Fractal Characteristics and Model Applicability for Pores in Tight Gas Sandstone Reservoirs: A Case Study of the Upper Paleozoic in Ordos Basin

Abstract

Thirty-eight samples from tight sandstone reservoir in the upper Paleozoic layer of Ordos Basin, China were examined. The micropore structure of the reservoir was observed by casting thin sections, which were analyzed via scanning electron microscopy. The pore size distribution characteristics of the reservoir were studied via high-pressure mercury injection. The fit of five different models to the fractal characteristics of the tight gas sandstone reservoir were analyzed, and the fractal characteristics of pores in tight sandstone reservoirs were further revealed. Pores were divided into microscale macropores (P 1 ) (>10 μm), microscale micropores (P 2 ) (1−10 μm), submicron pores (P 3 ) (100 nm−1 μm), and nanopores (P 4 ) (2−100 nm). The results show that P 2 account for 63.24% of the total pore volume in type I reservoirs. P 3 are dominant in type II reservoirs, accounting for 51.74% of the total pore volume. Type III reservoirs are mainly composed of P 3 and P 4 , accounting for 48.96% and 41.88% of pore volume, respectively. In type IV reservoirs, P 4 is the main pore size followed by P 3 , accounting for 54.98% and 36.96%, respectively. The Brooks−Corey model can characterize the pore fractal characteristics of the tight sandstone reservoir effectively, while other models presented some limitations. The evaluation of fractal characteristics showed that the three-segment fractal fitting curve was closely related to the inflection point of the S Hg /P c −S Hg curve. The fractal dimensions of P 1 , P 2 , P 3 , and P 4 were 2.904−2.998, 2.384−2.999, 2.155−2.951, and 2.151−2.911, with average values of 2.9826, 2.951, 2.69, and 2.604, respectively. The correlation between the stage pore fractal dimensions and reservoir parameters showed that the fractal dimensions of P 3 and P 4 better reflected the complexity of the pore throats and were more suitable for pore throat heterogeneity characterization. In tight gas sandstone reservoirs, porosity shows relatively low sensitivity to fractal dimensions, while permeability is controlled by the fractal dimensions of P 1 to a great extent. Thus, reservoirs featuring regular macropores are favorable target areas for oil and gas filling.

Coupling Effect of Temperature, Gas, and Viscoelastic Surfactant Fracturing Fluid on the Microstructure and its Fractal Characteristics of Deep Coal

“…For mercury injection in porous materials, a correlation between the amount of mercury intake and the pore surface energy and a thermodynamic fractal model are proposed. , Specifically, in the process of mercury injection, the amount of mercury intake gradually increases with the increase of pressure, causing a continuous increase in pore surface energy. , The relation of the increment of mercury feed and pore surface energy is expressed in eq − where W is the pore surface energy, J; γ L is the surface tension between mercury and pore surface, J/m; θ is the contact angle between mercury and pore surface, (°); and S is the pore surface area, m 2 .…”

“…According to the fractal theory, the expression containing the thermodynamic pore fractal dimension D r is estimated by correlating the pore surface area S of the porous media with the pore diameter r with the precondition that the total pore volume V is larger than this pore diameter − where p i is the pressure of the i -th intake, Pa; Δ V i is the volume of the i -th intake, m 3 ; r n is the radius of the pore corresponding to the n -th intake operation, m; V n is the total volume of the intake, m 3 ; C ′ is a constant; and D r is the fractal dimension.…”

“…Equation can be simplified to the equation − Taking the logarithm of both sides of eq − where C n is a constant. According to the experimental data measured by the MIP, a bilogarithmic plot is constructed.…”

Oil utilization degree at various pore sizes via different displacement methods

“…The short components of T 2 generally respond to pores with smaller sizes, and the long components of T 2 respond to large pores in tight reservoirs (Wu et al 2018). Using this method, the pores can be divided into microscale macropores (> 10 μm), microscale micro-pore (1-10 μm), submicro-pores (0.1-1 μm) and nanopores (< 0.1 μm) (Hu et al 2020). The submicropores contribute to oil displacement efficiency, whereas the nanopores contribute to oil displacement via spontaneous imbibitions (Cheng et al 2019).…”

“…If the fractal dimension was approximately 3, the porosity and permeability of the tight reservoir would decrease significantly (Wang et al 2021). The fractal dimensions of submicro-pores and nanopores commonly reflect the complexity of the pores, and the fractal dimensions of the microscale macropores feature significantly influence the permeability of tight reservoirs (Hu et al 2020). The fractal dimension of partially movable pores and completely movable pores contributes to enhancement of the oil displacement (Wu et al 2020;Wang et al 2021).…”