Transport Mechanisms and Dynamics of Shales via Multiscale, Multiphysics Pore Network Modeling

2018 ◽  
Author(s):  
Saad Alafnan ◽  
I. Yucel Akkutlu
2020 ◽  
Vol 142 (9) ◽  
Author(s):  
Saad Alafnan ◽  
I. Yucel Akkutlu

Abstract Source rocks such as shale are highly heterogeneous, consisting of organic matter and various inorganic minerals. Microscopic images suggest that microcracks serve as conduits for the gas released from organic nanopores. The permeability of the shale matrix is primarily attributed to stress-sensitive microcracks that are highly influenced by changes in fluid pressure. As the microcracks are depleted, more gas molecules desorb from the organic nanopores; this, in turn, affects the fluid pressure in the microcracks. Linking the local properties of the organic nanopores to the microcracks allows for a better understanding of the coupling between them, which is necessary for improved modeling. In this research, a multiscale pore network modeling approach is presented to describe the organic material and microcrack system and investigate the large-scale features of gas transport in shale. A multiscale pore network model consisting of clusters of organic pore networks and microcracks was built to examine shale gas transport on a microscopic scale. The organic part of the network model consisted of nano-capillaries interconnected at nanopores. The network accounted for the adsorptive–convective–diffusive transport mechanisms recently derived for a single capillary. This organic nanopore network was hydraulically connected to a single microcrack. Then, the mass balance at each node in the new domain was solved, along with the assumed boundary conditions. Using the information at the nodes, the total flowrate and pressure distribution in the system were obtained as a function of time. The results show that the fluid pressure in the microcrack was primarily sensitive to the content of the organic material and its permeability. Then, the microcracks–organic materials interactions are studied and empirically quantified at larger macroscopic scale of gridblocks. This relationship can be investigated in the laboratory and used in theoretical models to predict shale gas production.


2011 ◽  
Vol 29 (17) ◽  
pp. 1803-1810 ◽  
Author(s):  
C. Z. Sun ◽  
H. Q. Jiang ◽  
J. J. Li ◽  
S. J. Ye

2021 ◽  
Author(s):  
Prakash Purswani ◽  
Russell T. Johns ◽  
Zuleima T. Karpyn

Abstract The relationship between residual saturation and wettability is critical for modeling enhanced oil recovery (EOR) processes. The wetting state of a core is often quantified through Amott indices, which are estimated from the ratio of the saturation fraction that flows spontaneously to the total saturation change that occurs due to spontaneous flow and forced injection. Coreflooding experiments have shown that residual oil saturation trends against wettability indices typically show a minimum around mixed-wet conditions. Amott indices, however, provides an average measure of wettability (contact angle), which are intrinsically dependent on a variety of factors such as the initial oil saturation, aging conditions, etc. Thus, the use of Amott indices could potentially cloud the observed trends of residual saturation with wettability. Using pore network modeling (PNM), we show that residual oil saturation varies monotonically with the contact angle, which is a direct measure of wettability. That is, for fixed initial oil saturation, the residual oil saturation decreases monotonically as the reservoir becomes more water-wet (decreasing contact angle). Further, calculation of Amott indices for the PNM data sets show that a plot of the residual oil saturation versus Amott indices also shows this monotonic trend, but only if the initial oil saturation is kept fixed. Thus, for the cases presented here, we show that there is no minimum residual saturation at mixed-wet conditions as wettability changes. This can have important implications for low salinity waterflooding or other EOR processes where wettability is altered.


2021 ◽  
Vol 143 (3) ◽  
pp. 106-114
Author(s):  
Zh.K. Akasheva ◽  
◽  
D.A. Bolysbek ◽  
B.K. Assilbekov ◽  
A.K. Yergesh ◽  
...  

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