Digital imaging technology-based method for calculating relative permeability of tight core

Abstract

The invention discloses a digital imaging technology-based method for calculating relative permeability of tight core, comprising the following steps: step S1: preparing a small column sample of tight core satisfying resolution requirements; step S2: scanning the sample by MicroCT-400 and establish a digital core; step S3: performing statistical analysis on parameters reflecting the characteristics of rock pore structure and shape according to the digital core; step S4: calculating tortuosity fractal dimension DT and porosity fractal dimension Df by a 3D image fractal box dimension algorithm; step S5: performing statistical analysis on maximum pore equivalent diameter λmax and minimum pore equivalent diameter λmin by a label. The present invention solves the problems of time consumption of experiment, instrument accuracy, incapability of repeated calculation simulations and resource waste by repeated physical experiment.

Description

BACKGROUND TECHNOLOGY

Technical Field

The invention relates to the field of analysis of microphysical properties of tight rock, in particular to a digital imaging technology-based method for calculating relative permeability of tight core.

Description of Related Art

The tight reservoir is currently the focus of research on the development of unconventional oil and gas resources, with great commercial value. The flow of oil and gas in low-permeability tight reservoir is often accompanied by non-Darcy flow. In order to effectively characterize the effect of non-Darcy flow at low speed, the threshold pressure gradient is introduced. Due to the low permeability and the threshold pressure gradient, the measurement of relative permeability curve takes a long time and has poor accuracy. Therefore, it is very critical to establish a method for calculating relative permeability with consideration of low permeability characteristics of porous media.

For the tight reservoir, there are two ways to obtain the permeability curve. One is the displacement experiment, and the other is the theoretical calculation. Due to the low permeability of tight reservoirs, it takes a long time to obtain the relative permeability curve by the displacement experiment, takes a long time to stabilize the flow rate, and requires high accuracy of measuring instruments. The theoretical calculation method is divided into two types: the steady displacement method and the dynamic displacement method. They are calculated based on steady Darcy's law and unsteady JBN theory. Neither the steady method nor the dynamic method considers the influence of rock morphological characteristics (such as rock internal structure and pore distribution) on the relative permeability curve. The calculated permeability curve is often quite different from the measured curve. Therefore, it is necessary to consider the influence of the threshold pressure gradient and the capillary force, and combine the characteristics of the rock pore structure to find a calculation method suitable for the low-permeability tight rock.

SUMMARY

In order to solve the problems in the prior art, the present invention provides a digital imaging technology-based method for calculating relative permeability of tight core to solve the problems.

The technical solution employed in the present invention is a digital imaging technology-based method for calculating relative permeability of tight core, including the following steps:

• • Step S1: preparing a small column sample of tight core satisfying resolution requirements;
  • Step S2: scanning the sample by MicroCT-400 and establishing a digital core;
  • Step S3: performing statistical analysis on parameters reflecting rock pore structures and shape characteristics according to the digital core;
  • Step S4: calculating a tortuosity fractal dimension D_T and a porosity fractal dimension D_f by a 3D image fractal box dimension algorithm;
  • Step S5: performing statistical analysis on maximum pore equivalent diameter λ_max and minimum pore equivalent diameter λ_min by a label;
  • Step S6: simulating a water-oil displacement in single fractal capillary, calculating a critical capillary diameter λ_cr, and obtaining the critical capillary diameter at a displacement time t;
  • Step S7: determining a fluid type at an outflow end with the critical capillary diameter, calculating a water-phase fluid volume V_w and a pore volume V_p in the tight core at the time t, and then calculating a water saturation S_w of the core;
  • Step S8: calculating a flow rate Q_s of a single phase flow;
  • Step S9: simulating the water-oil displacement in the low-permeability tight core, and calculating the oil phase flow rate Q_o and water phase flow rate Q_w at the outflow end at the time t;
  • Step S10: calculating the relative permeability k_rw of water phase and the relative permeability k_ro of oil phase at the displacement time t;
  • Step S11: changing the time t and judging whether the water saturation S_w remains unchanged; if so, go to Step S12; if not, return to Step S6; and
  • Step S12: plotting a relative permeability curve.

Preferably, the tight core mentioned in Step S1 is 5 to 10 mm in diameter, and greater than 10 mm in length.

Preferably, Step S2 includes the following sub-steps:

• • Step S21: performing CT scanning with appropriate lens and reconstruct 3D image data according to a size of the core;
  • Step S22: defining and selecting Region of Interest (ROI) in 3D image data; and
  • Step S23: performing filtering and threshold segmentation on ROI to obtain 3D digital core of pore structure distribution.

Preferably, the 3D image fractal box dimension algorithm mentioned in Step S4 comprises the following sub-steps:

• • Step S41: based on the graph statistics parameters obtained in Step S3, drawing N(r)˜r diagram in log-log coordinates and a negative slope of the line is the value of fractal dimension D_f,lgN(r)=lga−D_flgr;

where, D_f is porosity fractal dimension, r is pore equivalent diameter, N(r) is the number of pores with radius greater than r, a is a constant coefficient; Step S42: the porosity φ of the core is obtained by image statistics and the average tortuosity is calculated by the following formula:

$\tau =\frac{1}{2}\left[1+\frac{1}{2}\sqrt{1-\phi }+\sqrt{1-\phi }\sqrt{{\left(\frac{1}{\sqrt{1-\phi }}-1\right)}^2+\frac{1}{4}}/\left(1-\sqrt{1-\phi }\right)\right];$

where, τ is tortuosity, φ is porosity; and

• • Step S43: calculating the tortuosity fractal dimension D_T by the following formula:

$D_T=1+\frac{\ln \tau }{\ln \left(\frac{L_m}{2r_{\mathrm{av}}}\right)};$

where, D_T is the tortuosity fractal dimension, r_av is a mean pore radius, L_m is a characteristic length obtained by:

$L_m=\sqrt{\frac{1-\phi }{\phi }\frac{\pi D_f{r}_{\max }^2}{2-D_f}};$

where, r_max is a maximum pore radius.

Preferably, Step S6 comprises the following sub-steps:

• • Step S61: at a given time t, for a single capillary with the capillary equivalent diameter λ≥λ_cr, determining that there is only single-phase water flow, and the fluid at the outflow end is water;
  • Step S62: for a single equivalent capillary with the capillary equivalent diameter λ <λ_cr, determining that there is oil and water flow, and the fluid at the outflow end is oil; and
  • Step S63: dividing the capillary in the porous medium into two parts for analysis: the single capillary with λ≥λ_cr, and the single capillary with λ<λ_cr.

Preferably, the calculation formula of the critical capillary diameter mentioned in Step S6 is:

${\lambda }_{\mathrm{cr}}^{2D_T}+4{\lambda }_{\mathrm{cr}}^{2D_T-1}\frac{\delta \cos \theta }{\Delta p}-\frac{{\lambda }_{\mathrm{cr}}^{D_T+1}{J}_o{L}^{D_r}}{\Delta p}-\frac{16\left({\mu }_w+{\mu }_o\right)L^{2D_T}}{\Delta pt}=0;$

where, Jo is threshold pressure gradient of oil phase, δ is surface tension; θ is contact angle, μw is water phase viscosity, μo is oil phase viscosity, λcr is critical capillary diameter, Δp is pressure difference between the two ends of the core, t is time, in s, L is core length, and DT is tortuosity fractal dimension.

Preferably, the calculation formula of water phase volume Vw in Step S7 is:

$V_w=-{\int }_{{\lambda }_{\min }}^{{\lambda }_{\mathrm{cr}}}\frac{{\mathrm{\pi \lambda }}^2}{4}{X}_T\mathrm{dN}-{\int }_{{\lambda }_{\mathrm{cr}}}^{{\lambda }_{\max }}\frac{{\mathrm{\pi \lambda }}^2}{4}{L}_T\mathrm{dN}.$

The calculation formula of pore volume Vp is:

$V_P=-{\int }_{{\lambda }_{\min }}^{{\lambda }_{\max }}\frac{{\mathrm{\pi \lambda }}^2}{4}{L}_T\mathrm{dN}=\frac{\pi D_f{\lambda }_{\max }^{3-D_f}{L}^{D_f}}{4\left(3-D_T-D_f\right)}\left[1-{\left(\frac{{\lambda }_{\min }}{{\lambda }_{\max }}\right)}^{3-D_T-D_f}\right].$

The calculation formula of water saturation Sw of the core is:

$S_w=\frac{V_w}{V_P}=\frac{\frac{3-D_T-D_f}{L^{D_f}{\lambda }_{\max }^{3-D_T-D_f}}{\int }_{{\lambda }_{\min }}^{{\lambda }_{\mathrm{cr}}}{X}^{D_T}{\lambda }^{2-D_T-D_f}d\lambda +\left[1-{\left(\frac{{\lambda }_{\mathrm{cr}}}{{\lambda }_{\max }}\right)}^{\left(3-D_T-D_f\right)}\right]}{\left[1-{\left(\frac{{\lambda }_{\min }}{{\lambda }_{\max }}\right)}^{3-D_T-D_f}\right]};$

where, DT is tortuosity fractal dimension, Df is porosity fractal dimension, λmax is maximum pore equivalent diameter, λmin is minimum pore equivalent diameter, λcr is critical capillary diameter, LT is actual length of the fractal capillary bundle, XT is linear length of a fractal capillary tube bundle, and N is the number of capillary bundles.

Preferably, the calculation formula of single-phase fluid flow rate Qs mentioned in Step S8 is:

$Q_s=-{\int }_{{\lambda }_{\min }}^{{\lambda }_{\max }}\mathrm{qdN}={\int }_{{\lambda }_{\min }}^{{\lambda }_{\max }}\frac{{\mathrm{\pi \lambda }}^4}{128}·\frac{{\lambda }^{D_T-1}\Delta p-J_w{L}^{D_T}}{{\mu }_w{L}^{D_T}}{D}_f{\lambda }_{\max }^{D_f}{\lambda }^{-\left(D_f+1\right)}d\lambda ;$

where, DT is tortuosity fractal dimension, Df is porosity fractal dimension, λmax is maximum pore equivalent diameter, λmin is minimum pore equivalent diameter, μw is water phase viscosity, and Δp is pressure difference between the two ends of the core.

Preferably, the calculation formula of oil phase flow rate Qo at the outflow end mentioned in Step S9 is:

$Q_o=-{\int }_{{\lambda }_{\min }}^{{\lambda }_{\mathrm{cr}}}\mathrm{qdN}=\frac{\pi D_f{\lambda }_{\max }^{D_f}\Delta p}{128}{\int }_{{\lambda }_{\min }}^{{\lambda }_{\mathrm{cr}}}\frac{{\lambda }^{2+D_T-D_j}}{\left({\mu }_w-{\mu }_o\right)X^{D_T}+{\mu }_o{L}^{D_T}}d\lambda +\frac{\pi D_f{\lambda }_{\max }^{D_f}\delta \cos \theta }{32}{\int }_{{\lambda }_{\min }}^{{\lambda }_{\mathrm{cr}}}\frac{{\lambda }^{1+D_T-D_j}}{\left({\mu }_w-{\mu }_o\right)X^{D_T}+{\mu }_o{L}^{D_r}}d\lambda -\frac{\pi D_f{\lambda }_{\max }^{D_f}}{128}{\int }_{{\lambda }_{\min }}^{{\lambda }_{\mathrm{cr}}}\frac{\left(X^{D_T}\left(J_w-J_o\right)+J_o{L}^{D_T}\right){\lambda }^{3-D_j}}{\left({\mu }_w-{\mu }_o\right)X^{D_T}+{\mu }_o{L}^{D_T}}d\lambda .$

The calculation formula of water phase flow rate Qw is:

$Q_w=-{\int }_{{\lambda }_{\mathrm{cr}}}^{{\lambda }_{\max }}qdN=\frac{\pi D_f{\lambda }_{\max }^{D_f}\Delta p}{128{\mu }_w{L}^{D_T}\left(D_T+3-D_f\right)}\left({\lambda }_{\max }^{D_T+3-D_f}-{\lambda }_{\mathrm{cr}}^{D_T+3-D_f}\right)-\frac{\pi D_f{\lambda }_{\max }^{D_f}{J}_w}{128{\mu }_w\left(4-D_f\right)}\left({\lambda }_{\max }^{4-D_f}-{\lambda }_{\mathrm{cr}}^{4-D_f}\right);$

where, λcr is critical capillary diameter, Df is porosity fractal dimension, λcr is critical capillary diameter, w is water phase viscosity, and Jw is threshold pressure gradient of water phase.

Preferably, the relative permeability krw of water phase and the relative permeability kro of oil phase at displacement time t mentioned in Step S10 can be obtained according to Darcy's law of single-phase flow

$k=\frac{Q_s\mu L}{A\Delta p}$ and Darcy's law of two-phase flow

$k_i=\frac{Q_i{\mu }_{i}L}{A\Delta p}:$

$k_{\mathrm{rw}}=\frac{k_w}{k}=\frac{Q_w}{Q_s};k_{\mathrm{ro}}=\frac{k_o}{k}=\frac{{\mu }_o}{{\mu }_w}\frac{Q_o}{Q_s};$

where, Qw is water phase flow rate, Qo is oil phase flow rate at outflow end, Qs is single-phase fluid flow rate, w is water phase viscosity, and μo is oil phase viscosity.

The digital imaging technology-based method for calculating relative permeability of tight core of the present invention has the following beneficial effects:

• • 1. This method considers the influence of the threshold pressure gradient and the capillary pressure, and reflects the characteristics of the low-permeability tight core.
  • 2. This method is based on the fractal capillary number model of porous media to calculate the relative permeability, which avoids the problems related to time consumption and instrument accuracy.
  • 3. The present invention is to establish associated digital core of actual rock sample based on the results of laboratory CT scanning experiment, take into account the influence of rock morphological characteristics (such as rock internal structure and pore distribution) on the relative permeability curve, and repeat calculations and simulations for many times, avoiding resource waste caused by repeated physical experiments.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a flow chart for calculating relative permeability of tight core provided for the digital imaging technology-based method for calculating relative permeability of tight core in the present invention.

FIG. 2 is a digital core diagram obtained by an embodiment of the digital imaging technology-based method for calculating relative permeability of tight core in the present invention.

FIG. 3 is a schematic diagram of single fractal capillary flow involved in the calculation with the digital imaging technology-based method for calculating relative permeability of tight core in the present invention.

FIG. 4 is a schematic diagram of core water-oil displacement fractal capillary flow involved in the calculation with the digital imaging technology-based method for calculating relative permeability of tight core in the present invention.

FIG. 5 is a comparison diagram of the measured data and the relative permeability curve obtained in Embodiment 1 of the digital imaging technology-based method for calculating relative permeability of tight core in the present invention.

FIG. 6 is a comparison diagram of relative permeability curve corresponding to different fractal dimensions obtained in Embodiment 2 of the digital imaging technology-based method for calculating relative permeability of tight core in the present invention.

DETAIL DESCRIPTION

The following is a description of the preferred embodiments of the present invention to facilitate those skilled in the art to understand the present invention. However, it should be understood that the present invention is not limited to the scope of the preferred embodiments. For persons of ordinary skill in the art, these changes are obvious without departing from the spirit and scope of the present invention defined and determined by the appended claims, and all inventions and creations using the concept of the present invention are protected.

A digital imaging technology-based method for calculating relative permeability of tight core, as shown in FIG. 1, comprising the following steps:

• • Step S1: preparing a small column sample of tight core satisfying resolution requirements;
  • Step S2: scanning the sample by MicroCT-400 and establishing a digital core;
  • Step S3: performing statistical analysis on parameters reflecting rock pore structures and shape characteristics according to the digital core;
  • Step S4: calculating a tortuosity fractal dimension D_r and a porosity fractal dimension D_f by a 3D image fractal box dimension algorithm;
  • Step S5: performing statistical analysis on maximum pore equivalent diameter Amax and minimum pore equivalent diameter λ_min by a label;
  • Step S6: simulating a water-oil displacement in single fractal capillary, calculating a critical capillary diameter λ_cr, and obtaining the critical capillary diameter at a displacement time t;
  • Step S7: determining a fluid type at an outflow end with the critical capillary diameter, calculating a water-phase fluid volume V_w and a pore volume V_p in the tight core at the time t, and then calculating a water saturation S_w of the core;
  • Step S8: calculating a flow rate Q_s of a single phase flow;
  • Step S9: simulating the water-oil displacement in the low-permeability tight core, and calculating the oil phase flow rate Q_o and water phase flow rate Q_w at the outflow end at the time t;
  • Step S10: calculating the relative permeability k_rw of water phase and the relative permeability k_ro of oil phase at the displacement time t;
  • Step S11: changing the time t and judging whether the water saturation S_w remains unchanged; if so, go to Step S12; if not, return to Step S6; and
  • Step S12: plotting a relative permeability curve.

In this embodiment, the tight core mentioned in Step S1 is 5 to 10 mm in diameter, and greater than 10 mm in length.

In this embodiment, Step S2 including the following sub-steps:

• • Step S21: performing CT scanning with appropriate lens and reconstruct 3D image data according to a size of the core;
  • Step S22: defining and selecting Region of Interest (ROI) in 3D image data; and
  • Step S23: performing filtering and threshold segmentation on ROI to obtain 3D digital core of pore structure distribution.

In this embodiment, the 3D image fractal box dimension algorithm mentioned in Step S4 includes the following sub-steps:

• • Step S41: based on the graph statistics parameters obtained in Step S3, drawing N(r)˜r diagram in log-log coordinates and a negative slope of the line is the value of fractal dimension D_f,lgN(r)=lga−D_flgr;

where, D_f is porosity fractal dimension, r is pore equivalent diameter, N(r) is the number of pores with radius greater than r, a is a constant coefficient;

• • Step S42: the porosity φ of the core is obtained by image statistics and the average tortuosity is calculated by the following formula:

$\tau =\frac{1}{2}\left[1+\frac{1}{2}\sqrt{1-\phi }+\sqrt{1-\phi }\sqrt{{\left(\frac{1}{\sqrt{1-\phi }}-1\right)}^2+\frac{1}{4}}/\left(1-\sqrt{1-\phi }\right)\right];$

where, τ is tortuosity, φ is porosity; and

• • Step S43: calculating the tortuosity fractal dimension D_T by the following formula:

$D_T=1+\frac{\ln \tau }{\ln \left(\frac{L_m}{2r_{\mathrm{av}}}\right)};$

where, D_T is the tortuosity fractal dimension, r_av is a mean pore radius, L_m is a characteristic length obtained by:

$L_m=\sqrt{\frac{1\phi }{\phi }\frac{\pi D_f{r}_{\max }^2}{2-D_f}};$

where, r_max is a maximum pore radius.

As shown in FIG. 3, in this embodiment, Step S6 includes the following sub-steps:

• • Step S61: at a given time t, for a single capillary with the capillary equivalent diameter λ≥λ_cr, determining that there is only single-phase water flow, and the fluid at the outflow end is water;
  • Step S62: for a single equivalent capillary with the capillary equivalent diameter λ <λcr, determining that there is oil and water flow, and the fluid at the outflow end is oil; and
  • Step S63: dividing the capillary in the porous medium into two parts for analysis: the single capillary with λ≥λ_cr and the single capillary with λ<λ_cr.

In this embodiment, the calculation formula of the critical capillary diameter mentioned in Step S6 is:

${\lambda }_{\mathrm{cr}}^{2D_T}+4{\lambda }_{\mathrm{cr}}^{2D_T-1}\frac{\delta \cos \theta }{\Delta p}-\frac{{\lambda }_{\mathrm{cr}}^{D_T+1}{J}_o{L}^{D_T}}{\Delta p}-\frac{16\left({\mu }_w+{\mu }_o\right)L^{2D_T}}{\Delta \mathrm{pt}}=0;$

where, Jo is threshold pressure gradient of oil phase, δ is surface tension; θ is contact angle, w is water phase viscosity, μo is oil phase viscosity, λcr is critical capillary diameter, Δp is pressure difference between the two ends of the core, t is time, in s, L is core length, and DT is tortuosity fractal dimension.

In this embodiment, the calculation formula of water phase volume Vw mentioned in Step S7 is:

$V_w=-{\int }_{{\lambda }_{\min }}^{{\lambda }_{\mathrm{cr}}}\frac{\pi {\lambda }^2}{4}{X}_T\mathrm{dN}-{\int }_{{\lambda }_{\mathrm{cr}}}^{{\lambda }_{\max }}\frac{\pi {\lambda }^2}{4}{L}_T\mathrm{dN}.$

The calculation formula of pore volume Vp is:

$V_P=-{\int }_{{\lambda }_{\min }}^{{\lambda }_{\max }}\frac{\pi {\lambda }^2}{4}{L}_T\mathrm{dN}=\frac{\pi D_f{\lambda }_{\max }^{3-D_T}{L}^{D_f}}{4\left(3-D_T-D_f\right)}\left[1-{\left(\frac{{\lambda }_{\min }}{{\lambda }_{\max }}\right)}^{3-D_T-D_f}\right]$

The calculation formula of water saturation Sw of the core is:

$S_w=\frac{V_w}{V_p}=\frac{\frac{\left(3-D_T-D_f\right)}{L^{D_f}{\lambda }_{\max }^{3-D_T-D_f}}{\int }_{{\lambda }_{\min }}^{{\lambda }_{\mathrm{cr}}}{X}^{D_T}{\lambda }^{2-D_T-D_f}d\lambda +\left[1-{\left(\frac{{\lambda }_{\mathrm{cr}}}{{\lambda }_{\max }}\right)}^{\left(3-D_T-D_f\right)}\right]}{\left[1-{\left(\frac{{\lambda }_{\min }}{{\lambda }_{\max }}\right)}^{3-D_T-D_f}\right]};$

where, DT is tortuosity fractal dimension, Df is porosity fractal dimension, λmax is maximum pore equivalent diameter, λmin is minimum pore equivalent diameter, λcr is critical capillary diameter, LT is actual length of the fractal capillary bundle, XT is linear length of a fractal capillary tube bundle, and N is the number of capillary bundles.

In this embodiment, the calculation formula of single-phase fluid flow rate Qs mentioned in Step S8 is:

$Q_s=-{\int }_{{\lambda }_{\min }}^{{\lambda }_{\max }}\mathrm{qdN}={\int }_{{\lambda }_{\min }}^{{\lambda }_{\max }}\frac{\pi {\lambda }^4}{128}·\frac{{\lambda }^{D_T-1}\Delta p-J_w{L}^{D_T}}{{\mu }_w{L}^{D_T}}{D}_f{\lambda }_{\max }^{D_f}{\lambda }^{-\left(D_f+1\right)}d\lambda$

where, DT is tortuosity fractal dimension, Df is porosity fractal dimension, λmax is maximum pore equivalent diameter, λmin is minimum pore equivalent diameter, pw is water phase viscosity, and Δp is pressure difference between the two ends of the core.

In this embodiment, the calculation formula of oil phase flow rate Qo at the outflow end mentioned in Step S9 is:

$Q_o=-{\int }_{{\lambda }_{\min }}^{{\lambda }_{\mathrm{cr}}}\mathrm{qdN}=\frac{\pi D_f{\lambda }_{\max }^{D_f}\Delta p}{128}{\int }_{{\lambda }_{\min }}^{{\lambda }_{\mathrm{cr}}}\frac{{\lambda }^{2+D_T-D_j}}{\left({\mu }_w-{\mu }_o\right)X^{D_T}+{\mu }_o{L}^{D_T}}d\lambda +\frac{\pi D_f{\lambda }_{\max }^{D_f}\delta \cos \theta }{32}{\int }_{{\lambda }_{\min }}^{{\lambda }_{\mathrm{cr}}}\frac{{\lambda }^{1+D_T-D_j}}{\left({\mu }_w-{\mu }_o\right)X^{D_T}+{\mu }_o{L}^{D_T}}d\lambda -\frac{\pi D_f{\lambda }_{\max }^{D_f}}{128}{\int }_{{\lambda }_{\min }}^{{\lambda }_{\mathrm{cr}}}\frac{\left(X^{D_T}\left(J_w-J_o\right)+J_o{L}^{D_T}\right){\lambda }^{3-D_f}}{\left({\mu }_w-{\mu }_o\right)X^{D_T}+{\mu }_o{L}^{D_T}}d\lambda ;$

The calculation formula of water phase flow rate Qw is:

$Q_w=-{\int }_{{\lambda }_{\mathrm{cr}}}^{{\lambda }_{\max }}\mathrm{qdN}=\frac{\pi D_f{\lambda }_{\max }^{D_f}\Delta p}{128{\mu }_w{L}^{D_T}\left(D_T+3-D_f\right)}\left({\lambda }_{\max }^{D_T+3-D_f}-{\lambda }_{\mathrm{cr}}^{D_T+3-D_f}\right)-\frac{\pi D_f{\lambda }_{\max }^{D_f}{J}_w}{128{\mu }_w\left(4-D_f\right)}\left({\lambda }_{\max }^{4-D_f}-{\lambda }_{\mathrm{cr}}^{4-D_f}\right);$

where, λcr is critical capillary diameter, Df is porosity fractal dimension, λcr is critical capillary diameter, μw is water phase viscosity, and Jw is threshold pressure gradient of water phase.

In this embodiment, the relative permeability krw of water phase and the relative permeability kro of oil phase at displacement time t mentioned in Step S10 can be obtained according to Darcy's law of single-phase flow

$k=\frac{Q_s\mu L}{A\Delta p}$ and Darcy's law of two-phase flow

$k_i=\frac{Q_i{\mu }_{i}L}{A\Delta p}:$

$k_{\mathrm{rw}}=\frac{k_w}{k}=\frac{Q_w}{Q_s};k_{\mathrm{ro}}=\frac{k_o}{k}=\frac{{\mu }_o}{{\mu }_w}\frac{Q_o}{Q_s};$

where, Qw is water phase flow rate, Qo is oil phase flow rate at outflow end, Qs is single-phase fluid flow rate, μw is water phase viscosity, and μo is oil phase viscosity.

When the embodiments are implemented, in Embodiment 1:

• • (1) Select low-permeability tight sandstone sample, prepare a small column sample satisfying resolution requirements, with a size of 8 mm (diameter)×20 mm, and then scan the sample and establish a digital core by MicroCT-400, as shown in FIG. 2.
  • (2) Calculate tortuosity fractal dimension DT=1.1 and porosity fractal dimension Df=1.3 by 3D image fractal box dimension algorithm, and perform statistical analysis on maximum pore equivalent diameter λmax=2.6×10−5 m and minimum pore equivalent diameter λmin=4.3×10−8 m by a label.
  • (3) Taking t=0 as the starting time, calculate associated critical capillary diameter, and judge the distribution of all capillary fluids in the core at that time.
  • (4) Simulate and calculate single-phase fluid flow rate Qs, then calculate water phase flow rate Qw and oil phase flow rate Qo at t=0.
  • (5) Simulate and calculate water-phase fluid volume, pore volume and water saturation in the core at t=0.
  • (6) Calculate relative permeability kro and krw corresponding to water saturation.
  • (7) Repeat the steps (3) to (6) of Embodiment 1, calculate the parameters at the next time Step St=1, and then t+1, until the calculated core water saturation remains unchanged, and plot a relative permeability curve, as shown in FIG. 5.

Comparing the relative permeability curve based on calculated values with the measured data, it can be seen that the calculation reliability is high. The embodiment provides a convincing evidence for the beneficial effects of the present invention.

In Embodiment 2:

• • (1) Select different porosity fractal dimensions Df=1.3, 1.4 and 1.5, the same tortuosity fractal dimension DT, maximum pore equivalent diameter λmax and minimum pore equivalent diameter λmin as the characteristic values of the core pore structure parameters, and use them to calculate the influence of difference porosity fractal dimensions on the relative permeability curve.
  • (2) Taking t=0 as the starting time, calculate associated critical capillary diameter, and judge the distribution of all capillary fluids in the core at that time.
  • (3) Simulate and calculate single-phase fluid flow rate Qs, then calculate water phase flow rate Qw and oil phase flow rate Qo at t=0.
  • (4) Simulate and calculate water-phase fluid volume, pore volume and water saturation in the core at t=0.
  • (5) Calculate relative permeability kro and krw corresponding to water saturation.
  • (6) Repeat the steps (3) to (5) of Embodiment 2, calculate the parameters at the next time Step St=1, and then t+1, until the calculated core water saturation remains unchanged, and plot a relative permeability curve, as shown in FIG. 6.

Claims

1. A digital imaging technology-based method for calculating relative permeability of tight core, comprising the following steps: Step S1: preparing a small column sample of tight core satisfying resolution requirements;Step S2: scanning the sample by MicroCT-400 and establishing a digital core;Step S3: performing statistical analysis on parameters reflecting rock pore structures and shape characteristics according to the digital core;Step S4: calculating a tortuosity fractal dimension DT and a porosity fractal dimension Df by a 3D image fractal box dimension algorithm;Step S5: performing statistical analysis on maximum pore equivalent diameter λmax and minimum pore equivalent diameter λmin by a label;Step S6: simulating a water-oil displacement in single fractal capillary, calculating a critical capillary diameter λcr, and obtaining the critical capillary diameter at a displacement time t;Step S7: determining a fluid type at an outflow end with the critical capillary diameter, calculating a water-phase fluid volume Vw and a pore volume Vp in the tight core at the time t, and then calculating a water saturation Sw of the core;Step S8: calculating a flow rate Qs of a single phase flow;Step S9: simulating the water-oil displacement in the low-permeability tight core, and calculating the oil phase flow rate Qo and water phase flow rate Qw at the outflow end at the time t;Step S10: calculating the relative permeability krw of water phase and the relative permeability kro of oil phase at the displacement time t;Step S11: changing the time t and judging whether the water saturation Sw remains unchanged; if so, go to Step S12; if not, return to Step S6; andStep S12: plotting a relative permeability curve.

2. The digital imaging technology-based method for calculating relative permeability of tight core according to claim 1, wherein the tight core in Step S1 is 5 to 10 mm in diameter, and greater than 10 mm in length.

3. The digital imaging technology-based method for calculating relative permeability of tight core according to claim 1, wherein Step S2 comprises the following sub-steps: Step S21: performing CT scanning with appropriate lens and reconstruct 3D image data according to a size of the core;Step S22: defining and selecting Region of Interest (ROI) in 3D image data; andStep S23: performing filtering and threshold segmentation on ROI to obtain 3D digital core of pore structure distribution.

4. The digital imaging technology-based method for calculating relative permeability of tight core according to claim 1, wherein the 3D image fractal box dimension algorithm in Step S4 comprises the following sub-steps: Step S41: based on the graph statistics parameters obtained in Step S3, drawing N(r)˜r diagram in log-log coordinates and a negative slope of the line is the value of fractal dimension Df, lgN(r)=lga−Dflgr; where, Df is porosity fractal dimension, r is pore equivalent diameter, N(r) is the number of pores with radius greater than r, a is a constant coefficient;Step S42: the porosity p of the core is obtained by image statistics and the average tortuosity is calculated by the following formula:

5. The digital imaging technology-based method for calculating relative permeability of tight core according to claim 1, wherein Step S6 comprises the following sub-steps: Step S61: at a given time t, for a single capillary with the capillary equivalent diameter λ≥λcr, determining that there is only single-phase water flow, and the fluid at the outflow end is water;Step S62: for a single equivalent capillary with the capillary equivalent diameter λ<λcr, determining that there is oil and water flow, and the fluid at the outflow end is oil; andStep S63: dividing the capillary in the porous medium into two parts for analysis: the single capillary with λ≥λcr and the single capillary with λ<λcr.

6. The digital imaging technology-based method for calculating relative permeability of tight core according to claim 4, wherein the calculation formula of the critical capillary diameter in Step S6 is:

7. The digital imaging technology-based method for calculating relative permeability of tight core according to claim 1, wherein the calculation formula of the water phase volume Vw in Step S7 is:

8. The digital imaging technology-based method for calculating relative permeability of tight core according to claim 1, wherein the calculation formula of single-phase fluid flow rate Qs in Step S8 is:

9. The digital imaging technology-based method for calculating relative permeability of tight core according to claim 1, wherein the calculation formula of oil phase flow rate Qo at the outflow end mentioned in Step S9 is:

10. The digital imaging technology-based method for calculating relative permeability of tight core according to claim 1, wherein the relative permeability krw of water phase and the relative permeability kro of oil phase at the displacement time t in Step S10 is obtained according to Darcy's law of single-phase flow