Search Results (222)

This study focuses on the Chang 8 Member tight sandstone reservoir in the Xifeng Oilfield. Integrated approaches including 3D reconstruction of CT digital cores, seepage simulation, and multi-parameter coupling analysis were employed to systematically classify lamina types, quantitatively characterize lamina-associated fractures, and elucidate the pore–lamina fracture coupling seepage mechanisms. The results show that laminae in the study area can be categorized into three types: banded, inclined, and cross-laminated. Lamina-associated fractures are dominated by bedding-parallel fractures, with a small number of cross-bedding fractures having developed in cross-laminated intervals. The development of lamina-associated fractures is jointly controlled by sedimentary heterogeneity and mechanical differences between interlaminar layers. A significant positive correlation exists between the volume proportion of interlaminar layers and fracture porosity (R² = 0.8913). Cross-laminated intervals exhibit the optimal fracture parameters, with fracture porosity reaching up to 3.6% and maximum fracture volume exceeding 3500 mm³, facilitating the formation of three-dimensional interconnected fracture networks. Distinct pore–lamina fracture coupling patterns are observed in different lamina types: independent development with weak coupling in banded laminae, segmented synergy with heterogeneous coupling in inclined laminae, and strong synergy with network coupling in cross-laminated intervals. In cross-laminated sections, matrix porosity and fracture porosity evolve synchronously, yielding the highest permeability (up to 7.3 mD) and superior storage–permeability performance. Seepage simulations confirm that permeability in tight reservoirs is not directly controlled by matrix porosity; instead, lamina-associated fractures act as the dominant fluid migration pathways. Cross-laminated fractures form multi-directional high-efficiency seepage networks, while banded and inclined laminae exhibit unidirectional linear seepage and segmented dominant channeling characteristics, respectively. These findings provide critical geological insights for sweet spot evaluation, horizontal well trajectory optimization, and hydraulic fracturing design in tight oil reservoirs. Full article

Deep metal mines face increasing risks of water and sand inrush under complex fracture network conditions, where the unclear mechanism of slurry diffusion limits the reliability of horizontal curtain grouting. Taking the Cuihongshan iron–polymetallic mine as a case study, this paper establishes a stochastic three-dimensional discrete fracture network model and adopts an orthogonal experimental design to systematically investigate the effects of key engineering parameters on grout diffusion behavior. The results reveal that grouting pressure acts as the dominant controlling factor, significantly expanding the diffusion range and promoting the formation of continuous high-fill zones within the fracture network. Conversely, slurry viscosity exhibits a negative correlation with diffusion performance, leading to reduced inter-borehole connectivity as viscosity increases. Compared with conventional macro-indicators, the inter-borehole overlap rate provides a more precise quantitative measure of curtain continuity. The study demonstrates that achieving a sufficiently high overlap rate is critical for transitioning from discontinuous filling to a reliable impermeable curtain. These findings offer a theoretical basis for optimizing grouting parameters and evaluating sealing effectiveness in deep mine construction. Full article

Cemented natural fractures are widely developed in unconventional reservoirs and play a key role in controlling hydraulic fracture propagation and fracture network evolution. However, their mechanical effects are often oversimplified in conventional numerical models, limiting the reliability of fracture prediction. A numerical framework was established to investigate hydraulic fracture propagation in reservoirs containing cemented natural fractures. Cementation effects are quantitatively characterized using two parameters—cementation degree ($C_d$) and cementation strength ($C_s$)—representing the filling condition and interfacial resistance of natural fractures. Based on this formulation, both single-fracture and multiple-fracture models are constructed to analyze the influence of cementation properties and fracture density on fracture propagation. The results show that $C_d$ mainly controls fracture activation and propagation mode. Lower $C_d$ promotes fracture diversion and branching, whereas higher $C_d$ favors fracture penetration through the interface. $C_s$ governs interfacial resistance, with higher $C_s$ leading to more stable propagation. Increasing fracture density enhances fracture network complexity but also intensifies stress interference, affecting propagation stability and connectivity. These findings provide mechanistic insights into the role of cemented natural fractures in hydraulic fracturing and may support a more reliable interpretation of fracture propagation behavior in naturally fractured reservoirs. Full article

Hydraulic fracturing in naturally fractured shale reservoirs commonly generates complex mesh-like fracture networks governed by hydraulic fracture–natural fracture interactions, which strongly affect stimulated volume, fracture connectivity, and early-time production. Existing simulation and monitoring-based methods often cannot simultaneously capture interaction mechanisms, rapidly generate field-scale fracture networks, and validate production responses. This study proposes a mechanics-constrained recursive propagation framework. A field-constrained stochastic natural-fracture model is first constructed, an explicit hydraulic fracture–natural fracture interaction criterion is incorporated to identify penetration, opening, and shear slipping, and a fully vectorized bidirectional recursive algorithm is developed to efficiently generate complex fracture networks. The method is applied to a 40-stage fractured horizontal well in the Changqing Oilfield, where the target interval has a porosity of 6.1%, a permeability of 0.1 mD, and a horizontal stress contrast of 7.0 MPa. The simulated network reproduces crossing, arrest, unilateral diversion, and bilateral diversion, and agrees well with microseismic observations. EDFM-based fully implicit flow simulation further shows early-time production deviations of 2–10%. These results demonstrate that the proposed framework can efficiently generate physically plausible field-scale fracture networks for fracturing design, post-fracturing evaluation, and short-term production forecasting. Full article

The inherent heterogeneity of coal significantly influences cutting efficiency, directly impacting energy consumption and dust generation in mining operations. To investigate this effect, this study established a heterogeneous coal model using PFC 2D 5.0, assigning strength parameters based on the Weibull distribution. The influence of the heterogeneity index (λ) on macroscopic strength, brittleness, and micro-crack propagation during coal cutting was systematically analyzed, and comparisons were made with homogeneous models of varying uniaxial compressive strength (UCS). The results show that as λ increases, both UCS and Brazilian tensile strength (BTS) increase exponentially, approaching the values of the homogeneous models, with BTS exhibiting greater sensitivity to λ than UCS. The brittleness index also increases with λ. During cutting, a higher λ leads to more concentrated crack propagation and stress distribution, as well as a reduced proportion of shear cracks, indicating a shift toward a more controllable fragmentation mode. Correspondingly, the specific energy (SE) for cutting decreases monotonically with λ, reflecting enhanced cutting efficiency, a trend attributed to the reduced energy dissipation from shear friction and the homogenization of internal stress distribution. Compared with homogeneous models, the heterogeneous models produce a more complex crack network and a greater number of cracks at lower strength levels, though these differences diminish as λ increases. These findings provide theoretical insights for optimizing cutting parameters to reduce energy consumption and minimize uncontrolled fracturing in efficient coal resource exploitation. Full article

Amid the restructuring of the global knowledge economy, the structural imbalance of “high input, low commercialization” and the “valley of death” trap have emerged as core bottlenecks restricting the high-quality development of regional innovation. This study aims to explore the collaborative pathway connecting knowledge production to value creation by constructing a ternary Innovation–Platform–Commercialization (IPC) system, which covers front-end research and development (R&D), mid-end integration, and back-end commercialization. Based on China’s provincial panel data from 2013 to 2023, this paper comprehensively employs the coupling coordination model, spatial disparity analysis, and machine learning methods to quantitatively evaluate the coordinated evolutionary pattern of the system and deconstruct its core driving factors. The results indicate the following: First, the overall coordination of the IPC system has steadily improved, yet it exhibits significant spatial agglomeration and local lock-in risks. Second, the underlying cause of spatial disequilibrium has evolved from an absolute scale gap to cross-regional structural fractures. Third, the current core constraint on system development is no longer front-end R&D investment but rather high-value technology trading barriers and the insufficient empowerment of intermediary networks. Finally, the driving effects of traditional elements such as R&D funds and platform scale significantly diminish or even stagnate after crossing specific thresholds, whereas agile organizational structures exhibit superior potential for coordination empowerment. This research breaks through the limitations of traditional unidirectional linear transfer models, confirming that the constraint logic of regional coordination has substantially shifted from “insufficient macro-resource investment” to “micro-organizational operational friction.” Consequently, it provides a theoretical and decision-making basis for local governments to implement precise governance tailored to regional endowments. Full article

Quantitative characterization of internal stress fields in fracture-dominated geological materials remains a significant challenge due to the limitations of conventional measurement techniques. This study presents the first quantitative full-field stress analysis of slightly sandy dolomite (Level I sandification) using an enhanced CT-3D printing–photoelasticity workflow. Five transparent physical models were fabricated from CT-scanned dolomite specimens to replicate the natural fracture-matrix structure and tested under diametrical compression (800 N) using ten-step phase-shifting digital photoelasticity. To overcome the severe optical noise generated by dense fracture networks, a robust phase unwrapping procedure (CPULSI) was incorporated into the data processing pipeline, enabling continuous stress parameter retrieval where conventional unwrapping methods fail. The recovered full-field principal stress-difference maps reveal that the internal stress field is dominated by meso-scale fracture geometry: Stress concentrations localize at fracture tips and narrow intact matrix bridges, reaching 3–5 times the far-field stress, while the macro-scale loading pattern becomes progressively obscured as fracture complexity increases across the five models. Quantitative validation against CT-based finite element simulations (RFPA-3D) demonstrates good agreement in intact matrix regions, with mean relative errors of 9–18%. These results provide new experimental evidence for the meso-scale stress distribution mechanisms governing the mechanical behavior of sandy dolomite—a geomaterial of significant engineering relevance in Southwest China—and establish a validated experimental pathway for investigating stress fields in other fracture-dominated geomaterials. Full article

Coal fire zones represent both severe geological hazards and viable sources of clean geothermal energy for coal-fired power plant integration. However, the precise delineation of their boundaries remains a critical scientific deficit, hindering high-resolution exploration in complex terrains. To address this, the ground-based Distributed Wide-Field Electromagnetic Method (DWFEM) was employed to investigate a surface coal mine in Xinjiang. Leveraging its high anti-interference capability and lateral resolution, DWFEM enables us to obtain high-quality data, and create the construction of a 3D geoelectrical model to characterize subsurface structures. The results demonstrate that DWFEM effectively identifies the morphology of coal fire zones, revealing a distinct NE-SW trending fracture network which has width serving as geothermal reservoirs. Compared with conventional geological data, DWFEM provides a significantly more detailed characterization and resolves internal structures undetectable by traditional surveys. This study confirms the efficacy of DWFEM in anti-interference, lateral resolution, providing essential technical support for safe mining and geothermal development. Full article

To clarify the migration characteristics of overlying strata during backfill mining of close-distance coal seams, the 3306 working face of Chaili Coal Mine was taken as the engineering background, and similar-material simulation, fracture-fractal analysis, and FLAC3D numerical simulation were carried out under an 85% backfill ratio. The study reveals the coordinated inherited and reactivated evolution of fractures, displacement, and stress in the overlying strata during successive extraction of the upper and lower seams. The results indicate that the movement of the overlying strata shows pronounced stage dependence and inheritance. After extraction of the upper No. 3 coal seam, the response of the overlying strata evolves from local disturbance to overall structural readjustment, with continuous bending subsidence and progressive fracture propagation, and ultimately forms a two-belt structure. During extraction of the lower No. 3 coal seam, the response develops on the basis of the structural state formed after upper-seam mining and is manifested mainly by the reactivation and readjustment of the pre-existing fracture network and displacement field. The fractures undergo a dynamic process of generation, development, closure, redevelopment, and reclosure. Compared with upper-seam mining, lower-seam mining produces a larger vertical displacement and a weaker stress response. The maximum vertical displacement in-creases from 478.85 mm to 1019.76 mm, whereas the stress concentration coefficient of the immediate roof decreases from 2.01–2.03 to 1.93–1.99. Under the geological and mining conditions considered in this study, the 85% backfill ratio maintains overall bending subsidence of the overlying strata and alleviates strata pressure manifestations during lower-seam extraction. These findings provide a reference for strata control under similar backfill mining conditions. Full article

Reinforced Concrete (RC) structures experience progressive degradation over their service life due to mechanical loading and environmental exposure, leading to reduced bearing capacity and compromised structural safety. Incorporating discrete fibers into concrete mitigates crack propagation and enhances ductility, resulting in fiber-reinforced concrete (FRC) with superior fracture energy, durability, and sustainability characteristics. Despite these advantages, research on Structural Health Monitoring (SHM) techniques for FRC elements remains limited. The Electromechanical Impedance (EMI) method, which exploits piezoelectric transducers as both actuators and sensors, offers high sensitivity for detecting early-stage damage by monitoring variations in local mechanical impedance. This study investigates the effectiveness of a deep learning-enabled EMI framework for assessing the structural condition of FRC beams under flexural loading. A one-dimensional convolutional neural network (1D-CNN) is proposed to automatically extract salient features from high-frequency EMI signatures and classify structural health into three predefined states. The model is rigorously evaluated using specimen-invariant validation to ensure generalization across different FRC specimens, addressing a critical limitation of conventional cross-validation approaches in SHM research. Experimental tests on FRC beams instrumented with surface-bonded PZT transducers provide a dataset of 264 EMI responses for training and validation, enabling direct comparison between common and specimen-invariant validation schemes. The results demonstrate the superior robustness of the specimen-invariant approach and confirm the capability of the proposed 1D-CNN to identify flexural damage progression in FRC elements accurately. An ablation study further highlights the contribution of each architectural component to overall model performance. The findings underscore the potential of integrating EMI-based sensing with advanced deep learning models for reliable, automated, and scalable SHM of next-generation resilient concrete infrastructures. Full article

To address severe strata pressure induced by large end-area hanging spans and poor caving of thick, hard roofs in western coal mines, this study takes the 1302 working face of Zhujiamao Coal Mine as a case study. A multiscale mechanical model is developed to describe the progressive evolution of a stratified hard roof from a continuous beam to a cantilever beam and finally to an arched triangular hanging roof. Limit criteria for the maximum hanging length under bending and shear failure are derived, indicating that bending governs end-area roof instability. The theoretical results show good agreement with field observations and numerical simulations, providing guidance for liquid nitrogen fracturing target selection. Coupled FLAC3D-3DEC simulations reveal the staged deformation of overlying strata and clarify the spatial correspondence between the “O-X” fracture pattern and the arched triangular hanging roof. Based on these findings, a collaborative weakening strategy integrating directional drilling, hydraulic pre-cracking, and deep liquid nitrogen fracturing is proposed. Field observations and comparative tests confirm that this method effectively forms a three-dimensional fracture network, reduces roof stiffness and strength, shortens the caving interval, lowers peak shield resistance, and promotes stable caving of the end-area hanging roof. Full article

Shale oil in continental faulted basins of eastern China, represented by Jiyang Depression, has achieved breakthroughs in productivity. However, challenges such as deep burial, high formation pressure, and poor crude oil mobility pose significant obstacles to achieving high and stable production. Hydraulic fracturing is required to form complex fracture networks for stimulation. Factors such as the lamellar structure of shale, geomechanical conditions, and fracturing operation parameters affect fracture propagation. Therefore, this study establishes a numerical model of fracture propagation in lamina-developed shale using the discrete element software PFC2D 6.0, conducts simulation analysis of fracture propagation laws under in situ stress conditions, and characterizes the influence of lamellar structure and construction technology on fracture complexity. The results show that, for lamina-developed shale, the initiation pressure decreases with increasing injection rate; as the difference between the two horizontal principal stresses increases, hydraulic fractures gradually tend to propagate toward the direction of the maximum principal stress; under high injection pressure, a complex network of short fractures is formed, while, under low injection pressure, the length of the main fracture is prompted to increase. High density (9–10 strips/100 mm) enhances lamina penetration, favoring extension toward maximum horizontal principal stress; low density (4–5 strips/100 mm) strengthens lamina guidance, with fractures propagating along laminae near the injection hole. This research clarifies the mechanisms of fracture initiation and propagation in laminated shale, providing theoretical and technical support for optimizing hydraulic fracturing designs. Full article

Deep shale of the Lower Cambrian Qiongzhusi Formation in the Sichuan Basin represents a critical frontier for shale gas exploration in China. However, systematic understanding of the multi-scale links among lamination type, mechanical anisotropy, and fracture complexity remains limited. Based on lamination characteristics and total organic carbon (TOC) content, core samples were classified into four types. Using a multi-scale approach (uniaxial compression, Brazilian splitting, in situ CT scanning, QEMSCAN, and SEM), this study elucidates how lamination structure controls mechanical anisotropy, failure modes, and fracture mechanisms. The novelties of this work are threefold: (1) quantitatively linking specific lamination types (ORM, OPM, PAFC, PAF) to anisotropic mechanical responses; (2) introducing 3D fractal dimensions to evaluate fracture network complexity; and (3) integrating micro- (SEM) and macro-scale tests to reveal the coupled control of weak planes and brittle minerals on fracture propagation. Results indicate that laminated shales exhibit pronounced mechanical anisotropy. Loading parallel to laminations induces tensile splitting along weak planes, significantly reducing strength. Conversely, perpendicular loading generates complex fracture networks of horizontal secondary fractures along laminae and vertical main fractures through the matrix. Furthermore, 3D fractal dimension analysis quantifies fracture network complexity as follows: organic-poor clay-feldspar laminated shale > organic-poor clay-feldspar-calcareous laminated shale > organic-rich massive shale. Microscopic observations confirm that fracture propagation is jointly governed by weak plane systems and brittle mineral content, which collectively determine macroscopic failure patterns. These findings clarify how lamination type controls the laboratory mechanical response and fracture morphology of deep shale and provide a laboratory-scale framework for comparing lamination-related differences in mechanical anisotropy and fracture complexity in the Qiongzhusi Formation. Full article

The efficient recovery of coalbed methane (CBM) is critically constrained by the inherent low permeability of coal reservoirs, a challenge predominantly attributed to mineral blockages within the pore-fracture structure. In this study, the deashing efficacy of several acid solutions (HCl, HNO₃, HF, and CH₃COOH) on bituminous coals from the Yushuwan (YSW) and Jiangna (JN) mines was initially assessed to determine the optimal acidizing system. Subsequently, the multi-scale evolution of pore-fracture structures and the fractal characteristics of coal samples treated with the optimized acids were systematically investigated. A multi-analytical approach, integrating scanning electron microscopy (SEM), X-ray diffraction (XRD) with microcrystalline peak-fitting, and low-temperature nitrogen gas adsorption (LT-N₂GA), was employed to quantitatively elucidate the underlying transformation mechanisms. The experimental results indicate that HCl and HNO₃ emerged as the most effective agents for the YSW and JN coals, respectively. Optimized acidification achieved significant reductions in ash content (specifically, an ash removal efficiency of 83.99% for HCl-treated YSW coal) through the selective dissolution of carbonate and clay minerals, thereby facilitating the exposure of the organic matrix and the induction of extensive dissolution pits and secondary fractures. Although the dissolution-induced collapse of mineral-supported fine pores led to a reduction in both total pore volume and BET specific surface area, the average pore diameter undergoes a substantial increase (e.g., nearly doubling from 9.0068 nm to 16.5126 nm for the JN coal). Furthermore, the reduction in Frenkel–Halsey–Hill (FHH) fractal dimensions (D₁ and D₂) indicates a decrease in pore-surface complexity and structural heterogeneity. These findings reveal that optimized acidification induces significant alterations in pore structure and mineral composition. The treatment facilitates the conversion of isolated pores into interconnected networks, accompanied by an increase in pore volume and a shift in pore size distribution toward larger dimensions. This research elucidates the mechanisms of mineral dissolution and pore expansion, providing a fundamental characterization of the microstructural evolution of coal in response to acid treatment. Full article

Fractures as critical discontinuous structural planes in rock masses, directly govern their stability and serve as the core controlling factor in rock mechanics engineering. Existing deep learning models for fracture extraction face persistent challenges, including imbalanced integration of deep and shallow features, limited suppression of background noise, inadequate multi-scale feature representation, and large parameter sizes—making it difficult to strike a balance between detection accuracy and deployment efficiency. Focusing on the Wanshanshan quarry in Yunnan, this study first constructs a high-precision digital model using close-range photogrammetry and 3D real-scene reconstruction. A lightweight yet high-accuracy intelligent detection method, termed MSEM-Deeplabv3+, is then proposed for rock mass fracture extraction. The model adopts lightweight MobileNetV2 as the backbone network, incorporating inverted residual modules and depthwise separable convolutions, resulting in a parameter size of only 6.02 MB and FLOPs of 30.170 G—substantially reducing computational overhead. Furthermore, the proposed MAGF (Multi-Scale Attention Gated Fusion) and SCSA (Spatial-Channel Synergistic Attention) modules are integrated to enhance the representation of fracture details and semantic consistency while effectively suppressing multi-source and multi-scale background interference. Experimental results demonstrate that the proposed model achieves an mPA of 89.69%, mIoU of 83.71%, F1-Score of 90.41%, and Kappa coefficient of 80.81%, outperforming the classic Deeplabv3+ model by 5.81%, 6.18%, 4.53%, and 9.2%, respectively. It also significantly surpasses benchmark models such as U-Net and HRNet. The method accurately captures fine and continuous fracture details, preserves the spatial distribution of long-range continuous fractures, and maintains robust performance on the CFD cross-scene dataset, showcasing strong adaptability and generalization capability. This approach effectively mitigates the risks associated with manual high-altitude inspections and provides a lightweight, high-precision, non-contact intelligent solution for fracture detection in high-steep rock slopes. Full article