Search Results (204)

Underground gas storage (UGS) facilities are fundamental for national energy security and global decarbonization efforts. However, solid phase production in carbonate reservoirs, such as Qianmi Bridge, poses a significant operational challenge by compromising wellbore integrity and formation permeability. To address this, this study develops a novel, comprehensive methodology for predicting and mitigating solid phase production risk in carbonate UGS under dynamic operating conditions, specifically focusing on the Qianmi Bridge gas storage. This approach systematically integrates qualitative susceptibility assessments (using acoustic time difference, B index, and S index) with quantitative models for critical and ultimate pressure difference forecasting. Crucially, the methodology rigorously accounts for dynamic process parameters, including rock strength degradation due to acidizing, in situ stress variations, and fluid flow dynamics throughout the reservoir’s operational life cycle, a critical aspect often overlooked in conventional models designed for sandstone reservoirs. Analysis reveals that the safe operating pressure window dramatically narrows as formation pressure declines and rock strength is weakened, especially under high-intensity, multi-cycle alternating loads. Specifically, acidizing treatments can reduce the critical pressure difference by over 50% (e.g., from 40.49 MPa to 19.63 MPa), and under depleted conditions (0.6 P₀, 0.8 UCS), the reservoir’s ability to resist solid phase production approaches zero, highlighting an extremely high risk. These findings provide an essential theoretical and technical basis for formulating robust operational control strategies, enabling data-driven decision-making to enhance the long-term safety, efficiency, and overall process integrity of carbonate gas storage operations. Full article

To address the limitation that single-index evaluation fails to fully reflect the development performance of reservoirs of different types and at various development stages, a multi-index comprehensive evaluation system featuring the workflow of “index screening–weight determination–model evaluation–strategy guidance” was established. Firstly, the grey correlation analysis method (with a correlation degree threshold set at 0.65) was employed to screen 12 key evaluation indicators, including reservoir physical properties (porosity, permeability) and development dynamics (recovery factor, water cut, well activation rate). Subsequently, the fuzzy analytic hierarchy process (FAHP, for subjective weighting, with the consistency ratio (CR) of expert judgments < 0.1) was coupled with the attribute measurement method (for objective weighting, with information entropy redundancy < 5%) to determine the indicator weights, thereby balancing the influences of subjective experience and objective data. Finally, two evaluation models, namely the fuzzy comprehensive decision-making method and the unascertained measurement method, were constructed to conduct evaluations on 308 reservoirs in the Liaohe Oilfield (covering five major categories: integral medium–high-permeability reservoirs, complex fault-block reservoirs, low-permeability reservoirs, special lithology reservoirs, and thermal recovery heavy oil reservoirs). The results indicate that there are 147 high-efficiency reservoirs categorized as Class I and Class II in total. Although these reservoirs account for 47.7% of the total number, they control 71% of the geological reserves (154,548 × 10⁴ t) and 78% of the annual oil production (738.2 × 10⁴ t) in the oilfield, with an average well activation rate of 65.4% and an average recovery factor of 28.9. Significant quantitative differences are observed in the development characteristics of different reservoir types: Integral medium–high-permeability reservoirs achieve an average recovery factor of 37.6% and an average well activation rate of 74.1% by virtue of their excellent physical properties (permeability mostly > 100 mD), with Block Jin 16 (recovery factor: 56.9%, well activation rate: 86.1%) serving as a typical example. Complex fault-block reservoirs exhibit optimal performance at the stage of “recovery degree > 70%, water cut ≥ 90%”, where 65.6% of the blocks are classified as Class I, and the recovery factor of blocks with a “good” rating (42.3%) is 1.8 times that of blocks with a “poor” rating (23.5%). For low-permeability reservoirs, blocks with a rating below medium grade account for 68% of the geological reserves (8403.2 × 10⁴ t), with an average well activation rate of 64.9%. Specifically, Block Le 208 (permeability < 10 mD) has an annual oil production of only 0.83 × 10⁴ t. Special lithology reservoirs show polarized development performance, as Block Shugu 1 (recovery factor: 32.0%) and Biantai Buried Hill (recovery factor: 20.4%) exhibit significantly different development effects due to variations in fracture–vug development. Among thermal recovery heavy oil reservoirs, ultra-heavy oil reservoirs (e.g., Block Du 84 Guantao, with a recovery factor of 63.1% and a well activation rate of 92%) are developed efficiently via steam flooding, while extra-heavy oil reservoirs (e.g., Block Leng 42, with a recovery factor of 19.6% and a well activation rate of 30%) are constrained by reservoir heterogeneity. This system refines the quantitative classification boundaries for four development levels of water-flooded reservoirs (e.g., for Class I reservoirs in the high water cut stage, the recovery factor is ≥35% and the water cut is ≥90%), as well as the evaluation criteria for different stages (steam huff and puff, steam flooding) of thermal recovery heavy oil reservoirs. It realizes the transition from traditional single-index qualitative evaluation to multi-index quantitative evaluation, and the consistency between the evaluation results and the on-site development adjustment plans reaches 88%, which provides a scientific basis for formulating development strategies for the Liaohe Oilfield and other similar oilfields. Full article

Uncertainty quantification (UQ) is critical for predicting solute transport in heterogeneous porous media, with applications in groundwater management and contaminant remediation. Traditional UQ methods, such as Monte Carlo (MC) simulations, are computationally expensive and impractical for real-time decision-making. This study introduces a novel machine learning framework to address these limitations. We developed a surrogate model for a 2D advection-dispersion solute transport model using a Bayesian Neural Network (BNN). The BNN was trained on a synthetic dataset generated by simulating solute transport across various stochastic permeability and dispersivity fields. Uncertainty was quantified through variational inference, capturing both data-related (aleatoric) and model-related (epistemic) uncertainties. We evaluated the framework’s performance against traditional MC simulations. Our BNN model accurately predicts solute concentration distributions with a mean squared error (MSE) of 9.8 × ${10}^{-5}$, significantly outperforming other machine learning surrogates. The framework successfully quantifies uncertainty, providing calibrated confidence intervals that align closely with the spread of the MC results. The proposed approach achieved a 98.5% reduction in computational time compared to a standard Monte Carlo simulation with 1000 realizations, representing a 65-fold speed-up. A sensitivity analysis revealed that permeability field heterogeneity is the dominant source of uncertainty in plume migration. The developed machine learning framework offers a computationally efficient and robust alternative for quantifying uncertainty in solute transport models. By accurately predicting solute concentrations and their associated uncertainties, our approach can inform risk-based decision-making in environmental and hydrogeological applications. The method shows promise for scaling to more complex, three-dimensional systems. Full article

Permeability of fissured sorbing rocks, such as coal and shale, controls gas transport and is relevant to a variety of scientific problems and industrial processes. Multiple gas transport and rock deformation mechanisms affect permeability evolution, including gas rarefaction effects, gas-sorption-induced anisotropic matrix–fracture interaction, and anisotropic deformation induced by effective stress variation. In this paper, a generic anisotropic permeability model is proposed to address the impacts of the above mechanisms and effects. Specifically, the influence of matrix–fracture interactions on permeability evolution is depicted through the nonuniform matrix swelling caused by the gas diffusion process from fracture walls into the matrix. The following characteristics are also incorporated in this model: (1) anisotropic mechanical and swelling properties, (2) arbitrary box-shaped matrix blocks due to the anisotropic rock structure, (3) adsorbability variation of different matrix blocks because of complex rock compositions, (4) adsorption hysteresis, and (5) dynamic tortuosity. The directional permeability models are derived based on the anisotropic poroelasticity theory and anisotropic swelling equations considering adsorption hysteresis. We use a gas-invaded-volume ratio to describe the nonuniform swelling of matrix blocks. Additionally, swelling of blocks with different adsorption and mechanical properties are characterized by a volume-weighted function. Finally, the anisotropic tortuosity is defined as a power law function of effective porosity. The model is verified against experimental data. Results show that four-stage permeability evolution with time can be observed. Permeability evolution in different directions follows its own ways and depends on anisotropic swelling, mechanical properties, and structures, even when the boundary conditions are identical. Adsorption hysteresis controls the local shrinkage region. Tortuosity variation significantly affects permeability but has the smallest influence on the local swelling region. The existence of multiple matrix types complicates the permeability evolution behavior. Full article

This study develops a novel analytical solution for three-dimensional axisymmetric consolidation of unsaturated soils incorporating radial–vertical composite seepage mechanisms and anisotropic permeability characteristics. A groundbreaking dual orthogonal expansion framework is established, utilizing innovative Bessel–trigonometric function coupling to solve the inherently complex spatiotemporal coupled partial differential equations in cylindrical coordinate systems. The mathematical approach synergistically combines modal expansion theory with Laplace transform methodology, achieving simultaneous spatial expansion of gas–liquid two-phase pressure fields through orthogonal function series, thereby transforming the three-dimensional problem into solvable ordinary differential equations. Rigorous validation demonstrates exceptional accuracy with coefficient of determination R² exceeding 0.999 and relative errors below 2% compared to numerical simulations, confirming theoretical correctness and practical applicability. The analytical solutions reveal four critical findings with quantitative engineering implications: (1) dual-directional drainage achieves 28% higher pressure dissipation efficiency than unidirectional drainage, providing design optimization criteria for vertical drainage systems; (2) normalized matric suction variation exhibits characteristic three-stage evolution featuring rapid decline, plateau stabilization, and slow recovery phases, while water phase follows bidirectional inverted S-curve patterns, enabling accurate consolidation behavior prediction under varying saturation conditions; (3) gas-water permeability ratio k_a/k_w spanning 0.1 to 1000 produces two orders of magnitude time compression effect from 10⁻² s to 10⁻⁴ s, offering parametric design methods for construction sequence control; (4) initial pressure gradient parameters λ_a and λ_w demonstrate opposite regulatory mechanisms, where increasing λ_a retards consolidation while λ_w promotes the process, providing differentiated treatment strategies for various geological conditions. The unified framework accommodates both uniform and gradient initial pore pressure distributions, delivering theoretical support for refined embankment engineering design and construction control. Full article

Settlement-relevant load combinations play a critical role in the serviceability design of buildings, particularly for structures on soils with time-dependent deformation behavior. While permanent loads must be fully considered, the contribution of variable actions depends on their duration relative to soil response. This study investigates suitable settlement-relevant load combinations and their influence on the restrained load redistribution within buildings, based on parametric finite element analyses of wall-type and frame-type structures on sand, silt, and clay using PLAXIS 3D (Version 2024.3). Results show that structural stiffness significantly affects force redistribution due to settlements: stiffer structures exhibit greater redistribution, while soft soils generate higher absolute restraining forces but are less sensitive to load combinations. Based on these findings, the reduced characteristic load combination (including α_n) is recommended for coarse-grained, drained soils, as it balances safety and realistic deformation. For fine-grained, low-permeability soils, the quasi-permanent combination should be applied to capture long-term consolidation effects. Short-term load variations after consolidation have negligible impact and should be addressed through safety factors rather than separate settlement analyses. These recommendations provide a clear and practical framework for selecting settlement-relevant load combinations, enhancing reliability and efficiency in structural design. Full article

This study aims to elucidate the geochemical reactions between CO₂-saturated water and rocks in CO₂-enhanced geothermal system (CO₂-EGS) reservoirs by focusing on andesite found in island arc regions, such as Japan. Laboratory flow tests of CO₂-saturated water (3 wt.% CO₂) and rocks (particle size: 0.14–1 mm) were conducted under varying temperature (150–250 °C) and flow rate (0.3 and 1.0 mL/min) conditions using a flow-through reactor. Elevated temperatures enhanced the dissolution of silicate minerals, reflected by increased Na⁺, K⁺, Ca²⁺, and Si concentrations, whereas those of Fe²⁺ and Al³⁺ remained low, suggesting secondary mineral precipitation. The dissolution process was dominant at 150 °C. Al-bearing minerals, such as gibbsite and boehmite, as well as clay minerals, including beidellite and kaolinite, were predominant at higher temperatures (200–250 °C). Carbonate minerals were not observed, attributable to low pH and limited availability of divalent cations. Flow rate substantially influenced Si dissolution rates, with lower flow rates promoting longer residence times and higher Si dissolution rates. These results indicate that the test conditions simulate the environment around the injection well, where the fluid is acidic and dissolution is the main reaction in the rock. Although a small amount of secondary minerals precipitated and the Si dissolution rates were of the same order of magnitude as those for labradorite, it may be considered that andesite has less impact on permeability variations than basalt near the injection well in CO₂-EGS reservoirs. Full article

A permeable reactive barrier (PRB) containing zero-valent iron (ZVI) is an in situ groundwater remediation technology that passively intercepts and treats contaminated groundwater plumes. Over time, secondary mineral precipitation within the PRB diminishes porosity and hydraulic conductivity, altering flow paths, residence times, and sometimes causing bypass of the reactive zone. This study utilizes the THMC software to simulate porosity reduction in a PRB, capturing the coupled effects of fluid flow and geochemical interactions. The simulation results indicate that porosity loss is most significant at the PRB entrance and stabilizes beyond 0.2 m. Porosity reduction is primarily caused by aragonite, siderite, and ferrous hydroxide precipitating in pore spaces. The model further elucidates the influence of groundwater chemistry, demonstrating that variations in bicarbonate concentrations significantly impact mineral precipitation processes, thereby leading to porosity reduction. Furthermore, the study highlights reaction kinetics, with anaerobic iron corrosion rates being critical in controlling porosity reduction via mineral precipitation. THMC software effectively simulates porosity reduction in PRBs, identifies key factors driving clogging, and informs design optimization for long-term remediation. Full article

The shelf life of perishable foods is traditionally determined by microbiological, chemical, and sensory analyses, which are well-established and reliable. However, these methods can be time-consuming and resource-intensive, and they may not fully account for unexpected storage deviations, such as temperature fluctuations or equipment failures. Smart films emerge as a promising alternative, enabling rapid, visual, and low-cost food quality monitoring. This study developed smart films based on zein/gelatin/cellulose nanocrystals (Z/G/CNC) functionalized with alizarin (AL, 0–3% w/w), produced by casting (12.5% zein, 12.5% gelatin, and 5% CNC w/w). The films were characterized for morphological, physicochemical, thermal, and spectroscopic properties, chromatic response at pH 3–11, activity against Escherichia coli and Staphylococcus aureus, and applicability in monitoring Merluccid hake fillets. The incorporation of AL reduced water solubility, increased water vapor permeability and contact angle, imparted a more intense orange coloration, and improved thermal resistance. AL also increased thickness and elongation at break while reducing tensile strength and Young’s modulus. All films exhibited excellent UV-blocking capacity (<1% transmittance). Noticeable color changes were observed, with the Z/G/CNC/AL1 film being the most sensitive to pH variations. During Merluccid hake storage, ΔE values exceeded 3 within 72 h, with a color change from orange to purple, correlating with fillet pH (8.14) and total volatile basic nitrogen (TVB-N) (24.73 mg/100 g). These findings demonstrate the potential of the developed films as biodegradable sensors for smart packaging of perishable foods. Full article

The Shenhu sea area is rich in unconsolidated hydrate reserves, but the formation mineral particles are small, the rock cementation is weak, and the coupling mechanism of hydrate phase change, fluid seepage, and formation deformation is complex, resulting in unclear productivity change law under depressurization exploitation. Therefore, a thermal–fluid–solid–chemical coupling model for natural gas hydrate depressurization exploitation in the Shenhu sea area was constructed to analyze the variation law of reservoir parameters and productivity. The results show that within 0–30 days, rapid near-well pressure drop (13.83→9.8 MPa, 36.37%) drives peak gas production (25,000 m³/d) via hydrate dissociation, with porosity (0.41→0.52) and permeability (75→100 mD) increasing. Within 30–60 days, slower pressure decline (9.8→8.6 MPa, 12.24%) and fines migration cause permeability fluctuations (120→90 mD), reducing gas production to 20,000 m³/d. Within 60–120 days, pressure stabilizes (~7.6 MPa) with residual hydrate saturation < 0.1, leading to stable low permeability (60 mD) and gas production (15,000 m³/d), with cumulative production reaching 2.2 × 10⁶ m³. This study clarifies that productivity is governed by coupled “pressure-driven dissociation–heat limitation–fines migration” mechanisms, providing key insights for optimizing depressurization strategies (e.g., timed heat supplementation, anti-clogging measures) to enhance commercial viability of unconsolidated hydrate reservoirs. Full article

The synergistic development of low-permeability reservoirs such as deep coalbed methane (CBM) and tight gas has emerged as a key technology to reduce development costs, enhance single-well productivity, and improve gas recovery. However, due to fundamental differences between coal seams and tight sandstones in their pore structure, permeability, water saturation, and pressure sensitivity, significant variations exist in their flow capacities and fluid production behaviors. To address the challenges of production allocation and main reservoir identification in the co-development of CBM and tight gas within deep gas-bearing basins, this study employs the transient multiphase flow simulation software OLGA to construct a representative dual-gas co-production well model. The regulatory mechanisms of the gas–liquid distribution, deliquification efficiency, and interlayer interference under two typical vertical stacking relationships—“coal over sand” and “sand over coal”—are systematically analyzed with respect to different tubing setting depths. A high-precision dynamic production allocation method is proposed, which couples the wellbore structure with real-time monitoring parameters. The results demonstrate that positioning the tubing near the bottom of both reservoirs significantly enhances the deliquification efficiency and bottomhole pressure differential, reduces the liquid holdup in the wellbore, and improves the synergistic productivity of the dual-reservoirs, achieving optimal drainage and production performance. Building upon this, a physically constrained model integrating real-time monitoring data—such as the gas and liquid production from tubing and casing, wellhead pressures, and other parameters—is established. Specifically, the model is built upon fundamental physical constraints, including mass conservation and the pressure equilibrium, to logically model the flow paths and phase distribution behaviors of the gas–liquid two-phase flow. This enables the accurate derivation of the respective contributions of each reservoir interval and dynamic production allocation without the need for downhole logging. Validation results show that the proposed method reliably reconstructs reservoir contribution rates under various operational conditions and wellbore configurations. Through a comparison of calculated and simulated results, the maximum relative error occurs during abrupt changes in the production capacity, approximately 6.37%, while for most time periods, the error remains within 1%, with an average error of 0.49% throughout the process. These results substantially improve the timeliness and accuracy of the reservoir identification. This study offers a novel approach for the co-optimization of complex multi-reservoir gas fields, enriching the theoretical framework of dual-gas co-production and providing technically adaptive solutions and engineering guidance for multilayer unconventional gas exploitation. Full article

Asphaltene deposition remains a critical challenge in water-injected reservoirs, where pressure and compositional variations destabilize the oil phase, triggering precipitation and formation damage. This study explores the application of intermittent waterflooding (IWF) as a practical mitigation strategy, combining alternating injection and well shut-in times to stabilize fluid conditions. A synthetic reservoir model was developed in Eclipse 300 to evaluate how key parameters such as shut-in time, injection rate, and injection timing affect asphaltene behavior under varying operational regimes. Comparative simulations against traditional continuous waterflooding reveal that IWF can significantly suppress near-wellbore deposition, preserve permeability, and improve overall oil recovery. The results show that early injections and optimized cycling schedules maintain reservoir pressure above the bubble point, thereby reducing the extent of destabilization. This study offers a simulation-based framework for IWF design, providing insights into asphaltene control mechanisms and contributing to more efficient reservoir management in fields prone to flow assurance issues. Full article

Fluid flow and mass transfer processes in some fractured aquifers are negligible in the low-permeability rock matrix and occur mainly in the fracture network. In this work, we consider coupled variable-density flow (VDF) and mass transport with dissolution in discrete fracture networks (DFNs). These three processes are ruled by nonlinear and strongly coupled partial differential equations (PDEs) due to the (i) density variation induced by concentration and (ii) fracture aperture evolution induced by dissolution. In this study, we develop an efficient model to solve the resulting system of nonlinear PDEs. The new model leverages the method of lines (MOL) to combine the robust finite volume (FV) method for spatial discretization with a high-order method for temporal discretization. A suitable upwind scheme is used on the fracture network to eliminate spurious oscillations in the advection-dominated case. The time step size and the order of the time integration are adapted during simulations to reduce the computational burden while preserving accuracy. The developed VDF-DFN model is validated by simulating saltwater intrusion and dissolution in a coastal fractured aquifer. The results of the VDF-DFN model, in the case of a dense fracture network, show excellent agreement with the Henry semi-analytical solution for saltwater intrusion and dissolution in a coastal aquifer. The VDF-DFN model is then employed to investigate coupled flow, mass transfer and dissolution for an injection/extraction well pair problem. This test problem enables an exploration of how dissolution influences the evolution of the fracture aperture, considering both constant and variable dissolution rates. Full article

Ammonia (NH₃) detection in liquids and biological fluids is essential for monitoring environmental contamination and industrial processes, ensuring food safety, and diagnosing health conditions. Existing detection techniques are often unsuitable for point-of-care (POC) use due to limitations including complex sample handling, lack of portability, and poor compatibility with miniaturized systems. This study introduces a proof-of-concept for a compact, portable device tailored for POC detection of gaseous ammonia released from liquid samples. The device combines a polyaniline (PANI)-based chemoresistive sensor with interdigitated electrodes and a resistance readout circuit, enclosed in a gas-permeable hydrophobic membrane that permits ammonia in the vapor phase only to reach the sensing layer, ensuring selectivity and protection from liquid interference. The ink formulation was optimized. PANI nanoparticle suspension exhibited a monomodal, narrow particle size distribution with an average size of 120 nm and no evidence of larger aggregates. A key advancement of this device is its ability to limit the impact of water vapor, a known source of interference in PANI-based sensors, while maintaining a simple sensor design. A tailored signal processing strategy was implemented, extracting the slope of resistance variation over time as a robust metric for ammonia quantification. The sensor demonstrated reliable performance across a concentration range of 1.7 to 170 ppm with strong logarithmic correlation (R² = 0.99), and very good linear correlations in low (R² = 0.96) and high (R² = 0.97) subranges. These findings validate the feasibility of this POC platform for sensitive, selective, and practical ammonia detection in clinical and environmental applications. Full article

The shale oil reservoirs in the Liang Gaoshan area of the Sichuan Basin exhibit extremely low porosity and permeability, as well as significant heterogeneity. Consequently, hydraulic fracturing of horizontal wells is critical for achieving effective production enhancement. Early diagnostic monitoring revealed substantial variations in fracture propagation. Some hydraulic fractures extended beyond the target layer into adjacent river sandstone, leading to increased fracturing costs and reduced reserve utilization rates. To address these challenges, temporary plugging fracturing (TPF) was implemented to optimize fluid distribution among fracture clusters. However, previous TPF operations in this basin relied heavily on empirical methods, resulting in a relatively low sealing success rate of approximately 70%. This study proposes a fracture propagation model that incorporates stress interference dynamics induced by temporary plugging fracturing agents. Additionally, through laboratory experiments, a high-pressure (30.2 MPa) degradable temporary-plugging agent was selected for use in horizontal well fracturing. Key process parameters, including the insertion timing, dosage, and distribution strategy of the temporary-plugging agent, were optimized using a numerical simulation system. The results indicate that injecting 50% of the fracturing fluid followed by the simultaneous deployment of 12 temporary blocking nodes ensures uniform fracture cluster extension while maximizing the reconstruction volume. Furthermore, deploying all temporary blocking nodes at once reduces the fracturing operation time by approximately 20%. These findings were validated via field applications at Well NC1. Microseismic monitoring during fracturing confirmed the accuracy of the research outcomes presented in this paper. After temporary plugging, the extension uniformity of each fracture cluster significantly improved, with the stimulated reservoir volume (SRV) of a single section reaching 530,000 cubic meters. These results provide a foundation for optimizing horizontal well fracturing in Liang Gaoshan shale oil reservoirs within the Sichuan Basin, facilitating efficient and economical fracturing operations. Full article