A method for predicting the viscosity of ground crude oil based on the gray value of wall-core fluorescence images

Abstract

The present invention discloses a method for predicting the viscosity of ground crude oil based on the gray value of the fluorescence image of the oil-bearing core wall. Step 1: Extract the fluorescence main-tone color image from the fluorescence color image of the oil-bearing core wall of the reservoir by color picking. Step 2: Convert the fluorescence main-tone color image into a gray image in the same color mode. Step 3: Extract the gray value from the gray image. Step 4: Obtain the ground crude oil viscosity data of the crude oil sample taken at the same reservoir depth position of the oil-bearing core wall of the reservoir. Step 5: Establish a quantitative characterization equation between the ground crude oil viscosity data and the gray value. Step 6: Predict the ground crude oil viscosity through the regression equation. Compared with the prior art, the present invention realizes the quantitative prediction of the ground viscosity data of crude oil at the same depth position through the fluorescence image of the oil-bearing core wall.

Description

Technical Field

[0001] The present invention relates to the technical field of oil and gas field development, and particularly to a method for predicting the ground crude oil viscosity. Background Art

[0002] The ground crude oil viscosity is one of the important parameters for evaluating the fluid properties of crude oil. Currently, in the exploration evaluation stage and the reserve evaluation stage, the evaluation of the reservoir crude oil fluid properties for most structures is carried out by taking crude oil samples for laboratory tests to obtain the ground crude oil viscosity data. However, the sampling of crude oil samples involves certain sampling costs. Therefore, for oil companies, crude oil samples are not taken for every exploration well or evaluation well. How to quantitatively evaluate the reservoir crude oil fluid properties without obtaining crude oil fluid samples has become a production problem.

[0003] During the on-site drilling process, oil-bearing core samples are generally taken at the depth positions with oil and gas logging shows. The oil-bearing core samples will complete the acquisition of fluorescence color images in the laboratory. How to make full use of the fluorescence image data of the oil-bearing cores, excavate valuable color parameters from the images, establish the correlation between the color parameters and the ground viscosity of crude oil, and achieve quantitative evaluation is a research direction with high difficulty. Summary of the Invention

[0004] In order to overcome the technical problems existing in the prior art, the present invention proposes a method for predicting the ground crude oil viscosity based on the gray value of the core fluorescence image. By processing the color of the fluorescence image of the reservoir oil-bearing core, a regression formula between the gray value of the gray image and the ground viscosity of crude oil is established, and the ground viscosity data of crude oil at the same depth position can be quantitatively predicted through the fluorescence image of the oil-bearing core.

[0005] The present invention is realized by the following technical solutions:

[0006] A method for predicting the ground crude oil viscosity based on the gray value of the core fluorescence image, the method comprising the following steps:

[0007] Step 1, extracting the fluorescence main tone color image from the fluorescence color image of the reservoir oil-bearing core;

[0008] Step 2, converting the fluorescence main tone color image into a gray image in the same color mode;

[0009] Step 3, extracting the gray value from the gray image;

[0010] Step 4, obtaining the ground crude oil viscosity data of the crude oil sample taken at the same reservoir depth position of the reservoir oil-bearing core;

[0011] Step 5, establishing a regression equation between the ground crude oil viscosity data and the gray value, and the expression is as follows:

[0012]

[0013] Among them, μ is the ground viscosity of crude oil, M is the gray value, and b1 and b2 are both regression coefficients;

[0014] Step 6: Predict the ground crude oil viscosity through the regression equation.

[0015] In the said Step 5, linear regression is performed on the data of the reservoir oil-bearing wall core sample points to obtain the regression coefficients b1 and b2.

[0016] In the said Step 6, if a fluorescence image of an oil-bearing wall core is obtained at a certain point in the reservoir, the gray value of the gray image of the oil-bearing wall core can be obtained through Steps 1 to 3, and the gray value is substituted into Equation (1) to calculate the ground crude oil viscosity data at the sampling depth position of the oil-bearing wall core.

[0017] In the said Step 1, the fluorescence color image of the reservoir oil-bearing wall core is obtained by collecting an image of a certain end face in the original state of the oil-bearing wall core at a certain reservoir depth position.

[0018] Compared with the prior art, the present invention can achieve the following beneficial technical effects:

[0019] 1) The coefficient is relatively high, and it realizes the quantitative prediction of the ground crude oil viscosity data at the same depth position through the fluorescence image of the oil-bearing wall core;

[0020] 2) It can be used as a quality control means for the accuracy of the ground viscosity test data of crude oil samples;

[0021] 3) Even when no crude oil sample is obtained on site, reservoir researchers can also quantitatively evaluate the fluid properties of the reservoir crude oil through the technology of the present invention.

[0022] 4) The technical operation is simple and practical, which can save a large amount of sampling costs of crude oil samples for oil enterprises and can generate greater economic benefits. Description of the Drawings

[0023] Figure 1 It is the overall flow chart of a method for predicting the ground crude oil viscosity based on the gray value of the fluorescence image of the wall core;

[0024] Figure 2Schematic diagram of the fluorescence color image of the oil-bearing core in the mining area according to the embodiment of the present invention; (a) 50°C - ground viscosity: 2.117 mPa·s, (b) 50°C - ground viscosity: 3.072 mPa·s, (c) 50°C - ground viscosity: 5.502 mPa·s, (d) 50°C - ground viscosity: 5.54 mPa·s, (e) 50°C - ground viscosity: 7.731 mPa·s, (f) 50°C - ground viscosity: 39.66 mPa·s, (g) 50°C - ground viscosity: 95.05 mPa·s, (h) 50°C - ground viscosity: 291.6 mPa·s, (i) 50°C - ground viscosity: 497.4 mPa·s, (j) 50°C - ground viscosity: 439.3 mPa·s;

[0025] Figure 3 Schematic diagram of the display of the fluorescence main color image of the oil-bearing core in the mining area according to the embodiment of the present invention;

[0026] Figure 4 Schematic diagram of the display of the fluorescence grayscale image of the oil-bearing core in the mining area according to the embodiment of the present invention;

[0027] Figure 5 Regression diagram of ground crude oil viscosity and grayscale value. Detailed implementation mode

[0028] The technical solution of the present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0029] As Figure 1 shown, it is the overall flow chart of a method for predicting the ground crude oil viscosity based on the grayscale value of the core fluorescence image. The method includes the following steps:

[0030] Step 1, extract the fluorescence main color image from the fluorescence color image of the oil-bearing core in the reservoir by color picking;

[0031] Step 2, convert the fluorescence main color image into a grayscale image in the same color mode through decolorization processing;

[0032] Step 3, extract the grayscale value from the grayscale image;

[0033] Step 4, conduct chemical analysis on the crude oil samples collected at the same reservoir depth position as the reservoir core to obtain the ground crude oil viscosity data;

[0034] Step 5, establish a quantitative characterization equation between the ground crude oil viscosity data and the grayscale value, and the expression is as follows:

[0035]

[0036] Among them, μ is the ground viscosity of crude oil (unit: mPa·s), M is the grayscale value (dimensionless), and b1 to b2 are regression coefficients (dimensionless);

[0037] Step 6: Predict the ground viscosity of crude oil through a quantitative characterization equation.

[0038] Among them, in the said Step 5, a quantitative characterization equation between the ground viscosity data of crude oil and the grayscale value is established, and its relationship characterization equation is as follows:

[0039] In the said Step 5, the regression coefficients b1 and b2 obtained based on the sample data are used for power function regression on Equation (1), and b1 and b2 of Equation (1) can be obtained;

[0040] In the said Step 6, if a fluorescence image of an oil-bearing core wall is obtained at a certain point in the reservoir, the grayscale value of the grayscale image of the oil-bearing core wall can be obtained through Steps 1 to 3, and the grayscale value is substituted into Equation (1), and the ground viscosity data of the crude oil at the sampling depth position of the oil-bearing core wall can be calculated.

[0041] Among them, in the said Step 1, the color extraction process of the fluorescence color image of the oil-bearing core wall of the reservoir can be realized through the color extraction function of image processing software including but not limited to Photoshop, extract the main fluorescence color, and fill it into a new document to obtain a main fluorescence color image;

[0042] Among them, in the said Step 2, the color removal process of the main fluorescence color image can be realized through the color removal function of image processing software including but not limited to Photoshop, and convert the main fluorescence color image into a grayscale image in the same color mode;

[0043] Among them, in the said Step 3, when extracting the grayscale value of the grayscale image, in the RGB color mode, the values of R, G, and B of the grayscale image are the same, and this value is taken as the grayscale value of the grayscale image;

[0044] Among them, in the said Step 4, the crude oil sample and the oil-bearing core wall sample of the reservoir must be obtained at the same depth position in the reservoir, conduct tests on the crude oil sample, and obtain the ground viscosity data;

[0045] An example of the embodiment of the present invention is the fluorescence color image of an oil-bearing core wall at a certain depth position of an oil reservoir in a mining area:

[0046] In the said Step 1, the fluorescence color image of the oil-bearing core wall is obtained by collecting an image of a certain end face in the original state of the oil-bearing core wall. The color extraction process of the fluorescence color image of the oil-bearing core wall of the reservoir can be realized through the color extraction function of image processing software including but not limited to Photoshop, extract the main fluorescence color, and fill it into a new document to obtain a main fluorescence color image;

[0047] As shown Figure 2 in the figure, it is a fluorescence color image of the oil-bearing wall core in the mining area according to an embodiment of the present invention; (a) 50°C - ground viscosity: 2.117 mPa·s, (b) 50°C - ground viscosity: 3.072 mPa·s, (c) 50°C - ground viscosity: 5.502 mPa·s, (d) 50°C - ground viscosity: 5.54 mPa·s, (e) 50°C - ground viscosity: 7.731 mPa·s, (f) 50°C - ground viscosity: 39.66 mPa·s, (g) 50°C - ground viscosity: 95.05 mPa·s, (h) 50°C - ground viscosity: 291.6 mPa·s, (i) 50°C - ground viscosity: 497.4 mPa·s, (j) 50°C - ground viscosity: 439.3 mPa·s; The color sampling is achieved through the color sampling function of image processing software including but not limited to Photoshop. Taking Photoshop software as an example, import the fluorescence color image of the oil-bearing wall core, use the eyedropper tool, select the sampling size of the eyedropper tool as 3×3 average, use the eyedropper tool to absorb the main fluorescence color on the fluorescence color image of the oil-bearing wall core. The selection of the main color should be made from the area where the fluorescence shows continuous and stable distribution within the field of view. It can be selected multiple times, and after careful comparison, select the main color of the fluorescence color image of the oil-bearing wall core. It is a schematic diagram of color sampling processing using image processing software. It includes the position of the color sampling point. After the eyedropper tool absorbs the color, the software defaults to the foreground color. By creating a new document (shortcut key CTRL+N), fill the newly absorbed foreground color into the new document (shortcut key ALT+DELETE) to obtain the main fluorescence color image, as Figure 3 shown in the figure, it is a schematic diagram of the display of the main fluorescence color image of the oil-bearing wall core in the mining area according to an embodiment of the present invention, with R value of 181, G value of 153, and B value of 79;

[0048] In step 2, perform desaturation processing on the main fluorescence color image, which is achieved through the desaturation function of image processing software including but not limited to Photoshop. Taking Photoshop software as an example, convert the main fluorescence color image into a grayscale image in the same color mode (shortcut key CTRL+SHIFT+U). In the RGB color mode, the R value is 130, the G value is 130, and the B value is 130. As Figure 4 shown in the figure, it is a schematic diagram of the display of the grayscale image of the fluorescence color image of the oil-bearing wall core in the mining area according to an embodiment of the present invention.

[0049] In step 3, extract the grayscale value from the grayscale image. Taking Photoshop software as an example, in the RGB color mode, the R, G, and B values of the grayscale image are the same, all being 130, and this value is taken as the grayscale value of the grayscale image;

[0050] In step 4, the crude oil sample and the oil-bearing core sample of the reservoir must be obtained at the same depth position in the reservoir. The crude oil sample is tested to obtain the ground viscosity data of 95.05 mPa·s. At this time, a corresponding relationship is established between the gray value of the fluorescence gray-scale image of the oil-bearing core at this point and the ground viscosity data.

[0051] In step 5, all the oil-bearing core samples and crude oil samples with corresponding relationships within the mining area are summarized and sorted according to steps 1 to 4 to obtain the mining area sample point data shown in Table 1. This data includes ground viscosity, fluorescence main color tone color image parameters (i.e., R, G, B values), and gray-scale image parameters, namely gray values.

[0052] Table 1

[0053]

[0054] Establish a regression formula for the ground crude oil viscosity data and gray values in the mining area. Its relationship characterization equation is as follows:

[0055] μ = 2×10 17 ×M -7.373 (1)

[0056] Where, μ is the ground viscosity of the crude oil (unit: mPa·s), M is the gray value (dimensionless), and the regression coefficients are: b1 = 2×10 17 , b2 = -7.373.

[0057] As Figure 5 shown, it is the linear regression diagram of the ground crude oil viscosity and gray value of the embodiment of the present invention.

[0058] In step 6, if a fluorescence image of an oil-bearing core is obtained at a certain point in the reservoir, the gray value of the gray-scale image of the oil-bearing core can be obtained through steps 1 to 3, and substituting the gray value into formula (1), the ground viscosity data of the crude oil at the sampling depth position of the oil-bearing core can be calculated.

[0059] The above is only the specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by those skilled in the art within the technical scope disclosed in the embodiments of the present invention should be covered by the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.

Claims

1. A method for predicting the viscosity of ground crude oil based on the gray value of the fluorescence image of the wall center, characterized in that, The method comprises the following steps: Step 1, extract the fluorescence main tone color image from the fluorescence color image of the oil-bearing core wall of the reservoir; Step 2, convert the fluorescence main tone color image into a grayscale image in the same color mode; Step 3, extract the grayscale value from the grayscale image; Step 4, obtain the ground crude oil viscosity data of the crude oil sample taken at the same reservoir depth position of the oil-bearing core wall of the reservoir; Step 5, establish a regression equation between the ground crude oil viscosity data and the grayscale value, and the expression is as follows: （1） Among them, is the ground viscosity of crude oil, is the gray value, , are both regression coefficients; Step 6, perform ground crude oil viscosity prediction through the regression equation. If a fluorescence image of the oil-bearing core wall is obtained at a certain point in the reservoir, the grayscale value of the grayscale image of the oil-bearing core wall can be obtained through Steps 1 to 3, and the grayscale value is substituted into Equation (1) to calculate the ground crude oil viscosity data at the sampling depth position of the oil-bearing core wall.

2. A method for predicting the ground crude oil viscosity based on the grayscale value of the fluorescence image of the core wall as claimed in claim 1, It is characterized in that In the said step 5, linear regression is performed on the data of the reservoir oil-bearing core sample points to obtain the regression coefficients , .

3. A method for predicting the ground crude oil viscosity based on the grayscale value of the fluorescence image of the core wall as claimed in claim 1, It is characterized in that In Step 6, if a fluorescence image of the oil-bearing core wall is obtained at a certain point in the reservoir, the grayscale value of the grayscale image of the oil-bearing core wall can be obtained through Steps 1 to 3, and the grayscale value is substituted into Equation (1) to calculate the ground crude oil viscosity data at the sampling depth position of the oil-bearing core wall.

4. A method for predicting the ground crude oil viscosity based on the grayscale value of the fluorescence image of the core wall as claimed in claim 1, It is characterized in that In Step 1, the fluorescence color image of the oil-bearing core wall of the reservoir is obtained by collecting an image of a certain end face in the original state of the oil-bearing core at a certain reservoir depth position.

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