A quantitative evaluation method, storage medium and system for low-permeability reservoir permeability based on resistivity radial detection difference

Abstract

The present invention discloses a method, a storage medium and a system for quantitatively evaluating the permeability of a low-permeability reservoir based on the radial detection difference of resistivity. Core samples at different depths of the low-permeability reservoir in an oil and gas field are drilled; according to the distribution range of the characteristic values of the square of the ratio of the deep resistivity to the shallow resistivity at the corresponding depths of the core samples, the core samples are classified and the functional relationship between the core porosity and the core permeability of each type of core sample is obtained; the logging data of the low-permeability reservoir are measured to obtain the logging porosity, and the logging porosity and the calculation model of the low-permeability reservoir are determined; the logging data of the low-permeability reservoir of a new well drilled in the oil and gas field are measured, and the logging porosity of the new well is obtained according to the calculation model; the low-permeability reservoir of the new well is classified; the permeability of each type of low-permeability reservoir is calculated respectively based on the classified types of the low-permeability reservoir of the new well, that is, the evaluation of the permeability of the low-permeability reservoir in the entire well section of the new well is realized. The present invention can accurately calculate the permeability of deep and ultra-deep low-permeability reservoirs.

Description

Technical Field

[0001] The present invention relates to a method, a storage medium and a system for quantitatively evaluating the permeability of a low-permeability reservoir based on the radial detection difference of resistivity, and belongs to the technical field of quantitative evaluation of the permeability of a low-permeability reservoir. Background Technique

[0002] With the continuous development of oil and gas exploration and development towards deeper and ultra-deeper layers, low-permeability reservoirs (permeability less than 50 mD) have gradually become an important area for increasing reserves and production. Among them, permeability is a key parameter for evaluating the physical properties and productivity of low-permeability reservoirs. Therefore, the quantitative evaluation of the permeability of low-permeability reservoirs has always been the focus and difficulty of research in the industry.

[0003] At present, there are two major categories of quantitative evaluation methods for permeability:

[0004] The first category is based on the porosity and permeability analyzed by rock physics experiments, establishing a high-precision functional relationship between the core-analyzed porosity and permeability, using the porosity calculated by logging as a bridge, and further calculating the permeability by using the porosity calculated by logging. Due to the complex pore structure of low-permeability reservoirs, it is necessary to divide each type of low-permeability reservoir based on the difference in pore structure, and then in each type of low-permeability reservoir, based on the high-precision functional relationship between the core-analyzed porosity and permeability, using the porosity calculated by logging as a bridge, and calculating the permeability by using the porosity calculated by logging. However, conventional classification methods are either difficult to classify accurately or difficult to promote and apply.

[0005] The second category is based on nuclear magnetic resonance logging, and the permeability is calculated by using the free fluid model and the average T2 model;

[0006] In the free fluid model, the calculation formula for permeability is:

[0007]

[0008] In the formula: K is the permeability, mD; is the porosity, in decimals; C is an empirical constant, dimensionless; FFI is the pore volume of free fluid, %; BVI is the pore volume of bound water, %.

[0009] In the average T2 model, the calculation formula for permeability is:

[0010]

[0011] In the formula: K is the permeability, mD; a is an empirical constant, dimensionless; T 2gm is the geometric mean of the T2 distribution, ms; is the porosity, in decimals.

[0012] In low-permeability reservoirs, since the empirical constants in the above formulas (1) and (2) cannot be accurately determined, the errors of the permeabilities calculated by formulas (1) and (2) are relatively large.

[0013] Therefore, for low-permeability reservoirs, a quantitative evaluation method for permeability is formed, which lays an important foundation for evaluating the physical properties of low-permeability reservoirs and predicting the productivity of low-permeability reservoirs, thereby effectively improving the exploration and development benefits of deep and ultra-deep low-permeability oil and gas reservoirs. Summary of the Invention

[0014] The object of the present invention is to provide a quantitative evaluation method for the permeability of low-permeability reservoirs based on the difference in resistivity radial detection, which can accurately calculate the permeability of deep and ultra-deep low-permeability reservoirs.

[0015] The quantitative evaluation method for the permeability of low-permeability reservoirs based on the difference in resistivity radial detection provided by the present invention includes the following steps:

[0016] S1. Drill core samples at different depths of the low-permeability reservoir in the oil and gas field, and measure the deep resistivity and shallow resistivity at the corresponding depths of the core samples;

[0017] S2. Make the core samples into cast thin sections, test the capillary pressure of the core samples to obtain a capillary pressure curve; based on the pore structure of the cast thin sections and the capillary pressure curve, according to the distribution range of the characteristic values of the square of the ratio of the deep resistivity to the shallow resistivity at the corresponding depths of the core samples, divide the core samples into n categories, and obtain the functional relationship between the core porosity and the core permeability of each category of core samples;

[0018] n is usually a number between 3 and 6;

[0019] S3. Measure the logging data of the low-permeability reservoir in the oil and gas field, obtain the logging porosity according to the logging data, and minimize the error between the logging porosity and the core porosity obtained in step S2, and then determine the logging porosity and calculation model of the low-permeability reservoir in the oil and gas field;

[0020] S4. Measure the logging data of the low-permeability reservoir of a new well drilled in the oil and gas field, and obtain the logging porosity of the new well according to the calculation model obtained in step S3; use the characteristic value of the square of the ratio of the deep resistivity to the shallow resistivity to divide the types of the low-permeability reservoir of the new well;

[0021] S5. Based on the results of the types of the low-permeability reservoir of the new well divided in step S4, calculate the permeabilities K1, K2... K of the first type, the second type until the nth type of low-permeability reservoirs respectively; n ;

[0022] S6. Based on the logging permeabilities of different types of low-permeability reservoirs in the newly drilled well obtained in step S5, the combination of the logging permeabilities of different types of low-permeability reservoirs realizes the quantitative evaluation of the permeability of low-permeability reservoirs in the entire well section of the newly drilled well.

[0023] In the above quantitative evaluation method, the logging data includes natural gamma, deep resistivity, shallow resistivity, bulk density, neutron porosity, and compressional wave transit time, etc.

[0024] In the above quantitative evaluation method, in step S2, the accuracy R of the functional relationship is greater than 0.8.

[0025] The present invention also provides a computer storage medium, on which a computer program is stored. When the computer program is executed by a processor, the quantitative evaluation method of the present invention is realized.

[0026] The present invention further provides a system for quantitatively evaluating the permeability of low-permeability reservoirs, including a processor and a memory storing a computer program; the processor is configured to execute the computer program to realize the quantitative evaluation method of the present invention.

[0027] Due to the above technical solutions adopted by the present invention, it has the following advantages:

[0028] 1. The method of the present invention avoids carrying out a large number of petrophysical experiments and collecting a series of high-end logging series, can effectively save costs, improve the efficiency of exploration and development of low-permeability oil and gas reservoirs, and has strong economic viability.

[0029] 2. While ensuring accurate calculation of the permeability of deep and ultra-deep low-permeability reservoirs, the method of the present invention provides an effective, simple and practical new method. Description of the Drawings

[0030] Figure 1 It is the pore structure shown by the cast thin section and capillary pressure curve of the first type of low-permeability reservoir in the S oilfield;

[0031] Figure 2 It is the pore structure shown by the cast thin section and capillary pressure curve of the second type of low-permeability reservoir in the S oilfield;

[0032] Figure 3 It is the pore structure shown by the cast thin section and capillary pressure curve of the third type of low-permeability reservoir in the S oilfield;

[0033] Figure 4 It is a schematic diagram of the deep resistivity, shallow resistivity and mud invasion degree of the low-permeability reservoir in the S oilfield;

[0034] Figure 5 It is a crossplot of core porosity and core permeability of the first type of low-permeability reservoir in the S oilfield;

[0035] Figure 6 It is a cross-plot of core porosity and core permeability of the second type of low-permeability reservoir in the S Oilfield;

[0036] Figure 7 It is a cross-plot of core porosity and core permeability of the third type of low-permeability reservoir in the S Oilfield;

[0037] Figure 8 It is a quantitative evaluation result map of the permeability of the new drilled well F low-permeability reservoir in the S Oilfield. Specific Embodiments

[0038] Unless otherwise specified, the experimental methods used in the following embodiments are all conventional methods.

[0039] Unless otherwise specified, the materials, reagents, etc. used in the following embodiments can all be obtained from commercial channels.

[0040] The quantitative evaluation method of low-permeability reservoir permeability based on resistivity radial detection difference provided by the present invention includes the following steps:

[0041] 1) For the low-permeability reservoir of a certain oil and gas field, a series of logging data (natural gamma, spontaneous potential, deep resistivity, shallow resistivity, bulk density, neutron porosity, compressional wave slowness, etc.) are measured by a logging instrument; core samples are drilled from the low-permeability reservoir of the oil and gas field at a certain depth, and the deep resistivity (RD) and shallow resistivity (RS) at the corresponding depth of the core samples are recorded.

[0042] 2) For the low-permeability reservoir of the oil and gas field, rock physical properties, cast thin section and capillary pressure experiments are carried out on the core samples; among them, the rock physical property experiment can measure the porosity and permeability of each core sample in the low-permeability reservoir, that is, the core porosity and the core permeability (K c ); the cast thin section can show the pore structure of the low-permeability reservoir, and the capillary pressure can characterize the pore structure of the low-permeability reservoir.

[0043] 3) Based on the cast thin section and capillary pressure curve of the core samples of the low-permeability reservoir in the oil and gas field in step 2), the low-permeability reservoir can be divided into n categories. According to the distribution range of the eigenvalue of the square of the ratio of the deep resistivity (RD) to the shallow resistivity (RS) ((RD / RS) f 2 ) of the core samples corresponding to the depth of the low-permeability reservoir in the oil and gas field, the eigenvalue of the square of the ratio of the deep resistivity (RD) to the shallow resistivity (RS) ((RD / RS) f 2 ) of the core samples is divided into n categories, and the accuracy R of the functional relationship between the core porosity and the core permeability in each category is ensured to be greater than 0.8.

[0044] The first category: the eigenvalue (RD / RS) of the square of the ratio of deep resistivity (RD) to shallow resistivity (RS) f 2 >n1, the functional relationship between core porosity and core permeability is as follows:

[0045]

[0046] Where: K c1 is the core permeability of the first type of low-permeability reservoir, mD; is the core porosity, in decimals.

[0047] The second category: the eigenvalue n2 of the square of the ratio of deep resistivity (RD) to shallow resistivity (RS) < (RD / RS) f 2 ≤n1, the functional relationship between core porosity and core permeability is as follows:

[0048]

[0049] Where: K c2 is the core permeability of the second type of low-permeability reservoir, mD; is the core porosity, in decimals.

[0050] And so on, until the nth category: the eigenvalue n of the square of the ratio of deep resistivity (RD) to shallow resistivity (RS) n < (RD / RS) f 2 ≤n2, the functional relationship between core porosity and core permeability is as follows:

[0051]

[0052] Where: K cn is the core permeability of the nth type of low-permeability reservoir, mD; is the core porosity, in decimals.

[0053] 4) Based on the logging data such as natural gamma, deep resistivity, shallow resistivity, bulk density, neutron porosity, and compressional wave slowness of the low-permeability reservoir in this oil and gas field obtained in step 1), calculate the rock mineral component content and porosity of the low-permeability reservoir, that is, the logging porosity And make the porosity calculated by logging and the core porosity measured experimentally in step 2 have the minimum error, so as to determine the calculation model of the logging porosity of the low-permeability reservoir in this oil and gas field.

[0054] 5) For the low-permeability reservoir of a new well in this oil and gas field, logging instruments can measure the logging data of the new well: natural gamma, deep resistivity, shallow resistivity, bulk density, neutron porosity, compressional wave slowness, etc.; using the calculation model of the logging porosity of the low-permeability reservoir in this oil and gas field determined in step 4), the logging porosity of this new well can be calculated.

[0055] In addition, the eigenvalue of the square of the ratio of deep resistivity (RD) to shallow resistivity (RS) ((RD / RS) f 2 ) is used to divide the types of low-permeability reservoirs in the new well. When the eigenvalue of the square of the ratio of deep resistivity (RD) to shallow resistivity (RS) (RD / RS) f 2 > n1, it is the first type of low-permeability reservoir; when the eigenvalue of the square of the ratio of deep resistivity (RD) to shallow resistivity (RS) n2 < (RD / RS) f 2 ≤ n1, it is the second type of low-permeability reservoir; and so on. When the eigenvalue of the square of the ratio of deep resistivity (RD) to shallow resistivity (RS) n n < (RD / RS) f 2 ≤ n2, it is the nth type of low-permeability reservoir.

[0056] 6) Based on the results of the types of low-permeability reservoirs in the new well divided in step 5), the permeabilities K1, K2... K of the first type, the second type until the nth type of low-permeability reservoirs are calculated respectively using equations (1), (2)... equation (n), where n

[0057]

[0058]

[0059] ………

[0060]

[0061] In the formula: K1, K2... K n are the logging permeabilities of the first type, the second type, the nth type of low-permeability reservoirs respectively, mD; is the core porosity, in decimals; is the logging porosity, in decimals;

[0062] 7) Based on the logging permeabilities of different types of low-permeability reservoirs in the new well obtained in step 6), the combination of the logging permeabilities of different types of low-permeability reservoirs completes the quantitative evaluation of the permeability of the low-permeability reservoir in the entire well section of the new well, as shown in the formula:

[0063] ​​K = K1 + K2 + K3(n + 4)

[0064] Where: K is the total permeability, mD; K1, K2... K n are the logging permeabilities of the first type, second type... nth type of low-permeability reservoirs respectively, mD.

[0065] Taking the low-permeability reservoirs in S Oilfield as an example, the specific process of the quantitative evaluation method for the permeability of low-permeability reservoirs based on the resistivity radial detection difference of the present invention will be elaborated in detail with reference to the attached drawings.

[0066] 1) For the low-permeability reservoirs in S Oilfield, core samples at a certain depth of the low-permeability reservoirs in S Oilfield are drilled, and rock physical properties, cast thin sections and capillary pressure experiments are carried out on the core samples; among them, the rock physical property experiment can measure the porosity and permeability of each core sample, that is, the core porosity and the core permeability (K c ); the cast thin section can show the pore structure, and the capillary pressure can characterize the pore structure.

[0067] 2) The cast thin sections and capillary pressure curves of three core samples with different pore structures in the low-permeability reservoirs of S Oilfield are shown in Figure 1 , Figure 2 and Figure 3 respectively, where Figure 1 is the first type of low-permeability reservoir, with the best pore structure quality and reservoir physical properties (permeability is 41.78 mD); Figure 2 is the second type of low-permeability reservoir, with medium pore structure quality and reservoir physical properties (permeability is 1.23 mD); Figure 3 is the third type of low-permeability reservoir (permeability is 0.17 mD), with the worst pore structure quality and reservoir physical properties.

[0068] 3) For the low-permeability reservoirs in S Oilfield, a series of logging data can be obtained by the logging instrument measuring the low-permeability reservoirs in each well: natural gamma, deep resistivity, shallow resistivity, bulk density, neutron porosity, longitudinal wave travel time, etc.; the schematic diagram of the deep resistivity, shallow resistivity and mud invasion degree of the low-permeability reservoirs in S Oilfield is shown in Figure 4 .

[0069] 4) Based on the cast thin sections and capillary pressure curves of the core samples of the low-permeability reservoirs in S Oilfield in step 2), the low-permeability reservoirs can be divided into three categories; therefore, according to the eigenvalue (RD / RS) f 2 of the square of the ratio of the deep resistivity (RD) to the shallow resistivity (RS) of the core samples corresponding to the depth of the low-permeability reservoirs in S Oilfield, the eigenvalue (RD / RS) f 2Divide them into three categories and ensure that the accuracy R of the functional relationship between core porosity and core permeability in each category is greater than 0.8.

[0070] The first category: the eigenvalue of the square of the ratio of deep resistivity (RD) to shallow resistivity (RS) (RD / RS) f 2 > 2.0, the functional relationship between core porosity and core permeability is as follows (see Figure 5 ):

[0071]

[0072] Where: K c1 is the core permeability of the first type of low-permeability reservoir, mD; is the core porosity, in decimals.

[0073] The second category: the eigenvalue of the square of the ratio of deep resistivity (RD) to shallow resistivity (RS) 1.5 <(RD / RS) f 2 ≤ 2.0, the functional relationship between core porosity and core permeability is as follows (see Figure 6 ):

[0074]

[0075] Where: K c2 is the core permeability of the second type of low-permeability reservoir, mD; is the core porosity, in decimals.

[0076] The third category: the eigenvalue of the square of the ratio of deep resistivity (RD) to shallow resistivity (RS) 1.0 <(RD / RS) f 2 ≤ 1.5, the functional relationship between core porosity and core permeability is as follows (see Figure 7 ):

[0077]

[0078] Where: K c3 is the core permeability of the third type of low-permeability reservoir, mD; is the core porosity, in decimals.

[0079] 5) Based on the logging data such as natural gamma, deep resistivity, shallow resistivity, bulk density, neutron porosity, and compressional wave slowness of the low-permeability reservoir in the S Oilfield obtained in step 3), the rock mineral component content and porosity of the low-permeability reservoir can be calculated, that is, the logging porosity And make the porosity calculated by logging and the core porosity obtained from the experimental measurement in step 1) The error is minimized, thus determining the logging porosity calculation model for the low-permeability reservoir in the S Oilfield. The calculation model.

[0080] 6) For the low-permeability reservoir of a new well F in the S Oilfield, the logging instrument can measure the logging data of the new well F: natural gamma, deep resistivity, shallow resistivity, bulk density, neutron porosity, compressional wave slowness, etc.; using the logging porosity calculation model for the low-permeability reservoir in the S Oilfield determined in step 5), the logging porosity of the new well F can be calculated.

[0081] In addition, the eigenvalue of the square of the ratio of deep resistivity (RD) to shallow resistivity (RS) ((RD / RS) f 2 ) is used to divide the types of low-permeability reservoirs in the new well. When the eigenvalue of the square of the ratio of deep resistivity (RD) to shallow resistivity (RS) (RD / RS) f 2 > 2.0, it is the first type of low-permeability reservoir; when 1.5 < (RD / RS) f 2 ≤ 2.0, it is the second type of low-permeability reservoir; when 1.0 < (RD / RS) f 2 ≤ 1.5, it is the third type of low-permeability reservoir.

[0082] 7) Based on the result of dividing the types of low-permeability reservoirs in the new well F in step 6), the permeabilities K1, K2, and K3 of the first, second, and third types of low-permeability reservoirs are calculated respectively using equations (1), (2), and (3), where

[0083]

[0084]

[0085]

[0086] In the formula: K1, K2, and K3 are the logging permeabilities of the first, second, and third types of low-permeability reservoirs, mD; is the core porosity, in decimal; is the logging porosity, in decimal;

[0087] 8) Based on the logging permeabilities of different types of low-permeability reservoirs in the new well F obtained in step 7), the combination of the logging permeabilities of different types of low-permeability reservoirs, the quantitative evaluation of the permeability of the low-permeability reservoir in the entire well section of the new well F is completed, as shown in the formula:

[0088] K = K1 + K2 + K3 (7)

[0089] Where: K is the total permeability, mD; K1, K2, and K3 are the logging permeabilities of the first, second, and third types of low-permeability reservoirs, respectively, mD.

[0090] As Figure 8 shown, in the quantitative evaluation result diagram of the permeability of the low-permeability reservoir in some intervals of the new well F, the first track is the depth; the second track is the natural gamma ray, spontaneous potential, and caliper logging curves, indicating the lithological characteristics of the formation; the third track is the deep and shallow resistivity logging curves, depicting the electrical characteristics of the formation; the fourth track is the bulk density, neutron porosity, and compressional wave slowness logging curves, reflecting the physical properties of the formation; the fifth track is the classification result of the low-permeability reservoir; the sixth track is the porosity from core analysis of the low-permeability reservoir and the porosity calculated by logging; the seventh track is the permeability from core analysis of the low-permeability reservoir and the permeability calculated by logging using the original method (referring to the logging permeability calculated before classification according to the method of the present invention), and there is a large error between the two; the eighth track is the permeability from core analysis of the low-permeability reservoir and the permeability calculated by logging using the method of the present invention, and there is a small error between the two; the ninth track is the lithological profile calculated by logging of the low-permeability reservoir, the contents of sandstone and mudstone; the tenth track is the lithological profile shown by mud logging of the low-permeability reservoir; the eleventh track is the comprehensive logging interpretation conclusion.

[0091] It can be seen from the above analysis results that the method of the present invention can accurately calculate the permeability of deep and ultra-deep low-permeability reservoirs.

Claims

1. A quantitative evaluation method for the permeability of low-permeability reservoirs based on the radial detection difference of resistivity, comprising the following steps: S1. Drill core samples at different depths of the low-permeability reservoir in the oil and gas field, and measure the deep resistivity and shallow resistivity at the corresponding depths of the core samples; S2. Make the core samples into cast thin sections, and test the capillary pressure of the core samples to obtain a capillary pressure curve; based on the pore structure of the cast thin sections and the capillary pressure curve, according to the distribution range of the characteristic values of the square of the ratio of the deep resistivity to the shallow resistivity at the corresponding depths of the core samples, divide the core samples into n categories, and obtain the functional relationship between the core porosity and the core permeability of each category of core samples; S3. Measure the logging data of the low-permeability reservoir in the oil and gas field, obtain the logging porosity according to the logging data, and minimize the error between the logging porosity and the core porosity obtained in step S2, so as to determine the logging porosity and calculation model of the low-permeability reservoir in the oil and gas field; S4. Measure the logging data of the low-permeability reservoir of a new well drilled in the oil and gas field, and obtain the logging porosity of the new well according to the calculation model obtained in step S3; use the characteristic value of the square of the ratio of the deep resistivity to the shallow resistivity to divide the types of the low-permeability reservoir of the new well; S5. Based on the results of the new drilled low-permeability reservoir types divided in step S4, calculate the permeability K1, K2... Kn of the first type, the second type until the nth type of low-permeability reservoir respectively n ; S6. Based on the logging permeabilities of different categories of low-permeability reservoirs in the new well obtained in step S5, the combination of the logging permeabilities of different categories of low-permeability reservoirs realizes the quantitative evaluation of the permeability of the low-permeability reservoir in the entire well section of the new well.

2. The quantitative evaluation method according to claim 1, wherein: The logging data includes natural gamma, deep resistivity, shallow resistivity, bulk density, neutron porosity, and compressional wave slowness.

3. The quantitative evaluation method according to claim 1 or 2, characterized in that: In step S2, the accuracy R of the functional relationship is greater than 0.

8.

4. A computer storage medium, characterized in that: The computer storage medium stores a computer program, and when the computer program is executed by a processor, it implements the quantitative evaluation method according to any one of claims 1-3.

5. A system for quantitatively evaluating the permeability of low-permeability reservoirs, comprising a processor and a memory storing a computer program; the processor is configured to execute the computer program to implement the quantitative evaluation method according to any one of claims 1-3.

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