[go: up one dir, main page]
More Web Proxy on the site http://driver.im/
You seem to have javascript disabled. Please note that many of the page functionalities won't work as expected without javascript enabled.
 
 
Sign in to use this feature.

Years

Between: -

Subjects

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Journals

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Article Types

Countries / Regions

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Search Results (1,161)

Search Parameters:
Keywords = reservoir volume

Order results
Result details
Results per page
Select all
Export citation of selected articles as:
19 pages, 9589 KiB  
Article
Numerical Simulation of Gas–Liquid–Solid Three-Phase Erosion in a Gas Storage Tank Tee
by Zongxiao Ren, Chenyu Zhang, Zhaoyang Fan and Yanfei Ren
Lubricants 2025, 13(1), 39; https://doi.org/10.3390/lubricants13010039 - 20 Jan 2025
Viewed by 89
Abstract
The objective is to address the issue of gas-carrying particles generated by erosion wear problems in the transportation process of gas storage reservoir pipelines. In accordance with the principles of the multiphase flow theory, the particle discrete phase model, high temperature, high pressure, [...] Read more.
The objective is to address the issue of gas-carrying particles generated by erosion wear problems in the transportation process of gas storage reservoir pipelines. In accordance with the principles of the multiphase flow theory, the particle discrete phase model, high temperature, high pressure, water volume fraction, and other pertinent factors, this paper presents a three-phase gas–liquid–solid erosion mathematical model of a three-way gas storage reservoir. The effects of temperature, pressure, water content volume fraction, gas extraction, particle mass flow rate, and particle size on the tee’s erosion location and erosion rate were investigated based on this model. The findings indicate that, as the pressure and temperature decline, the maximum erosion rate of the tee exhibits a decreasing trend. Gas storage reservoir water production is relatively low, and its maximum erosion rate of the tee exerts a negligible influence. Conversely, the maximum erosion rate of the tee is significantly influenced by the gas extraction rate, exhibiting an exponential relationship with the maximum erosion rate and the rate of gas extraction. It was observed that, when the volume of gas extracted exceeded 70 × 104 m3/d, the maximum erosion rate of the tee exceeded the critical erosion rate of 0.076 mm/a. The maximum erosion rate of the tee caused by the sand mass flow rate remained relatively constant. However, the maximum erosion rate of the tee exhibited a linear correlation with the salt mass flow rate and the maximum erosion rate. The maximum erosion rate of the tee is greater than the critical erosion rate of 0.076 mm/a when the gas extraction volume is greater than 37.3 × 104 m3/d and the salt mass flow rate is greater than approximately 25 kg/d. As the sand and salt particle sizes increase, the maximum erosion rate of the tee initially rises, then declines, and finally stabilizes. The findings of this study offer valuable insights into the mechanisms governing tee erosion under elevated temperatures and pressures within storage reservoirs. Full article
(This article belongs to the Special Issue Fundamentals and Applications of Tribocorrosion)
Show Figures

Figure 1

Figure 1
<p>Schematic diagram of the particle–wall collision.</p>
Full article ">Figure 2
<p>Tee structure schematic.</p>
Full article ">Figure 3
<p>Tee model and mesh discretization.</p>
Full article ">Figure 4
<p>Independence analysis of the mesh number.</p>
Full article ">Figure 5
<p>Changing law of the maximum erosion rate with gas extraction under different pressures.</p>
Full article ">Figure 6
<p>Changing law of the maximum erosion rate with gas extraction under different temperatures.</p>
Full article ">Figure 7
<p>Particle trajectories at different temperatures.</p>
Full article ">Figure 8
<p>Simulation cloud diagram.</p>
Full article ">Figure 9
<p>Changing law of the maximum erosion rate with gas extraction under different water content volume fractions.</p>
Full article ">Figure 10
<p>Erosion cloud and particle trajectory maps for different gas extraction rates.</p>
Full article ">Figure 11
<p>Changes in the maximum erosion rate with gas production.</p>
Full article ">Figure 12
<p>Particle trajectories under varying sand mass flow rates.</p>
Full article ">Figure 13
<p>Changes in the maximum erosion rate with the salt mass flow rate.</p>
Full article ">Figure 14
<p>Erosion cloud and particle trajectory maps under changing salt mass flow rates.</p>
Full article ">Figure 15
<p>Changes of the maximum erosion rate with the sand grain sizes.</p>
Full article ">Figure 16
<p>Erosion cloud and particle trajectory maps for different sand grain sizes.</p>
Full article ">Figure 17
<p>Changes in the maximum erosion rate with the salt grain sizes.</p>
Full article ">Figure 18
<p>Erosion cloud and particle trajectory maps for different salt grain sizes.</p>
Full article ">
20 pages, 4819 KiB  
Article
Experimental Study on the Application of Polymer Agents in Offshore Oil Fields: Optimization Design for Enhanced Oil Recovery
by Xianjie Li, Jian Zhang, Yaqian Zhang, Cuo Guan, Zheyu Liu, Ke Hu, Ruokun Xian and Yiqiang Li
Polymers 2025, 17(2), 244; https://doi.org/10.3390/polym17020244 - 20 Jan 2025
Viewed by 175
Abstract
The Bohai oilfield is characterized by severe heterogeneity and high average permeability, leading to a low water flooding recovery efficiency. Polymer flooding only works for a certain heterogeneous reservoir. Therefore, supplementary technologies for further enlarging the swept volume are still necessary. Based on [...] Read more.
The Bohai oilfield is characterized by severe heterogeneity and high average permeability, leading to a low water flooding recovery efficiency. Polymer flooding only works for a certain heterogeneous reservoir. Therefore, supplementary technologies for further enlarging the swept volume are still necessary. Based on the concept of discontinuous chemical flooding with multi slugs, three chemical systems, which were polymer gel (PG), hydrophobically associating polymer (polymer A), and conventional polymer (polymer B), were selected as the profile control and displacing agents. The optimization design of the discontinuous chemical flooding was investigated by core flooding experiments and displacement equilibrium degree calculation. The gel, polymer A, and polymer B were classified into three levels based on their profile control performance. The degree of displacement equilibrium was defined by considering the sweep conditions and oil displacement efficiency of each layer. The effectiveness of displacement equilibrium degree was validated through a three-core parallel displacement experiment. Additionally, the parallel core displacement experiment optimized the slug size, combination method, and shift timing of chemicals. Finally, a five-core parallel displacement experiment verified the enhanced oil recovery (EOR) performance of discontinuous chemical flooding. The results show that the displacement equilibrium curve exhibited a stepwise change. The efficiency of discontinuous chemical flooding became more significant with the number of layers increasing and heterogeneity intensifying. Under the combination of permeability of 5000/2000/500 mD, the optimal chemical dosage for the chemical discontinuous flooding was a 0.7 pore volume (PV). The optimal combination pattern was the alternation injection in the form of “medium-strong-weak-strong-weak”, achieving a displacement equilibrium degree of 82.3%. The optimal shift timing of chemicals occurred at a water cut of 70%, yielding a displacement equilibrium degree of 87.7%. The five-core parallel displacement experiment demonstrated that discontinuous chemical flooding could get a higher incremental oil recovery of 24.5% compared to continuous chemical flooding, which presented a significantly enhanced oil recovery potential. Full article
(This article belongs to the Special Issue New Studies of Polymer Surfaces and Interfaces)
Show Figures

Figure 1

Figure 1
<p>Molecular structure.</p>
Full article ">Figure 2
<p>Experimental flow chart of the heterogeneous core model.</p>
Full article ">Figure 3
<p>Physical diagram and flow diagram of the three-core large parallel model with electrodes.</p>
Full article ">Figure 4
<p>Viscosity curves of different polymer-to-crosslinker ratio systems.</p>
Full article ">Figure 5
<p>Relationship between viscoelastic moduli and vibration frequency of the gel under the optimal formula.</p>
Full article ">Figure 6
<p>Comparison of discontinuous displacement and continuous flooding using displacement equilibrium degree.</p>
Full article ">Figure 7
<p>Oil saturation distribution diagram at different shift times of the combined system.</p>
Full article ">Figure 8
<p>Displacement equilibrium degree curves for different discontinuous combination methods.</p>
Full article ">Figure 9
<p>Displacement equilibrium degree curves at different injection times.</p>
Full article ">Figure 10
<p>Comparison of recovery factors for different layers between DCF and CF in the five-core parallel flooding experiment.</p>
Full article ">Figure 11
<p>Comparison of fractional flow rate distribution between DCF and CF in five-core parallel flooding experiment.</p>
Full article ">Figure 12
<p>Comparison of displacement equilibrium degree between DCF and CF in five-core parallel flooding experiments.</p>
Full article ">
23 pages, 74396 KiB  
Article
Change of NDVI in the Upper Reaches of the Yangtze River and Its Influence on the Water–Sand Process in the Three Gorges Reservoir
by Yiming Ma, Mingyue Li, Huaming Yao, Peng Chen and Hongzhong Pan
Sustainability 2025, 17(2), 739; https://doi.org/10.3390/su17020739 - 18 Jan 2025
Viewed by 295
Abstract
Vegetation coverage in the upper reaches of the Yangtze River is very important to the ecological balance in this area, and it also has an impact on the inflow runoff and sediment transport processes of the Three Gorges Reservoir. Based on the normalized [...] Read more.
Vegetation coverage in the upper reaches of the Yangtze River is very important to the ecological balance in this area, and it also has an impact on the inflow runoff and sediment transport processes of the Three Gorges Reservoir. Based on the normalized vegetation index data (NDVI) with 250 m resolution in the upper reaches of the Yangtze River, annual runoff, sediment transport, land use, meteorology, and other data—and by using the methods of Sen + Mann–Kendall trend analysis, partial correlation analysis, and Hurst index—this paper analyzes the temporal and spatial variation characteristics, driving factors, and the influence on the water and sediment inflow processes of the Three Gorges Reservoir in each sub-basin in the upper reaches of the Yangtze River. The results show that (1) NDVI in the upper Yangtze River showed a fluctuating upward trend from 2001 to 2022, and the overall vegetation cover continued to increase, showing a spatial pattern of low in the west and high in the east. At the same time, the runoff volume of the upper reaches of the Yangtze River did not show a significant upward trend from 2006 to 2022, while the sand transport decreased significantly; (2) Among the NDVI-influencing factors in the upper reaches of the Yangtze River, the area driven by the land use factor accounts for about 43% of the whole study area, followed by precipitation; (3) Precipitation significantly affected runoff, and NDVI was negatively correlated with sand transport in most of the watersheds, suggesting that improved vegetation could help reduce sediment loss. In addition, the future trend of vegetation change was predicted to be dominated by improvement (Hurst > 0.5) based on the Hurst index, which will provide a reference for the NDVI change in the upper Yangtze River and the prediction of sediment inflow to the Three Gorges Reservoir. Full article
Show Figures

Figure 1

Figure 1
<p>Schematic diagram of the location, scope, and terrain of the research area.</p>
Full article ">Figure 2
<p>Annual variation of NDVI in various basins in the upper reaches of the Yangtze River from 2001 to 2022.</p>
Full article ">Figure 3
<p>Spatial distribution of NDVI in the Upper Yangtze River Basin from 2001 to 2022.</p>
Full article ">Figure 4
<p>Significance of spatial variation in NDVI in the Upper Yangtze River Basin from 2001 to 2022.</p>
Full article ">Figure 5
<p>Spatial fluctuation of annual NDVI in the Upper Yangtze River Basin from 2001 to 2022.</p>
Full article ">Figure 6
<p>Interannual variability of runoff (<b>a</b>) and sand transport (<b>b</b>) in the Yangtze River Basin. Error bars indicate percentage of data for each year (5%).</p>
Full article ">Figure 7
<p>Spatial distribution of NDVI and precipitation correlation coefficients (<b>a</b>) and correlation coefficients significance (<b>b</b>) in the upper Yangtze River Basin from 2001 to 2022.</p>
Full article ">Figure 8
<p>Distribution of land cover types in the Upper Yangtze River Basin in 2001, 2010, and 2022.</p>
Full article ">Figure 9
<p>Vegetation change for different land cover types in the upper Yangtze River Basin from 2001 to 2022.</p>
Full article ">Figure 10
<p>Spatial distribution of partial correlation coefficient (<b>A</b>–<b>C</b>) and partial correlation significance (<b>D</b>–<b>F</b>) between NDVI and climate factors in the upper Yangtze River Basin from 2000 to 2022.</p>
Full article ">Figure 11
<p>Spatial distribution of dominant climate factors for NDVI changes in the upper Yangtze River Basin from 2001 to 2022.</p>
Full article ">Figure 12
<p>Persistence of NDVI in the Upper Yangtze River Basin from 2001 to 2022.</p>
Full article ">Figure 13
<p>Future trends of NDVI changes in the upper reaches of the Yangtze River.</p>
Full article ">
26 pages, 9807 KiB  
Article
Critical Geochemical and Microbial Reactions in Underground Hydrogen Storage: Quantifying Hydrogen Loss and Evaluating CO2 as Cushion Gas
by Rana Al Homoud, Marcos Vitor Barbosa Machado, Hugh Daigle and Harun Ates
Hydrogen 2025, 6(1), 4; https://doi.org/10.3390/hydrogen6010004 - 17 Jan 2025
Viewed by 575
Abstract
Hydrogen is a pivotal energy carrier for achieving sustainability and stability, but safe and efficient geological underground hydrogen storage (UHS) is critical for its large-scale application. This study investigates the impacts of geochemical and biochemical reactions on UHS, addressing challenges that threaten storage [...] Read more.
Hydrogen is a pivotal energy carrier for achieving sustainability and stability, but safe and efficient geological underground hydrogen storage (UHS) is critical for its large-scale application. This study investigates the impacts of geochemical and biochemical reactions on UHS, addressing challenges that threaten storage efficiency and safety. Geochemical reactions in saline aquifers, particularly the generation of hydrogen sulfide (H2S), were analyzed using advanced compositional and geochemical modeling calibrated with experimental kinetic data. The results indicate that geochemical reactions have a minimal effect on hydrogen consumption. However, by year 10 of storage operations, H2S levels could reach 12–13 ppm, necessitating desulfurization to maintain storage performance and safety. The study also examines the methanogenesis reaction, where microorganisms consume hydrogen and carbon dioxide to produce methane. Numerical simulations reveal that microbial activity under suitable conditions can reduce in situ hydrogen volume by up to 50%, presenting a critical hurdle to UHS feasibility. These findings highlight the necessity of conducting microbial analyses of reservoir brines during the screening phase to mitigate hydrogen losses. The novelty of this work lies in its comprehensive field-scale analysis of impurity-induced geochemical and microbial reactions and their implications for underground hydrogen storage. By integrating kinetic parameters derived from experimental data with advanced computational modeling, this study uncovers the mechanisms driving these reactions and highlights their impact on storage efficiency, and safety. By offering a detailed field-scale perspective, the findings provide a pivotal framework for advancing future hydrogen storage projects and ensuring their practical viability. Full article
Show Figures

Figure 1

Figure 1
<p>Synthetic 2D homogeneous model representing the saline aquifer studied in this paper (grid top map in meters).</p>
Full article ">Figure 2
<p>Relative permeability curves applied for this study [<a href="#B45-hydrogen-06-00004" class="html-bibr">45</a>,<a href="#B46-hydrogen-06-00004" class="html-bibr">46</a>].</p>
Full article ">Figure 3
<p>Comparison of the H<sub>2</sub>S formation in moles over the years for two cases with different pyrite concentrations (0.5% in black and 2% in red).</p>
Full article ">Figure 4
<p>Comparison of the H<sub>2</sub>S formation in moles over the years for two cases with different hydrogen injection rates (1000 m<sup>3</sup>/d in solid blue, and 5000 m<sup>3</sup>/d in solid red).</p>
Full article ">Figure 5
<p>Comparison of H<sub>2</sub>S production in moles for three scenarios where the cushion gas was hydrogen, methane, and carbon dioxide.</p>
Full article ">Figure 6
<p>Cumulative volume of available H<sub>2</sub> in m<sup>3</sup> in the reservoir over 9 years.</p>
Full article ">Figure 7
<p>Cumulative volume of H<sub>2</sub>S generated in m<sup>3</sup> in the reservoir over 9 years.</p>
Full article ">Figure 8
<p>H<sub>2</sub>S gas mole fraction captured after an elapsed time of one year and a half from the initiation of the simulation.</p>
Full article ">Figure 9
<p>Cumulative produced H<sub>2</sub>S in m<sup>3</sup>.</p>
Full article ">Figure 10
<p>Cumulative produced volume of H<sub>2</sub> in m<sup>3</sup> over time.</p>
Full article ">Figure 11
<p>Cumulative hydrogen production (in kg) for different cases.</p>
Full article ">Figure 12
<p>H<sub>2</sub> volume (in m<sup>3</sup>) in the reservoir with methanation process.</p>
Full article ">Figure 13
<p>Hydrogen cumulative production (in kg) with the prolonged producing operation for Case H and base case.</p>
Full article ">Figure 14
<p>The minimum and maximum impurity levels for the different gases within UHS.</p>
Full article ">Figure 15
<p>Water saturation at the same time point for the base case (on <b>top</b>) and Case H (on <b>bottom</b>).</p>
Full article ">Figure 16
<p>Volume of water (in m<sup>3</sup>) in the aquifer for the base case and Case H.</p>
Full article ">Figure 17
<p>Cumulative water production (in m<sup>3</sup>) for 2 different cases.</p>
Full article ">Figure 18
<p>Average reservoir pressure (in kPa) for 2 different cases.</p>
Full article ">Figure 19
<p>H<sub>2</sub> cumulative moles in the reservoir.</p>
Full article ">Figure 20
<p>CO<sub>2</sub> cumulative moles in the reservoir.</p>
Full article ">
27 pages, 16020 KiB  
Article
Pore Structure and Its Fractal Dimension: A Case Study of the Marine Shales of the Niutitang Formation in Northwest Hunan, South China
by Wei Jiang, Yang Zhang, Tianran Ma, Song Chen, Yang Hu, Qiang Wei and Dingxiang Zhuang
Fractal Fract. 2025, 9(1), 49; https://doi.org/10.3390/fractalfract9010049 - 17 Jan 2025
Viewed by 289
Abstract
To analyze the pore structure and fractal characteristics of marine shale in the lower Cambrian Niutitang Formation in northwestern Hunan Province, China, the pore characteristics of shale were characterized using total organic carbon (TOC) content, field emission scanning electron microscopy (FESEM), X-ray diffraction [...] Read more.
To analyze the pore structure and fractal characteristics of marine shale in the lower Cambrian Niutitang Formation in northwestern Hunan Province, China, the pore characteristics of shale were characterized using total organic carbon (TOC) content, field emission scanning electron microscopy (FESEM), X-ray diffraction (XRD), low temperature nitrogen adsorption (LT-N2GA) and methane adsorption experiments. The pore surface and pore space fractal dimensions of samples were calculated, respectively. The influencing factors of fractal dimensions and their impact on the adsorption of shale reservoirs were discussed. The results indicate the Niutitang Formation shale mainly develops four types of pores: organic pores, intragranular pores, intergranular pores and microcracks. The pores have a large specific surface area (SSA), primarily consisting of mesopores. The fractal dimensions are calculated using the FHH model and the XS model. The fractal dimensions (D2 and Df) are greater than D1, indicating that the pore surface with larger pore size is rougher, and the pore structure of shale is complex. The pore volume (PV), SSA, and TOC show positive correlations with the fractal dimensions but negative correlations with APS. There is no obvious correlation between fractal dimensions and quartz content, while clay minerals show a negative correlation with D2 and Df. This is mainly because clay mineral particles are small in size and have weak resistance to compaction. The pyrite content is positively correlated with the fractal dimensions because pyrite promotes the development of organic, intergranular, and mold pores. According to Pearson correlation analysis, the main influencing factors of the pore surface fractal dimension are PV, SSA, and APS. The main influencing factors of the pore space fractal dimension are APS and the content of clay minerals. Further analysis of the influence of the fractal dimension on the adsorption capacity of shale reveals that the fractal dimensions are positively correlated with Langmuir volume, indicating that fractal dimensions can be used as a quantitative target for evaluating shale gas reservoirs. Full article
Show Figures

Figure 1

Figure 1
<p>(<b>a</b>) Location map of the study area in the Middle Yangtze Region, Northwest Hunan, China (modified after [<a href="#B32-fractalfract-09-00049" class="html-bibr">32</a>]); (<b>b</b>) Niutitang Formation in the study area (modified after [<a href="#B32-fractalfract-09-00049" class="html-bibr">32</a>]).</p>
Full article ">Figure 2
<p>The bar graph of shale mineral composition.</p>
Full article ">Figure 3
<p>Correlations between mineral content and depth.</p>
Full article ">Figure 4
<p>(<b>a</b>) 3-end-number diagram of shale mineral composition (modified after [<a href="#B45-fractalfract-09-00049" class="html-bibr">45</a>]). (<b>b</b>) Ternary plot of shale mineral compositions of Niutitang Formation. (S = Siliceous shale lithofacies, CR = Clay-rich shale lithofacies, C = Calcareous shale lithofacies, M = Mixed shale lithofacies).</p>
Full article ">Figure 5
<p>Microscopic pore types and characteristics of shale samples from the Niutitang Formation. Polished surface observation: (<b>a</b>) Pyrite and microfractures in sample X-2; (<b>b</b>) OM pores and interP pores in sample X-5; (<b>c</b>) IntraP pores and OM pores in sample X-6; (<b>d</b>) Pore system of clay minerals in sample X-6; (<b>e</b>) OM pores, pyrite and pore system of clay minerals in sample X-7; (<b>f</b>) OM pores and interP pores in sample X-9; Natural section observation: (<b>g</b>) OM pores, pyrite and interP pores in sample X-7; (<b>h</b>) Microfractures in sample X-7; (<b>i</b>) OM pores and intraP pores in sample X-13.</p>
Full article ">Figure 6
<p>LT-N<sub>2</sub>GA curves of the Niutitang Formation shale in northwestern Hunan province.</p>
Full article ">Figure 7
<p>Pore size distribution of the shale sample.</p>
Full article ">Figure 8
<p>Fractal dimensions of the Niutitang Formation shale in northwestern Hunan province.</p>
Full article ">Figure 9
<p>The plot of lnN vs. lnε from the Niutitang Formation shales.</p>
Full article ">Figure 10
<p>Correlations between fractal dimensions and depth.</p>
Full article ">Figure 11
<p>The isothermal CH<sub>4</sub> adsorption curves for the Niutitang formation shale in Northwest Hunan.</p>
Full article ">Figure 12
<p>Correlations between fractal dimensions and TOC.</p>
Full article ">Figure 13
<p>Correlation between pore attributes and fractal dimensions of the Niutitang Formation shale in northwestern Hunan province. (<b>a</b>) Surface area and fractral dimension; (<b>b</b>) PV and fractral dimension; (<b>c</b>) APS and fractral dimension.</p>
Full article ">Figure 14
<p>Correlation between inorganic mineral content and fractal dimensions. (<b>a</b>) Quartz and fractral dimension; (<b>b</b>) Carbonate and fractral dimension; (<b>c</b>) Feldspar and fractral dimension; (<b>d</b>) Clay and fractral dimension; (<b>e</b>) Pyrite and fractral dimension.</p>
Full article ">Figure 15
<p>Correlation between different clay mineral contents and fractal dimensions. (<b>a</b>) Chlorite and fractral dimension; (<b>b</b>) Illite and fractral dimension.</p>
Full article ">Figure 16
<p>Correlation between TOC and pyrite content.</p>
Full article ">Figure 17
<p>Correlation coefficients of the shale mineral composition, TOC, pore parameters and fractal parameters.</p>
Full article ">Figure 18
<p>Correlation between Langmuir volume and fractal dimensions.</p>
Full article ">
19 pages, 8273 KiB  
Article
Numerical Simulation of Gas–Liquid–Solid Erosive Wear in Gas Storage Columns
by Zongxiao Ren, Chenyu Zhang, Wenbo Jin, Bingyue Han and Zhaoyang Fan
Coatings 2025, 15(1), 82; https://doi.org/10.3390/coatings15010082 - 14 Jan 2025
Viewed by 366
Abstract
Gas reservoirs play an increasingly important role in oil and gas consumption and safety in China. To study the problem of erosion and wear caused by gas-carrying particles in the process of gas extraction from gas storage reservoirs, a mathematical model of gas–liquid–solid [...] Read more.
Gas reservoirs play an increasingly important role in oil and gas consumption and safety in China. To study the problem of erosion and wear caused by gas-carrying particles in the process of gas extraction from gas storage reservoirs, a mathematical model of gas–liquid–solid three-phase erosion of gas storage reservoir columns was established through theories of multiphase flow and particle motion. Based on this model, the effects of the water volume fraction, gas extraction rate, particle mass flow rate, particle size, and bending angle on the erosion location and rate of the pipe columns were investigated. The findings indicate that when the water content volume fraction is low, the water production volume minimally affects the maximum erosion rate of pipe columns. Conversely, the gas extraction rate exerted the most significant influence on the column erosion, showing a power function relationship between the two. When gas extraction volume exceeds 60 × 104 m3/d, the maximum erosion rate surpasses the critical erosion rate of 0.076 mm/a. This coincided with the increased sand mass flow rate, although the maximum erosion rate of the pipe columns remained relatively steady. The salt mass flow rate demonstrated a linear relationship with the erosion rate, with the maximum erosion rate exceeding the critical erosion rate of 0.076 mm/a. The maximum erosion rate of the pipe columns increased, stabilized with larger sand and salt particle sizes, and exhibited an increasing trend with the bending angle. For gas extraction volumes exceeding 46.4 × 104 m3/d and salt mass flow rates exceeding 22 kg/d, the maximum erosion rate of pipe columns exceeds the critical erosion rate of 0.076 mm/a. The conclusions of this study are of some importance for the clarification of the influencing law of pipe column erosion under high temperature and high pressure in gas storage reservoirs and for the formulation of measures for the prevention and control of pipe column erosion in gas storage reservoirs. Full article
(This article belongs to the Collection Feature Paper Collection in Corrosion, Wear and Erosion)
Show Figures

Figure 1

Figure 1
<p>Cloud diagram of validation results.</p>
Full article ">Figure 2
<p>Schematic of pipe column geometry.</p>
Full article ">Figure 3
<p>Discretization of elbow mesh.</p>
Full article ">Figure 4
<p>Grid irrelevance analysis.</p>
Full article ">Figure 5
<p>Change the law of maximum erosion rate with gas extraction under different water content volume fractions.</p>
Full article ">Figure 6
<p>Variation pattern of maximum erosion rate with sand mass flow rate.</p>
Full article ">Figure 7
<p>Particle trajectories under varying sand mass flow rate. (<b>a</b>) Sand trajectory for a mass flow rate of 8.64 kg/d; (<b>b</b>) sand trajectory for a mass flow rate of 0.0864 kg/d; (<b>c</b>) salt motion trajectory at sand mass flow rate.</p>
Full article ">Figure 8
<p>Variation pattern of maximum erosion rate with salt mass flow rate.</p>
Full article ">Figure 9
<p>Erosion cloud and particle trajectory maps under varying salt mass flow rates. (<b>a</b>) Salt mass flow rate 0.0864 kg/d; (<b>b</b>) salt mass flow 69.1 kg/d; (<b>c</b>) sand trajectory with a salt mass flow rate of 0.0864 kg/d; (<b>d</b>) sand trajectory with a salt mass flow rate of 69.1 kg/d; (<b>e</b>) salt particle trajectories for a salt mass flow rate of 0.0864 kg/d; (<b>f</b>) salt grain trajectory for a salt mass flow rate of 69.1 kg/d.</p>
Full article ">Figure 9 Cont.
<p>Erosion cloud and particle trajectory maps under varying salt mass flow rates. (<b>a</b>) Salt mass flow rate 0.0864 kg/d; (<b>b</b>) salt mass flow 69.1 kg/d; (<b>c</b>) sand trajectory with a salt mass flow rate of 0.0864 kg/d; (<b>d</b>) sand trajectory with a salt mass flow rate of 69.1 kg/d; (<b>e</b>) salt particle trajectories for a salt mass flow rate of 0.0864 kg/d; (<b>f</b>) salt grain trajectory for a salt mass flow rate of 69.1 kg/d.</p>
Full article ">Figure 10
<p>Variation rule of maximum erosion rate with grain size.</p>
Full article ">Figure 11
<p>Particle trajectories for different sand grain sizes. (<b>a</b>) Trajectory of 0.01 mm sand grains; (<b>b</b>) Trajectory of 1 mm sand grains; (<b>c</b>) Trajectory of 5 mm sand grains; (<b>d</b>) Maps of salt trajectories.</p>
Full article ">Figure 12
<p>Variation rule of maximum erosion rate with grain size.</p>
Full article ">Figure 13
<p>Erosion cloud and particle trajectory maps for different salt grain sizes; (<b>a</b>) 0.1 mm erosion maps; (<b>b</b>) plot of 0.1 mm particle trajectories; (<b>c</b>) 0.3 mm erosion map; (<b>d</b>) plot of 0.3 mm particle trajectories; (<b>e</b>) 0.5 mm erosion maps; (<b>f</b>) plot of 0.5 mm particle trajectories.</p>
Full article ">Figure 13 Cont.
<p>Erosion cloud and particle trajectory maps for different salt grain sizes; (<b>a</b>) 0.1 mm erosion maps; (<b>b</b>) plot of 0.1 mm particle trajectories; (<b>c</b>) 0.3 mm erosion map; (<b>d</b>) plot of 0.3 mm particle trajectories; (<b>e</b>) 0.5 mm erosion maps; (<b>f</b>) plot of 0.5 mm particle trajectories.</p>
Full article ">Figure 14
<p>Variation rule of maximum erosion rate with bending angle.</p>
Full article ">Figure 15
<p>Plots of different particle trajectories at different bending angles. (<b>a</b>) Trajectory of 15° sand particles; (<b>b</b>) 15° salt particle trajectory map; (<b>c</b>) trajectory of 45° sand particles; (<b>d</b>) 45° salt particle trajectory map; (<b>e</b>) trajectory of 75° sand particles; (<b>f</b>) 75° salt particle trajectory map.</p>
Full article ">
15 pages, 4570 KiB  
Article
Preparation of Heat and Salt Resistant Foam Composite System Based on Weathered Coal Particle Strengthening and a Study on Foam Stabilization Mechanism
by Yanyan Xu, Linghui Xi, Yajun Wu, Xin Shi, Zhi Kang, Beibei Wu and Chao Zhang
Processes 2025, 13(1), 183; https://doi.org/10.3390/pr13010183 - 10 Jan 2025
Viewed by 379
Abstract
Nitrogen foam is a promising enhanced oil recovery (EOR) technique with significant potential for tertiary oil recovery. This improves the efficiency of the oil displacement during the gas drive processes while expanding the swept volume. However, in the high-temperature, high-salinity reservoirs of the [...] Read more.
Nitrogen foam is a promising enhanced oil recovery (EOR) technique with significant potential for tertiary oil recovery. This improves the efficiency of the oil displacement during the gas drive processes while expanding the swept volume. However, in the high-temperature, high-salinity reservoirs of the Tahe Oilfield, conventional N2 foam systems show suboptimal performance, as their effectiveness is heavily limited by temperature and salinity. Consequently, enhancing the foam stability under these harsh conditions is crucial for unlocking new opportunities for the development of Tahe fracture-vuggy reservoirs. In this study, the Waring–Blender method was used to prepare weathered coal particles as a foam stabilizer. Compared to conventional foam stabilizers, weathered coal particles were found to enhance the stability of the liquid film under high-temperature and high-salinity conditions. Firstly, the foaming properties of the six foaming agents were comprehensively evaluated and their foaming properties were observed at different concentrations. YL-3J with a mass concentration of 0.7% was selected. The foaming stabilization performance of four types of solid particles was evaluated and weathered coal solid particles with a mass concentration of 15% and particle size of 300 mesh were selected. Therefore, the particle-reinforced foam system was determined to consist of “foaming agent YL-3J (0.7%) + weathered coal (15.0%) + nitrogen”. This system exhibited a foaming volume of 310 mL at 150 °C and salinity of 210,000 mg/L, with a half-life of 1920 s. Finally, through interfacial tension and viscoelastic modulus tests, the synergistic mechanism between weathered coal particles and surfactants was demonstrated. The incorporation of weathered coal particles reduced the interfacial tension of the system. The formation of a skeleton at the foam interface increased the apparent viscosity and viscoelastic modulus, reduced the liquid drainage rate from the foam, and mitigated the disproportionation effect. These effects enhanced the temperature, salinity resistance, and stability of the foam. Consequently, they contributed to the stable flow of foam under high-temperature and high-salinity conditions in the reservoir, thereby improving the oil displacement efficiency of the system. Full article
Show Figures

Figure 1

Figure 1
<p>Schematic of the high-temperature and high-pressure foam evaluator. 1, Pressure control valve; 2, electric heating sleeve; 3, visualization window; 4, control box; 5, temperature-pressure digital display.</p>
Full article ">Figure 2
<p>Effects of foaming agent and concentration on foaming volume.</p>
Full article ">Figure 3
<p>Effect of foaming agent concentration on half-life.</p>
Full article ">Figure 4
<p>Effects of foaming agent and concentration on foam composite index.</p>
Full article ">Figure 5
<p>Comparison of the salinity resistance of different foaming agents.</p>
Full article ">Figure 6
<p>Comparison of temperature resistance of different foaming agents.</p>
Full article ">Figure 7
<p>Performance of foam system strengthened by fly ash (<b>a</b>), weathering coal (<b>b</b>), 1000 mesh graphite (<b>c</b>), and graphite milk (<b>d</b>) with different mass concentrations.</p>
Full article ">Figure 8
<p>Comparison of foaming performance of weathered coal and fly ash reinforced foam system. (<b>a</b>) Weathered coal reinforced foam system. (<b>b</b>) Fly ash reinforced foam system.</p>
Full article ">Figure 9
<p>Effect of weathered coal with different particle sizes on the foam properties. (<b>a</b>) Effect of weathered coal particles with different mesh numbers on the foam volume. (<b>b</b>) Effect of weathered coal particles with different mesh numbers on the half-life. (<b>c</b>) Effect of weathered coal particles with different mesh numbers on the foam composite index.</p>
Full article ">Figure 10
<p>Interface properties of foaming solutions with different concentrations of YL-3J.</p>
Full article ">Figure 11
<p>Interface properties of foaming solutions with different solid particle concentrations.</p>
Full article ">Figure 12
<p>Photograph of weathered coal particle-reinforced foam at room temperature. (Red circle shows that the local amplification of the foam layer).</p>
Full article ">Figure 13
<p>Foam disproportionation diagram.</p>
Full article ">
17 pages, 1919 KiB  
Article
Design Flood Calculation Model for Extra-Small Watersheds in Ungauged Basin
by Yun Wang, Zengchuan Dong, Xinhua Zhu, Wenzhuo Wang, Yupeng Liu, Ronghao Chen and Yunjia He
Hydrology 2025, 12(1), 9; https://doi.org/10.3390/hydrology12010009 - 7 Jan 2025
Viewed by 452
Abstract
Designing floods in ungauged watersheds with limited data is a significant challenge in water conservancy projects. To address this, the method of calculating the design flood peak and flood volume using the weighted average method was proposed, which is based on the instantaneous [...] Read more.
Designing floods in ungauged watersheds with limited data is a significant challenge in water conservancy projects. To address this, the method of calculating the design flood peak and flood volume using the weighted average method was proposed, which is based on the instantaneous unit hydrograph method and the inference formula method, combined with the characteristics of heavy rainfall floods in ungauged watersheds. The calculation results are analyzed in terms of reasonableness through the distribution pattern of the flood peak modulus under different frequencies of the constructed reservoirs, the relative error analysis, and the HEC-RAS model. Based on the one-day flood process of the adjacent basin, the calculation of deducing the design flood process using the hydrological comparison method was proposed. Taking the “Stormwater Runoff Chart” as the data source, the runoff generation, and concentration model was established with the design flood of Baludi Reservoir in the Gelangram River basin of Menglian, Yunnan Province as the research object. A comparative study of the results of the design floods calculated by different methods was carried out. The results show that the new method can well describe the rainstorm process. The method has better performance in the application to the design flood calculation of ungauged basins due to its consideration of the influence of subsurface conditions. The method not only reduces the construction cost but also improves the safety of the reservoir through a better-fitted design flood calculation. Full article
Show Figures

Figure 1

Figure 1
<p>Overview of the Baludi Reservoir and the river system in the basin.</p>
Full article ">Figure 2
<p>Design Flood Flow for Baludi Reservoir. (The flood frequency shown in the figure is primarily determined by the Standard for flood control (GB50201-2014) and Standard for rank classification and flood protection criteria of water and hydropower projects (SL252-2017)).</p>
Full article ">Figure 3
<p>Maximum One-Day Flood Volume for the Baludi Reservoir. (The flood frequency shown in the figure is primarily determined by the Standard for flood control (GB50201-2014) and Standard for rank classification and flood protection criteria of water and hydropower projects (SL252-2017)).</p>
Full article ">Figure 4
<p>Relative error method reasonableness analysis results. (The flood frequency shown in the figure is primarily determined by the Standard for flood control (GB50201-2014) and Standard for rank classification and flood protection criteria of water and hydropower projects (SL252-2017)).</p>
Full article ">Figure 5
<p>Rationality analysis table of flood results. (The flood frequency shown in the figure is primarily determined by the Standard for flood control (GB50201-2014) and Standard for rank classification and flood protection criteria of water and hydropower projects (SL252-2017)).</p>
Full article ">Figure 6
<p>Design flood process line of Baludi Reservoir dam site. (The flood frequency shown in the figure is primarily determined by the Standard for flood control (GB50201-2014) and Standard for rank classification and flood protection criteria of water and hydropower projects (SL252-2017)).</p>
Full article ">
14 pages, 4767 KiB  
Article
Experimental Assessment of Magnetic Nanofluid Injection in High-Salinity and Heavy-Crude-Saturated Sandstone: Mitigation of Formation Damage
by Jimena Lizeth Gómez-Delgado, Nelson Gutierrez-Niño, Luis Felipe Carrillo-Moreno, Raúl Andres Martínez-López, Nicolás Santos-Santos and Enrique Mejía-Ospino
Energies 2025, 18(1), 212; https://doi.org/10.3390/en18010212 - 6 Jan 2025
Viewed by 412
Abstract
The depletion of conventional oil reserves has intensified the search for enhanced oil recovery (EOR) techniques. Recently, nanoparticle research has focused on graphene oxide-based materials, revealing a critical challenge in their practical application. Laboratory investigations have consistently demonstrated that these nanoparticles have significant [...] Read more.
The depletion of conventional oil reserves has intensified the search for enhanced oil recovery (EOR) techniques. Recently, nanoparticle research has focused on graphene oxide-based materials, revealing a critical challenge in their practical application. Laboratory investigations have consistently demonstrated that these nanoparticles have significant potential for formation damage, a critical limitation that substantially constrains their potential field implementation. This research addresses a critical challenge in EOR: developing magnetic graphene oxide nanoparticles (MGONs) that can traverse rock formations without causing formation damage. MGONs were synthesized and stabilized in formation brine with a high total dissolved solids (TDS) content with a xanthan gum polymer. Two coreflooding experiments were conducted on sandstone cores. The first experiment on high-permeability sandstone (843 mD) showed no formation damage; instead, permeability increased to 935 mD after MGON injection. Irreducible water saturation (Swirr) and residual oil saturation (Sor) were 25.1% and 31.5%, respectively. The second experiment on lower-permeability rock (231.3 mD) evaluated nanoparticle retention. The results showed that 0.09511 mg of MGONs was adsorbed per gram of rock under dynamic conditions. Iron concentration in effluents stabilized after 3 pore volumes, indicating steady-state adsorption. The successful synthesis, stability in high-TDS brine, favorable interfacial properties, and positive effects observed in coreflooding experiments collectively highlight MGONs’ potential as a viable solution for enhancing oil recovery in challenging reservoirs, without causing formation damage. Full article
(This article belongs to the Special Issue Failure and Multiphysical Fields in Geo-Energy)
Show Figures

Figure 1

Figure 1
<p>FTIR spectra of graphene oxide (GO) and magnetic graphene oxide (Fe<sub>3</sub>O<sub>4</sub>@GO).</p>
Full article ">Figure 2
<p>Micrographs of GO on the <b>left</b> and Fe<sub>3</sub>O<sub>4</sub>@GO on the <b>right</b>.</p>
Full article ">Figure 3
<p>Size distribution of magnetic graphene oxide Fe<sub>3</sub>O<sub>4</sub>@GO.</p>
Full article ">Figure 4
<p>Compatibility test (formation brine and Fe<sub>3</sub>O<sub>4</sub>@GO magnetic nanofluid).</p>
Full article ">Figure 5
<p>Coreflooding Stage 1.</p>
Full article ">Figure 6
<p>Iron concentration in effluents.</p>
Full article ">
21 pages, 5790 KiB  
Article
Sealing Effects on Organic Pore Development in Marine Shale Gas: New Insights from Macro- to Micro-Scale Analyses
by Qiumei Zhou, Hao Xu, Wen Zhou, Xin Zhao, Ruiyin Liu and Ke Jiang
Energies 2025, 18(1), 193; https://doi.org/10.3390/en18010193 - 5 Jan 2025
Viewed by 393
Abstract
The physics of how organic pores change under high thermal evolution conditions in overmature marine shale gas formations remains unclear. In this study, systematic analyses at the macro- to micro-scales were performed to reveal the effects of the sealing capacity on organic pore [...] Read more.
The physics of how organic pores change under high thermal evolution conditions in overmature marine shale gas formations remains unclear. In this study, systematic analyses at the macro- to micro-scales were performed to reveal the effects of the sealing capacity on organic pore development. Pyrolysis experiments were conducted in semi-closed and open systems which provided solid evidence demonstrating the importance of the sealing capacity. Low-maturity marine shale samples from the Dalong Formation were used in the pyrolysis experiments, which were conducted at 350 °C, 400 °C, 450 °C, 500 °C, 550 °C, and 600 °C. The pore characteristics and geochemical parameters of the samples were examined after each thermal simulation stage. The results showed that the TOC of the semi-closed system decreased gradually, while the TOC of the open system decreased sharply at 350 °C and exhibited almost no change thereafter. The maximum porosity, specific surface area, and pore volume of the semi-closed system (10.35%, 2.99 m2/g, and 0.0153 cm3/g) were larger than those of the open system (3.87%, 1.97 m2/g, and 0.0059 cm3/g). In addition, when the temperature was 600 °C, the pore diameter distribution in the open system was 0.001–0.1 μm, while the pore diameter distribution in the semi-closed system was 0.001–10 μm. The pore volumes of the macropores and mesopores in the semi-closed system remained larger than those in the open system. The pore volumes of the micropores in the semi-closed and open systems were similar. The pyrolysis results indicated that (1) the pressure difference caused by the sealing capacity controls organic pore development; (2) organic pores developed in the semi-closed system, and the differences between the two systems mainly occurred in the overmature stage; and (3) the differences were caused by changes in the macropore and mesopore volumes, not the micropore volume. It was concluded that the sealing capacity is the key factor for gas pore generation in the overmature stage of marine shale gas reservoirs when the organic matter (OM) type, volume, and thermal evolution degree are all similar. The macropores and mesopores are easily affected by the sealing conditions, but the micropores are not. Finally, the pyrolysis simulation results were validated with the Longmaxi shale and Qiongzhusi shale properties. The Longmaxi shale is similar to semi-closed system, and the Qiongzhusi shale is similar to open system. Two thermal evolution patterns of organic pore development were proposed based on the pyrolysis results. This study provides new insights into the evolution patterns of organic pores in marine shale gas reservoirs. Full article
Show Figures

Figure 1

Figure 1
<p>Geographic locations of the well sites and stratigraphic columns of the Longmaxi and Qiongzhusi Formations. The floor of the Longmaxi Formation is composed of the limestone of the Baota Formation. The floor of the Qiongzhusi Formation, where the Madiping layer is missing, is composed of the Dengying Formation, and they are separated by the Tongwan unconformity (modified from [<a href="#B24-energies-18-00193" class="html-bibr">24</a>,<a href="#B25-energies-18-00193" class="html-bibr">25</a>,<a href="#B26-energies-18-00193" class="html-bibr">26</a>,<a href="#B27-energies-18-00193" class="html-bibr">27</a>]).</p>
Full article ">Figure 2
<p>Comparative analyses of the average porosity, TOC, Ro, and mineral content of the First Members of the Longmaxi and Qiongzhusi Formations in selected wells. The well data for the First Member of the Longmaxi Formation are from wells WA, WB, Ning 201, Ning203, JY1, and JY2. The well data for the First Member of the Qiongzhusi Formation are from wells WA and WB (the values are from [<a href="#B24-energies-18-00193" class="html-bibr">24</a>,<a href="#B25-energies-18-00193" class="html-bibr">25</a>,<a href="#B26-energies-18-00193" class="html-bibr">26</a>,<a href="#B27-energies-18-00193" class="html-bibr">27</a>]).</p>
Full article ">Figure 3
<p>Outlook sample of Dalong shale from the Guangyuan Changjianggou area. (<b>a</b>) Outlook samples collection site; (<b>b</b>) Sample used for pyrolysis simulation experiments.</p>
Full article ">Figure 4
<p>Relationship between the breakthrough pressure and permeability in the Qiongzhusi Formation [<a href="#B40-energies-18-00193" class="html-bibr">40</a>,<a href="#B41-energies-18-00193" class="html-bibr">41</a>].</p>
Full article ">Figure 5
<p>Micro-sealing conditions observed using SEM. (<b>a</b>) The sample of the semi-closed system was collected from the Sanxingcun outcrop (TOC = 4.5%, Ro = 3.05%), OM pores developed. (<b>b</b>) The sample of the open system was collected from well S2 (TOC = 3.4%, Ro = 1.52%), OM pores did not develop.</p>
Full article ">Figure 6
<p>Morphology of the organic pores in the semi-closed and open systems. The kerogen oil pores were generated in the (<b>a</b>) semi-closed and (<b>b</b>) open systems; OM–clay mineral complex pores in the (<b>c</b>) semi-closed and (<b>d</b>) open systems; OM shrinkage cracks in the (<b>e</b>) semi-closed and (<b>f</b>) open systems; bitumen pores in the (<b>g</b>) semi-closed and (<b>h</b>) open systems.</p>
Full article ">Figure 7
<p>Organic pores in the semi-closed and open systems at different temperatures. (<b>a</b>) T = 350 °C, semi-closed system; (<b>b</b>) T = 350 °C, open system; (<b>c</b>) T = 500 °C, semi-closed system; (<b>d</b>) T = 500 °C, open system; (<b>e</b>) T = 600 °C, semi-closed system; and (<b>f</b>) T = 600 °C, open system.</p>
Full article ">Figure 8
<p>Thermal evolution of (<b>a</b>) porosity, (<b>b</b>,<b>c</b>) SSA, and (<b>d</b>) PV in the semi-closed and open systems.</p>
Full article ">Figure 9
<p>Carbon dioxide adsorption curves for the semi-closed and open systems at different temperatures: (<b>a</b>) T = 400 °C, (<b>b</b>) T = 450 °C, and (<b>c</b>) T = 550 °C.</p>
Full article ">Figure 10
<p>Nitrogen adsorption and desorption curves for the semi-closed and open systems at different temperatures: (<b>a</b>) T = 350 °C, (<b>b</b>) T = 400 °C, (<b>c</b>) T = 450 °C, (<b>d</b>) T = 550 °C, and (<b>e</b>) T = 600 °C.</p>
Full article ">Figure 11
<p>Mercury intrusion curves for the semi-closed and open systems at different temperatures: (<b>a</b>) T = 400 °C, (<b>b</b>) T = 450 °C, and (<b>c</b>) T = 600 °C.</p>
Full article ">Figure 12
<p>Pore diameter distributions in the semi-closed and open systems from the high-pressure mercury intrusion experiments at different temperatures: (<b>a</b>) T = 400 °C, (<b>b</b>) T = 450 °C, and (<b>c</b>) T = 600 °C.</p>
Full article ">Figure 13
<p>PV vs. Ro: (<b>a</b>) all pores; (<b>b</b>) macropores; (<b>c</b>) mesopores; and (<b>d</b>) micropores.</p>
Full article ">Figure 14
<p>Similarity between the pyrolysis simulation results and the Longmaxi and Qiongzhusi Formations’ real properties. The black points represent the pyrolysis simulation results. The red points represent the Longmaxi and Qiongzhusi Formations’ properties that were obtained from lab experiments and filed data.</p>
Full article ">Figure 15
<p>Thermal evolution patterns of the organic pores in a (<b>a</b>) semi-closed system and (<b>b</b>) open system.</p>
Full article ">
24 pages, 25702 KiB  
Article
Productivity Evaluation Modeling by Numerical Simulation for Shale Gas with Variable Dynamic Viscosity in Fractured Horizontal Wells
by Yufan Gao, Dong Yang, Hu Han, Qiao Deng and Chunxiao Wang
Processes 2025, 13(1), 119; https://doi.org/10.3390/pr13010119 - 5 Jan 2025
Viewed by 503
Abstract
Horizontal well hydraulic fracturing technology has been widely used in the efficient development of shale gas to address the challenges posed by these reservoirs’ low permeability and porosity. Despite the availability of numerous models for evaluating shale gas productivity post-fracturing, the effect of [...] Read more.
Horizontal well hydraulic fracturing technology has been widely used in the efficient development of shale gas to address the challenges posed by these reservoirs’ low permeability and porosity. Despite the availability of numerous models for evaluating shale gas productivity post-fracturing, the effect of gas dynamic viscosity has been neglected. This study establishes a multiple-media and multiple-permeability coupled flow model based on the Barnett Shale and introduces Lee’s correlation for gas viscosity. The model’s feasibility and accuracy were verified by comparing the simulation results with the Barnett Shale data. The effects of reservoir damage, stimulation intensity, and fracture spacing on shale gas productivity are discussed. The results demonstrated that shale gas productivity decreased by more than 50% with intensified reservoir damage. Increasing stimulation intensity in the reservoir volume enhanced shale gas productivity. When the stimulation coefficient for the reservoir was increased from 0 to 2.5, the productivity increased by over 25%. A larger fracture spacing resulted in a smaller increase in shale gas productivity. Conversely, excessively narrow spacings significantly hindered productivity, resulting in an approximate 25% decrease. This study provides a theoretical reference for the productivity evaluation of horizontal wells in shale gas reservoirs. Full article
Show Figures

Figure 1

Figure 1
<p>The diagram of a multi-stage fractured horizontal well in a two-dimensional shale gas reservoir.</p>
Full article ">Figure 2
<p>Diagram of the simulation model of the multi-stage fractured horizontal well in the shale gas reservoir.</p>
Full article ">Figure 3
<p>Diagram of grid generation for the numerical simulation.</p>
Full article ">Figure 4
<p>Grid refinement of areas around hydraulic fractures and horizontal wells.</p>
Full article ">Figure 5
<p>Daily productivity comparison of dynamic viscosity, constant viscosity, and Barnett daily productivity data.</p>
Full article ">Figure 6
<p>Daily productivity comparison of the simulation results, other researchers’ modelled findings, and actual Barnett Shale productivity [<a href="#B8-processes-13-00119" class="html-bibr">8</a>].</p>
Full article ">Figure 7
<p>(<b>a</b>) Reservoir pressure distribution on 0th day. (<b>b</b>) Darcy velocity on 0th day.</p>
Full article ">Figure 8
<p>(<b>a</b>) Reservoir pressure distribution on 10th day. (<b>b</b>) Darcy velocity on 10th day.</p>
Full article ">Figure 9
<p>(<b>a</b>) Reservoir pressure distribution on 300th day. (<b>b</b>) Darcy velocity on 300th day.</p>
Full article ">Figure 10
<p>(<b>a</b>) Reservoir pressure distribution on 800th day. (<b>b</b>) Darcy velocity on 800th day.</p>
Full article ">Figure 11
<p>(<b>a</b>) Reservoir pressure distribution on 2000th day. (<b>b</b>) Darcy velocity on 2000th day.</p>
Full article ">Figure 12
<p>Daily productivity of multi-stage fractured horizontal wells under different damage coefficients.</p>
Full article ">Figure 13
<p>The pressure distribution around the hydraulic fracture on the 800th day under different damage coefficients.</p>
Full article ">Figure 14
<p>Cumulative productivity of multi-stage fractured horizontal wells under different damage coefficients.</p>
Full article ">Figure 15
<p>Daily productivity of multi-stage fractured horizontal wells under different stimulation coefficients.</p>
Full article ">Figure 16
<p>Pressure distribution in SRV under different stimulation coefficients on the 800th day.</p>
Full article ">Figure 17
<p>Cumulative productivity of multi-stage fractured horizontal wells under different stimulation coefficients.</p>
Full article ">Figure 18
<p>Daily productivity of multi-stage fractured horizontal wells with different fracture spacing.</p>
Full article ">Figure 19
<p>Pressure distribution in the reservoir on the 800th day under conditions of different fracture spacing.</p>
Full article ">Figure 20
<p>Cumulative productivity of multi-stage fractured horizontal wells under conditions of different fracture spacing.</p>
Full article ">
14 pages, 9067 KiB  
Article
Study on Improving Recovery of Highly Heterogeneous Reservoirs by Unsteady Water Injection Technology
by Lun Zhao, Wenqi Zhao, Meng Sun, Jincai Wang, Hongfei Ma, Yi Li and Xiaoliang Zhao
Energies 2025, 18(1), 159; https://doi.org/10.3390/en18010159 - 3 Jan 2025
Viewed by 381
Abstract
Unstable water injection can effectively improve the recovery ratio of reservoirs with strong heterogeneity. However, the oil displacement mechanism and the determination method of unstable water injection parameters still need to be clarified, especially for complex fracture reservoirs, which greatly restrict the popularization [...] Read more.
Unstable water injection can effectively improve the recovery ratio of reservoirs with strong heterogeneity. However, the oil displacement mechanism and the determination method of unstable water injection parameters still need to be clarified, especially for complex fracture reservoirs, which greatly restrict the popularization and development of unstable water injection technology. This paper studies unstable water injection technology in highly heterogeneous reservoirs from the core and reservoir scales, utilizing many displacement experiments and numerical simulations. The differences in oil displacement efficiency, remaining oil distribution, pressure field, and streamlines between continuous water injection and unstable water injection are compared and evaluated. Five flow stages of unstable injection and production are precisely divided, and the microscopic and macroscopic displacement mechanism is clarified. A numerical model of two injection wells and one production is established to determine the best time to implement unstable water injection technology. Based on the principle of pressure superposition, the expression of pressure field distribution between injection and production well in each period of unstable water injection is analytically solved. This formula has provided a new development parameter optimization method aiming at the maximum pressure fluctuation range and optimized the development technology parameters in the water injection process. The results show that precise control injection and production parameters can expand water swept volume, effectively improve the degree of reserve utilization, and improve the recovery of complex reservoirs by 3–7%, which provides a reliable basis for the practical implementation of unstable water injection technology. Full article
(This article belongs to the Special Issue Advances in the Development of Geoenergy: 2nd Edition)
Show Figures

Figure 1

Figure 1
<p>3D schematic diagram of experimental model.</p>
Full article ">Figure 2
<p>CT core scanning displacement system.</p>
Full article ">Figure 3
<p>Comparison chart of the degree of spread in each stage.</p>
Full article ">Figure 4
<p>Variation law of water saturation in the low permeability area at each stage of periodic water injection.</p>
Full article ">Figure 5
<p>The typical fractured reservoir simulation model.</p>
Full article ">Figure 6
<p>Cycle water injection simulation results for typical reservoirs.</p>
Full article ">Figure 7
<p>Simulation results of periodic water injection in different wettability reservoirs.</p>
Full article ">Figure 8
<p>Distribution of water saturation and water injection swept volume change law.</p>
Full article ">Figure 9
<p>Development effect of periodic water injection at different water cuts.</p>
Full article ">Figure 10
<p>The effective time of periodic water injection at different water cuts.</p>
Full article ">Figure 11
<p>Distribution characteristics of the pressure field at a reasonable injection and stop injection time.</p>
Full article ">Figure 12
<p>Pressure distribution at different injection-production ratios in the continuous injection phase, water injection boost phase, and stop injection pressure reduction phase.</p>
Full article ">Figure 13
<p>Distribution characteristics of the pressure field at different injection and stop injection times.</p>
Full article ">Figure 14
<p>A reservoir development status field diagram.</p>
Full article ">Figure 15
<p>Development mode partition.</p>
Full article ">Figure 16
<p>Comparison chart of plane spread degree of different systems.</p>
Full article ">Figure 17
<p>Comparison of recovery levels of different systems.</p>
Full article ">
19 pages, 8124 KiB  
Article
Impact of Deep Shale Gas Dense-Cutting Fracturing Parameters on EUR
by Tianyi Wang, Guofa Ji, Jiansheng Liu and Zelong Xie
Processes 2025, 13(1), 66; https://doi.org/10.3390/pr13010066 - 31 Dec 2024
Viewed by 279
Abstract
Deep shale formations pose significant challenges in forming high-conductivity fractures, leading to low ultimate recoverable reserves (EUR) per well under conventional fracturing techniques. Dense-cutting fracturing is a commonly employed method to enhance the EUR of individual wells; however, the critical process parameters influencing [...] Read more.
Deep shale formations pose significant challenges in forming high-conductivity fractures, leading to low ultimate recoverable reserves (EUR) per well under conventional fracturing techniques. Dense-cutting fracturing is a commonly employed method to enhance the EUR of individual wells; however, the critical process parameters influencing EUR remain unclear. This study develops a novel EUR calculation model tailored for deep shale gas dense-cutting, integrating the Warren-Root model with the constant-volume gas reservoir material balance equation. The model comprehensively incorporates Knudsen diffusion and adsorption-desorption phenomena in deep shale gas, corrects apparent permeability, and employs the finite element method to simulate dynamic pressure depletion during production. The study examines the impact of fracture half-lengths, cluster spacing, fracture conductivity and horizontal section lengths on EUR under tight-cutting fracturing. Orthogonal experiments combined with multiple linear regression analysis reveal the hierarchy of influence among the four factors on EUR: horizontal section length > fracture half-length > cluster spacing > fracture conductivity. The study derives EUR correlation expressions that incorporate the effects of crack half-length, cluster spacing, fracture conductivity, and horizontal segment length. The orthogonal experimental results indicate that EUR exhibits positive correlations with crack half-length, fracture conductivity, and horizontal segment length, while showing a negative correlation with cluster spacing. The multiple regression equation achieves a coefficient of determination (R2) of 0.962 and an average relative error of 3.79%, outperforming traditional prediction methods in both accuracy and computational simplicity. The findings are of substantial significance for the rapid estimation of EUR in individual wells following deep shale gas fracturing and offer valuable theoretical insights for practical engineering applications. Full article
(This article belongs to the Special Issue Oil and Gas Drilling Processes: Control and Optimization)
Show Figures

Figure 1

Figure 1
<p>The physical model of intensive stage fracturing in Shale Horizontal Wells.</p>
Full article ">Figure 2
<p>Flowchart for the calculation of EUR in a single well.</p>
Full article ">Figure 3
<p>The relationship between the deviation factor (z) and the average reservoir pressure (p).</p>
Full article ">Figure 4
<p>A cloud of simulation results over 30 years of production, varying with different fracture half-lengths.</p>
Full article ">Figure 5
<p>The impact of fracture half-length on reservoir average pressure EUR. (<b>a</b>) The relationship between fracture half-length and reservoir average pressure and EUR. (<b>b</b>) The increase rate of reservoir average pressure and EUR under different fracture half-length in 30 years of production.</p>
Full article ">Figure 6
<p>Modeling results of different cluster spacing production for 30 years.</p>
Full article ">Figure 7
<p>The impact of cluster spacing on reservoir average pressure and EUR. (<b>a</b>) The relationship between cluster spacing and reservoir average pressure and EUR. (<b>b</b>) The increase rate of reservoir average pressure and EUR under different cluster spacing in 30 years of production.</p>
Full article ">Figure 8
<p>Modeling results of different fracture conductivity production for 30 years.</p>
Full article ">Figure 9
<p>The impact of fracture conductivity on reservoir average pressure EUR. (<b>a</b>) The relationship between fracture conductivity and reservoir average pressure and EUR. (<b>b</b>) The increase rate of reservoir average pressure and EUR under different fracture conductivity in 30 years of production.</p>
Full article ">Figure 10
<p>Modeling results of different horizontal section length production for 30 years.</p>
Full article ">Figure 11
<p>The impact of horizontal section length on reservoir average pressure EUR. (<b>a</b>) The relationship between horizontal section length and reservoir average pressure and EUR. (<b>b</b>) The increase rate of reservoir average pressure and EUR under different horizontal section length in 30 years of production.</p>
Full article ">Figure 12
<p>Relationship diagram between regression prediction and calculated value.</p>
Full article ">Figure 13
<p>Test set sample prediction results and relative error analysis diagram.</p>
Full article ">
27 pages, 11152 KiB  
Systematic Review
Systematic Exploration of the Knowledge Graph on Rock Porosity Structure
by Chengwei Geng, Fei Xiong, Yong Liu, Yun Zhang, Yi Xue, Tongqiang Xia and Ming Ji
Buildings 2025, 15(1), 101; https://doi.org/10.3390/buildings15010101 - 30 Dec 2024
Viewed by 511
Abstract
The porosity structure of rocks is an important research topic in fields such as civil engineering, geology, and petroleum engineering, with significant implications for groundwater flow, oil and gas reservoir exploitation, and geological hazard prediction. This paper systematically explores the research progress and [...] Read more.
The porosity structure of rocks is an important research topic in fields such as civil engineering, geology, and petroleum engineering, with significant implications for groundwater flow, oil and gas reservoir exploitation, and geological hazard prediction. This paper systematically explores the research progress and knowledge graph construction methods for rock porosity structure, aiming to provide scientific foundations for a multidimensional understanding and application of rock porosity structure. It outlines the basic concepts and classifications of rock porosity, including the definitions and characteristics of macropores, micropores, and nanopores. This paper provides a comprehensive overview of the main technical methods employed in recent research on rock porosity structure, including X-ray computed tomography, scanning electron microscopy, nuclear magnetic resonance, and 3D reconstruction technologies. It explores the relationship between porosity structure and the physical and mechanical properties of rocks, focusing on the impact of porosity, permeability, and pore morphology on rock mechanical behavior. A knowledge graph of rock porosity structure is constructed to highlight key research areas, core technologies, and emerging applications in this field. The study utilizes extensive literature review and data mining techniques, analyzing 4807 papers published over the past 20 years, sourced from the Web of Science database. Bibliometric and knowledge graph analyses were performed, examining trends such as annual publication volume, country/region distribution, institutional affiliations, journal sources, subject categories, and research databases, as well as research hotspots and frontier developments. This analysis offers valuable insights into the current state of rock porosity structure research, shedding light on its progress and providing references for further advancing research in this area. Full article
(This article belongs to the Section Building Materials, and Repair & Renovation)
Show Figures

Figure 1

Figure 1
<p>PRISMA flow diagram.</p>
Full article ">Figure 2
<p>Annual publication volume of journals.</p>
Full article ">Figure 3
<p>Co creation of national distribution knowledge graph.</p>
Full article ">Figure 4
<p>Knowledge graph of research institution distribution.</p>
Full article ">Figure 5
<p>Knowledge graph of major journal distribution.</p>
Full article ">Figure 6
<p>Knowledge graph of author distribution in the research.</p>
Full article ">Figure 7
<p>Knowledge graph of keyword distribution.</p>
Full article ">Figure 8
<p>Column chart of the top ten high-frequency keywords.</p>
Full article ">Figure 9
<p>Knowledge graph of keyword time distribution.</p>
Full article ">Figure 10
<p>Knowledge graph of keyword clustering distribution.</p>
Full article ">Figure 11
<p>Knowledge graph of keyword clustering timeline distribution.</p>
Full article ">
30 pages, 19890 KiB  
Article
The Sedimentary Characteristics and Resource Potential of a Lacustrine Shallow-Water Delta on a Hanging-Wall Ramp in a Rift Basin: A Case Study from the Paleogene of the Raoyang Sag, Bohai Bay Basin, China
by Lei Ye, Xiaomin Zhu, Nigel P. Mountney, Shuanghui Xie, Renhao Zhang and Luca Colombera
Sustainability 2025, 17(1), 208; https://doi.org/10.3390/su17010208 - 30 Dec 2024
Viewed by 668
Abstract
The hanging-wall ramps of rift basins are prone to the accumulation of large sedimentary bodies and are potential areas for the presence of large subsurface geological reservoir volumes. This paper comprehensively utilizes data from sedimentology, seismic reflection, geochemistry, and palynology to study the [...] Read more.
The hanging-wall ramps of rift basins are prone to the accumulation of large sedimentary bodies and are potential areas for the presence of large subsurface geological reservoir volumes. This paper comprehensively utilizes data from sedimentology, seismic reflection, geochemistry, and palynology to study the paleotopography, water conditions, paleoclimate, and sediment supply of the fourth member (Mbr 4) of the Shahejie Formation in the Raoyang Sag of the Bohai Bay Basin, China. The sedimentary characteristics, evolution, and preserved stratigraphic architectures of shallow-water deltaic successions are analyzed. Multiple indicators—such as sporopollen, ostracoda, fossil algae, major elements, and trace elements—suggest that when Mbr 4 was deposited, the climate became progressively more humid, and the lake underwent deepening followed by shallowing. During rift expansion, the lake level began to rise with supplied sediment progressively filling available accommodation; sand delivery to the inner delta front was higher than in other parts of the delta, and highly active distributary channels formed a reticular drainage network on the delta plain, which was conducive to the formation of sandstone up-dip pinch-out traps. In the post-rift period, the lake water level dropped, and the rate and volume of sediment supply decreased, leading to the formation of a stable dendritic network of distributary channels. At channel mouths, sediments were easily reworked into sandsheets. The distribution of sandstone and mudstone volumes is characterized by up-dip pinch-out traps and sandstone lens traps. The network of channel body elements of the shallow-water deltaic successions is expected to act as an effective carbon dioxide storage reservoir. This study reveals the influence of multiple factors on the sedimentary characteristics, evolution, and internal network of shallow-water deltas at different stages of rift basin evolution. This knowledge helps improve resource utilization and the sustainable development of comparable subsurface successions. Full article
Show Figures

Figure 1

Figure 1
<p>The geological setting and cross section of the Raoyang Sag. (<b>A</b>) The location of the Bohai Bay Basin in China. (<b>B</b>) The regional tectonic units of the Raoyang Sag and the location of the study area. (<b>C</b>) The regional stratigraphic cross section of the Raoyang Sag (the location of the cross section is shown in (<b>B</b>)).</p>
Full article ">Figure 2
<p>The paleogene stratigraphic column of the Raoyang Sag. The paleoenvironment curves refer to [<a href="#B38-sustainability-17-00208" class="html-bibr">38</a>]. The target interval is the fourth member of the Shahejie Formation, highlighted in yellow. Mbr = Member, U = Upper, M = Middle, L = Lower.</p>
Full article ">Figure 3
<p>Seismic-well ties of well XL10. Synthetic seismograms were carried out on 43 wells.</p>
Full article ">Figure 4
<p>Sedimentary successions of the fourth member of the Shahejie Formation. The facies characteristics (<b>A</b>) and dip profile of subenvironments (<b>B</b>) of the shallow-water deltas. Refer to <a href="#sustainability-17-00208-t001" class="html-table">Table 1</a> for codes denoting facies associations.</p>
Full article ">Figure 5
<p>The imbricate seismic reflection characteristics of lacustrine shallow-water deltas of the fourth member of the Shahejie Formation. (<b>A</b>) The seismic profile along depositional dip. The dotted arrows indicate imbricated seismic reflections. (<b>B</b>) The seismic interpretation of the seismic profile in <a href="#sustainability-17-00208-f005" class="html-fig">Figure 5</a>A. (<b>C</b>) The sedimentary characteristics and interpretation of well G104. The dotted arrows indicate stratal geometries.</p>
Full article ">Figure 6
<p>RMS amplitude stratal slices (Ss49) and corresponding interpretations. (<b>A</b>) Relationship between lithology and impedance. (<b>B</b>) RMS amplitude stratal slice (Ss49) extracted in upper fourth member of Shahejie Formation; box in (<b>A</b>) represents ratio of sand to strata. (<b>C</b>) Interpretation of (<b>B</b>). (<b>D</b>) Well profile used to calibrate lithologies in (<b>B</b>).</p>
Full article ">Figure 7
<p>RMS amplitude stratal slices (Ss05) and corresponding sedimentary interpretations. (<b>A</b>) RMS amplitude stratal slice (Ss05) extracted in lower fourth member of Shahejie Formation; box in (<b>A</b>) represents ratio of sand to strata. (<b>B</b>) Interpretation of (<b>A</b>). (<b>C</b>) Well profile used to calibrate lithologies in (<b>B</b>).</p>
Full article ">Figure 8
<p>Paleotopographic features of the fourth member of the Shahejie Formation before deposition on the hanging-wall ramp of the Raoyang Sag. (<b>A</b>) A paleotopographic map. The red dotted curves indicate the boundaries of different tectonic units. The gray dotted lines indicate the five seismic profiles used to measure the original gradients. (<b>B</b>) The original seismic profile used to measure gradients. The location of the profile is shown in (<b>A</b>), marked in gray dotted lines, C-C′. (<b>C</b>) The seismic profile was flattened to T<sub>3</sub>. (<b>D</b>) A diagram illustrating the approach to gradient measurement. H<sub>1</sub> and H<sub>2</sub> indicate the decompacted stratal thickness of N56 and G108, respectively; L is the distance between the two wells, α is the slope angle, and S is the gradient. A-A’, B-B’, C-C’, D-D’, E-E’ are profiles used to measure slopes.</p>
Full article ">Figure 9
<p>Stratigraphic variations in major elements and trace elements in mudstones of fourth member of Shahejie Formation as indicators of environmental change. Data on 56 mudstone samples.</p>
Full article ">Figure 10
<p>Sporopollen characterization of fourth member of Shahejie Formation. (<b>A</b>) proportions of different types of vegetation; (<b>B</b>) Pie charts of vegetation proportions in different ecological environments. (<b>C</b>) I Radar map of vegetation proportions across different climatic zones.</p>
Full article ">Figure 11
<p>Depositional models of the lacustrine shallow-water deltas of the lower (<b>A</b>) and upper areas of the fourth member of the Shahejie Formation (<b>B</b>). a-a’, b-b’, c-c’ and d-d’ are profiles through different parts of the delta.</p>
Full article ">Figure 12
<p>Fluid trap types in the fourth member of the Shahejie Formation, Raoyang Sag, Bohai Bay Basin.</p>
Full article ">
Back to TopTop