Method for simulating deep shale gas flow based on dual-site langmuir adsorption model

Patent metadata

Field	Value
Publication number	US-2026044654-A1
Application number	US-202519293600-A
Country	US
Kind code	A1
Filing date	Aug 7, 2025
Priority date	Aug 8, 2024
Publication date	Feb 12, 2026
Grant date	—

Abstract

A method for simulating deep shale gas flow based on a dual-site Langmuir adsorption model is provided. The method includes: reconstructing a digital core of a deep shale gas reservoir, and extracting a pore network model; analyzing a structural parameter of the pore network model, and establishing calculation models of a free-phase shale gas conductivity and an adsorption-phase shale gas conductivity; establishing a calculation model of a shale gas conductivity for pores and throats in the pore network model, and determining the shale gas conductivity in pores and throats in the pore network model; combining the pore network model with the calculation models of the free-phase shale gas conductivity, the adsorption-phase shale gas conductivity and the shale gas conductivity in pores and throats, establishing a simulation model of a deep shale gas conductivity and simulating a flow law of deep shale gas.

First claim

What is claimed is:

1 . A method for simulating deep shale gas flow based on a dual-site Langmuir adsorption model, comprising:
step 1, reconstructing a digital core and extracting a pore network model based on a core scanning image of a deep shale gas reservoir; step 2, analyzing a structural parameter of the pore network model, setting a pore structural property, establishing a calculation model of a free-phase shale gas conductivity and a calculation model of an adsorption-phase shale gas conductivity, and determining the free-phase shale gas conductivity and the adsorption-phase shale gas conductivity in the pore network model; step 3, establishing a calculation model of a shale gas conductivity for pores and throats in the pore network model according to the calculation model of the free-phase shale gas conductivity and the calculation model of the adsorption-phase shale gas conductivity, and determining shale gas conductivity for the pores and throats in the pore network model to obtain shale gas conductivities in organic pores, inorganic pores, organic pores and throats and inorganic pores and throats; step 4, based on the calculation model of the free-phase shale gas conductivity, the calculation model of the adsorption-phase shale gas conductivity and the calculation model of the shale gas conductivity for the pores and throats in the pore network model, establishing a simulation model of a deep shale gas conductivity in combination with the pore network model, and determining a flow law of deep shale gas under different sensitivity parameter conditions by using the simulation model of the deep shale gas conductivity for simulation.

2 . The method for simulating the deep shale gas flow based on the dual-site Langmuir adsorption model according to claim 1 , wherein in step 1, the core scanning image of the deep shale gas reservoir is obtained, a binary image is obtained by performing binary segmentation on the core scanning image, after a pore phase and a matrix phase in the binary image are identified, the digital core is reconstructed by using a Markov Chain Monte Carlo method according to a binary segmented image, and the pore network model is extracted by using a maximum sphere method.

3 . The method for simulating the deep shale gas flow based on the dual-site Langmuir adsorption model according to claim 2 , wherein the core scanning image is a Computed Tomography (CT) scanning image or a Scanning Electron Microscope (SEM) scanning image of the core.

4 . The method for simulating the deep shale gas flow based on the dual-site Langmuir adsorption model according to claim 1 , wherein in step 2, analyzing structural parameters of the pore network model comprises: determining a pore radius, a throat radius, a coordination number and a shape factor of the pore network model, assigning water-wet inorganic pores and gas-wet organic pores in the pore network model, wherein shale gas comprising free-phase shale gas and adsorption-phase shale gas is provided in the pore network model, and the adsorption-phase shale gas is single-layer adsorption in the pore network model.

5 . The method for simulating the deep shale gas flow based on the dual-site Langmuir adsorption model according to claim 4 , wherein for the free-phase shale gas in the pore network model, when the adsorption-phase shale gas exists, an effective migration space of the free-phase shale gas in the organic pores is reduced to obtain:

θ
=

p
Z

p
L

+

p
Z

,

(
1
)

h
=

θ
⁢

d
m

,

(
2
)

r
eff

=

r
-

d
m

⁢
θ

,

(
3
)

where θ denotes a gas coverage degree on surface of a pore and throat; p denotes a pressure of the pore and throat in unit of MPa; p L denotes a Langmuir pressure in unit of MPa; Z denotes a gas compressibility factor; h denotes a thickness of an adsorption phase in unit of m; d m denotes a collision diameter of gas molecules in unit of m; r eff denotes an effective flow radius of the free-phase shale gas in unit of m; r denotes a cross-sectional radius of the pore and throat in unit of m;
taking into account an influence of high-temperature and high-pressure environment on a critical temperature and a critical pressure of the shale gas in the pore network model, a gas property of the free-phase shale gas in the pore network model changes;
the critical temperature and the critical pressure of the shale gas in the pore network model are calculated as follows:

T
c

=

8

27
⁢
bR

[

a
-

2
⁢

σ
3

⁢
ε
⁢

Assignees

• Univ China Petroleum East China

Inventors

• Yang Yongfei
• Yao Jun
• Zhao Chaoyang
• Zhang Kai
• Sun Hai
• Zhong Junjie
• Zhang Lei
• Li Jiawei
• Li Haoyun
• Liu Tonghui

Classifications

• G06F30/20

  Design optimisation, verification or simulation (optimisation, verification or simulation of circuit designs G06F30/30) · CPC title

• G06F2111/10

  Numerical modelling · CPC title

• G06F2113/08

  Fluids · CPC title

• G06F30/28 Primary

  using fluid dynamics, e.g. using Navier-Stokes equations or computational fluid dynamics [CFD] · CPC title

• G06F2119/14

  Force analysis or force optimisation, e.g. static or dynamic forces · CPC title