Multiscale and multiphysics inﬂuences on ﬂuids in unconventional reservoirs: Modeling and simulation

Cai, Jianchao; Wood, David А.; Hajibeygi, Hadi; Iglauer, Stefan

doi:10.46690/ager.2022.02.01

Cited by 32 publications

(12 citation statements)

References 18 publications

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“…The laboratory core experimental methods can measure the meso-scale transport properties while the detailed pore scale gas transport process is not available (Tian et al, 2022). Therefore, it is essential to study pore scale shale gas transport mechanisms and establish the corresponding flow simulation method (Cai et al, 2022). This work highlights the recent findings on understanding gas transport mechanisms in shale gas reservoir by pore network model (PNM).…”

Section: Main Textmentioning

confidence: 96%

Understanding gas transport mechanisms in shale gas reservoir: Pore network modelling approach

Song

Jun

Zhang

et al. 2022

Adv. Geo-Energy Res.

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Section: Main Textmentioning

confidence: 96%

Understanding gas transport mechanisms in shale gas reservoir: Pore network modelling approach

Song

Jun

Zhang

et al. 2022

Adv. Geo-Energy Res.

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“…The current important development trend and direction is to establish a 3D digital core including minerals and a spatial distribution of pores−throats on the basis of the above characterization, which lays the foundation for a series of problems such as simulating the flow and distribution of fluids in the pore space. 88,89 Usually digital core construction methods are divided into two categories: (1) the physical experiment method, that is, using physical methods to scan the core and using an image processing algorithm to directly build a three-dimensional digital core; 90,91 (2) the numerical reconstruction method, that is, nanometer CT, SEM technology, and the MCMC method are used to reconstruct 3D digital cores. 92 The advantage of reconstructing 3D digital cores by the physical method is to approximate the actual sample, but the outstanding problem lies in the contradiction between the imaging accuracy and the sample analysis size (view field).…”

Section: Challenges and Perspectivesmentioning

confidence: 99%

“…It can be seen that the comprehensive application of the above-mentioned techniques can effectively characterize the size, distribution, and connectivity of pore–throats and mineral compositions of shales. The current important development trend and direction is to establish a 3D digital core including minerals and a spatial distribution of pores–throats on the basis of the above characterization, which lays the foundation for a series of problems such as simulating the flow and distribution of fluids in the pore space. , …”

Section: Challenges and Perspectivesmentioning

confidence: 99%

Research Progress of Microscopic Pore–Throat Classification and Grading Evaluation of Shale Reservoirs: A Minireview

Xiao

et al. 2022

Energy Fuels

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The grading evaluation of shales helps in understanding the shale reservoir formation and sweet-spot screening of physical properties. Reservoir formation of shale is closely related to the size, distribution, and connectivity of shale pore−throats. Therefore, characterization and classification of microscopic pore−throats are the basis for shale reservoir grading. However, previous microscopic pore−throat classification schemes for materials science are unsuitable for shales with strong heterogeneity. In recent years, the author's team has proposed a new classification method for microscopic pore−throats of shale reservoirs based on the comprehensive characterization of numerous shales with varied maturities in different basins. Results show that the microscopic pore−throats for all shales can be divided into micropores, small pores, mesopores, and macropores. The component, size, and distribution of microscopic pore−throats in shales in different basins differ due to the differences in mineral composition and diagenetic evolution of shales caused by varying depositional environments and burial histories. Correspondingly, the demarcation points of different types of pore−throats are different. After clustering statistical analysis of different types of microscopic pore−throats, shales can be divided into grade I, II, III, and IV reservoirs, regarded as good, medium, poor, and nonshale reservoirs, respectively. Grading evaluation criteria for shale reservoirs were then established. Further, a new technique for evaluating the reservoir flow zone index (FZI) and dividing flow units based on logging data was constructed using the relationship of permeability with porosity in the same hydraulic flow unit. The grading evaluation criteria can be applied to single wells, multiwells, and planes using logging data. The application in numerous shale oil and gas exploration areas in China shows that the established classification scheme can be applied to the grading evaluation and sweet-spot screening of shale reservoirs.

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“…Pore-scale fluid flow experiment is an effective method to investigate the transport mechanisms and distribution characteristics of residual oil, including microfluidics [5][6][7][8], natural sandstone models [9][10][11][12][13], nuclear magnetic resonance [14][15][16], confocal laser [17][18][19], and CT scan [20][21][22]. Owing to the rapid development of CT technology, it has been widely used in EOR [23][24][25][26][27], carbon dioxide storage [28], environmental governance [29], water-rock interaction [30,31], reservoir modelling [32][33][34][35][36], hydraulic conductivity [37,38], and reservoir evaluation [39][40][41][42][43][44][45][46][47]. Due to the advantages of high resolution, nondestructive, and in situ, CT scan has become an effective method for investigating residual oil.…”

Section: Introductionmentioning

confidence: 99%

Effects of Wettability and Minerals on Residual Oil Distributions Based on Digital Rock and Machine Learning

Zhang

Lin

et al. 2022

Lithosphere

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The wettability of mineral surfaces has significant impacts on transport mechanisms of two-phase flow, distribution characteristics of fluids, and the formation mechanisms of residual oil during water flooding. However, few studies have investigated such effects of mineral type and its surface wettability on rock properties in the literature. To unravel the dependence of hydrodynamics on wettability and minerals distribution, we designed a new experimental procedure that combined the multiphase flow experiments with a CT scan and QEMSCAN to obtain 3D digital models with multiple minerals and fluids. With the aid of QEMSCAN, six mineral components and two fluids in sandstones were segmented from the CT data based on the histogram threshold and watershed methods. Then, a mineral surface analysis algorithm was proposed to extract the mineral surface and classify its mineral categories. The in situ contact angle and pore occupancy were calculated to reveal the wettability variation of mineral surface and distribution characteristics of fluids. According to the shape features of the oil phase, the self-organizing map (SOM) method, one of the machine learning methods, was used to classify the residual oil into five types, namely, network, cluster, film, isolated, and droplet oil. The results indicate that each mineral’s contribution to the mineral surface is not proportional to its relative content. Feldspar, quartz, and clay are the main minerals in the studied sandstones and play a controlling role in the wettability variation. Different wettability samples show various characteristics of pore occupancy. The water flooding front of the weakly water-wet to intermediate-wet sample is uniform, and oil is effectively displaced in all pores with a long oil production period. The water-wet sample demonstrates severe fingering, with a high pore occupancy change rate in large pores and a short oil production period. The residual oil patterns gradually evolve from networks to clusters, isolated, and films due to the effects of snap-off and wettability inversion. This paper reveals the effects of wettability of mineral surface on the distribution characteristics and formation mechanisms of residual oil, which offers us an in-deep understanding of the impacts of wettability and minerals on multiphase flow and helps us make good schemes to improve oil recovery.

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Multiscale and multiphysics inﬂuences on ﬂuids in unconventional reservoirs: Modeling and simulation

Cited by 32 publications

References 18 publications

Understanding gas transport mechanisms in shale gas reservoir: Pore network modelling approach

Understanding gas transport mechanisms in shale gas reservoir: Pore network modelling approach

Research Progress of Microscopic Pore–Throat Classification and Grading Evaluation of Shale Reservoirs: A Minireview

Effects of Wettability and Minerals on Residual Oil Distributions Based on Digital Rock and Machine Learning

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