibrium most likely represents original thermogenic CBM characteristics during coalification. The low-temperature equilibrium clumped isotopologue distributions suggest microbial alteration to CH4 isotopic bond ordering by increased enzymatically catalyzed isotopic exchange. The independent constraints from clumped isotopes, integrated with other geochemical and genomic evidence, confirm notable secondary microbial methane from biodegradation in the highly mature reservoir. Thus, methane clumped isotopes can be used as unequivocal tracers to distinguish secondary microbial methane from thermogenic gases and hence provide the ability to incorporate them separately into global methane budgets.

High-Order Models for Gas Transport in Multiscale Coal Rock.

The coal reservoirs exhibit great heterogeneity and strong anisotropy in multiscale pore/fracture structures. Developing highly accurate multiscale models for real-time prediction of microgaseous flow in complicated porous media with pronounced contrast in transport coefficients is crucial but not yet available, which is time-consuming, expensive, and even computationally impossible. In this study, a multiscale approximate solution of the gas flow and pressure field is derived in this paper for predicting coalbed methane (CBM) transport in macro-microscopic two-scale porous media of typical coal rocks in Guizhou Province, China, and the detailed finite element algorithm is established. The multiscale approximate solutions are constructed from the first- and second-order auxiliary cell functions and low- or high-order derivatives of the homogenized pressure field, which can accurately approximate the solution of the original problem to a certain extent. The numerical accuracy and validity of the multiscale approximate solutions under various working conditions are analyzed in detail by comparing and verifying the results with the direct numerical simulation results of fine-mesh high-precision finite elements. The results show that the homogenized approximate solution can only roughly capture the characteristics of the macroscopic pressure evolution, the first-order approximate solution can partially reproduce the macro-microscopic pressure oscillation phenomenon, and the second-order approximate solution can accurately predict the pressure profile and its evolution law with time in porous media with macro-micro configuration under various complex conditions. The second- and high-order two-scale approximate solutions constructed in this paper exhibit high numerical accuracy and excellent computational efficiency. We also develop multiscale approximate solutions for predicting microgaseous flow at a low reservoir pressure where the slippage effects are very pronounced. Potential applications of our high-order models to the coal reservoirs with a hierarchical matrix and fractures are discussed. The developed multiscale models exhibit excellent applicability to investigating the crossflow effects and coupling mechanisms between the matrix and cleats or fractures with multiple configurations in the CBM and shale gas reservoirs, which is crucial for the effective implementation of hydraulic fracturing technology. This study provides a fundamental understanding of gas transport in multiscale matrix-fracture networks, which helps to improve the optimization design of hydraulic fracturing in tight reservoirs.

Maximal information coefficient and geodetector coupled quantification model: a new data-driven approach to coalbed methane reservoir potential evaluation

In coalbed methane (CBM) development, it is imperative to evaluate the reservoir’s potential and identify the favorable areas to achieve higher production. This paper presents a novel quantified model inspired by the reservoir hydrodynamic heterogeneity. Treating the groundwater hydrodynamic zones as the computation units, the maximal information coefficient (MIC) and the geodetector model (GDM) were applied to measure the correlation between reservoir parameter and average daily gas production. An evaluation index system was then established, and its weight vector was obtained from a game theory model which couples the MIC scores with the GDM q-values. Taking the Gujiao mining area in the northern Qinshui Basin as a case study, the proposed model demonstrates a reliable classification of reservoir potential in alignment with the prior studies. The result indicates that the proposed model provides an insight into the relationship between CBM production and the reservoir heterogeneity, e.g., the distinction of hydrodynamics leads to the importance variation of the primary reservoir parameters and results in the uneven CBM production. Moreover, the model offers a quantified measurement of the correlation between reservoir heterogeneity and CBM production, and eliminates the subjective influence from the conventional methods.

Lithofacies identification of deep coalbed methane reservoir based on high-resolution seismic inversion

During the exploration and development of deep coalbed methane (CBM), delineating the thickness of coal seam and lithofacies of the roof and floor is one of the major challenging tasks. In past attempts, the prediction methods of these parameters have been limited to the conventional inversion. However, the effect of coal shielding on adjacent reflecting layers restricts the identification of underlying sand effectively by conventional inversion. Also, the depth at which the deep CBM zone is located (1,500–2000 m) produces a significant overlap of P-wave impedance and Vp/Vs of sands and shale which increases classification uncertainty between these two lithofacies. We proposed a new workflow for high-precision quantitative seismic interpretation of deep CBM reservoir. Not only P-wave impedance but also GR is selected as the optimized attributes for lithofacies classification. To reduce the effect of strong reflection of coal seam and identifying thin coal layers, the seismic waveform indication inversion method is used to obtain high-resolution results of P-wave impedance and GR. It uses horizontal changes in seismic waveforms to reflect lithological assemblage characteristics for facies-controlled constraints. Then, Bayesian classification theory is used to achieve three-dimensional lithofacies classification with multi-source data. To improve the continuity and accuracy of the interpreted results, a Markov chain is applied in the Bayesian rule as the spatial prior constraint. A well-associated synthetic test and field data application in Ordos Basin demonstrates the accuracy of the proposed workflow. Compared with conventional inversion, the results of proposed workflow showed higher resolution and accuracy. By providing a new solution for the identification of roof and floor lithofacies of deep CBM reservoir, this workflow aims to contribute to the better exploration and development of deep CBM.

Image-based quantitative probing of 3D heterogeneous pore structure in CBM reservoir and permeability estimation with pore network modeling

Coalbed methane (CBM) recovery is attracting global attention due to its huge reserve and low carbon burning benefits for the environment. Fully understanding the complex structure of coal and its transport properties is crucial for CBM development. This study describes the implementation of mercury intrusion and μ-CT techniques for quantitative analysis of 3D pore structure in two anthracite coals. It shows that the porosity is 7.04%–8.47% and 10.88%–12.11%, and the pore connectivity is 0.5422–0.6852 and 0.7948–0.9186 for coal samples 1 and 2, respectively. The fractal dimension and pore geometric tortuosity were calculated based on the data obtained from 3D pore structure. The results show that the pore structure of sample 2 is more complex and developed, with lower tortuosity, indicating the higher fluid deliverability of pore system in sample 2. The tortuosity in three-direction is significantly different, indicating that the pore structure of the studied coals has significant anisotropy. The equivalent pore network model (PNM) was extracted, and the anisotropic permeability was estimated by PNM gas flow simulation. The results show that the anisotropy of permeability is consistent with the slice surface porosity distribution in 3D pore structure. The permeability in the horizontal direction is much greater than that in the vertical direction, indicating that the dominant transportation channel is along the horizontal direction of the studied coals. The research results achieve the visualization of the 3D complex structure of coal and fully capture and quantify pore size, connectivity, curvature, permeability, and its anisotropic characteristics at micron-scale resolution. This provides a prerequisite for the study of mass transfer behaviors and associated transport mechanisms in real pore structures.

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.

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.

Implication of fast shear wave azimuth and critically stressed fractures in a coalbed methane reservoir

The orientation of the fractures and stresses within coal seams plays a critical role in gas production from coalbed methane reservoirs. In this study, we used resistivity images and sonic logs to investigate these parameters, aiming to (1) establish the relationship between fracture orientations and the polarization angles of fast shear waves and (2) detect active fractures in the coal seam. Shear waves in anisotropic formations are split into fast and slow components, with Alford’s rotation method used to determine the polarization angles of the fast shear wave. We found that the fast shear wave aligns with the direction of higher fracture intensity. Subsequently, we incorporated the poroelastic strain model to estimate the vertical ([Formula: see text]), maximum horizontal ([Formula: see text]), and minimum horizontal ([Formula: see text]) stresses in the wellbore. These stress magnitudes aided in identifying the faulting regime and were corroborated by vertical opening mode fractures. Validation of [Formula: see text] and [Formula: see text] involved comparisons with the breakout width in image logs and the closure pressure observed during hydraulic fracturing treatments. Applying Mohr’s Coulomb criteria, the stress model discerned the state of the fractures, transforming the stress magnitudes into shear and effective normal stress on each fracture plane. Our observations indicated that the identified fractures existed in a noncritically stressed condition, suggesting a lack of interconnectivity among them. These findings correspond to the absence of gas production to date, providing insights into the dynamics of fractures and their impact on production behavior.