Laboratory simulation of CO<sub>2</sub> immiscible gas flooding and characterization of seepage resistance

doi:10.1007/s11707-022-1074-2

Front. Earth Sci.

2023, Vol. 17

Issue (3) : 797-817 https://doi.org/10.1007/s11707-022-1074-2

RESEARCH ARTICLE

Laboratory simulation of CO₂ immiscible gas flooding and characterization of seepage resistance

Jie CHI¹(

), Binshan JU^2,³, Wenbin CHEN^2,³, Mengfei ZHANG¹, Rui ZHANG⁴, Anqi MIAO⁴, Dayan WANG⁴, Fengyun CUI⁴

¹. School of Big Data and Fundamental Sciences, Shandong Institute of Petroleum and Chemical Technology, Dongying 257061, China
². School of Energy Resources, China University of Geosciences (Beijing), Beijing 100083, China
³. Key Laboratory of Geological Evaluation and Development Engineering of Unconventional Natural Gas Energy, Beijing 100083, China
⁴. School of Chemical Engineering, Shandong Institute of Petroleum and Chemical Technology, Dongying 257061, China

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Abstract

CO₂ flooding can significantly improve the recovery rate, effectively recover crude oil, and has the advantages of energy saving and emission reduction. At present, most domestic researches on CO₂ flooding seepage experiments are field tests in actual reservoirs or simulations with reservoir numerical simulators. Although targeted, the promotion is poor. For the characterization of seepage resistance, there are few studies on the variation law of seepage resistance caused by the combined action in the reservoir. To solve this problem, based on the mechanism of CO₂, a physical simulation experiment device for CO₂ non-miscible flooding production manner is designed. The device adopts two displacement schemes, gas-displacing water and gas-displacing oil, it mainly studies the immiscible gas flooding mechanism and oil displacement characteristics based on factors such as formation dip angle, gas injection position, and gas injection rate. It can provide a more accurate development simulation for the actual field application. By studying the variation law of crude oil viscosity and start-up pressure gradient, the characterization method of seepage resistance gradient affected by these two factors in the seepage process is proposed. The field test is carried out for the natural core of the S oilfield, and the seepage resistance is described more accurately. The results show that the advancing front of the gas drive is an arc, and the advancing speed of the gas drive oil front is slower than that of gas drive water; the greater the dip angle, the higher the displacement efficiency; the higher the gas injection rate is, the higher the early recovery rate is, and the lower the later recovery rate is; oil displacement efficiency is lower than water displacement efficiency; taking the actual core of S oilfield as an example, the mathematical representation method of core start-up pressure gradient in low permeability reservoir is established.

Keywords laboratory simulation viscosity starting pressure gradient CO₂ immiscible flooding characterization of seepage resistance

Corresponding Author(s): Jie CHI

Online First Date: 17 November 2023 Issue Date: 12 December 2023

Cite this article:

Jie CHI,Binshan JU,Wenbin CHEN, et al. Laboratory simulation of CO₂ immiscible gas flooding and characterization of seepage resistance[J]. Front. Earth Sci., 2023, 17(3): 797-817.

URL:

https://academic.hep.com.cn/fesci/EN/10.1007/s11707-022-1074-2
https://academic.hep.com.cn/fesci/EN/Y2023/V17/I3/797

Fig.1 Experimental supplies.

Tab.1 Model parameters

Fig.2 the schematic diagram of the experimental apparatus for measuring permeability.

Tab.2 gravel permeability data

Groups	1	2	3
?V (cm³)	3.3	4.5	3.8
V1 (cm³)	12	16	13
$?$	0.275	0.281	0.292

Tab.3 Experimental data of gravel porosity

Tab.4 Experimental Scheme

Tab.5 Gas flooding inclination angle of water 30° gas injection velocity 5.0 cm³/s data

Tab.6 Gas flooding inclination angle of water 45° gas injection velocity 5.0 cm³/s data

Tab.7 Gas flooding inclination angle of water 30° gas injection velocity 7.7 cm³/s data

Fig.3 Physical simulation of carbon dioxide flooding.

Fig.4 Gas driving water of gas flooding front.

Fig.5 Different strata dip angle and recovery degree.

Fig.6 Different gas injection velocity and recovery degree.

Tab.8 Gas drive oil dip angle 30° gas injection velocity 5.0 cm³/s data

Tab.9 Gas drive oil dip angle 45° gas injection velocity 5.0 cm³/s data

Tab.10 Gas drive oil dip angle 30° gas injection velocity 7.7 cm³/s data

Fig.7 Relationship between different gas injection velocities and recovery degree at 30° dip angle of formation.

Fig.8 Relationship between different dip angles of strata and recovery degree when gas injection rate is 5 cm³/s.

Fig.9 Experimental process diagram.

Fig.10 Experimental effect diagram.

Fig.11 Typical low velocity non-Darcy seepage characteristic curve (Si, 2006).

Fig.12 Distribution of effective pressure gradient between injection and production wells.

Fig.13 distribution and utilization of effective pressure gradient between injection and production wells (ΔP₁ < ΔP₂ < ΔP₃).

Fig.14 Starting pressure gradient versus permeability curve (Huang, 1998).

Fig.15 tart pressure gradient and permeability double logarithmic relationship (Lv et al., 2002).

Fig.16 Relationship between crude oil viscosity and starting pressure gradient (Sun et al., 2010).

Fig.17 Double logarithmic relationship between starting pressure gradient and flow rate (Yang et al., 2010).

Fig.18 Non-Darcy flow characteristic curve of core 1.

Fig.19 Non-Darcy flow characteristic curve of core 2.

Fig.20 Non-Darcy flow characteristic curve of core 3.

Fig.21 Non-Darcy flow characteristic curve of core 4.

Fig.22 Non-Darcy flow characteristic curve of core 5.

Fig.23 Curves of relationship between starting pressure gradient and permeability.

Fig.24 Double logarithmic curve of starting pressure gradient and fluidity.

Fig.25 Starting pressure gradient and permeability double logarithmic curve.

Fig.26 Distribution of displacement pressure gradient (absolute value G) on main flow line between injection and production wells in low permeability reservoir.

Fig.27 Relationship curve between starting pressure gradient and fluidity.

K—fluid measuring permeability, μm²;

Q—liquid flow, cm³/s;

L—height of gravel filled, cm;

A—section area, cm²;

ρ—fluid density, kg/cm³;

g—acceleration of gravity, m/s²;

μ—liquid viscosity, mPa?s;

h—discharge head, m;

?—porosity, %;

μ T 1

—Viscosity of crude oil at pressure 1 atm, temperature T₁, mPa?s;

μ T 2

—Viscosity of crude oil at pressure 1 atm, temperature T₂, mPa?s;

μ₁—Viscosity of crude oil at pressure of 1 atm (0.101MPa), mPa?s;

μ₂—Viscosity of crude oil at pressure p, mPa?s;

A_T—Proportion coefficient of temperature and crude oil density;

γ—crude oil density, kg/cm³;

R_s—solubility, g;

T—temperature, °C;

P—pressure, pa;

V—volume fraction;

α—Empirical coefficients of temperature, pressure and crude oil density;

F_S—inflation factor;

F C O 2

—the ratio of CO₂ volume under standard condition to the volume under reservoir temperature and pressure;

F_o—the ratio of the volume of crude oil under reservoir temperature and 0.1MPa pressure to the volume under reservoir temperature and reservoir pressure;

τ_ο—Yield stress of formation crude oil, N/m²;

r_H—Oil supply radius of well area, m;

R_w—Effective oil supply radius, m;

F—the utilization degree of movable oil;

A—drainage area, m²;

Δ p Δ L

—Effective displacement pressure gradient, MPa/m;

n—Fitting index;

τ o

—Shearing stress, MPa;

C—Fluid component content, %.

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