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Obtainable recovery vs. water accessible pore volumes. Comparative test where ω = αβ∆s is constant for 5 values: ω i =0.025, 0.06, 0.15 (base), 0.4 and 1 (i=1,..,5). O and W denote POW and PWW sets. Parameters α, β, ∆s are varied in 20 tests. ω seems to characterize the flow regime of the fracture-matrix system. Unspecified parameters are given by reference case.

Obtainable recovery vs. water accessible pore volumes. Comparative test where ω = αβ∆s is constant for 5 values: ω i =0.025, 0.06, 0.15 (base), 0.4 and 1 (i=1,..,5). O and W denote POW and PWW sets. Parameters α, β, ∆s are varied in 20 tests. ω seems to characterize the flow regime of the fracture-matrix system. Unspecified parameters are given by reference case.

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The flow of oil and water in naturally fractured reservoirs (NFR) can be highly complex and a simplified model is presented to illustrate some main features of this flow system. NFRs typically consist of low-permeable matrix rock containing a high-permeable fracture network. The effect of this network is that the advective flow bypasses the main po...

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... We make a number of variations of the base case to obtain 5 different values of omega: ω 1 , ω 2 , ..., ω 5 . For each fixed ω i we vary parameters like α, β, and saturation flow functions (POW, PWW) to take into account different flow scenarios. The values of ω differ roughly by a factor of 2.5 between adjacent groups. The results are shown in Fig. 13. For comparison the results are plotted as fraction of obtainable recovery, R/R ∞ (where obtainable recovery is R ∞ = 1+β∆s 1+β(1−s m 0 ) ) vs injected water-accessible reservoir pore volumes (WARPVs) (τ f /(1 + β∆s)). The reason for this visualization is that if no water leaves until all possible imbibition has occurred and the ...

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... The imbibition of conventional reservoirs has been studied extensively in recent years. A large number of studies have shown that imbibition in tight oil reservoirs is one of the important driving forces for crude oil recovery [4][5][6]. The spontaneous imbibition induced by capillary force is especially remarkable because the pore size is in micron or even nanometer range [7]. ...
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... x(t) actual imbibition length, m N r cumulative number of pores D f fractal parameter of pore size, dimensionless A d total pore area, m 2 β comparison of d min /d max , dimensionless P i imbibition pressures, MPa P f displacement pressure, MPa P c capillary pressure, MPa P π osmotic pressure in clay, MPa P g gas pressure of free gas, MPa P g0 initial gas pressure, MPa P a increased gas pressure from the desorption of adsorbed gas, MPa V im , V c fluid loss in shale gas well, shale sample, m 3 x f fracture half-length, m h reservoir thickness, m η m , η o , η c area ratio of fragile mineral, organic matter and clay mineral, per unit area, % φ, φ m , φ o , φ c total porosity and the surface porosity in fragile mineral, organic matter, clay mineral, % 2020; Zarringhalam et al., 2019;Rostami et al., 2020), the lattice Boltzmann method (LBM) (Arabjamaloei and Ruth, 2014;Warda et al., 2017;Zheng et al., 2018), pore network models (PNMs) (Øren et al., 1998;Øren and Bakke, 2003;Sorbie and Skauge, 2012;Zhou et al., 2012;Sun et al., 2016;Li et al., 2017;Qin and Brummelen, 2019;Qin et al., 2021a), and continuum models (Schmid and Geiger, 2012;Andersen et al., 2014;Jabbari et al., 2019). However, MD and LBM cannot be applied on a large scale and longtime interval (Wang and Zhao, 2019); PNM is complex with enormous amounts of data and is difficult to use in the descriptive combination of pore structures and hydrodynamic processes (Li and Zhao, 2012), and current continuum models lack the analysis of spontaneous imbibition mechanisms in shale gas wells (Wang and Zhao, 2019). ...
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Spontaneous imbibition is the main factor that reduces the fracturing efficiency and damages gas production in shale gas wells, which is regulated by the gas–water interaction. Water (fracturing fluid) is imbibed spontaneously due to the characteristics of the water–rock interface, especially in shale with micro–nano–scale pores, while imbibition is not impeded but prevented by the pore structure resistance and original free gas compression as well as the increased fraction from the desorption of adsorbed gas. To accurately predict the fluid loss in a shale gas reservoir during fracturing, the imbibition pressures of the gas–water phase were comprehensively analyzed in this study, and the increased gas pressure from the desorption of adsorbed gas was first considered with other imbibition pressures, such as gas pressure from free gas compression, displacement pressure, capillary pressure, and osmotic pressure. By substituting the gas–water phase pressures into the Lucas–Washburn equation with the fractal characteristic of the capillary bundle, an imbibition model for micro–nano-scale pores in shale gas reservoirs considering gas–water interaction is established. The proposed model is compared with the traditional imbibition models and verified through imbibition experiments, and a case application to a shale gas well in the Sichuan Basin is undertaken. The results prove that the new fractal imbibition model performs better than the other models for imbibition estimation in reservoir shale, and it can accurately predict the fluid loss during the hydraulic fracturing process for shale gas wells.