Simulation and visualization of the displacement between CO2 and formation fluids at pore-scale levels and its application to the recovery of shale gas
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This article reports recent developments and advances in the simulation of the CO2-formation fluid displacement behaviour at the pore scale of subsurface porous media. Roughly, there are three effective visualization approaches to detect and observe the CO2-formation fluid displacement mechanism at the micro-scale, namely, magnetic resonance imaging, X-ray computed tomography and fabricated micromodels, but they are not capable of investigating the displacement process at the nano-scale. Though a lab-on-chip approach for the direct visualization of the fluid flow behaviour in nanoscale channels has been developed using an advanced epi-fluorescence microscopy method combined with a nanofluidic chip, it is still a qualitative analysis method. The lattice Boltzmann method (LBM) can simulate the CO2 displacement processes in a two-dimensional or three-dimensional (3D) pore structure, but until now, the CO2 displacement mechanisms had not been thoroughly investigated and the 3D pore structure of real rock had not been directly taken into account in the simulation of the CO2 displacement process. The status of research on the applications of CO2 displacement to enhance shale gas recovery is also analyzed in this paper. The coupling of molecular dynamics and LBM in tandem is proposed to simulate the CO2-shale gas displacement process based on the 3D digital model of shale obtained from focused ion beams and scanning electron microscopy.
KeywordsCO2-formation fluid displacement Micro- and nano-pore scale Shale gas recovery Lattice Boltzmann methods Molecular dynamics FIB-SEM
CO2, as one of the greenhouse gases, plays a key role in the cause of global warming, and its accumulation in the atmosphere is still increasing (Allen et al. 2014). As a result, CO2 mitigation has attracted increasing attention (Edenhofer et al. 2014). CO2 capture and sequestration (CCS) technology is an alternative to effectively reduce the CO2 emission in the short term (IEA 2013). Popularly, brine or saline aquifers, oceans, depleted oil reservoirs, and coal beds are considered potential geological formations for CO2 storage. For example, Fujii et al. (2010) and Zahid et al. (2011) argue that saline aquifers are the most viable alternative to store CO2 because they possess the greatest potential for carbon storage and wide geographical spread. Other studies suggest that CO2 is a working fluid that can be used to enhance oil recovery (EOR) and natural gas recovery (EGR) (Hughes et al. 2012; Liu et al. 2015a, b; Middleton et al. 2015). Injecting CO2 into oil or gas reservoirs is promising because it can also offset the costs of CCS (Koide et al. 1992; Blunt et al. 1993; Gunter et al. 1997). When CO2 is injected into a deep geological formation in the liquid or supercritical state, it will cause large volumes of formation fluids such as oil, water (brine) or natural gas to be physically displaced (Kazemifar et al. 2016; Wang et al. 2013; Zhang et al. 2011b). In the CO2 displacement process, the major concern is the primary CO2 plume migration, which is closely related to how much CO2 can be stored in the respective porous subsurface sedimentary formation, the displacement efficiency of the oil/gas and the security of the stored CO2 (Berg and Ott 2012; Chen and Zhang 2010; Song et al. 2014). Therefore, a better understanding of the displacement mechanisms of CO2 and formation fluids in porous media is essential to assess the CO2 leakage risks and predict the amount of CO2 that can be absorbed and the oil/gas production as well.
Predicting changes in the flow and transport properties of CO2 and formation fluids in porous rock is still a challenging issue owing to the multi-phase flow, complexity of the fluid–rock interactions and intrinsic heterogeneity of porous rocks (Garcia-Rios et al. 2015). Thus, the CO2 displacement process in porous media has attracted increasing attention. Extensive research on CO2 displacement has been performed over multiple spatial scales that range from a few nanometres to tens or hundreds of kilometres, and it is also clear that the appropriate methods to be employed vary between different scales. At the macro-scale, average properties must be employed, as an explicit description of the pore-scale phenomena is simply impossible. Additionally, the physical and chemical processes occur in discontinuous pore geometries and are controlled by interfacial processes, which have a large influence on the large-scale phenomena of the system and ultimately require a pore-scale perspective for obtaining a better understanding of the mechanisms (Blunt et al. 2013; Wildenschild and Sheppard 2013; Ferrari 2014; Morais et al. 2016). In the last decades, the pore-scale modelling of CO2-formation fluid displacement has been promoted by three factors: the recent advances in porous media characterizations by visualization techniques, some novel numerical theories, and advances in high-performance computing (Ferrari 2014). However, studies on the CO2-formation fluid displacement using these promising technical and theoretical approaches have not been systematically analysed in the published literature.
Thus, the objective of this contribution is to outline the recent developments and advances in the simulation and visualization of the CO2-formation fluid displacement process occurring at the micro-scale and nano-scale—also referred to here as the pore-scale—and to highlight perspectives for future research. In Sect. 2, some relevant important processes and characterizations of the CO2-formation fluid displacement are briefly discussed. In Sect. 3, several novel visualization techniques and numerical simulation methods for the CO2-formation fluid displacement are introduced in detail, including a discussion of their strengths and weaknesses. Finally, Sect. 4 provides a comprehensive overview of the applications of CO2 displacement to enhanced shale gas production including the status of research, challenges and possible solutions.
2 Characterizations of the CO2-formation fluid displacement
2.1 Viscous fingering
In porous media, viscous and capillary forces play key roles in impacting the CO2-formation fluid displacement. The injected CO2 viscosity is generally lower than that of formation fluids (Nordbotten et al. 2005), and the interfacial tension between the CO2 and formation fluids depends on the pressure, temperature, and other system conditions (Chiquet et al. 2007; Espinoza and Santamarina 2010). Two dimensionless parameters, namely, the capillary number (Ca) and viscosity ratio (M), are commonly employed to describe the various forces encountered by the two fluids during their displacement in the porous media. These two parameters are defined as
2.2 CO2–rock interaction
With a deep understanding of the CO2-formation fluid displacement process, the CO2–rock interactions intervene in more areas than initially anticipated, whereby certain areas have attracted less attention to date. When CO2 is injected into formations, scCO2 will dissolve, and interaction will occur between the CO2 and formation rock (Gaus 2010). As a consequence, these interactions will lead to changes in the pore structure of the formation rock, decreasing the porosity and permeability of the rock. These changes in the pore geometry of the formation rock will seriously impact the fluid transport in the CO2-formation fluid displacement. Thus, there are three key issues summarized in the review of Gaus (2010), that is, where do CO2–rock interactions occur, what are the drivers of CO2–rock interactions and what is their influence on the porosity and permeability, and how can the CO2–rock interactions be assessed.
3 Displacement simulation and visualization
3.1 Experimental visualization
Laboratory experiments on CO2-formation fluid displacement can provide valuable insights into processes that control the displacement process at the pore scale of porous media and improve our understanding of multi-phase flow. Pore-scale experiments also permit the evaluation of the constitutive relationships that are used in large-scale simulators (Dehoff et al. 2012). Roughly, there are three main visualization approaches to detect and observe CO2 displacement processes at the pore scale: magnetic resonance imaging (MRI), X-ray computed tomography (CT) (Shi et al. 2009, 2011a, b; Zhao et al. 2011a; Alemu et al. 2013; Berg et al. 2013b) and fabricated micromodels (Ferer et al. 2004; Cottin et al. 2010; Zhang et al. 2011a; Wang et al. 2013; Al-Housseiny et al. 2012). These methods are recognized as effective approaches to directly characterize the transport properties of the displaced fluid and displacing fluid at the pore scale.
3.1.1 X-ray CT
However, based on previous studies, the front fingering and the mixing zone of the displacement process can only be qualitatively analysed by the CT imaging and cannot be quantified. Moreover, the microscopic fluid state cannot be detected using medical CT scanners owing to the insufficiently high resolution (millimetre-scale) compared with the pore sizes, which could make the results of the experiments less credible. The resolution of nano-CT (50 nm)is high, but it takes a long time to collect one image unless fast synchrotron-based sources are used.
Summary of results for CO2/water displacement experiments of Song et al. (2012)
Effective porosity (%)
Flow rate (mL/min)
Visual displacement process
Displacement efficiency (%)
Although a number of studies have been conducted to investigate the CO2-formation fluid displacement in a sand pack using MRI, and some CO2-formation fluid displacement mechanisms have been clearly analyzed, there have been almost no studies on natural rocks owing to the harsh conditions of MRI against the experimental materials. As the geometry of the natural rock sample is more complex than that of the sand packs, the reliability achieved for the previous experimental results can be compromised.
3.1.3 Fabricated micromodels
The rock cores have an advantage in characterizing individual formations, but on the pore scale, the fluid flow is difficult to monitor since sophisticated and unique micro-tomographic facilities are needed to visualize the internal distribution of the fluids within the rock cores. The natural media also presents other challenges in that the porosity, pore size, connectivity, and wetting properties are unable to be independently manipulated. These limitations can be overcome by micromodels, which allow for the visualization of the fluid distribution using cameras with or without fluorescence microscopy. The subsequent quantification of the fluid transport and interfacial area may provide mechanistic insight into the physical fluid displacement process at the microscopic level. Experimental studies on the CO2-formation fluid displacement have been widely conducted in 2D micromodels to reveal the mechanisms of the fluid displacement.
Er et al. (2010) investigated the porous matrix and fracture interaction during CO2 injection into a glass micromodel initially saturated with oil, demonstrating the importance of the CO2–oil interaction near the matrix-fracture interface. Chalbaud et al. (2009) visualized the scCO2 displacement of water in glass micromodels, but the saturations of the fluids could not be quantified owing to difficulties in distinguishing between the fluids. Riazi et al. (2011) simulated CO2-oil and CO2-water displacement processes in an etched glass micromodel, and the results showed a faster CO2 breakthrough in the micromodel saturated with oil than that with water. The above studies were all limited to qualitative visualizations of the fluid flow during the displacement process, and quantitative information about the interfacial areas and fluid saturations was not acquired. The study of Zhang et al. (2011b) was the first to quantitatively evaluate the influence of the capillary forces and porous media heterogeneity on the liquid CO2-water displacement in a dual-permeability pore network micromodel using fluorescence microscopy. Wang et al. (2013) simulated the effects of the injection rates and injection methods on the scCO2 displacement of water in a homogeneous micromodel, and the results of the simulation are quantitatively compared using the obtained fluorescent images. Kazemifar et al. (2016) quantified the flow dynamics of the scCO2 displacement of water in a 2D porous micromodel by combining fluorescence microscopy and microscopic particle image velocimetry (PIV).
Unfortunately, micromodels lack the complex geometry of real media, which often have multiscale and random characteristics that will dictate the fluid and solute transport. In addition, these experimental studies used simple two-dimensional porous media. To overcome the above limitations, Ju et al. (2014a) incorporated several advanced technologies, such as CT scan, three-dimensional (3D) reconstruction (Gomi et al. 2007; Geiger et al. 2009; Hajizadeh et al. 2011; Zhang et al. 2013; Birk et al. 2014; Ju et al. 2014b), and 3D printing, to produce a physical model representing the natural rock. A 3D digital image can be obtained to represent the real rock structure based on the high-resolution X-ray CT imaging and the reconstruction, and then its three-dimensional micromodel using transparent material can be generated using a 3D printer. This novel idea offers a very good opportunity to accurately investigate the properties of complex flows.
These experimental simulation methods greatly promote our understanding of the CO2-formation fluid displacement mechanism. However, it is worth noting that these simulation experiments are performed based on the pore geometric characteristics of a convention formation that has a minimum pore size on the micrometre scale. The pore sizes and pore throat radii of unconventional gas reservoirs range from 1 to 300 nm, which are much smaller than those of conventional reservoirs with pore sizes in the range of 1–100 μm (Cipolla et al. 2009). These popular experimental simulation methods are thus not able to investigate fluid flow at the nano-metre scale because the maximum precision of these techniques is on the micro-meter scale in general. Special characteristic features that can be produced at the nanometre scale include a high capillary pressure, low porosity, and high wetting phase residue saturation (Wu 2014). Other transportation mechanisms may also occur. The displacements of two-phase flow in nano-pores are poorly understood. Wu (2014) developed a lab-on-chip approach for the direct visualization of the fluid flow behaviour in nanoscale channels using an advanced epi-fluorescence microscopy method combined with a nanofluidic chip. This method is expected to improve the understanding of the CO2 displacement behaviour on the nano-scale. However, it is still a qualitative analysis method and cannot quantifiably reflect the displacement process.
3.2 Numerical simulation
A large number of the porous media studies on fluid displacement have been numerically performed, and numerical simulations can provide an economical and efficient pathway to explore the influences of the flow and physical parameters in various complicated porous media. Pore-scale simulations provide a level of information on flow characteristics that cannot be obtained in laboratory experiments, for example, the full pressure and velocity fields and the position of the interface. Modelling approaches of multiphase flow at the pore scale can be divided into two categories: direct simulations, in which the flow equations are directly solved on a discretized pore space obtained from images of rock cores, and network modelling, in which simplified flow equations are solved in an idealized pore network extracted from the real geometry (Blunt et al. 2013).
Since the first pioneering work (Fatt 1956), pore network models have been widely used to simulate multi-phase fluid flow at the pore scale. However, the validity of the pore network models is always limited by the approximations and simplifications used (Ferrari and Lunati 2013). Many pore network models may not be suited for the simulation of multiphase fluid flow in complex porous media (Crawshaw and Boek 2013). One of the most popular approaches is the lattice Boltzmann method (LBM), in which particles move and collide on a discrete lattice in such a way that the average motion of the particles mimics the solution of the Navier–Stokes equations (Shan and Chen 1993; He and Luo 1997). Since the late 1980s, the LBM has emerged as a powerful tool for numerical simulations and investigations of a broad class of complex flows. The LBM can be considered as a mesoscopic method, occupying the middle ground between the microscopic molecular dynamics and macroscopic fluid dynamics. Unlike pore-network models, which use a simplified representation of the pore geometry and approximate transient flow with a steady-state Poiseuille law, LBM can simulate complex multiphase flows in pore media with natural pore geometries (Bandara et al. 2013). The basic idea of the LBM is to construct simplified kinetic models that incorporate the essential physics of microscopic or mesoscopic processes to ensure that the macroscopic averaged properties obey the desired macroscopic equations (Ghassemi and Pak 2011). LBM has many advantages over the conventional grid-based computational fluid dynamics (CFD) methods, such as volume-of-fluid (VOF) and level-set (LS) methods, especially in handling complex boundaries, flexible reproducing interfaces, incorporating the microscopic interactions between multiple phases, and the parallelisation of the algorithm (Liu et al. 2015a).
Based on the above analysis, at present, the numerical simulation of the CO2 displacement in porous media is mainly performed using the LBM, and few studies use conventional methods to simulate the displacement process. Gunde et al. (2010) investigated the displacement of oil by CO2 within the pore structures of a realistic porous geometry (730 μm × 450 μm) derived from processed micro-CT images based on the finite element method. However, the COMSOL simulations require a minimum of 48 h of CPU time to obtain a converged solution for a 10 s displacement process. Berg and Ott (2012) used the phenomenological two-phase extension of Darcy’s law to study the stability of CO2-brine immiscible displacement in a two/three-dimensional numerical grid. They found that the capillarity, viscosity ratio, gravity and length scales have effects on the stability of the displacement.
From the above review, we see that only a limited number of numerical simulation studies have been reported focusing on fundamental processes at the microscopic pore scale during CO2 injection into a porous formation. These studies also did not systematically investigate the CO2 displacement mechanisms. During the CO2 flow in saline aquifers or oil/gas reservoirs, the main physical and chemical interactions among the water, oil/gas and rocks include (Ju et al. 2013): (1) the immiscible and miscible displacement of oil, water and CO2; (2) convection and diffusion; (3) the phase change and behaviour of insitu fluids in flow and mass transfer; (4) precipitation/dissolution and its effects on porosity and permeability; (5) the CO2 adsorption characteristics in the adsorption of the reservoir. Therefore, in further work, these interactions need to be considered. In addition, although there have been a few studies on the use of LBM for the simulation of the CO2 displacement process in 3D porous media, the 3D pore structure of real rock has not been used. The main reason is that attaining an accurate description of the 3D microstructure of porous rock is difficult, laborious, time-consuming, and economically expensive with the use of advanced 3D CT measurement techniques, e.g., synchrotron X-ray CT (Coker et al. 1996; Spanne et al. 1994), and directly using the 3D microstructure of porous rock for the numerical simulations will entail a massive computational cost. Recently, Ju et al. (2014b) proposed a faster, more accurate, and more efficient reconstruction algorithm (an improved simulated annealing algorithm reconstruction method) to create a 3D model of the porous rock microstructure. On the other hand, the appearance and application of modern high-performance computers offer a new way to study complex flows in a domain with realistic pore geometries.
4 Applications in shale gas
4.1 Special properties of shale reservoirs
4.1.1 Nanopore structure
4.1.2 Knudsen flow
4.1.3 Adsorption and desorption
4.2 LB-MD multiscale method
Molecular dynamics (MD) simulation is an effective method to study complex flows at the nanoscale (Li et al. 2010). In MD simulations, the fluid behaviour is described by the motion of the individual particles interacting with each other via intermolecular potentials (Koplik and Banavar 1995). As a result, it is only suitable to simulate fluid behaviours at the nanoscale owing to the limitation of computation cost (Zhao et al. 2016). LBM, as an intermediate method between continuum and atomistic simulations, is considered to have tremendous potential for simulating the fluid flow at the meso-scale, and detailed information on it has been presented in Sect. 2.2. However, the interaction force between the fluid and rock is assumed to be directly proportional to the density of the fluid in conventional LB models, which has no theory to support it and does not represent the real physical phenomena in certain situations (Liu et al. 2015a, b). To combine the advantages of the two described methods, coupling the LBM and MD is proposed to simulate fluid flows. MD describes the atomistic recognition of the fluid flow process near the walls of the porous media, while LBM is responsible for the rest of the simulation process and decreases the computational cost (Marsh et al. 2010). Combinations of the LB and MD methods can be divided into two categories. The first type is the synchronous coupling of the two methods performed by Ahlrichs and Dünweg (1998, 1999) and Fyta et al. (2006). In their studies, the simulation of the motion of DNA, polymers and other macromolecules in water was performed by the method. However, such a synchronous calculation method is very time-consuming for the simulation of fluid flow in porous media owing to the large computation cost of parameter passing between MD and LBM. The second type is the coupling of MD and LB in tandem to settle a problem, rather than simultaneous coupling (Marsh et al. 2010; Choi et al. 2014; Liu et al. 2015a, b; Pereira et al. 2016). MD provides the atomistic recognition of the flow physics near the walls, while LBM describes the rest of the simulation domain (including the Knudsen flow and absorption/dissolution-induced pore structure changes) and substantially reduces the computational cost.
First, the interaction forces between CO2–CH4 are obtained from the P–R EOS calculation (Liu et al. 2015a, b), and the shale matrix–CO2/CH4 interaction (including the displacement of adsorbed CH4 by CO2 and the interaction force of fluids-shale) is acquired from the MD simulation. According to the MD simulation, we can calculate the interfacial tension of CO2/CH4, the density of CO2/CH4 and the concentration of CO2/CH4. Then, we run the lattice Boltzmann simulation based on the 3D digital core of shale to obtain the real and whole CO2–CH4 displacement process.
CO2-formation fluid displacement at the pore scale is a key issue in CO2 sequestration and enhanced oil/gas recovery. The current situation and limitations of experiments and numerical simulations in studying the CO2-formation fluid displacement at the pore scale are described in detail. From the review, we can conclude that there are many influencing factors for CO2 displacement at the pore scale, e.g., displacement type, effective porosity, flow rate, Ca and M. The use of MRI or X-ray CT and the observation of the fluid displacement in fabricated micromodels are recognized as effective approaches to detect and observe the CO2-formation fluid displacement processes. The LBM can precisely simulate the CO2-formation fluid displacement processes in a 2D or 3D complex pore structure, but at the present, realistic rock pore geometries are not used directly to simulate the displacement process based on LBM. Various enhancements to overcome the limitations of experiments and numerical simulations in studying the CO2-formation fluid displacement are suggested. Applications of CO2 displacement have been highlighted for shale gas production. Therefore, the status of research and challenges in the application of CO2 displacement to enhanced shale gas production are reviewed in the paper. Then, the coupling of MD and LB in tandem is proposed to simulate the CO2-shale gas displacement process in the 3D images of shale obtained by an FIB-SEM device.
The authors gratefully acknowledge the financial support of the National Natural Science Foundation of China (Grant Nos. 51374213 and 51674251), the State Key Research Development Program of China (Grant No. 2016YFC0600705), the National Natural Science Fund for Distinguished Young Scholars of China (Grant No. 51125017), the Fund for Innovative Research and Development Group Program of Jiangsu Province (Grant No. 2014-27), the Science Fund for Creative Research Groups of the National Natural Science Foundation of China (Grant No. 51421003), and the Priority Academic Program Development of the Jiangsu Higher Education Institutions (PAPD 2014).
- Allen SK, Plattner GK, Nauels A, Xia Y, Stocker TF (2014) Climate change 2013: the physical science basis. An overview of the working group 1 contribution to the fifth assessment report of the intergovernmental panel on climate change (IPCC). In: EGU General Assembly Conference, vol 16. EGU general assembly conference abstractsGoogle Scholar
- Chalmers GR, Bustin RM, Power IM (2012a) Characterization of gas shale pore systems by porosimetry, pycnometry, surface area, and field emission scanning electron microscopy/transmission electron microscopy image analyses: examples from the Barnett, Woodford, Haynesville, Marcellus, and Doig units. AAPG Bull 96:1099–1119CrossRefGoogle Scholar
- Chen C, Zhang D (2010) Pore-scale simulation of density-driven convection in fractured porous media during geological CO2 sequestration. Water Resour Res 46(11):275–284Google Scholar
- Cipolla CL, Lolon E, Mayerhofer MJ (2009) Reservoir modeling and production evaluation in shale-gas reservoirs. In: International petroleum technology conferenceGoogle Scholar
- Curtis JB (2002) Fractured shale-gas systems. AAPG Bull 86:1921–1938Google Scholar
- Edenhofer O, Pichsmadruga R, Sokana Y (2014) Climate change 2014: mitigation of climate change. Contribution of working group III to the fifth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, United Kingdom and New YorkGoogle Scholar
- Espinoza DN, Santamarina JC (2010) Water-CO2-mineral systems: interfacial tension, contact angle, and diffusion-implications to CO2 geological storage. Water Resour Res 46(7)Google Scholar
- Fatt I (1956) The network model of porous media. Pet Trans AIME 207:144–181Google Scholar
- Ferer M, Ji C, Bromhal GS, Cook J, Ahmadi G, Smith DH (2004) Crossover from capillary fingering to viscous fingering for immiscible unstable flow: experiment and modeling. Phys Rev E 70(2):127–150Google Scholar
- Ferrari A (2014) Pore-scale modeling of two-phase ow instabilities in porous media. University of Torino, TurinGoogle Scholar
- Fujii T, Gautier S, Gland N, Boulin P, Norden B, Schmidt-Hattenberger C (2010) Sorption characteristics of CO2 on rocks and minerals in storing CO2 processes. Nat Resour 1(1):1–10Google Scholar
- Huang F, Lu YY, Tang JR, Ao X, Jia YZ (2015) Research on erosion of shale impacted by supercritical carbon dioxide jet. Chin J Rock Mech Eng 34(4):787–794 (in Chinese) Google Scholar
- IEA (2013) Technology roadmap: carbon capture and storage. http://www.iea.org/publications/freepublications/publication/technology-roadmap-carboncapture-and-storage-2013.html
- King GE (2010) Thirty years of gas shale fracturing: what have we learned. In: SPE annual technical conference and exhibition, Florence, SPE, p 133456Google Scholar
- Li X, Feng Z, Han G, Elsworth D, Marone C, Saffer D (2015) Hydraulic fracturing in shale with H2O, CO2 and N2. In: US rock mechanics/geomechanics symposiumGoogle Scholar
- Marsh DD, Vanka SP, Marsh DD, Vanka SP (2010) Multiscale MD/LBM simulations of flow in complex nano/micro channels. In: ASME 2010 international mechanical engineering congress and exposition, pp 735–742Google Scholar
- Rogala A, Ksiezniak K, Krzysiek J, Hupka J (2014) Carbon dioxide sequestration during shale gas recovery. Physicochem Probl Miner Process 50(2):681–692Google Scholar
- Seo JG (2004) Experimental and simulation studies of sequestration of supercritical carbon dioxide in depleted gas reservoirs. Texas A&M University, College StationGoogle Scholar
- Sondergeld CH, Newsham KE, Comisky JT, Rice MC, Rai CS (2010) Petrophysical considerations in evaluating and producing shale gas resources. In: SPE unconventional gas conference, Society of Petroleum EngineersGoogle Scholar
- Wellington SL, Vinegar HJ (1985) CT studies of surfactant-induced CO2 mobility control. In: SPE annual technical conference and exhibition, SPE-14393-MSGoogle Scholar
- Wu Q (2014) Investigation of fluids flow behavior in nano-scale channels by using optic imaging system. Missouri University of Science and Technology, RollaGoogle Scholar
- Zhang X, Xiao L, Shan X, Guo L (2014) Lattice boltzmann simulation of shale gas transport in organic nano-pores. Sci Rep 4(6183):536–538Google Scholar
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