A pore type carbonate rock sub-resolution remaining oil classification and identification method

Abstract

The application provides a pore type carbonate rock sub-resolution residual oil classification and identification method, the classification and identification method realizes scanning image pixel enhancement by adopting a double cubic difference method and a nearest neighbor interpolation method, establishes different accuracy pore network models, improves sub-resolution pore and residual oil characterization accuracy, establishes a micro residual oil classification and identification and characterization method by comparing CT value differences of enhanced enlarged images and equal proportion enlarged images under different accuracies, and realizes sub-resolution three-dimensional model reconstruction of oil, water, pores and rock skeletons.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of oilfield development, and particularly relates to a pore type carbonate rock sub-resolution residual oil classification and identification method. BACKGROUND

[0002] Carbonate rock oil and gas fields play an important role in the world oil and gas distribution, and the oil and gas reserves thereof account for about 50% of the total oil and gas reserves in the world, and the oil and gas production thereof accounts for more than 60% of the total oil and gas production in the world. The carbonate rock stratum has a long deposition age, experiences multiple diagenetic stages and types, has complex reservoir spaces including pores, fractures and caves, has strong heterogeneity, and has a large difference in pore space size, and micrometer and nanometer pores are relatively developed, which is manifested in that the porosity is very high, but the permeability is relatively low, and low-permeability and ultra-low-permeability conditions are common.

[0003] Digital core technology, as an effective method for core analysis, has been greatly developed, and is widely applied in the field of carbonate rock analysis and has achieved great success. The digital core modeling method can be divided into two categories: physical experiment method and numerical reconstruction method. The physical experiment method is to first obtain a planar image of a core by means of high-precision instruments such as a high-power optical microscope, a scanning electron microscope or a CT imager, and then to reconstruct a digital core from the planar image; and the numerical reconstruction method is to extract modeling information by image analysis with the aid of a small amount of data such as a planar image of a core, and then to establish a digital core by using a certain mathematical method.

[0004] At present, the method for establishing a three-dimensional digital core based on Micro-CT is limited by the scanning resolution, and it is difficult to identify nanometer and part of micrometer pores, so that the residual oil in the micro pores cannot be classified. In particular, there are many micro pores in the carbonate rock that cannot be identified by conventional Micro-CT, and if the digital core is reconstructed only according to the pores identified from the scanning image, the calculated porosity will be much lower than the gas logging porosity, and the established digital core cannot represent the actual core, which further affects the identification and classification of the residual oil. Therefore, there is an urgent need for a widely applicable micro residual oil classification and identification and characterization method for pore type carbonate rock. SUMMARY

[0005] The pore type carbonate rock sub-resolution residual oil classification and identification method provided by the application realizes the enhanced enlargement and equal-proportion enlargement of the image pixels by using the bicubic difference method and the nearest neighbor interpolation method, and establishes a micro residual oil classification and identification method by comparing the CT value differences of the enlarged images with different accuracies.

[0006] To achieve the purpose of the application, the following technical solutions are adopted in the application.

[0007] The application provides a pore-type carbonate rock sub-resolution remaining oil classification and identification method, and the classification and identification method comprises the following steps:

[0008] (1) The carbonate rock core is cut and pretreated, and the pretreated core is subjected to Micro-CT scanning to obtain a first CT value.

[0009] (2) The core pretreated in step (1) is subjected to pressure increasing treatment, low-speed displacement using KI aqueous solution and then standing, the core after standing is subjected to Micro-CT scanning to obtain a second CT value, and the second CT value is subtracted from the first CT value for difference analysis.

[0010] (3) The core after standing in step (2) is subjected to an oil displacement water experiment, and then the core is subjected to four water displacement oil experiments, and the core after the oil displacement water experiment and after each water displacement oil experiment is independently subjected to Micro-CT scanning to obtain third to seventh CT values.

[0011] (4) The second to seventh scanning images are enhanced and enlarged by using a bicubic interpolation method, the enhanced and enlarged CT values of the second scanning image and the third to seventh scanning images are independently subtracted to obtain difference values.

[0012] (5) The second to seventh scanning images are enlarged at a constant ratio by using a nearest neighbor interpolation method, the constant ratio enlarged CT values of the second scanning image and the third to seventh scanning images are independently subtracted to obtain difference values.

[0013] (6) After analyzing the difference values in step (4) and the difference values in step (5), the remaining oil is classified and identified.

[0014] The bicubic difference method and the nearest neighbor interpolation method are used to realize the enhanced enlargement and constant ratio enlargement of the image pixels, the micro remaining oil classification and identification method is established by comparing the CT value differences of the enlarged images with different accuracies, and the problem that the remaining oil in the micropore cannot be classified due to the limitation of the scanning resolution in the prior art analysis method is solved.

[0015] As a preferred technical scheme of the application, the diameter of the cut carbonate rock core in step (1) is 7.5-8.5 mm, and the length is 4.5-5.5 cm.

[0016] In the present application, the diameter of the cut carbonate rock core is 7.5-8.5 mm, for example, it can be 7.5 mm, 7.7 mm, 7.9 mm, 8 mm, 8.1 mm, 8.3 mm or 8.5 mm, etc., but not limited to the listed values, other values not listed in the value range are also applicable.

[0017] In the present application, the length of the cut carbonate rock core is 4.5-5.5 cm, for example, it can be 4.5 cm, 4.7 cm, 4.9 cm, 5 cm, 5.1 cm, 5.3 cm or 5.5 cm, etc., but not limited to the listed values, other values not listed in the value range are also applicable.

[0018] Preferably, the pretreatment of step (1) includes sequentially performing oil removal treatment, drying treatment and vacuum treatment on the carbonate rock core.

[0019] As a preferred technical solution of the present application, the pressure boosting treatment of step (2) includes raising the pore pressure of the core to 7.5-8.5 MPa, raising the confining pressure to 11.5-12.5 MPa, and stabilizing for 4-6 h.

[0020] In the present application, the pore pressure is raised to 7.5-8.5 MPa, for example, it can be 7.5 MPa, 7.7 MPa, 7.9 MPa, 8 MPa, 8.1 MPa, 8.3 MPa or 8.5 MPa, etc., but not limited to the listed values, other values not listed in the value range are also applicable.

[0021] In the present application, the confining pressure is raised to 11.5-12.5 MPa, for example, it can be 11.5 MPa, 11.7 MPa, 11.9 MPa, 12 MPa, 12.1 MPa, 12.3 MPa or 12.5 MPa, etc., but not limited to the listed values, other values not listed in the value range are also applicable.

[0022] In the present application, the stabilization time is 4-6 h, for example, it can be 4 h, 4.2 h, 4.4 h, 4.6 h, 4.8 h, 5 h, 5.2 h, 5.4 h, 5.6 h, 5.8 h or 6 h, etc., but not limited to the listed values, other values not listed in the value range are also applicable.

[0023] As a preferred technical solution of the present application, the concentration of the KI aqueous solution of step (2) is 25-35 wt%, for example, it can be 25 wt%, 27 wt%, 29 wt%, 30 wt%, 31 wt%, 33 wt% or 35 wt%, etc., but not limited to the listed values, other values not listed in the value range are also applicable.

[0024] Preferably, the low-speed displacement in step (2) has a speed of 0.01-0.03 mL / min, for example, it can be 0.01 mL / min, 0.015 mL / min, 0.02 mL / min, 0.025 mL / min or 0.03 mL / min, etc., but not limited to the listed values, other values not listed in the value range are also applicable.

[0025] Preferably, the standing time in step (2) is 10-12 h, for example, it can be 10 h, 10.2 h, 10.4 h, 10.6 h, 10.8 h, 11 h, 11.2 h, 11.4 h, 11.6 h, 11.8 h or 12 h, etc., but not limited to the listed values, other values not listed in the value range are also applicable.

[0026] As a preferred technical solution of the present application, the difference analysis in step (2) is analyzed by using formula (1):

[0027] ΔCT 21 = CT2- CT1 (1)

[0028] Wherein, CT1=0, indicating that the pores in this area are macroscopic pores; ΔCT 21 =0, indicating that this area is the rock skeleton; CT1≠0 and ΔCT 21 ≠0, indicating that the pores in this area are sub-resolution pores.

[0029] In the present application, the macroscopic pores are ≥3 μm, for example, they can be 3 μm, 3.5 μm, 4 μm, 5 μm or 6 μm, etc., but not limited to the listed values, other values not listed in the value range are also applicable.

[0030] In the present application, the sub-resolution pores are <3 μm, for example, they can be 1 μm, 1.5 μm, 2 μm, 2.5 μm or 2.7 μm, etc., but not limited to the listed values, other values not listed in the value range are also applicable.

[0031] In the present application, based on the CT values of the first and second scanning images, the equivalent porosity of the sub-resolution pore area is calculated according to formula (1'):

[0032] CT s = CT w φ e + CT r (1-φ e ) (1’)

[0033] Wherein, CT s represents the CT value of each pixel point in the sub-resolution pore area, CT w represents the CT value of KI aqueous solution, CTr represents the CT value of the rock matrix, φ e represents the equivalent porosity of the sub-resolution pore region.

[0034] As a preferred technical solution of the present application, the displacement speed of the oil displacement water experiment in step (3) is 0.01-0.03 mL / min, for example, it can be 0.01 mL / min, 0.015 mL / min, 0.02 mL / min, 0.025 mL / min or 0.03 mL / min, etc., but not limited to the listed values, other values not listed in the value range are also applicable.

[0035] Preferably, the ratio of the displacement oil volume to the pore volume of the core in the oil displacement water experiment in step (3) is (49-51):1, for example, it can be 49:1, 49.5:1, 50:1, 50.5:1 or 51:1, etc., but not limited to the listed values, other values not listed in the value range are also applicable.

[0036] As a preferred technical solution of the present application, the displacement speed of the 4 times water displacement oil experiment in step (3) is independently 0.01-0.03 mL / min, 0.04-0.06 mL / min, 0.09-0.11 mL / min and 0.49-0.52 mL / min, respectively.

[0037] In the present application, the displacement speed of the first time in the 4 times water displacement oil experiment is 0.01-0.03 mL / min, for example, it can be 0.01 mL / min, 0.015 mL / min, 0.02 mL / min, 0.025 mL / min or 0.03 mL / min, etc., but not limited to the listed values, other values not listed in the value range are also applicable.

[0038] In the present application, the displacement speed of the second time in the 4 times water displacement oil experiment is 0.04-0.06 mL / min, for example, it can be 0.04 mL / min, 0.045 mL / min, 0.05 mL / min, 0.055 mL / min or 0.06 mL / min, etc., but not limited to the listed values, other values not listed in the value range are also applicable.

[0039] In the present application, the displacement speed of the third time in the 4 times water displacement oil experiment is 0.09-0.11 mL / min, for example, it can be 0.09 mL / min, 0.095 mL / min, 0.01 mL / min, 0.015 mL / min or 0.011 mL / min, etc., but not limited to the listed values, other values not listed in the value range are also applicable.

[0040] In the present application, the displacement rate of the fourth water flooding oil experiment is 0.49-0.52 mL / min, for example, it can be 0.49 mL / min, 0.495 mL / min, 0.5 mL / min, 0.51 mL / min or 0.52 mL / min, etc., but not limited to the listed values, other values not listed in the value range are also applicable.

[0041] The present application adopts the displacement rate increasing gradually, because the subsequent water content increases, the displacement rate of crude oil decreases, and increasing the displacement rate can shorten the experimental time.

[0042] Preferably, the volume ratio of displacement water to the pore volume of the core in the fourth water flooding oil experiment of step (3) is (19-21):1, for example, it can be 19:1, 19.5:1, 20:1, 20.5:1 or 21:1, etc., but not limited to the listed values, other values not listed in the value range are also applicable.

[0043] As a preferred technical solution of the present application, the enhancement amplification of step (4) includes: using a double cubic interpolation method to enhance and amplify the 3μm precision scanning images from the second to the seventh time, and the pixel point value B(X,Y) of the scanning image after enhancement amplification is obtained by using BiCubic base function weighted average of 16 pixel points adjacent to it in the source image;

[0044] The BiCubic base function is shown in formula (2):

[0045]

[0046] In the present application, the BiCubic base function is as follows:

[0047]

[0048] Where a is a constant, -0.5 or -1, for the pixel point B(X,Y) of the present application, take its nearby 4*4 neighborhood point A(x i ,y j ), i,j=0,1,2,3, calculated according to the following formula:

[0049]

[0050] The CT values of the second enhanced and amplified scanning image and the CT values of the third to seventh enhanced and amplified scanning images are independently subtracted, and formula (3) is used for subtraction analysis:

[0051] ΔCT 2k(jμm) =CT 2(jμm) -CT k(jμm) (3)

[0052] CT k(jμm) represents the CT value of the kth scan result amplified to j μm precision, k is 3, 4, 5, 6 or 7 respectively; j represents different precision of amplification, j is 0.01, 0.1 and 1 respectively.

[0053] As a preferred technical solution of the present application, the step (5) described equal scale amplification includes: using the nearest neighbor interpolation method to amplify the 3 μm precision scan image from the second to the seventh time, the pixel point value B'(X', Y') of the amplified scan image is the same as the value of the nearest center pixel point in the source image, and each pixel point value A'(x', y') in the source image is known;

[0054] The CT value of the second equal scale amplified scan image is independently subtracted from the CT value of the third to seventh scan image, and formula (4) is used for difference analysis:

[0055] ΔCT 2k(jμm) = CT 2(jμm) - CT k(jμm) (4)

[0056] Wherein, CT k(jμm) represents the CT value of the kth scan result amplified to j μm precision; k is 3, 4, 5, 6 or 7 respectively; j represents different precision of amplification, j is 0.01, 0.1 and 1 respectively.

[0057] As a preferred technical solution of the present application, the step (6) described analysis is to analyze the results of ΔCT 2k(jμm) in formula (3) and ΔCT 2k(jμm) in formula (4);

[0058] Wherein, ΔCT 2k(jμm) = ΔCT 2k(jμm) = 0, indicating that the state of rock skeleton or fluid in the pore at this position has not changed, and does not contain remaining oil;

[0059] ΔCT 2k(jμm) ≠ 0, indicating that the position contains remaining oil, and the classification and identification of remaining oil are carried out by comparing the difference between ΔCT 2k(jμm) and ΔCT 2k(jμm) under different precision;

[0060] 1) | ΔCT 2k(0.01μm) - ΔCT 2k(001μm) | ≤ 5, indicating that the remaining oil in this area is type I remaining oil;

[0061] 2) | ΔCT 2k(0.1μm) - ΔCT 2k(0.1μm) | ≤ 5, indicating that the remaining oil in this area is type II remaining oil;

[0062] 3) |ΔCT 2k(1μm) -ΔCT' 2k(1μm) |≤5, indicates that the remaining oil in this area is type III remaining oil.

[0063] In the present application, the type I remaining oil is small oil droplet remaining oil, the type II remaining oil is medium oil droplet remaining oil, and the type III remaining oil is large oil droplet remaining oil.

[0064] The present application also provides a pore type carbonate rock sub-resolution remaining oil characterization method, which uses the maximum sphere algorithm to equivalently process macroscopic pores with spherical pores and columnar throats, further uses the porosity equivalence method to equivalently process sub-resolution pores with spherical micropores, connects the spherical micropores and their adjacent spherical pores, and establishes a pore network model; in combination with the microcosmic remaining oil identification and classification results of different precision images, a three-dimensional reconstruction model of oil, water, pores and rock skeleton is established, and three-dimensional fine characterization of the pore type carbonate rock sub-resolution remaining oil is realized.

[0065] The numerical range in the present application not only includes the above-mentioned point values, but also includes any point values between the above-mentioned numerical ranges which are not mentioned, and the specific point values included in the range are not listed again in the present application due to the limitation of the length and the consideration of simplicity.

[0066] Compared with the prior art, the present application has the following beneficial effects:

[0067] (1) The present application realizes pixel enhancement of the scanning image by using the bicubic difference method and the nearest neighbor interpolation method, establishes different precision pore network models, significantly improves the sub-resolution pore and remaining oil characterization accuracy, establishes a microcosmic remaining oil classification and identification method by comparing the CT value differences of the enhanced enlarged image and the equal proportion enlarged image under different precision, and realizes the sub-resolution three-dimensional model reconstruction of oil, water, pores and rock skeleton;

[0068] (2) The pore type carbonate rock sub-resolution remaining oil classification and identification method provided by the present application can not only be applied to medium-high permeability carbonate rock reservoirs, but also be applied to the identification and classification of low permeability pore type carbonate rock sub-resolution remaining oil, and has a wide range of applications. BRIEF DESCRIPTION OF DRAWINGS

[0069] Figure 1 It is a pixel enhancement enlargement method schematic diagram of the 3 mu m precision scanning image in the embodiment 1 of the present application;

[0070] Figure 2 It is a pixel equal proportion enlargement method schematic diagram of the 3 mu m precision scanning image in the embodiment 1 of the present application;

[0071] Figure 3A three-dimensional characterization image of type I remaining oil in the seventh scan of the core provided for the embodiment 1 of the present application;

[0072] Figure 4 A three-dimensional characterization image of type II remaining oil in the seventh scan of the core provided for the embodiment 1 of the present application;

[0073] Figure 5 A three-dimensional characterization image of type III remaining oil in the seventh scan of the core provided for the embodiment 1 of the present application. DETAILED DESCRIPTION

[0074] The technical solutions of the present application will be further described below through specific embodiments. Those skilled in the art should understand that the embodiments are only to help understand the present application and should not be regarded as specific limitations of the present application.

[0075] Embodiment 1

[0076] The present embodiment provides a pore type carbonate rock sub-resolution remaining oil classification and identification method, which comprises the following steps:

[0077] (1) A carbonate rock core with a permeability of 1.02 mD and a helium porosity of 14.2% is cut into a standard rock sample with a diameter of 8 mm and a length of 5 cm, then the core is sequentially subjected to oil removal treatment, drying treatment, and then placed into a core holder and vacuumed, and the vacuumed core is subjected to Micro-CT scanning to obtain a first CT value;

[0078] (2) The vacuumed core in step (1) is used to increase the pore pressure to 8 MPa and the confining pressure to 12 MPa by using a back pressure pump, and then stabilized for 5 h, then a 30% wt KI aqueous solution is used to displace at a rate of 0.01 mL / min to make the core completely saturated, and then stand for 12 h until the water phase and the core reach chemical equilibrium, and then the stood core is subjected to Micro-CT scanning to obtain a second CT value, and then the second CT value is subtracted from the first CT value for difference analysis, and then formula (1) is used for analysis:

[0079] ΔCT 21 = CT2- CT1 (1)

[0080] Wherein, CT1 = 0 indicates that the pores in this area are macroscopic pores (≥ 3 μm); ΔCT 21 = 0 indicates that this area is the rock skeleton; CT1 ≠ 0 and ΔCT 21 ≠ 0 indicates that the pores in this area are sub-resolution pores (< 3 μm);

[0081] (3) the core after standing in step (2) is subjected to an oil flooding water experiment at a constant speed of 0.02 mL / min, the oil flooding water experiment has a ratio of a flooding oil volume to a pore volume of the core of 50:1, then the core is independently subjected to water flooding oil experiments at constant speeds of 0.02 mL / min, 0.05 mL / min, 0.10 mL / min and 0.50 mL / min, the water flooding oil experiments have a ratio of a flooding water volume to a pore volume of the core of 20:1, the core after the oil flooding water experiment and after each water flooding oil experiment is independently subjected to a Micro-CT scanning, and third to seventh CT values are sequentially obtained;

[0082] (4) the second to seventh 3-μm-precision scanning images are subjected to enhancement magnification by using a BiCubic interpolation method, the precision of the scanning images is magnified to 1 μm, 0.1 μm and 0.01 μm respectively, and a pixel point value B(X, Y) of the scanning image after the enhancement magnification is obtained by using a BiCubic base function to weight average 16 pixel points adjacent to the pixel point value in a source image, a relationship between B(X, Y) and A(x i , y j ) is shown in a schematic view as shown in Figure 1

[0083] The BiCubic base function is shown in formula (2):

[0084]

[0085] wherein A(x i , y j ) is a known point value;

[0086] the CT value of the second enhancement magnification scanning image and the CT value of the third to seventh enhancement magnification scanning images are independently subtracted, and formula (3) is used for subtraction analysis:

[0087] ΔCT 2k(jμm) = CT 2(jμm) - CT k(jμm) (3)

[0088] wherein CT k(jμm) represents a CT value of the kth scanning result enhancement magnification to j-μm-precision, k is 3, 4, 5, 6 or 7 respectively; and j represents different precision of magnification, j is 0.01, 0.1 and 1 respectively.

[0089] ​(5) Using the nearest neighbor interpolation method to scale up the second to seventh 3 μm precision scanning images, the precision of the scanning images is scaled up to 1 μm, 0.1 μm and 0.01 μm respectively. The pixel point value B'(X', Y') of the scaled up scanning image is the same as the value of the nearest center pixel point in the source image. The value of each pixel point A'(x', y') in the source image A is known. The relationship between B'(X', Y') and A'(x', y') is shown in the schematic diagram of Figure 2

[0090] The CT values of the second scaled up scanning image and the CT values of the scaled up scanning images of the third to seventh scanning images are independently subtracted, and formula (4) is used for subtraction analysis:

[0091] ΔCT' 2k(jμm) = CT' 2(jμm) - CT' k(jμm) (4)

[0092] Wherein, CT' k(jμm) represents the CT value of the kth scanning result scaled up to j μm precision; k is 3, 4, 5, 6 or 7 respectively; j represents different precision of scaling up, j is 0.01, 0.1 and 1 respectively;

[0093] (6) The analysis in step (6) is to analyze the results of ΔCT 2k(jμm) in formula (3) and ΔCT' 2k(jμm) in formula (4);

[0094] Wherein, ΔCT 2k(jμm) = ΔCT' 2k(jμm) = 0, indicating that the state of rock skeleton or fluid in the pore at this position has not changed, and there is no remaining oil;

[0095] ΔCT 2k(jμm) ≠ 0, indicating that this position contains remaining oil. By comparing the difference between ΔCT 2k(jμm) and ΔCT' 2k(jμm) at different precisions, the classification and identification of remaining oil are carried out:

[0096] 1) |ΔCT 2k(0.01μm) - ΔCT' 2k(0.01μm) | ≤ 5, indicating that the remaining oil in this area is type I remaining oil;

[0097] 2) |ΔCT 2k(0.1μm) - ΔCT' 2k(0.1μm) | ≤ 5, indicating that the remaining oil in this area is type II remaining oil;

[0098] 3) |ΔCT 2k(1μm) - ΔCT' 2k(1μm) ​|≤5, indicating that the remaining oil in this area is type III remaining oil.

[0099] The remaining oil after the seventh scanning is classified and identified by using the pore-type carbonate rock sub-resolution remaining oil classification and identification method provided in Embodiment 1, and type I remaining oil, type II remaining oil and type III remaining oil are respectively identified in different areas of the core (three-dimensional characterization images are respectively as shown in Figures 3-5 The saturations are respectively 3.74%, 12.49% and 14.28%.

[0100] The applicant declares that the detailed structural features of the present application are illustrated by the above embodiments, but the present application is not limited to the above detailed structural features, that is, it does not mean that the present application must rely on the above detailed structural features to be implemented. It should be understood by those skilled in the art that any improvement of the present application, equivalent replacement of the components selected by the present application, increase of auxiliary components, selection of specific modes, etc. fall within the protection scope and disclosure scope of the present application.

Claims

1. A method for classifying and identifying residual oil in porous carbonate rocks at sub-resolution, characterized in that, The classification and recognition method includes the following steps: (1) After cutting the carbonate rock core, it is pre-treated, and the pre-treated core is scanned by Micro-CT to obtain the first CT value; (2) The cores pretreated in step (1) are subjected to pressurization treatment, low-speed displacement with KI aqueous solution and then allowed to stand. The cores after standing are subjected to Micro-CT scanning to obtain the second CT value. The second CT value is compared with the first CT value. (3) An oil-flooding experiment was conducted on the core after step (2) and then four water-flooding experiments were conducted on the core. Micro-CT scans were performed independently on the core after the oil-flooding experiment and after each water-flooding experiment to obtain the third to seventh CT values. (4) The second to seventh scan images were enhanced and magnified using bicubic interpolation. The enhanced and magnified CT values ​​of the second scan image and the enhanced and magnified CT values ​​of the third to seventh scan images were independently subtracted to obtain the difference values. The enhancement and amplification includes: using bicubic interpolation to enhance and amplify the 3μm precision scan images from the second to the seventh scans, and then increasing the pixel values ​​of the enhanced and amplified scan images. It is obtained by weighting the 16 adjacent pixels in the source image using the BiCubic basis function; The BiCubic basis functions are as follows: ； Where a is a constant, -0.5 or -1, for the pixels of this invention. Take its nearest 4×4 neighborhood point A , Calculate according to the following formula (2): （2） The CT values ​​of the second enhanced magnified scan image and the CT values ​​of the third to seventh enhanced magnified scan images were independently subtracted, and the difference analysis was performed using formula (3): （3） in, This indicates that the result of the k-th scan has been enhanced and magnified. The CT value represents the magnification precision, with k being 3, 4, 5, 6, or 7; j represents different magnification precisions, with j being 0.01, 0.1, and 1 respectively. (5) The nearest neighbor interpolation method is used to enlarge the second to seventh scan images proportionally. The proportionally enlarged CT value of the second scan image is independently subtracted from the proportionally enlarged CT value of the third to seventh scan images to obtain the difference value. The proportional magnification includes: using nearest neighbor interpolation to proportionally magnify the 3μm precision scan images from the second to the seventh scans, and then proportionally magnifying the pixel values ​​of the scan images. The value of each pixel in source image A is the same as the value of the nearest center pixel in the source image. It is known; The CT values ​​of the second proportionally magnified scan image and the CT values ​​of the third to seventh proportionally magnified scan images are independently subtracted, and the difference analysis is performed using formula (4): （4） in, This indicates that the result of the k-th scan is proportionally magnified to... The CT value represents the magnification precision; k represents 3, 4, 5, 6, or 7; j represents different magnification precisions, with j being 0.01, 0.1, and 1 respectively; (6) After analyzing the difference between step (4) and step (5), the remaining oil is then classified and identified.

2. The classification and recognition method according to claim 1, characterized in that, The diameter of the carbonate rock core cut in step (1) is 7.5-8.5 mm and the length is 4.5-5.5 cm.

3. The classification and recognition method according to claim 1, characterized in that, The pretreatment in step (1) includes: sequentially performing degreasing, drying and vacuum treatment on the carbonate rock core.

4. The classification and identification method according to claim 1, characterized in that, The pressurization process in step (2) includes: increasing the pore pressure of the core to 7.5-8.5 MPa and the confining pressure to 11.5-12.5 MPa, and stabilizing it for 4-6 hours.

5. The classification and identification method according to claim 1, characterized in that, The concentration of the KI aqueous solution in step (2) is 25-35 wt%.

6. The classification and recognition method according to claim 1, characterized in that, The low-speed displacement rate in step (2) is 0.01-0.03 mL / min.

7. The classification and recognition method according to claim 1, characterized in that, The settling time in step (2) is 10-12 hours.

8. The classification and identification method according to claim 1, characterized in that, The difference analysis in step (2) is performed using formula (1): （1） in, This indicates that the pores in this region are macroscopic pores; This indicates that the area is a rock skeleton; This indicates that the pores in this region are sub-resolution pores.

9. The classification and identification method according to claim 1, characterized in that, The displacement rate of the oil-water displacement experiment in step (3) is 0.01-0.03 mL / min.

10. The classification and recognition method according to claim 1, characterized in that, In step (3), the ratio of the displacement oil volume to the core pore volume in the oil-water flooding experiment is (49-51):

1.

11. The classification and recognition method according to claim 1, characterized in that, The displacement rates of the four water-driven oil experiments in step (3) were independently 0.01-0.03 mL / min, 0.04-0.06 mL / min, 0.09-0.11 mL / min and 0.49-0.52 mL / min, respectively.

12. The classification and recognition method according to claim 1, characterized in that, In step (3), the ratio of the displacement water volume to the core pore volume in the four water-driven oil experiments was (19-21):

1.

13. The classification and recognition method according to claim 1, characterized in that, The analysis described in step (6) is for formula (3) With formula (4) The results were analyzed. in, This indicates that the fluid state in the rock skeleton or pores at that location has not changed and there is no residual oil. This indicates that there is residual oil at that location. This can be determined by comparing different levels of precision. and Based on the differences, residual oil is classified and identified: 1) This indicates that the remaining oil in this area is type I remaining oil; 2) This indicates that the remaining oil in this area is type II remaining oil; 3) This indicates that the remaining oil in this area is type III remaining oil.

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