Reservoir permeability acquisition method based on conventional logging pore structure classification

Abstract

The invention discloses a reservoir permeability obtaining method based on conventional logging pore structure classification, and belongs to the technical field of logging reservoir evaluation. The obtaining method comprises the following steps: obtaining a pore structure type and a permeability calculation model; establishing a macro-pore index DI and micro-pore index BI calculation model based on the combination of the interval transit time curve and the compensated neutron curve; according to the pore structure type, the macropore index DI and the micropore index BI calculation model, obtaining a quantitative division standard of the pore structure type; based on the quantitative division standard of the pore structure type, reservoir pore structure identification is carried out, and a pore structure type division result is obtained; and based on the pore structure type division result and in combination with the permeability calculation model, reservoir permeability parameters are obtained.

Description

Technical Field

[0001] The present invention belongs to the technical field of logging reservoir evaluation, and particularly relates to a method for obtaining reservoir permeability based on conventional logging pore structure classification. Background Art

[0002] Permeability, as a key parameter for reservoir evaluation, plays a crucial role in oil and gas field exploration and development. The pore structure of tight pore-type carbonate reservoirs is complex, the reservoir heterogeneity is strong, and it is difficult to accurately calculate the permeability. Currently, there are mainly three methods to obtain permeability: The first method is to calculate the permeability based on the relationship between porosity and permeability. This method does not consider the influence of pore structure on strongly heterogeneous carbonate reservoirs, has a poor pore-permeability relationship, and has a low accuracy in calculating permeability. The second method is mainly based on the Timur-Coates formula and the SDR model. By selecting the NMR T 2 cutoff value to separate the movable fluid from the bound fluid, and then obtain the permeability. This method is only applicable to wells with nuclear magnetic logging data, and its application range is limited. The third is the permeability calculation model based on flow unit classification, which calculates the permeability through the relationship between flow units and reservoir rock permeability. The limitation of this method is that it is difficult to identify different flow units. Currently, most of the existing technologies rely on methods such as neural networks and Fisher discrimination to identify the types of reservoir flow units, and the recognition rate is low, which increases the uncertainty of permeability prediction from the root cause. Summary of the Invention

[0003] In order to overcome the above-mentioned disadvantages of the prior art, the purpose of the present invention is to provide a method for obtaining reservoir permeability based on conventional logging pore structure classification. By using the principle differences of different logging curves, it realizes the quantitative characterization of the pore structure of tight pore-type carbonate reservoirs, and based on the pore structure classification, obtains accurate permeability parameters.

[0004] To achieve the above purpose, the present invention adopts the following technical solutions:

[0005] The present invention provides a method for obtaining reservoir permeability based on conventional logging pore structure classification, including the following steps:

[0006] Obtain the pore structure type and the permeability calculation model;

[0007] Based on the combination of the acoustic travel time curve and the compensated neutron curve, establish the calculation models for the macropore index DI and the micropore index BI;

[0008] According to the pore structure type, and the calculation models for the macropore index DI and the micropore index BI, obtain the quantitative division criteria for the pore structure type;

[0009] Based on the quantitative division standard of pore structure types, reservoir pore structure identification is carried out to obtain the division result of pore structure types;

[0010] Based on the division result of pore structure types and combined with the permeability calculation model, reservoir permeability parameters are obtained.

[0011] In the specific implementation process, the process of obtaining the pore structure types is as follows:

[0012] Core physical experiment data are obtained; based on the analysis of characteristic parameters of core physical experiment data, the pore structures of samples are classified to obtain pore structure types;

[0013] The pore structure types include Type I pore structure, Type II pore structure, and Type III pore structure.

[0014] In the specific implementation process, the characteristic parameters include pore types, filling material characteristics obtained through casting thin section analysis, and displacement pressure and pore throat radius obtained through mercury injection experiment data analysis.

[0015] In the specific implementation process, the displacement pressure of the Type I pore structure is less than 0.15 MPa, the throat radius is greater than 1.12 μm, and the median pressure is less than 2.01 Mpa; the reservoir space type of the Type I pore structure is mainly dissolved pores, with a small amount of intercrystalline pores;

[0016] The displacement pressure of the Type II pore structure is 0.13 MPa - 0.32 MPa, the throat radius is 0.46 μm - 1.36 μm, and the median pressure is 1.87 - 5.49 Mpa; the reservoir space type of the Type II pore structure is a mixed development of intercrystalline pores and dissolved pores;

[0017] The displacement pressure of the Type III pore structure is greater than 0.28 MPa, the throat radius is less than 0.52 μm, and the median pressure is greater than 5.12 Mpa; the reservoir space type of the Type III pore structure is mainly intercrystalline pores, with a small amount of dissolved pores developed or not developed.

[0018] In the specific implementation process, the process of obtaining the permeability calculation model is as follows:

[0019] Based on the core physical experiment data and pore structure types, a crossplot of porosity and permeability of pore structure types is established to obtain the permeability calculation model.

[0020] In the specific implementation process, the permeability calculation model of the Type I pore structure is:

[0021]

[0022] The permeability calculation model of the Type II pore structure is:

[0023]

[0024] The permeability calculation model of the Class III pore structure is as follows:

[0025]

[0026] Where: K represents the core permeability, mD; represents the core porosity, %; a, b, c, d, m, n are constant terms; a, b, c, d, m, n are obtained from the porosity-permeability cross-plot of the pore structure type.

[0027] In the specific implementation process, the calculation models of the macropore index DI and the micropore index BI are as follows:

[0028]

[0029]

[0030] Where: DI represents the macropore index; BI represents the micropore index; AC is the acoustic time difference measured by logging, μs / m; CNL is the neutron value measured by logging, %; AC 基线 is the reading of the acoustic time difference curve when the acoustic time difference curve and the compensated neutron curve coincide in the non-reservoir section, μs / m; AC max is the scale maximum value of the acoustic time difference curve, μs / m; CNL 基线 is the reading of the compensated neutron curve when the acoustic time difference curve and the compensated neutron curve coincide in the non-reservoir section, %; CNL max is the scale maximum value of the compensated neutron curve, %.

[0031] In the specific implementation process, the process of obtaining the quantitative classification standard of the pore structure type according to the pore structure type, the macropore index DI and the micropore index BI calculation models is as follows:

[0032] Calculate the macropore index DI and the micropore index BI corresponding to the depth of the core physical experiment data according to the macropore index DI and the micropore index BI calculation models; combine the pore structure type to establish a macropore index DI and a micropore index BI cross-plot to obtain the quantitative classification standard of the pore structure type.

[0033] In the specific implementation process, the pore structure types include Class I pore structure, Class II pore structure, and Class III pore structure; the quantitative classification standards of the pore structure types are as follows:

[0034] The quantitative classification standard of the Class I pore structure is: DI ≥ a1, BI ≥ b1;

[0035] The quantitative classification standard of the Class II pore structure is: a2 ≤ DI < a1, BI ≥ b1;

[0036] The quantitative division criteria for the Class III pore structure are: DI < a2, BI ≥ b1;

[0037] The quantitative division criteria for non-reservoirs are: BI < b1;

[0038] Where: a1, a2, and b1 are constant terms;

[0039] The above a1, a2, and b1 are obtained from the crossplot of the macropore index DI and the micropore index BI.

[0040] In the specific implementation process, in the crossplot of the macropore index DI and the micropore index BI, the macropore index DI is used as the vertical coordinate and the micropore index BI is used as the horizontal coordinate;

[0041] b1 is the minimum micropore index BI value of the reservoir pore structure in the crossplot of the macropore index DI and the micropore index BI;

[0042] a1 and a2 are the macropore index DI division boundaries of various reservoir pore structures in the crossplot of the macropore index DI and the micropore index BI.

[0043] In the specific implementation process, the process of obtaining the reservoir permeability parameters is as follows:

[0044] Calculate the macropore index DI and micropore index BI parameters at continuous depths and divide the pore structure types. Combine with the permeability calculation models of different pore structures to obtain the reservoir permeability parameters.

[0045] Compared with the prior art, the present invention has the following beneficial effects:

[0046] The present invention provides a method for obtaining reservoir permeability based on the classification of conventional logging pore structures. Through the principle differences of different logging curves, it realizes the quantitative characterization of the pore structures of tight pore-type carbonate rock reservoirs; based on the pore structure classification, accurate permeability parameters are obtained. The above method not only solves the problem of difficult calculation and acquisition of the permeability of tight pore-type carbonate rock reservoirs, but also saves the cost of nuclear magnetic resonance logging. Using this method to calculate the permeability of tight pore-type carbonate rock reservoirs has low cost, is easy to operate, and is convenient for popularization and application. The above method can accurately obtain the permeability of tight pore-type carbonate rock reservoirs based on the pore structure classification, effectively improving the exploration and development efficiency of tight pore-type carbonate rock reservoirs. Brief Description of the Drawings

[0047] Figure 1 It is a method flow chart of the method for obtaining reservoir permeability based on the classification of conventional logging pore structures of the present invention;

[0048] Figure 2Crossplot of core porosity and core permeability for an embodiment of the present invention;

[0049] Figure 3 Crossplot of reservoir macropore index and micropore index for an embodiment of the present invention;

[0050] Figure 4 Logging result diagram for calculating the permeability of a certain well for an embodiment of the present invention. Detailed implementation manners

[0051] In order to enable those skilled in the art to better understand the solution of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0052] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily need to be used to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0053] The present invention will be further described in detail below with reference to the accompanying drawings:

[0054] The present invention provides a method for obtaining reservoir permeability based on conventional logging pore structure classification, including the following steps:

[0055] Step 1: Obtain core physical experiment data; conduct core physical experiments, perform physical property, mercury injection, and cast thin section experiments on the core to obtain core porosity, permeability, cast thin section, and mercury injection experiment data. Select a series of cores that can represent the characteristics of tight pore-type carbonate rock reservoirs, and perform physical property experiments, mercury injection experiments, and cast thin section experiments on the cores according to the procedures specified in the "Core Analysis Method SY / T5336-2006" standard. The core physical property experiments include core porosity experiments and core permeability experiments, and obtain core porosity and core experimental permeability values. The cast thin section experiments and mercury injection experiments are mainly used to analyze the core pore structure characteristics.

[0056] Classify the pore structures of the samples based on the characteristic parameters analyzed from the core physical experiment data of thin sections of cast specimens and mercury injection experiments to obtain pore structure types; among them, the pore structures include Type I pore structure, Type II pore structure, and Type III pore structure.

[0057] The characteristic parameters include pore types and interstitial filling characteristics obtained through the analysis of thin sections of cast specimens, and displacement pressure and pore throat radius obtained through the analysis of mercury injection experiment data.

[0058] The displacement pressure of the Type I pore structure is less than 0.15 MPa, the throat radius is greater than 1.12 μm, and the median pressure is less than 2.01 Mpa; the reservoir space type of the Type I pore structure is mainly dissolved pores, with a small amount of intercrystalline pores.

[0059] The displacement pressure of the Type II pore structure is 0.13 MPa - 0.32 MPa, the throat radius is 0.46 μm - 1.36 μm, and the median pressure is 1.87 - 5.49 Mpa; the reservoir space type of the Type II pore structure is a mixed development of intercrystalline pores and dissolved pores.

[0060] The displacement pressure of the Type III pore structure is greater than 0.28 MPa, the throat radius is less than 0.52 μm, and the median pressure is greater than 5.12 Mpa; the reservoir space type of the Type III pore structure is mainly intercrystalline pores, with a small amount of dissolved pores developed or not developed.

[0061] Step 2: Obtain a permeability calculation model; based on the porosity and permeability data and pore structure types in the core physical experiment data, establish a cross-plot of porosity and permeability for different pore structure types to obtain the permeability calculation model for different pore structures in the reservoir.

[0062] The permeability calculation model for the Type I pore structure is:

[0063]

[0064] The permeability calculation model for the Type II pore structure is:

[0065]

[0066] The permeability calculation model for the Type III pore structure is:

[0067]

[0068] Among them: K represents the core permeability, mD; represents the core porosity, %; a, b, c, d, m, n are constant terms; a, b, c, d, m, n are obtained from the cross-plot of porosity and permeability for different pore structure types.

[0069] Step 3: Based on the combination of the acoustic travel time curve and the compensated neutron curve, establish the calculation models for the macropore index DI and the micropore index BI. Specifically, according to the principle of logging curves, the acoustic travel time reflects the interconnected intergranular pores in the rock, i.e., the macropores; the compensated neutron curve reflects the total pores of the rock. The acoustic travel time curve and the compensated neutron curve adopt linear scales. The acoustic travel time curve and the compensated neutron curve are basically overlapped in the non-reservoir section with pure lithology and poor physical properties, so as to determine the appropriate left and right scale values for the acoustic travel time curve and the compensated neutron curve in the study area.

[0070] The calculation models for the macropore index DI and the micropore index BI are as follows:

[0071]

[0072]

[0073] Where: DI represents the macropore index; BI represents the micropore index; AC is the measured acoustic travel time value in logging, μs / m; CNL is the measured neutron value in logging, %; AC 基线 is the reading value of the acoustic travel time curve when the acoustic travel time curve and the compensated neutron curve overlap in the non-reservoir section, μs / m; AC max is the maximum scale value of the acoustic travel time curve, μs / m; CNL 基线 is the reading value of the compensated neutron curve when the acoustic travel time curve and the compensated neutron curve overlap in the non-reservoir section, %; CNL max is the maximum scale value of the compensated neutron curve, %.

[0074] Step 4: Obtain the quantitative classification criteria for the pore structure types according to the pore structure types, the calculation models for the macropore index DI and the micropore index BI;

[0075] Calculate the macropore index DI and the micropore index BI corresponding to the depth of the core physical experiment data according to the calculation models for the macropore index DI and the micropore index BI; combined with the pore structure types, establish the cross plot of the macropore index DI and the micropore index BI, and obtain the quantitative classification criteria for the pore structure types.

[0076] The quantitative classification criteria for the type I pore structure are: DI≥a1, BI≥b1;

[0077] The quantitative classification criteria for the type II pore structure are: a2≤DI<a1, BI≥b1;

[0078] The quantitative classification criteria for the type III pore structure are: DI<a2, BI≥b1;

[0079] The quantitative classification criteria for the non-reservoir are: BI<b1;

[0080] Where: a1, a2, b1 are constant terms;

[0081] The a1, a2, and b1 are obtained from the crossplot of the macropore index DI and the micropore index BI.

[0082] In the crossplot of the macropore index DI and the micropore index BI, the macropore index DI is used as the vertical coordinate and the micropore index BI is used as the horizontal coordinate.

[0083] b1 is the minimum micropore index BI value of the reservoir pore structure in the crossplot of the macropore index DI and the micropore index BI.

[0084] a1 and a2 are the macropore index DI division boundaries of various reservoir pore structures in the crossplot of the macropore index DI and the micropore index BI.

[0085] Step Five: Based on the quantitative division standard of the pore structure type, identify the reservoir pore structure to obtain the division result of the pore structure type.

[0086] Step Six: Based on the division result of the pore structure type and combined with the permeability calculation model, obtain the reservoir permeability parameter.

[0087] Example

[0088] See Figure 1 , this example provides a method for obtaining reservoir permeability based on the classification of pore structures by conventional logging, including the following steps:

[0089] S1: Conduct physical property, mercury injection, and cast thin-section experiments on the core to obtain the physical experiment data of the core, namely core porosity, permeability, cast thin-section, and mercury injection experiment data.

[0090] See Figure 4 , where the 6th channel A-por is the core analysis porosity and A-perm is the core analysis permeability.

[0091] S2: Using the cast thin-section and mercury injection experiment data obtained in S1, through the pore type and filling material characteristics analyzed by the cast thin-section, and the characteristic parameters such as the displacement pressure and pore throat radius analyzed by the mercury injection, divide the pore structure into type I pore structure, type II pore structure, and type III pore structure.

[0092] Table 1 Parameters of different types of pore structures

[0093]

[0094]

[0095] Table 1 above shows the pore structure parameter tables of different types. For Type I pore structure, the displacement pressure is relatively small, less than 0.15 MPa, the throat radius is relatively large, greater than 1.12 μm, and thin section analysis shows that dissolution pores are mainly developed, with a small amount of intercrystalline pores. For Type II pore structure, the displacement pressure is medium, between 0.13 MPa and 0.32 MPa, the throat radius is mainly in the range of 0.46 μm - 1.36 μm, and thin section analysis shows that intercrystalline pores and dissolution pores are mixedly developed. For Type III pore structure, the displacement pressure is greater than 0.28 MPa, the throat radius is less than 0.52 μm, and the median pressure is greater than 5.12 Mpa; the reservoir space type of Type III pore structure is mainly intercrystalline pores, with a small amount of dissolution pores developed or not developed.

[0096] S3: Using the core porosity and permeability data obtained in S1, combined with the pore structure classification obtained in S2, establish a crossplot of core porosity and core permeability to obtain the permeability calculation model for different pore structures in the reservoir.

[0097] Figure 2 It is a crossplot of core porosity and core permeability for a pore reservoir based on pore structure classification. From the crossplot, the permeability calculation model for different pore structures can be obtained:

[0098] Type I pore structure:

[0099] Type II pore structure:

[0100] Type III pore structure:

[0101] Where: K represents the core permeability, mD; represents the core porosity, %. a, b, c, d, m, n are constant terms; a, b, c, d, m, n are obtained from the crossplot of porosity and permeability of the pore structure type.

[0102] S4: In this embodiment, the AC 基线 value is 150 us / m, the AC max is 350 us / m, the CNL 基线 value is 2%, and the CNL max is 40%. The calculation models for the macropore index DI and the micropore index BI are as follows:

[0103]

[0104]

[0105] Figure 4 In the third trace, it is the micropore index BI curve calculated using the above steps, and in the fourth trace, it is the macropore index DI curve calculated using the above steps.

[0106] S5: Calculate the macropore index DI and micropore index BI corresponding to the depth of the lithology experimental data using the model. Combine the pore structure type obtained in S2 to establish a crossplot of the macropore index DI and the micropore index BI. Based on the crossplot of the macropore index DI and the micropore index BI, obtain the quantitative classification criteria for the reservoir pore structure.

[0107] Specifically, the crossplot of the macropore index DI and the micropore index BI is plotted with the macropore index DI as the vertical coordinate and the micropore index BI as the horizontal coordinate.

[0108] See Figure 3 , and the quantitative classification criteria for the pore structure are obtained as follows:

[0109] Type Ⅰ pore structure: DI ≥ 0.061, BI ≥ 0.02;

[0110] Type Ⅱ pore structure: 0.032 ≤ DI < 0.061, BI ≥ 0.02;

[0111] Type Ⅲ pore structure: DI < 0.032, BI ≥ 0.02;

[0112] Non-reservoir: BI < 0.02.

[0113] S6: Calculate the macropore index DI and the micropore index BI using the model obtained in S4. Combine the quantitative classification criteria for the pore structure obtained in S5 to complete the classification of the pore structure type.

[0114] Figure 4 is the log result map for calculating the permeability of a certain well. The 5th track is the classification of the pore structure type of this example.

[0115] S7: Use the classification result of the pore structure type obtained in S6 and combine it with the permeability calculation model for different pore structures obtained in S3 to accurately calculate the reservoir permeability parameters, thereby judging the quality of the reservoir.

[0116] Figure 4 In, the 7th track A-perm is the core porosity analyzed by experiment, which is represented by a rod in the figure; perm is the permeability curve calculated using the above invention. It can be seen from the figure that the permeability obtained by the present invention is in good agreement with the permeability analyzed by the experimental core, and the calculation accuracy of the permeability is high.

[0117] The above content is only to illustrate the technical idea of the present invention and cannot be used to limit the protection scope of the present invention. Any modification made on the basis of the technical solution according to the technical idea proposed by the present invention falls within the protection scope of the claims of the present invention.

Claims

1. A reservoir permeability acquisition method based on conventional well logging pore structure classification, characterized in that: The following steps are involved: Obtain pore structure type and permeability calculation model; The calculation model of macropore index DI and micropore index BI is established based on the combination of acoustic time difference curve and compensated neutron curve; According to the calculation model of pore structure type, macropore index DI and micropore index BI, the quantitative classification standard of pore structure type is obtained; Based on the quantitative classification standard of pore structure types, the reservoir pore structure is identified to obtain the pore structure type classification results; Based on the pore structure type classification results and the permeability calculation model, the reservoir permeability parameters are obtained.

2. The reservoir permeability acquisition method based on conventional well logging pore structure classification according to claim 1 is characterized in that: The process of obtaining the pore structure type is as follows: Obtain core physical experiment data; classify the pore structure of the sample based on the characteristic parameters analyzed in the core physical experiment data to obtain the pore structure type; The pore structure types include type I pore structure, type II pore structure, and type III pore structure.

3. The reservoir permeability acquisition method based on conventional well logging pore structure classification according to claim 2 is characterized in that: The characteristic parameters include pore type and filling material characteristics obtained through casting thin section analysis, and displacement pressure and pore throat radius obtained through mercury injection experimental data analysis.

4. The reservoir permeability acquisition method based on conventional well logging pore structure classification according to claim 2, characterized in that: The displacement pressure of the Class I pore structure is less than 0.15 MPa, the roar radius is greater than 1.12 μm, and the median pressure is less than 2.01 MPa; the reservoir space type of the Class I pore structure is mainly solution pores, with a small amount of intercrystalline pores; The displacement pressure of the Class II pore structure is 0.13MPa-0.32MPa, the roar radius is 0.46μm-1.36μm, and the median pressure is 1.87-5.49Mpa; the reservoir space type of the Class II pore structure is a mixed development of intercrystalline pores and dissolved pores; The displacement pressure of the Type III pore structure is greater than 0.28 MPa, the roar radius is less than 0.52 μm, and the median pressure is greater than 5.12 MPa; the reservoir space type of the Type III pore structure is mainly intercrystalline pores, and dissolved pores are slightly developed or undeveloped.

5. The reservoir permeability acquisition method based on conventional well logging pore structure classification according to claim 2, characterized in that: The process of obtaining the permeability calculation model is as follows: Based on the core physical experimental data and pore structure types, the porosity and permeability cross-plot of pore structure types is established to obtain the permeability calculation model.

6. The reservoir permeability acquisition method based on conventional well logging pore structure classification according to claim 5, characterized in that: The permeability calculation model of the type I pore structure is: The permeability calculation model of the type II pore structure is: The permeability calculation model of the type III pore structure is: Where: K represents the core permeability, mD; represents the core porosity, %; a, b, c, d, m, n are constant terms; a, b, c, d, m, n are obtained according to the porosity and permeability cross-plot of the pore structure type.

7. The reservoir permeability acquisition method based on conventional well logging pore structure classification according to claim 1, characterized in that: The calculation model of the macropore index DI and the micropore index BI is as follows: Where: DI is the macropore index; BI is the micropore index; AC is the acoustic time difference value measured by logging, us / m; CNL is the neutron value measured by logging, %; AC 基线 The reading of the acoustic time difference curve when the acoustic time difference curve and the compensated neutron curve overlap in the non-reservoir section, us / m; AC max The maximum value of the acoustic time difference curve, us / m; CNL 基线 CNL is the reading value of the compensated neutron curve when the acoustic time difference curve and the compensated neutron curve overlap in the non-reservoir section, %; max To compensate for the maximum scale value of the neutron curve, %.

8. The reservoir permeability acquisition method based on conventional well logging pore structure classification according to claim 7, characterized in that: The process of obtaining the quantitative classification standard of pore structure type according to the calculation model of pore structure type, macropore index DI and micropore index BI is as follows: The macropore index DI and micropore index BI at the corresponding depth of core physical experimental data are calculated according to the calculation model of macropore index DI and micropore index BI; combined with the pore structure type, the intersection diagram of macropore index DI and micropore index BI is established to obtain the quantitative classification standard of pore structure type.

9. The reservoir permeability acquisition method based on conventional well logging pore structure classification according to claim 8, characterized in that: The quantitative classification criteria for the pore structure types are as follows: The pore structure types include type I pore structure, type II pore structure, and type III pore structure; The quantitative classification criteria for the type I pore structure are: DI ≥ a1, BI ≥ ​​b1; The quantitative classification standard of the type II pore structure is: a2≤DI<a1, BI≥b1; The quantitative classification standard of the Class III pore structure is: DI<a2, BI≥b1; The quantitative classification criteria for non-reservoir formations are: BI < b1; Among them: a1, a2, b1 are constant terms; The a1, a2, and b1 are obtained according to the intersection of the macropore index DI and the micropore index BI; In the cross-plot of the macropore index DI and the micropore index BI, the macropore index DI is used as the ordinate and the micropore index BI is used as the abscissa; b1 is the minimum micropore index BI value of the reservoir pore structure in the cross-plot of the macropore index DI and the micropore index BI; a1 and a2 are the dividing lines of the macropore index DI of various reservoir pore structures in the cross-plot of the macropore index DI and the micropore index BI.

10. The reservoir permeability acquisition method based on conventional well logging pore structure classification according to claim 1, characterized in that: The process of obtaining reservoir permeability parameters is as follows: The macropore index DI and micropore index BI parameters of continuous depth are calculated and the pore structure types are divided. The reservoir permeability parameters are obtained by combining the permeability calculation models of different pore structures.

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