Reconstruction of 3D porous media using multiple-point statistics based on a 3D training image

Wu, Yuqi; Lin, Chengyan; Liu, Ren; Yan, Weibo; An, Senyou; Chen, Bingyi; Wang, Yang; Zhang, Xianguo; Chunmei, You; Zhang, Yimin

doi:10.1016/j.jngse.2017.12.032

Cited by 59 publications

(32 citation statements)

References 54 publications

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“…There are both advantages and disadvantages to every technique. A detailed literature review of these methods is discussed elsewhere (Tahmasebi & Sahimi, 2012;Wu, Lin, Ren, Yan, An, et al, 2018a). In our study, we modified the conventional QSGS that was developed by Wang et al (2007).…”

Section: Quartet Structure Generation Setmentioning

confidence: 99%

Pore‐Scale 3D Dynamic Modeling and Characterization of Shale Samples: Considering the Effects of Thermal Maturation

Tahmasebi

et al. 2020

JGR Solid Earth

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The development of shale gas necessitates accurate modeling and characterization of these complicated formations, at both small and large scales. At the small scale, the studies based on experimental techniques have uncovered that the components and pore types in shales vary dramatically. Several pore types are identified and varied when the thermal maturation of shales changes. Therefore, accurate modeling and characterization of shale samples require taking such dynamic variations into consideration. This study presents a novel, dynamic, and three-dimensional (3D) modeling technique considering pore-system variation when the thermal maturation changes. The technique can construct dynamic shale models based on quartet structure generation set algorithm and morphological operation. This method can include various elements available in the shale samples in a very accurate way when the dynamic processes are reproduced. To evaluate the performance of the presented technique, 12 dynamic 3D shale models of three cases are constructed. These models are then characterized by analyzing the fractions of components and pores, pore and throat size distributions, coordination number distribution, fractal dimension, and tortuosity. Besides, gas transport in these dynamic 3D shale models is also simulated using pore network modeling to demonstrate the permeability variation of these models. Moreover, the fractions of interparticle and intraparticle pores and cementation degree are changed to further illustrate the capability of the developed algorithm. This study reveals such a dynamic modeling technique is a robust tool to construct various porous media with complicated elements and pores, which is not limited to shale samples. Key Points:• A novel, dynamic, and three-dimensional modeling technique considering pore-system evolution was presented • Generated shale models were characterized by analyzing the geometric, topological, and transport properties of pore systems • The simulation of the gas flow in shale models considers the viscous flow, Knudsen diffusion, and surface diffusion Correspondence to:

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Section: Quartet Structure Generation Setmentioning

confidence: 99%

Pore‐Scale 3D Dynamic Modeling and Characterization of Shale Samples: Considering the Effects of Thermal Maturation

Tahmasebi

et al. 2020

JGR Solid Earth

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“…Monte Carlo (MCMC) Method. In 2004, the MCMC reconstruction method was proposed by Wu et al, who applied this technique to the 2D reconstruction of soil structure [149]. In 2006, Wu et al extended the 2D digital core-reconstruction method into three dimensions and proposed an MCMC-based 3D digital corereconstruction method [150].…”

Section: Markov Chainmentioning

confidence: 99%

“…In 2017, Peng [173] established a digital core of a shale reservoir by using the MPS method and concluded that the MPS method can effectively reconstruct large-scale digital cores of shale reservoirs by evaluating the function and permeability results. In 2018, Wu et al [149] combined the MPS method with 3D digital core data to reconstruct a more accurate digital core.…”

Section: Markov Chainmentioning

confidence: 99%

Challenges and Prospects of Digital Core-Reconstruction Research

et al. 2019

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The simulation of various rock properties based on three-dimensional digital cores plays an increasingly important role in oil and gas exploration and development. The accuracy of 3D digital core reconstruction is important for determining rock properties. In this paper, existing 3D digital core-reconstruction methods are divided into two categories: 3D digital cores based on physical experiments and 3D digital core stochastic reconstructions based on two-dimensional (2D) slices. Additionally, 2D slice-based digital core stochastic reconstruction techniques are classified into four types: a stochastic reconstruction method based on 2D slice mathematical-feature statistical constraints, a stochastic reconstruction method based on statistical constraints that are related to 2D slice morphological characteristics, a physics process-based stochastic reconstruction method, and a hybrid stochastic reconstruction method. The progress related to these various stochastic reconstruction methods, the characteristics of constructed 3D digital cores, and the potential of these methods are analysed and discussed in detail. Finally, reasonable prospects are presented based on the current state of this research area. Currently, studies on digital core reconstruction, especially for the 3D digital core stochastic reconstruction method based on 2D slices, are still very rough, and much room for improvement remains. In particular, we emphasize the importance of evaluating functions, multiscale 3D digital cores, multicomponent 3D digital cores, and disciplinary intersection methods in the 3D construction of digital cores. These four directions should provide focus, alongside challenges, for this research area in the future. This review provides important insights into 3D digital core reconstruction.

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“…Figure shows the pore size distribution for the 3D printed real samples #1, # 4, #7 and the equivalent computationally-generated samples #9, #11, #15. In this paper, we considered pore size instead of average void diameter, as the former parameter captures better the local features of the 3D pore network [39]. It can be seen that the computationally generated samples have a more homogeneous pore size distribution than the real samples.…”

Section: Comparison Between Computationally-generated and Real 3d Primentioning

confidence: 99%

Virtual Asphalt to Predict Roads’ Air Voids and Hydraulic Conductivity

Aboufoul¹,

Chiarelli²,

Triguero³

et al. 2018

Preprint

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This paper investigates the effects of air void topology on hydraulic conductivity in asphalt mixtures with porosity in the range 14%-31%. Virtual asphalt pore networks were generated using the Intersected Stacked Air voids (ISA) method, with its parameters being automatically adjusted by the means of a differential evolution optimisation algorithm, and then 3D printed using transparent resin. Permeability tests were conducted on the resin samples to understand the effects of pore topology on hydraulic conductivity. Moreover, the pore networks generated virtually were compared to real asphalt pore networks captured via X-ray Computed Tomography (CT) scans. The optimised ISA method was able to generate realistic 3D pore networks corresponding to those seen in asphalt mixtures in term of visual, topological, statistical and air void shape properties. It was found that, in the range of porous asphalt materials investigated in this research, the high dispersion in hydraulic conductivity at constant air void content is a function of the average air void diameter. Finally, the relationship between average void diameter and the maximum aggregate size and gradation in porous asphalt materials was investigated.

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Reconstruction of 3D porous media using multiple-point statistics based on a 3D training image

Cited by 59 publications

References 54 publications

Pore‐Scale 3D Dynamic Modeling and Characterization of Shale Samples: Considering the Effects of Thermal Maturation

Pore‐Scale 3D Dynamic Modeling and Characterization of Shale Samples: Considering the Effects of Thermal Maturation

Challenges and Prospects of Digital Core-Reconstruction Research

Virtual Asphalt to Predict Roads’ Air Voids and Hydraulic Conductivity

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Reconstruction of 3D porous media using multiple-point statistics based on a 3D training image

Cited by 59 publications

References 54 publications

Pore‐Scale 3D Dynamic Modeling and Characterization of Shale Samples: Considering the Effects of Thermal Maturation

Pore‐Scale 3D Dynamic Modeling and Characterization of Shale Samples: Considering the Effects of Thermal Maturation

Challenges and Prospects of Digital Core-Reconstruction Research

Virtual Asphalt to Predict Roads&rsquo; Air Voids and Hydraulic Conductivity

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Virtual Asphalt to Predict Roads’ Air Voids and Hydraulic Conductivity