Investigation of pore geometry influence on fluid flow in heterogeneous porous media: A pore-scale study

Soltanmohammadi, Ramin; Iraji, Shohreh; Rodrigues de Almeida, Tales; Basso, Mateus; Ruidiaz Munoz, Eddy; Campane Vidal, Alexandre

doi:10.1016/j.engeos.2023.100222

Cited by 35 publications

(8 citation statements)

References 30 publications

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“…Prior research on single-phase flow in porous media has indicated that the distribution of water flow becomes nonuniform upon complete saturation of the porous structures. Certain regions within the system do not facilitate the movement, leading to a reduction in the inherent permeability of the porous structure. , It was suggested that the significant variation in the pore size distribution might be responsible for this phenomenon. Using a visualization setup, we were able to identify stationary areas and analyze the morphological properties that contribute to the presence of stagnant regions.…”

Section: Resultsmentioning

confidence: 99%

“…Permeable rocks are desirable reservoirs because they allow for the efficient flow of oil and gas through their pores, facilitating the extraction of these resources from the subsurface . Additionally, permeability plays a crucial role in determining the relative effectiveness of different oil recovery methods. , Intrinsic permeability is solely determined by the characteristics of the medium itself and is affected by the microscopic structure of its pores. − The evaluation of the complex nature of the microscopic pore structure entails an analysis of various properties, including the distribution of pore sizes, the distribution of pore throat sizes, the connectivity of pores, and the geometry of individual pores. Every single morphological component has been shown to affect the permeability.…”

Section: Introductionmentioning

confidence: 99%

“…To overcome these limitations, pore-scale measurements have gained popularity in recent years. These measurements can be conducted through micromodel flooding experiments or pore network modeling simulations. ,− Microscale approaches operate at a scale that is similar to the dimensions of the pores in an actual porous medium. These methods account for the influence of pore geometry and are applicable for visualizing flow in single or multiple phases. ,, Building upon this approach, Vogel and Roth found, using 3D pore network modeling, that the shape and connectivity of the pores in the pore space are both critical factors.…”

Section: Introductionmentioning

confidence: 99%

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Real-Time Pore-Scale Investigation of the Effects of Uniform, Random, and Heterogenous Porous Structures on Intrinsic Permeability Using Two-Dimensional Microfluidic Chips

Boumedjane,

Al-Maamari,

Rabbani

et al. 2024

Energy Fuels

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Permeability is a significant fluid flow property that is essential for the evaluation of oil recovery methods. The intrinsic permeability of a porous medium is influenced by factors such as the size distribution of pores and pore throats, the connectivity between pores, the topology of the pores, and the geometry of individual pores. Yet, it is not well understood how multiple elements of pore geometry interact to affect permeability due to the complex and heterogeneous nature of porous structures. This study examines the real-time porescale effects of uniform, random, and heterogeneous porous structures on intrinsic permeability, considering the broader complexity of the pore network as a single unit. The intrinsic permeability exhibited a negative correlation with increasing heterogeneity of the porous structure regardless of whether the porosities were the same or different. At a porosity of 0.59, the uniform pattern exhibited a permeability of 4.07 Darcy, while the heterogeneous pattern had a permeability of 2.37 Darcy. The random pattern demonstrated greater permeability (2.57 Darcy) at a lower porosity (0.47) in comparison to that of the heterogeneous network. Pore-scale experiments and simulations have demonstrated the significant influence of the pore network topology on the intrinsic permeability. As the complexity and heterogeneity of porous structures increase, the combined effect of morphological characteristics on intrinsic permeability becomes more significant than the individual influence of each morphological property. The differences in permeability observed in the experiments were attributed to the presence of stagnant water zones, which could be permanent or temporary. Stagnant water is more likely to be permanent in homogeneous patterns than in heterogeneous patterns. Heterogeneity appeared to promote water movement and redistribution because of variations in local pressure due to variations in pore sizes. The presence of dead-end pores in the random pattern led to a slight fluctuation in the experimental permeability. However, this effect was more prominent in the simulated permeability. Our study found experimental and numerical evidence that the broader heterogeneity of the porous structure significantly impacts permeability. Moreover, it highlights the importance of accounting for the actual microscopic porous structure of the reservoir being targeted when microfluidic devices are employed for enhanced oil recovery techniques.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Real-Time Pore-Scale Investigation of the Effects of Uniform, Random, and Heterogenous Porous Structures on Intrinsic Permeability Using Two-Dimensional Microfluidic Chips

Boumedjane,

Al-Maamari,

Rabbani

et al. 2024

Energy Fuels

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“…Reservoirs with low permeability and porosity are distinct due to their constrained pore spaces and fluid flow capabilities [24][25][26][27]. At present, scholars have used advanced CT imaging technology and machine learning algorithms to study fluid flow in complex, non-uniform, porous, low-permeability media [28][29][30]. This nature inherently complicates numerical computations for production rates [31].…”

Section: Introductionmentioning

confidence: 99%

Post-Fracture Production Prediction with Production Segmentation and Well Logging: Harnessing Pipelines and Hyperparameter Tuning with GridSearchCV

Sun,

Wang,

Wang

et al. 2024

Applied Sciences

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As the petroleum industry increasingly exploits unconventional reservoirs with low permeability and porosity, accurate predictions of post-fracture production are becoming critical for investment decisions, energy policy development, and environmental impact assessments. However, despite extensive research, accurately forecasting post-fracture production using well-log data continues to be a complex challenge. This study introduces a new method of data volume expansion, which is to subdivide the gas production of each well on the first day according to the depth of logging data, and to rely on the correlation model between petrophysical parameters and gas production to accurately combine the gas production data while matching the accuracy of the well-log data. Twelve pipelines were constructed utilizing a range of techniques to fit the regression relationship between logging parameters and post-fracture gas production These included data preprocessing methods (StandardScaler and RobustScaler), feature extraction approaches (PCA and PolynomialFeatures), and advanced machine learning models (XGBoost, Random Forest, and neural networks). Hyperparameter optimization was executed via GridSearchCV. To assess the efficacy of diverse models, metrics including the coefficient of determination (R2), standard deviation (SD), Pearson correlation coefficient (PCC), mean absolute error (MAE), mean squared error (MSE), and root-mean-square error (RMSE) were invoked. Among the several pipelines explored, the PFS-NN exhibited excellent predictive capability in specific reservoir contexts. In essence, integrating machine learning with logging parameters can be used to effectively assess reservoir productivity at multi-meter formation scales. This strategy not only mitigates uncertainties endemic to reservoir exploration but also equips petroleum engineers with the ability to monitor reservoir dynamics, thereby facilitating reservoir development. Additionally, this approach provides reservoir engineers with an efficient means of reservoir performance oversight.

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“…At present, micro-CT imaging [10][11][12], mercury injection capillary pressure (MICP) [13][14][15] and nuclear magnetic resonance (NMR) [16][17][18][19] experiments, as methods capable of accurately reflecting micro-to-nano scale pore features, are extensively employed for microscopic porosity studies in tight reservoirs. All techniques have certain limitations.…”

Section: Introductionmentioning

confidence: 99%

Utilizing Differences in Mercury Injection Capillary Pressure and Nuclear Magnetic Resonance Pore Size Distributions for Enhanced Rock Quality Evaluation: A Winland-Style Approach with Physical Meaning

Gu,

Wang,

Guo

et al. 2024

Applied Sciences

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Pore structure is a fundamental parameter in determining the hydrocarbon storage capacity and flow characteristics of a reservoir. Mercury injection capillary pressure (MICP) and nuclear magnetic resonance (NMR) are two commonly utilized techniques for characterizing rock pore structures. However, current studies indicate that disparities in testing methodologies due to distinct physical characteristics lead to a partial misalignment in pore size distributions. We conducted MICP (dynamic) and NMR (static) experiments on eight tight sandstone and eight shale samples and proposed a method to utilize information from the differences in MICP and NMR pore size distributions, aiming to enhance the accuracy of rock quality analysis. We observed that in rock cores where large pores are interconnected with smaller pore throats, MICP tends to overestimate the proportion of these smaller pores and underestimate the larger ones. Furthermore, we integrated information from both dynamic and static experimental processes based on physical significance and found that the fitting accuracy of the newly proposed method is superior to the Winland r35 equation. Compared to the Winland r35 equation, our new method significantly improves fitting accuracy, increasing the R-squared value from 0.46 to 0.93 in sandstones and from 0.80 to 0.87 in shales. This represents a potential high-precision, comprehensive tool for rock quality analysis, offering a new perspective for an in-depth understanding of rock properties.

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Investigation of pore geometry influence on fluid flow in heterogeneous porous media: A pore-scale study

Cited by 35 publications

References 30 publications

Real-Time Pore-Scale Investigation of the Effects of Uniform, Random, and Heterogenous Porous Structures on Intrinsic Permeability Using Two-Dimensional Microfluidic Chips

Real-Time Pore-Scale Investigation of the Effects of Uniform, Random, and Heterogenous Porous Structures on Intrinsic Permeability Using Two-Dimensional Microfluidic Chips

Post-Fracture Production Prediction with Production Segmentation and Well Logging: Harnessing Pipelines and Hyperparameter Tuning with GridSearchCV

Utilizing Differences in Mercury Injection Capillary Pressure and Nuclear Magnetic Resonance Pore Size Distributions for Enhanced Rock Quality Evaluation: A Winland-Style Approach with Physical Meaning

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