Figure 1.
The left is the rigid particle, and the right are the asphalt with different softening points: (a) rigid particle; (b)asphalt with different softening points.
Figure 1.
The left is the rigid particle, and the right are the asphalt with different softening points: (a) rigid particle; (b)asphalt with different softening points.
Figure 2.
The inside and outside structure of simulated fractured core: (a) Inside network structure of fractured core; (b) Outside structure of fractured core.
Figure 2.
The inside and outside structure of simulated fractured core: (a) Inside network structure of fractured core; (b) Outside structure of fractured core.
Figure 3.
Flow chart of core-displacement experiment in high-temperature.
Figure 3.
Flow chart of core-displacement experiment in high-temperature.
Figure 4.
The asphalt-rigid particles system applied to anti gas-channeling in high-temperature and high-salinity environment (here the thickener is xanthan gum).
Figure 4.
The asphalt-rigid particles system applied to anti gas-channeling in high-temperature and high-salinity environment (here the thickener is xanthan gum).
Figure 5.
The particle size distribution of rigid particles and asphalt: (a) Distribution histogram and accumulation curve of rigid particles; (b) Distribution histogram and accumulation curve of asphalt.
Figure 5.
The particle size distribution of rigid particles and asphalt: (a) Distribution histogram and accumulation curve of rigid particles; (b) Distribution histogram and accumulation curve of asphalt.
Figure 6.
The change of asphalt with different softening point and long-term aging property: (a) The relationship between the asphalt softening point and apparent viscosity; (b) The long-term aging performance of asphalt with different softening points.
Figure 6.
The change of asphalt with different softening point and long-term aging property: (a) The relationship between the asphalt softening point and apparent viscosity; (b) The long-term aging performance of asphalt with different softening points.
Figure 7.
The bonding performance of asphalt with different softening points on rigid particles, the top is the system before heating, the bottom is the system after heating, and the softening point from left to right is 60 °C, 90 °C, 105 °C and 130 °C.
Figure 7.
The bonding performance of asphalt with different softening points on rigid particles, the top is the system before heating, the bottom is the system after heating, and the softening point from left to right is 60 °C, 90 °C, 105 °C and 130 °C.
Figure 8.
The change of particle size of the anti-channeling system before and after high-temperature in different asphalt content, taken HA − 2%A + 8%RP as an example, HA represents heating after (on the contrary, HB represents heating before), 2%A + 8%RP means the test group contains 2 wt% asphalt and 8 wt% rigid particles (the same as below): (a) The change of particle size distribution of anti-channeling system before and after heating; (b) The change of d50 of anti-channeling system before and after heating.
Figure 8.
The change of particle size of the anti-channeling system before and after high-temperature in different asphalt content, taken HA − 2%A + 8%RP as an example, HA represents heating after (on the contrary, HB represents heating before), 2%A + 8%RP means the test group contains 2 wt% asphalt and 8 wt% rigid particles (the same as below): (a) The change of particle size distribution of anti-channeling system before and after heating; (b) The change of d50 of anti-channeling system before and after heating.
Figure 9.
The change of particle size of the anti-channeling system before and after high-temperature in different rigid particle content: (a) The change of particle size distribution of anti-channeling system before and after heating; (b) The change of d50 of anti-channeling system before and after heating.
Figure 9.
The change of particle size of the anti-channeling system before and after high-temperature in different rigid particle content: (a) The change of particle size distribution of anti-channeling system before and after heating; (b) The change of d50 of anti-channeling system before and after heating.
Figure 10.
The change of particle size of the anti-channeling system before and after high-temperature in different softening point (taken HA − 60 °C as an example, HA represents heating after (by contrast, HB represents heating before), 60 °C means the softening point of asphalt in test group): (a) The change of particle size distribution of anti-channeling system before and after heating; (b) The change of d50 of anti-channeling system before and after heating.
Figure 10.
The change of particle size of the anti-channeling system before and after high-temperature in different softening point (taken HA − 60 °C as an example, HA represents heating after (by contrast, HB represents heating before), 60 °C means the softening point of asphalt in test group): (a) The change of particle size distribution of anti-channeling system before and after heating; (b) The change of d50 of anti-channeling system before and after heating.
Figure 11.
Thickeners solubility in high-salinity brine, from left to right are: xanthan gum, AP-P4 and hydrolyzed polyacrylamide (HPAM), respectively, concentrations are all 3000 mg·L−1.
Figure 11.
Thickeners solubility in high-salinity brine, from left to right are: xanthan gum, AP-P4 and hydrolyzed polyacrylamide (HPAM), respectively, concentrations are all 3000 mg·L−1.
Figure 12.
(a) and (b) are the steady-state rheological property of HPAM and xanthan gum, respectively. (c) is the relation curve between the concentration of thickener and consistency coefficient.
Figure 12.
(a) and (b) are the steady-state rheological property of HPAM and xanthan gum, respectively. (c) is the relation curve between the concentration of thickener and consistency coefficient.
Figure 13.
The apparent viscosity and retention of xanthan gum over different aging times.
Figure 13.
The apparent viscosity and retention of xanthan gum over different aging times.
Figure 14.
Xanthan gum-suspended rigid particles (25 °C, the concentration from left to right is 0.1 wt%, 0.2 wt%, 0.3 wt%, 0.4 wt%, 0.5 wt% and 0.6 wt%).
Figure 14.
Xanthan gum-suspended rigid particles (25 °C, the concentration from left to right is 0.1 wt%, 0.2 wt%, 0.3 wt%, 0.4 wt%, 0.5 wt% and 0.6 wt%).
Figure 15.
Xanthan gum suspended rigid particles in high-temperature (130 °C, the xanthan gum concentration from top to bottom is 0.3 wt%, 0.4 wt% and 0.5 wt%, the sampling time from left to right is 4 h, 8 h, 12 h, 16 h, 20 h, 24 h and 28 h): (a) Suspension of rigid particles within 0.3 wt% xanthan gum; (b) Suspension of rigid particles within 0.4 wt% xanthan gum; (c) Suspension of rigid particles within 0.5 wt% xanthan gum.
Figure 15.
Xanthan gum suspended rigid particles in high-temperature (130 °C, the xanthan gum concentration from top to bottom is 0.3 wt%, 0.4 wt% and 0.5 wt%, the sampling time from left to right is 4 h, 8 h, 12 h, 16 h, 20 h, 24 h and 28 h): (a) Suspension of rigid particles within 0.3 wt% xanthan gum; (b) Suspension of rigid particles within 0.4 wt% xanthan gum; (c) Suspension of rigid particles within 0.5 wt% xanthan gum.
Figure 16.
Optimized maximum injected concentration by golden section algorithm (this uniaxial image here is only used to show the experimental sequence and results, and has no other meaning).
Figure 16.
Optimized maximum injected concentration by golden section algorithm (this uniaxial image here is only used to show the experimental sequence and results, and has no other meaning).
Figure 17.
The distribution of solid particles in 0.4 wt% xanthan gum solution by optical microscope. (a–f) are the micromorphology of the bonding system before heating under different fields of view.
Figure 17.
The distribution of solid particles in 0.4 wt% xanthan gum solution by optical microscope. (a–f) are the micromorphology of the bonding system before heating under different fields of view.
Figure 18.
Schematic representation of boundary layer thickness changing with fluid velocity.
Figure 18.
Schematic representation of boundary layer thickness changing with fluid velocity.
Figure 19.
Level trend of rigid particles concentration (brown particle is rigid particles and the black particle is asphalt).
Figure 19.
Level trend of rigid particles concentration (brown particle is rigid particles and the black particle is asphalt).
Figure 20.
Level trend of asphalt concentration (brown particle is rigid particles and the black particle is asphalt).
Figure 20.
Level trend of asphalt concentration (brown particle is rigid particles and the black particle is asphalt).
Figure 21.
Level trend of asphalt softening point.
Figure 21.
Level trend of asphalt softening point.
Figure 22.
The blocking ratio in different aging time.
Figure 22.
The blocking ratio in different aging time.
Figure 23.
The distribution of anti gas-channeling system in network fractures; black solid in the fracture is asphalt, and the rigid particles are colored brown.
Figure 23.
The distribution of anti gas-channeling system in network fractures; black solid in the fracture is asphalt, and the rigid particles are colored brown.
Figure 24.
Micromorphology observation of blocking zone. (a) and (b) are the micromorphology of the bonding system under different fields of view when the magnification is 300 times; (c) and (d) are the micromorphology of the bonding system under different fields of view when the magnification is 150 times.
Figure 24.
Micromorphology observation of blocking zone. (a) and (b) are the micromorphology of the bonding system under different fields of view when the magnification is 300 times; (c) and (d) are the micromorphology of the bonding system under different fields of view when the magnification is 150 times.
Table 1.
Components of simulated brine.
Table 1.
Components of simulated brine.
Components | NaCl | Na2SO4 | CaCl2 | MgCl2·6H2O | NaHCO3 | Total Salinity |
---|
g·L−1 | 181.88 | 0.22 | 31.22 | 9.70 | 0.05 | 223.07 |
Table 2.
Orthogonal experimental factors and levels table.
Table 2.
Orthogonal experimental factors and levels table.
Factors | Rigid Particles Content/wt% | Asphalt Content/wt% | Asphalt Coftening Point/°C |
---|
1 | (A1)2 | (B1)2 | (C1)60 |
2 | (A2)4 | (B2)4 | (C2)90 |
3 | (A3)6 | (B3)6 | (C3)105 |
4 | (A4)8 | (B4)8 | (C4)130 |
Table 3.
The grouping of orthogonal experimental.
Table 3.
The grouping of orthogonal experimental.
No. | Rigid Particles Content/% | Asphalt Content/% | Asphalt Softening Point/°C | Blocking Ratio/% |
---|
1# | 2 | 2 | 60 | W1 |
2# | 2 | 4 | 90 | W2 |
3# | 2 | 6 | 105 | W3 |
4# | 2 | 8 | 130 | W4 |
5# | 4 | 2 | 90 | W5 |
6# | 4 | 4 | 60 | W6 |
7# | 4 | 6 | 130 | W7 |
8# | 4 | 8 | 105 | W8 |
9# | 6 | 2 | 105 | W9 |
10# | 6 | 4 | 130 | W10 |
11# | 6 | 6 | 60 | W11 |
12# | 6 | 8 | 90 | W12 |
13# | 8 | 2 | 130 | W13 |
14# | 8 | 4 | 105 | W14 |
15# | 8 | 6 | 90 | W15 |
16# | 8 | 8 | 60 | W16 |
Table 4.
The laboratory results of asphalt - rigid particles system anti gas-channeling performance by means of orthogonal design (V0 and V1 are the gas flow rates measured before and after injecting anti gas-channeling system under the conditions of N2 displacement pressure of 0.25 MPa, V0* and V1* are the gas flow rates measured before and after injecting anti gas-channeling system under the conditions of N2 displacement pressure of 1 MPa. Wi and Wi* are the blocking rate under the N2 displacement pressure of 0.25 MPa and 1MPa which was calculated by Equation (3), and i = 1, 2, 3…15, 16).
Table 4.
The laboratory results of asphalt - rigid particles system anti gas-channeling performance by means of orthogonal design (V0 and V1 are the gas flow rates measured before and after injecting anti gas-channeling system under the conditions of N2 displacement pressure of 0.25 MPa, V0* and V1* are the gas flow rates measured before and after injecting anti gas-channeling system under the conditions of N2 displacement pressure of 1 MPa. Wi and Wi* are the blocking rate under the N2 displacement pressure of 0.25 MPa and 1MPa which was calculated by Equation (3), and i = 1, 2, 3…15, 16).
No. | 0.25 MPa | 1 MPa | 0.25 MPa | 1 MPa |
---|
V0/(L·min−1) | V1/(L·min−1) | V0*/(L·min−1) | V1*/(L·min−1) | Wi/% | Wi*/% |
---|
1# | 25.85 | 20.34 | 76.73 | 61.68 | 21.32 | 19.61 |
2# | 25.15 | 18.76 | 74.91 | 57.52 | 25.42 | 23.21 |
3# | 24.32 | 17.75 | 75.62 | 56.96 | 27.01 | 24.67 |
4# | 24.66 | 17.56 | 75.19 | 55.47 | 28.78 | 26.23 |
5# | 25.16 | 11.81 | 76.03 | 39.30 | 53.08 | 48.31 |
6# | 25.33 | 5.86 | 75.77 | 23.33 | 76.87 | 69.21 |
7# | 26.39 | 8.88 | 76.52 | 30.55 | 66.34 | 60.08 |
8# | 26.86 | 8.68 | 75.19 | 29.11 | 67.67 | 61.29 |
9# | 26.57 | 10.25 | 76.28 | 34.09 | 61.43 | 55.31 |
10# | 25.73 | 7.30 | 75.23 | 26.08 | 71.64 | 65.33 |
11# | 26.04 | 13.33 | 76.40 | 42.36 | 48.82 | 44.56 |
12# | 24.73 | 5.97 | 75.61 | 23.42 | 75.86 | 69.02 |
13# | 25.61 | 11.72 | 76.21 | 37.86 | 54.23 | 50.32 |
14# | 25.22 | 8.21 | 75.31 | 28.78 | 67.43 | 61.79 |
15# | 25.01 | 3.28 | 75.44 | 15.25 | 84.90 | 79.79 |
16# | 25.77 | 4.07 | 76.09 | 17.49 | 84.22 | 77.02 |
Table 5.
Evaluating indicators of three factors and four levels (ki refers to the ratio of the sum of the corresponding test results when the number of level on any column is i (i = 1, 2, 3, 4 in this study) to the occurrence times (4 times in this study) of each level on any column (for example, for the Factor B, its k1-0.25MPa = (W1 + W5 + W9 + W13)/4 and k2-0.25MPa = (W2 + W6 + W10 + W14)/4). Range refers to the variation range of the test index within the value range of a factor (the algorithm is max{k1, k2, k3, k4} − min{k1, k2, k3, k4}, for example, for the Factor A, its R0.25MPa = k4-0.25MPa − k1-0.25MPa and its R1MPa = k4-1MPa – k1-1MPa).
Table 5.
Evaluating indicators of three factors and four levels (ki refers to the ratio of the sum of the corresponding test results when the number of level on any column is i (i = 1, 2, 3, 4 in this study) to the occurrence times (4 times in this study) of each level on any column (for example, for the Factor B, its k1-0.25MPa = (W1 + W5 + W9 + W13)/4 and k2-0.25MPa = (W2 + W6 + W10 + W14)/4). Range refers to the variation range of the test index within the value range of a factor (the algorithm is max{k1, k2, k3, k4} − min{k1, k2, k3, k4}, for example, for the Factor A, its R0.25MPa = k4-0.25MPa − k1-0.25MPa and its R1MPa = k4-1MPa – k1-1MPa).
Factors | A | B | C |
---|
ki | k1-0.25MPa | 25.633 | 47.515 | 57.807 |
k1-1MPa | 19.635 | 43.388 | 52.600 |
k2-0.25MPa | 65.990 | 60.340 | 60.315 |
k2-1MPa | 58.617 | 54.885 | 55.083 |
k3-0.25MPa | 64.438 | 57.268 | 55.885 |
k3-1MPa | 56.580 | 52.275 | 50.765 |
k4-0.25MPa | 73.195 | 64.132 | 55.247 |
k4-1MPa | 65.472 | 58.390 | 50.490 |
Range R0.25MPa | 47.562 | 16.617 | 5.068 |
Range R1MPa | 45.837 | 15.002 | 4.593 |
Major-minor sequence | 1 | 2 | 3 |
Optimal scheme | A4B4C2 |
Table 6.
Blocking effect of optimal scheme (The meanings of each notations are the same as in
Table 4).
Table 6.
Blocking effect of optimal scheme (The meanings of each notations are the same as in
Table 4).
0.25 MPa | 1 MPa | 0.25 MPa | 1 MPa |
---|
V0/((L·min−1) | V1/(L·min−1) | V0*/(L·min−1) | V1*/(L·min−1) | W/% | W*/% |
25.49 | 2.29 | 76.73 | 10.56 | 91.02 | 86.24 |