Search Results (153)

Aiming at the technical bottlenecks of deep coalbed methane (DCBM) reservoirs, including ultra-low permeability, prominent stress sensitivity, difficulty in characterizing complex hydraulic fractures, and the inability to quantitatively differentiate produced free gas and adsorbed gas, this paper constructs a numerical simulation model coupling matrix, cleat fractures, hydraulic fractures and wellbores by adopting the matrix bordering treatment technique. This work couples a DCBM dual-porosity single-permeability model with the embedded discrete fracture model (EDFM) for numerical simulation. On the basis of the established numerical simulation model, a quantitative classification method for the proportions of free gas and adsorbed gas in produced DCBM is proposed to realize quantitative partitioning of the two gas components. Field verification based on vertical DCBM Well A demonstrates that the average relative error of daily gas production predicted by the proposed model is merely 7.54%, which delivers a 7.31% improvement in prediction accuracy compared with a commercial simulation software. Further parametric sensitivity investigations yield the following key findings: the gas content of DCBM reservoir acts as the dominant controlling factor of productivity, and an 8.1% rise in coalbed gas content yields a 98.07% increase in cumulative gas production; compared with the gas content, coalbed stress sensitivity ranks second among reservoir factors in terms of its influence on ultimate cumulative gas production. The impact of coalbed stress sensitivity is mainly reflected in the sharp productivity decline during the middle–late production stage. Hydraulic fracture length serves as the primary controlling factor for late-stage daily gas output; by contrast, early productivity is dominated by hydraulic fracture conductivity. Variations in bottom-hole pressure drawdown rate create marginal discrepancies in total cumulative production, and a drawdown regime of 0.05 MPa/d is recommended to maintain stable gas output over the entire production cycle. Quantitative classification calculation of free and adsorbed gas proportions in produced DCBM indicates that free gas only prevails in the early production stage and is quickly overtaken by adsorbed gas. After 660 days of production, free gas accounts for 33% of the total gas production of Well A, while adsorbed gas accounts for 67%. Moreover, the depletion of reservoir free gas is confined within the well drainage area, with nearly no pressure or gas content disturbance observed in far-well regions. The established model can provide theoretical support for dynamic productivity forecasting, production regime optimization and produced gas composition analysis of DCBM reservoirs. Full article

A two-dimensional dimensionless model is developed to investigate heat transfer during the melting of a pure phase change material (PCM) confined in a horizontal rectangular cavity. The model describes isothermal solid–liquid phase change in the presence of natural convection and is formulated using the momentum and energy conservation equations. To avoid explicit tracking of the moving solid–liquid interface, an enthalpy–porosity approach is employed, allowing the governing equations to be solved over the entire computational domain on a fixed grid. The finite volume method is used for spatial discretization, and a FORTRAN code based on the SIMPLER algorithm is implemented to simulate the melting process. Fluid motion in the solid region is suppressed through a porosity function linked to the local liquid fraction. After validation, a parametric analysis is performed to evaluate the effects of interpolation schemes, Fourier number, PCM subcooling, and liquid-phase superheating on melting dynamics and thermal energy storage. The results reveal that these parameters significantly influence melting behavior and storage performance. A predictive correlation for the dimensionless liquid volume during gallium melting is also proposed. Full article

The exploitation of deep coalbed methane is of great significance for easing China’s energy supply pressure and realizing the “Dual Carbon” goals. However, local grid refinement simulation methods for coalbed methane cannot well capture the characteristics of deep coalbed methane reservoirs, including strong stress sensitivity and high brittleness. To tackle this issue, this paper develops a novel numerical simulation approach dedicated to deep coalbed methane development. Integrated with the fluid–solid coupling effect in rock mechanics, this approach considers the interporosity flow between matrix pores and cleat fractures as well as that between cleat fractures and hydraulic fractures, and establishes a multi-dimensional coupled simulation framework on the basis of the dual-porosity single-permeability model and embedded discrete fracture model. Simulation results show that compared with the local grid refinement model, the daily gas production curve simulated by the proposed method is more consistent with the actual field curve. The local grid refinement method fails to accurately characterize the specific morphology of hydraulic fractures. The average relative error of the local grid refinement model reaches 25.61%, while that of the model in this paper is only 7.54%, representing an accuracy improvement of 18.07%. Sensitivity analysis draws the following conclusions: reservoir gas content is the dominant geological factor governing deep coalbed methane output, and raising reservoir gas content can boost cumulative gas production by 45.77%; hydraulic fracture length mainly affects gas production performance in the middle and late production stages, while fracture conductivity dominates early-stage productivity. This method can fully characterize the coupled flow behaviors of three types of media (matrix pores, cleat fractures and hydraulic fractures), and offers solid technical support for productivity forecasting and development scheme optimization of deep coalbed methane reservoirs. Full article

Petrophysical parameters of rocks and ores, influenced by composition, porosity, temperature, and pressure, are generally distributed uniformly or continuously in space—relatively homogeneous within individual geological units and varying smoothly across stratigraphic transition zones and contact boundaries. Based on this geological characteristic, this paper establishes a three-dimensional (3-D) piecewise linear continuous spectral parameter model to compute forward responses of apparent spectral parameters under low-frequency current excitation. The calculation follows a two-step workflow: finite-element forward simulation of multi-frequency apparent complex resistivity, followed by recursive inversion to obtain apparent spectral parameters. The subsurface medium is discretized with hexahedral meshes, with four Cole–Cole parameters (zero-frequency resistivity, chargeability, time constant, and frequency exponent) assigned to each mesh node. Linear interpolation is adopted for complex resistivity and potential within each element, ensuring piecewise linear continuity of both physical properties and simulated fields. To improve accuracy, the total complex potential is decomposed into a primary field from the source current and a secondary field from complex conductivity variations, and the corresponding boundary value problem and variational form are derived. On this basis, we implement the finite-element algorithm for 3-D piecewise linear continuous media and the recursive inversion algorithm for spectral parameters, and develop an interactive 3-D SIP forward modeling program. Comparison with analytical solutions for a continuous layered model shows good agreement, with relative errors below 1.5% for the real part and 3.8% for the imaginary part of apparent complex resistivity. Two numerical cases—a cubic anomaly in homogeneous half-space and a sandbox model—further verify the performance of the proposed method. Full article

Hydraulic fracturing is the core technology for stimulation and reform of low-permeability and unconventional oil and gas reservoirs. Reservoir fracability directly determines fracture morphology, complexity, and stimulated reservoir volume. To address the shortcomings of existing fracability evaluation models, such as poor applicability, subjective weighting and insufficient accuracy, five key indicators are selected, including brittleness index, brittle mineral index, stress difference coefficient, minimum horizontal principal stress and porosity. First, the three-dimensional discrete lattice method is used to clarify the influence of each parameter on fracture complexity. Then, the Analytic Hierarchy Process (AHP) and Entropy Weight Method (EWM) are combined to determine the indicator weights, a continuous fracability evaluation model is constructed, and a classification standard for fracturing applicability is established. The results show that the brittleness index has the greatest influence on fracture complexity with a weight of 0.3559, followed by brittle mineral index (0.2986), minimum principal stress (0.1994), stress difference coefficient (0.0993) and porosity (0.0467). The reservoir fracability indices of 0.37 and 0.59 are the mutation points of fracture complexity. Based on microseismic evaluation of stimulated reservoir volume (SRV) using an envelope surface method, it is found that reservoirs with low fracability are more suitable for fracturing designs characterized by large cluster spacing, fewer clusters, and smaller stage spacing. In contrast, reservoirs with medium and high fracability can develop more complex fracture networks by reducing cluster spacing, increasing the number of clusters, and adopting higher pumping rates. The research results can provide theoretical basis and technical support for hydraulic fracturing operation design. Full article

To address the industry challenge that the formation breathing effect in fractured formations narrows the safe mud weight window and significantly increases well control difficulty, this study employs two approaches—a self-designed experimental apparatus for the formation breathing effect and a combined finite-discrete element method (FDEM) numerical model—to systematically reveal the characteristic behavior and underlying mechanism of this effect, and to establish a prediction method for near-wellbore lost-circulation pressure that accounts for the breathing effect. The numerical simulation achieves high quantitative accuracy, with errors of less than 2.1% during the loss stage and less than 4.1% during the flowback stage. The results show that the typical signature of the breathing effect in fractured formations is a sustained loss of drilling fluid followed by rapid flowback, resulting in a pronounced reversible volume change in the wellbore. The intrinsic mechanism lies in the switching between fracture opening and closure triggered by the shift in the pressure differential between the wellbore and the formation. Parametric sensitivity analysis indicates that increasing wellbore pressure intensifies the breathing effect; formations with low fracture opening pressure, high porosity, and high permeability are more prone to severe breathing effects. Increasing the plastic viscosity and yield point of the drilling fluid can suppress the breathing effect, but careful management of the resulting increase in circulating friction and equivalent circulating density (ECD), which raises bottomhole pressure, is required. Field case calculations for a well in the Cameroon block show that, after improving the lost-circulation pressure calculation method to incorporate the breathing effect, the safe mud weight window can narrow by up to 0.03 g/cm³. This study advances the understanding of breathing effects in fractured formations and provides theoretical support for safe drilling within the narrow mud weight windows commonly encountered in such formations. Full article

The distribution and volume of karst caves are the core parameters for the development of fractured cave reservoirs. In this paper, the single-phase seepage equation is adopted to describe the pressure variation in the fracture system, the wave equation is introduced to characterize the pressure dynamics in the cave, and based on the discrete technology of unstructured grid and finite volume method, the numerical simulation algorithm of fractured caved reservoirs is realized. This framework uniquely enables the inversion of physically meaningful karst cave parameters—specifically volume and location—directly from interference/pulse test data, bridging a significant gap between conventional statistical multi-porosity models and practical reservoir characterization needs. Using this algorithm program, a simulation study was conducted on the impulse well test responses of active wells and observation wells in fractured caved reservoirs. Studies show that the volume of karst caves with connectivity and the distance between the active well and the karst cave are the key factors affecting the pressure response of the observation well: the larger the volume of the karst cave, the smaller the variation range of the pressure of the observation well; The greater the distance between the active well and the cave, the smaller the variation range of the observation well pressure. Based on the above rules, this paper proposes for the first time to use the pressure response and derivative historical fitting method of the observation well in pulse well testing to inversely explain key parameters such as the volume and location of the karst cave. This research provides a theoretical basis for the application of pulse well testing technology in the evaluation of fractured caved reservoirs. Full article

The modeling accuracy of rice straw remains limited, and discrete element method (DEM) simulations of its compression are computationally intensive. To address these challenges, this study systematically investigated the physical characteristics of rice straw and proposed an innovative DEM and parameter calibration approach. Uniaxial compression tests were conducted on individual straw stalks, and key DEM parameters were systematically calibrated using Plackett–Burman experiments, steepest ascent trials, and Central Composite design. The calibrated parameters were validated against single-straw compression tests, showing a relative error of only 1.9% between simulated and measured peak loads, indicating high model fidelity. Building on this foundation, vibration-assisted compression bench tests were performed on bulk straw, further validating the scaled-up DEM and its parameters. The evolution of normal forces and porosity during compression was analyzed by comparing experimental results with simulations, confirming the model’s accuracy in capturing straw compaction behavior. Finally, a comparison of computational efficiency between the scaled-up and original DEMs revealed that the scaled-up model reduced computation time by approximately 67.4% and 65.2%, respectively, significantly improving simulation efficiency. This study provides a robust methodology for modeling flexible agricultural fibers and establishes a foundation for efficient numerical simulation of straw compression. Full article

Subsoiling can break the plough pan and improve the root growth environment. The effect of the traditional subsoiler is poor, as it relies only on the chisel tine, but pneumatic subsoiling can improve the soil structure more efficiently through the negative pressure generated by the jet hole. This research used computational fluid dynamics and the discrete element method to optimize the biomimetic structure of the jet hole, model the pneumatic subsoiling process at a depth of 330 mm, and observe the movement of soil particles as airflow passes through. The effect of the jet hole at different positions and sizes on the plough pan soil was analyzed, and fluid domains and measurement areas were set up to observe the upward movement, diffusion, stabilization, and settling of soil particles under the action of airflow. The results of the soil bin experiment validated the accuracy of the simulation model through draft force and vertical force, and the average error between the simulation and experimental data was 2.8%. The study revealed that the increase in the rate of soil porosity reached a maximum of 3.65% when the jet hole was positioned above the chisel tine with a radius of 4 mm. The biomimetic jet hole pneumatic subsoiler designed in this study, along with the established CFD-DEM coupled simulation model capable of predicting pneumatic subsoiling performance, can provide references for the design and application of a pneumatic subsoiler. Furthermore, it also provides a theoretical basis for understanding the mechanism of airflow on soil during pneumatic subsoiling operations. Full article

In deep geothermal engineering, concrete slabs are prone to thermal cracking. The aggregates and pores are the core influencing factors for this failure behavior. However, existing research methods are unable to accurately capture the microscopic evolution process of thermal cracking and cannot clarify the intrinsic mechanism of how the characteristics of aggregates and pores affect the initiation and propagation of cracks. This limitation restricts the in-depth understanding of the laws of concrete thermal cracking. To address this deficiency, this study employs the discrete element method (DEM) and combines the particle flow program PFC2D to construct a microscopic model of concrete disks. By setting reasonable temperature parameters and thermal load boundaries, a numerical simulation system matching the actual deep geothermal high-temperature environment is established. Three sets of quantitative variables were designed: aggregate particle size (0.003, 0.004, 0.005, 0.006), aggregate volume fraction (0.35, 0.40, 0.45, 0.50), and porosity (0.11, 0.12, 0.13, 0.14). Through controlled variable simulations, the influence laws of each variable on the formation, propagation path, and time evolution of concrete thermal cracks were explored. The quantitative research results show that an increase in aggregate particle size significantly accelerates the generation and propagation of cracks. When the particle size is 0.006, the number of cracks is the highest and the propagation rate is the fastest. The aggregate volume fraction is negatively correlated with the final number of cracks, and 0.50 is the optimal fraction, at which the number of cracks is the smallest. A decrease in the fraction will lead to intensified stress concentration in the cement paste and a sudden increase in the number of cracks. An increase in porosity significantly disrupts the material continuity. When the porosity is 0.14, the bifurcation and connection of cracks are the most significant, while a low porosity of 0.11 can effectively inhibit the overall development process of thermal cracks. In addition, compared with traditional experimental methods and continuous medium numerical simulation techniques, the discrete element method has unique advantages in revealing the internal mechanism of concrete thermal cracking at the microscopic level. It can achieve real-time tracking of the evolution of discrete micro-cracks and the internal stress distribution characteristics. This study enriches the microscopic theoretical system of concrete thermal cracking and provides reliable quantitative references and technical support for the design of thermal crack resistance of concrete in deep geothermal engineering and the optimization of material composition. Full article

Shale gas, as an unconventional resource, requires hydraulic fracturing to create complex fracture networks due to its low porosity and permeability. However, the presence of interlayers significantly affects fracture propagation, leading to highly complex fracture morphologies. This study focuses on the interbedded shale of the WJP Formation in southern China. A three-dimensional block discrete element method (BDEM) was employed to establish a hydraulic fracture propagation model, systematically investigating the effects of geological parameters (stress difference, interlayer thickness), engineering parameters pumping rate, fluid volume, viscosity), and perforation parameters (cluster number, cluster spacing, perforation location) on fracture network morphology. The results indicate that: (1) Among geological parameters, interlayer thickness is the key factor inhibiting vertical fracture propagation. Due to the influence of interlayers, an increase in stress difference promotes fracture length but suppresses fracture height and stimulated reservoir volume (SRV); (2) For engineering parameters, there exists a “threshold effect” for pumping rate and fluid volume, with 16 m³/min and 2000 m³ identified as the critical thresholds for interlayer breakthrough. Low viscosity (1 mPa·s) is conducive to forming complex fracture networks, while high viscosity extends fracture length but reduces SRV; (3) Regarding perforation parameters, the optimal stimulation effect is achieved with 6–7 clusters, a cluster spacing of 10 m, and perforation locations in the center of the main shale layer (19.85–21.6 m); (4) By introducing grey relational analysis, the degree of correlation between various influencing factors and the response to interlayer breakthrough is systematically evaluated based on the breakthrough conditions under different factors. Thin interlayers or low stress differences can reduce the critical pumping rate, whereas thick interlayers (≥3 m) become the primary constraint, making breakthrough difficult even at high pumping rates. Reliable interlayer breakthrough requires the simultaneous satisfaction of Δσ ≤ 16 MPa, h < 1 m, and Q ≥ 16 m³/min. The reliability of the model was verified by comparing numerical simulation results with field microseismic data. This study reveals the extension laws of complex fracture networks in interbedded shale, providing a theoretical basis for fracturing design and development optimization. Full article

Granular deposition and grading strongly influence pore-space topology and hence hydraulic conductivity in natural and engineered porous media, yet quantitative links between deposition sequence, particle-scale morphology, pore-network descriptors, and permeability anisotropy remain incomplete. Here, we develop a process-based digital porous-media framework that couples discrete element method (DEM) deposition with pore-network characterization and Darcy-scale permeability evaluation. Two deposition sequences—normal grading (coarse-to-fine) and reverse grading (fine-to-coarse)—are simulated using bi-disperse particle sets with controlled size ratios. To further isolate the role of particle morphology, particle irregularity is parameterized by a Perlin-noise-based shape perturbation factor and incorporated into the DEM-generated packings. For each packing, pore networks are extracted and quantified in terms of pore/throat size distributions and connectivity, while pore-space complexity is measured via box-counting fractal dimension. Single-phase flow is solved under imposed pressure gradient, and intrinsic permeability is computed along three orthogonal directions to evaluate anisotropy. Results show that increasing size contrast reduces porosity, shifts pore and throat distributions toward smaller characteristic radii, increases pore-space fractal dimension, and yields a monotonic permeability reduction. For identical size ratios, reverse grading consistently yields higher permeability than normal grading, suggesting that deposition sequence exerts a strong control on the continuity and efficiency of effective flow pathways at the sample scale. Increasing particle irregularity decreases permeability and systematically modifies permeability anisotropy, transitioning from weak horizontal anisotropy toward near-isotropy and, at strong irregularity, toward preferential vertical permeability. The proposed framework provides a reproducible route to relate depositional history and particle morphology to pore-network structure and directional permeability, offering implications for filtration, packed-bed design, and sedimentary reservoir characterization. Full article

Molten Metal Jetting (MMJ) is an emerging metal additive manufacturing process that produces components via on-demand jetting of discrete droplets. This paper reports properties of T6 heat-treated AlSi7Mg alloy produced in different build orientations via MMJ. A Xerox ElemX machine was used to print AlSi7Mg coupons in horizontal, tilted, and vertical orientations. The aluminum feedstock was melted at 825 °C and was printed onto a 475 °C heated print bed using a jetting frequency of 400 Hz and a drop spacing of 500 μm. Coupons were heat treated to a T6 temper. The average yield strengths of heat-treated coupons in vertical and horizontal orientations were 240.4 ± 7.3 MPa and 244.6 ± 7.1 MPa respectively. This indicates that the vertical build orientation had minimal adverse effect on strength. However, average strain (11.5% ± 1.2% versus 14.6% ± 3.5%) values for the vertical and horizontal orientations, respectively, showed more pronounced effects. X-ray CT analysis of vertically oriented coupons revealed increases in porosity in material deposited above heights of ~90 mm. Above this build height, the measured surface temperature dropped below ~455 °C. External heating methods are therefore advised in order to maintain a surface temperature ≥ 455 ° and avoid excess porosity. Full article

Based on the discrete element method (DEM), a sand particle contact force model and a motion model for the 3D sand printing (3DSP) process were developed. By accounting for the viscous support force and contact force between sand particles, and gravity acting on each individual sand particle, the displacement of sand particles was calculated, enabling the simulation of the 3DSP process using sand particle ensembles. Furthermore, the effects of the ratio of silica sand to ceramsite sand and the recoating speed on sand-recoating performances and mechanical properties were investigated. Irregularly shaped sand particles (primarily silica sand) were constructed via the multi-sphere filling method. The simulation was performed on a virtual sand-recoating device (180 mm in length, 100 mm in width, 70 mm in height) with reference to the EXONE S-MAX printer. Meanwhile, the EXONE S-MAX was utilized to print the bending samples for experimental validation. Simulation and experimental results indicate that as the ratio increases, the porosity first decreases and then increases, whereas mechanical properties exhibit an initial increase followed by a decrease. At a ratio of 3:7, the porosity reaches a minimum of 21.3%; correspondingly, the shear force of bonding bridges peaks at 908 mN, and the bending strength of specimens attains a maximum of 2.87 MPa. With the increasing recoating speed, the porosity rises consistently, while the shear force of bonding bridges and the bending strength of specimens first increase and then decrease, which is primarily attributed to the penetration behavior of the binder under capillary force. At a recoating speed of 160 mm·s⁻¹, the shear force of bonding bridges reaches its maximum, and the specimens achieve a maximum bending strength of 2.89 MPa. The simulation results are well-validated by the experiments. The DEM-based simulation method proposed in this study offers a practical and convenient tool for parameter optimization in 3DSP process. Full article

Particle size distribution (PSD), also referred to as grain-size distribution (GSD), is a fundamental characteristic of granular materials, influencing packing density, porosity, permeability, and mechanical behavior across soils, sediments, and industrial powders. Accurate and reproducible representation of PSD is essential for computational modeling, digital twin development (i.e., virtual replicas of physical systems), and machine learning applications in geosciences and engineering. Despite the widespread use of classical distributions (log-normal, Weibull, Gamma), there remains a lack of systematic frameworks for generating synthetic datasets with controlled statistical properties and reproducibility. This paper introduces a unified computational framework for generating virtual PSDs/GSDs with predefined statistical characteristics and a specified number of grain-size fractions. The approach integrates parametric modeling with two histogram-based allocation strategies: the equal-width method, maintaining uniform bin spacing, and the equal-probability method, distributing grains according to quantiles of the target distribution. Both methods ensure statistical representativeness, reproducibility, and scalability across material classes. The framework is demonstrated on representative cases of soils (Weibull), sedimentary and industrial materials (Gamma), and food powders (log-normal), showing its generality and adaptability. The generated datasets can support sensitivity analyses, experimental validation, and integration with discrete element modeling, computational fluid dynamics, or geostatistical simulations. Full article