Permeability evaluation method and apparatus based on oil-based mud electrical imaging logging

Abstract

A permeability evaluation method based on oil-based mud electrical imaging logging, comprising: after processing oil-based mud electrical imaging logging data, determining a permeable layer section in a formation, and determining low-frequency relative permittivity and high-frequency relative permittivity of each sector of a target wellbore; on the basis of the low-frequency relative permittivity, the high-frequency relative permittivity, and characteristic parameters of each sector, constructing an invasion factor correlated with permeability; obtaining permeability experimental data generated after performing permeability measurements on rock cores of the permeable layer section, and performing formation depth alignment and orientation alignment; fitting the aligned permeability experimental data with the invasion factors, and generating a permeability calculation model; and calculating permeability by using the permeability calculation model. Further provided is a permeability evaluation apparatus based on oil-based mud electrical imaging logging. The invention achieves anisotropic permeability evaluation and continuous permeability evaluation in the longitudinal direction.

Description

Permeability evaluation method and device based on oil-based mud electrical imaging logging

[0001] Cross-reference to Related Applications

[0002] This application claims the benefit of Chinese Patent Application No. 202410582297.0, filed May 11, 2024, the contents of which are incorporated by reference herein. TECHNICAL FIELD

[0003] The present application belongs to the technical field of oil and gas exploration, particularly the technical field of formation permeability evaluation, and specifically relates to a permeability evaluation method based on oil-based mud electrical imaging logging, a permeability evaluation device based on oil-based mud electrical imaging logging, a computer device, and a machine-readable storage medium. BACKGROUND

[0004] Currently, fluid property identification methods mainly fall into four categories, namely, rock physics experiment method, nuclear magnetic resonance logging method, Stoneley wave method, and formation testing method. The rock physics experiment method generally includes gas permeability method, mercury injection method, etc. The obtained permeability experimental values can be used as the basis for subsequent logging evaluation. However, this method has the disadvantage of high cost and cannot perform continuous permeability characterization. The nuclear magnetic resonance logging method is one of the most commonly used methods for evaluating formations. The commonly used nuclear magnetic resonance permeability model in the industry is mainly based on T2 average value and cutoff value for permeability calculation. The T2 average value reflects the movable saturation, and the T2 cutoff value reflects the bound saturation. This method has achieved good results in the evaluation of permeability of various reservoirs under water-based mud environment. However, under oil-based mud environment, when oil-based mud invades the formation, the composition of oil-based mud can cause the hydrogen index of the wellbore formation to decrease, resulting in a significant decrease in the measured nuclear magnetic porosity. At the same time, due to the small detection range of nuclear magnetic resonance logging, most of the measured nuclear magnetic signals are oil-based mud signals, which cannot reflect the formation information, and thus cannot meet the prerequisites for nuclear magnetic permeability evaluation. The Stoneley wave method generally uses Stoneley wave waveform, phase velocity dispersion, attenuation, and the sensitivity of phase velocity to permeability to optimize the parameters most strongly related to permeability, and establish a permeability calculation model. This method has good results in the evaluation of permeability of fracture and cave type carbonate reservoirs, but has poor results for porous tight reservoirs. The formation testing method refers to determining the permeability parameters of the reservoir through fluid sampling and pressure testing. However, due to the limitation of the pumping capacity of the downhole pump, not all reservoirs are suitable for formation testing technology. At the same time, formation testing is usually point measurement, which cannot form continuous permeability data in the vertical direction, resulting in limitations in the practical application of permeability calculation based on well testing data. The above four methods cannot evaluate the permeability anisotropy of the formation around the wellbore. SUMMARY

[0005] The embodiment of the present application aims to provide a permeability evaluation method based on oil-based mud electrical imaging logging, a permeability evaluation device based on oil-based mud electrical imaging logging, a computer device and a machine readable storage medium, so as to overcome one or more defects of the existing permeability evaluation methods such as rock physical experiment method, nuclear magnetic resonance logging method, Stoneley wave method and formation testing method.

[0006] In order to achieve the above-mentioned purpose, the first aspect of the embodiment of the present application provides a permeability evaluation method based on oil-based mud electrical imaging logging, the method comprising:

[0007] processing the oil-based mud electrical imaging logging data of the target wellbore of the research formation to determine the permeable layer section in the formation, and determining the low-frequency relative dielectric constant and the high-frequency relative dielectric constant of each sector of the target wellbore in the permeable layer section;

[0008] constructing an invasion factor of the sector according to the low-frequency relative dielectric constant, the high-frequency relative dielectric constant and the characteristic parameter of the sector, the invasion factor having a correlation with the formation permeability, and the characteristic parameter being a geological parameter and / or an engineering parameter associated with the depth of the oil-based mud invasion into the formation caused by the change of the formation permeability;

[0009] obtaining the permeability experimental data generated after the permeability measurement of the core of the permeable layer section obtained by the annular sampling, and performing directional homing on the permeability experimental data;

[0010] fitting the homed permeability experimental data with the invasion factor to generate a permeability calculation model;

[0011] calculating the permeability of the determined sector in the target formation by using the permeability calculation model.

[0012] The second aspect of the embodiment of the present application provides a permeability evaluation device based on oil-based mud electrical imaging logging, the device comprising:

[0013] a sector relative dielectric constant determination module, configured to process the oil-based mud electrical imaging logging data of the target wellbore of the research formation to determine the permeable layer section in the formation, and determine the low-frequency relative dielectric constant and the high-frequency relative dielectric constant of each sector of the target wellbore in the permeable layer section;

[0014] a sector invasion factor construction module, configured to construct an invasion factor of the sector according to the low-frequency relative dielectric constant, the high-frequency relative dielectric constant and the characteristic parameter of the sector, the invasion factor having a correlation with the formation permeability, and the characteristic parameter being a geological parameter and / or an engineering parameter associated with the depth of the oil-based mud invasion into the formation caused by the change of the formation permeability;

[0015] The permeability experiment data homing module is used for obtaining permeability experiment data generated after measuring the permeability of a core of a permeable layer section obtained by annular sampling, and homing the permeability experiment data in a direction;

[0016] The model generating module is used for fitting the homed permeability experiment data with the invasion factor to generate a permeability calculation model;

[0017] The permeability evaluation module is used for calculating the permeability of a determined sector in a target formation by using the permeability calculation model.

[0018] The third aspect of the embodiment of the present application provides a computer device, which comprises a memory, a processor and a computer program stored in the memory and executable on the processor, and the processor implements the permeability evaluation method based on oil-based mud electrical imaging logging according to the first aspect of the embodiment of the present application when executing the program.

[0019] The fourth aspect of the embodiment of the present application provides a machine readable storage medium, which stores a computer program, and the computer program is executable on a processor to implement the permeability evaluation method based on oil-based mud electrical imaging logging according to the first aspect of the embodiment of the present application.

[0020] Through the above technical solution, the beneficial effects of the embodiment of the present application mainly include:

[0021] 1) In the above technical solution, the technical principle that the high-frequency relative dielectric constant and the low-frequency relative dielectric constant measured by the electrode plate exist differences caused by the invasion of oil-based mud into the formation and the differences between the high-frequency relative dielectric constant and the low-frequency relative dielectric constant measured are different according to the different permeability of the layer section is applied, a factor related to the permeability, i.e., the invasion factor in the above technical solution, is constructed, the invasion factor is constructed by the high-frequency relative dielectric constant, the low-frequency relative dielectric constant and other geological parameters and / or engineering parameters associated with the depth of the invasion of oil-based mud into the formation caused by the change of the permeability of the formation, and the permeability experiment data homed in the depth and direction is fitted with the invasion factor in combination with the core laboratory test, so as to construct the permeability calculation model, the permeability of each sector of the target formation can be calculated by the constructed permeability calculation model, and it can be seen that the above technical solution realizes the evaluation of the anisotropic permeability of the formation around the well and the continuous permeability evaluation in the vertical direction;

[0022] 2) The technical solution is used for core laboratory test, and the purpose is to realize fitting of the relationship between permeability and invasion factor, so that when the core laboratory test is performed, only the core sample of one permeable layer section can be taken for porosity and permeability test, and therefore, the continuous permeability evaluation result in the vertical direction can be obtained based on the small amount of core test results, and the low cost advantage is achieved;

[0023] 3) From the data source of the permeability evaluation, the key of the Stoneley wave method is to excite high-precision low-frequency Stoneley wave in the wellbore, and then to evaluate the permeability, however, the current dipole acoustic logging (such as sonic scanner, Xaminer) with Stoneley wave mode has insufficient temperature and pressure resistance limit, and deep and ultra-deep layer logging cannot be collected, and the Stoneley wave method is more suitable for the evaluation of the permeability caused by the fracture, and is not sensitive to the matrix permeability without fracture development, and therefore, the application range of the Stoneley wave method is small, and the oil-based mud electrical imaging logging in the technical solution has good temperature and pressure resistance, and can collect high-precision data around the wellbore, and therefore, the permeability evaluation precision is higher;

[0024] 4) Compared with the formation test method, the formation test method calculates the permeability through the pressure drop after pumping, however, the deep and dense reservoirs cannot extract fluid due to the influence of pumping capacity, and reliable permeability cannot be calculated, however, the technical solution is not limited by the pumping capacity, but uses the difference between the high-frequency relative dielectric constant and the low-frequency relative dielectric constant caused by the oil-based mud invasion to construct a permeability calculation model, and therefore, the scene applicability is stronger;

[0025] 5) For the nuclear magnetic resonance logging method, the industry commonly uses SDR model and COATES model to calculate the nuclear magnetic permeability, and the core parameter of the two methods is nuclear magnetic porosity, however, when the oil-based mud filtrate invades the formation, the hydrogen index of the well wall formation is reduced, and the measured nuclear magnetic porosity is obviously reduced, compared with the nuclear magnetic resonance logging method, the technical solution uses the difference between the high-frequency relative dielectric constant and the low-frequency relative dielectric constant caused by the oil-based mud invasion to evaluate the permeability, and therefore, the permeability evaluation precision is higher.

[0026] Other features and advantages of the embodiments of the present application will be described in detail in the following specific embodiments. BRIEF DESCRIPTION OF DRAWINGS

[0027] The accompanying drawings are included to provide a further understanding of the embodiments of the present application, and constitute a part of the specification, and are used together with the following specific embodiments to explain the embodiments of the present application, but do not constitute a limitation on the embodiments of the present application. In the drawings:

[0028] Fig. 1 schematically shows a flowchart of a permeability evaluation method based on oil-based mud electrical imaging logging according to an embodiment of the present application;

[0029] Fig. 2 schematically shows a diagram of a core ring drilling plunger in a specific application example;

[0030] Fig. 3 schematically shows a sector diagram of a borehole in a specific application example;

[0031] Fig. 4 schematically shows a difference comparison diagram of high-frequency relative dielectric constant and low-frequency relative dielectric constant of different polar plates in a mudstone section and a permeable section in a specific application example;

[0032] Fig. 5 schematically shows a diagram of relative positions of polar plates in a No. 1 sector in a specific application example;

[0033] Fig. 6 schematically shows a fitting relationship diagram between an invasion factor and a permeability in a specific application example;

[0034] Fig. 7 schematically shows a diagram of permeability evaluation results of different sectors in a specific application example;

[0035] Fig. 8 schematically shows a composition block diagram of a permeability evaluation device based on oil-based mud electrical imaging logging according to an embodiment of the present application;

[0036] Fig. 9 schematically shows a structural block diagram of a computer device according to an embodiment of the present application. DETAILED DESCRIPTION

[0037] The specific implementation of the embodiments of the present application will be described in detail below with reference to the accompanying drawings. It should be understood that the specific implementation described herein is only used to illustrate and explain the embodiments of the present application, and is not used to limit the embodiments of the present application.

[0038] Method embodiment

[0039] Referring to Fig. 1, a permeability evaluation method based on oil-based mud electrical imaging logging provided by an embodiment of the present application includes the following implementation steps:

[0040] Step S100, after processing the oil-based mud electrical imaging logging data of the target borehole of the research formation, the permeable section in the formation is determined, and the low-frequency relative dielectric constant and the high-frequency relative dielectric constant of each sector of the target borehole in the permeable section are determined.

[0041] It is known that the low-frequency relative dielectric constant and the high-frequency relative dielectric constant of each polar plate on the oil-based mud electrical imaging logging instrument can be inverted according to the oil-based mud electrical imaging logging data. The difference between the measured high-frequency relative dielectric constant and the low-frequency relative dielectric constant is different due to the different permeability of the section, therefore, the permeable section in the research formation can be determined by comparing the difference between the low-frequency relative dielectric constant and the high-frequency relative dielectric constant.

[0042] Step S200, constructing an invasion factor of the sector according to the low-frequency relative dielectric constant, the high-frequency relative dielectric constant and the characteristic parameter of the sector, the invasion factor having a correlation with the formation permeability, and the characteristic parameter being a geological parameter and / or an engineering parameter associated with the degree of the oil-based mud invasion into the formation caused by the change of the formation permeability.

[0043] In the oil-based mud environment, in addition to the correlation between the difference degree of the low-frequency relative dielectric constant and the high-frequency relative dielectric constant of the sector and the formation permeability measured by the electrode plate in the sector, there is also a related factor that affects the degree of the oil-based mud invasion into the formation caused by the change of the formation permeability, such as the inherent geological parameter of the formation and / or the engineering parameter during drilling. Based on the foregoing principle, the related factors, i.e., the characteristic parameter in step S200, are introduced into the construction of the invasion factor, so that the constructed invasion factor has a stronger correlation with the permeability, which is beneficial to the subsequent permeability evaluation.

[0044] Exemplarily, in a specific embodiment, when constructing the invasion factor of the sector, the introduced characteristic parameters include the mud density during the oil-based mud imaging logging in the target wellbore and the formation pressure coefficient calculated through the logging data.

[0045] Step S300, obtaining the permeability experimental data generated after the permeability measurement of the core of the permeable layer section obtained by the ring sampling, and performing directional homing on the permeability experimental data.

[0046] It is known that before the directional homing of the permeability experimental data, when the depth of the layer corresponding to the core cannot be accurately obtained, the depth of the formation usually needs to be homed first, and through the homing of the depth of the formation, the experimental data is homed to the accurate depth of the layer.

[0047] Exemplarily, in a specific embodiment, the homing of the depth of the formation includes the following implementation steps:

[0048] Obtaining the porosity experimental data generated after the porosity measurement of the core of the permeable layer section obtained by the ring sampling;

[0049] Obtaining the porosity curve obtained by logging; in a general embodiment, the porosity curve can be any one of the effective porosities obtained by density logging, acoustic logging and nuclear magnetic resonance logging;

[0050] Performing the homing of the depth of the layer of the permeability experimental data by comparing the porosity experimental data and the porosity curve.

[0051] For example, the average value of the porosity experimental data of different phase angles of a certain permeable layer section is obtained, and the average value of the porosity is compared with the porosity curve obtained by logging. According to the comparison result, the permeability experimental data is classified to the determined depth of the section.

[0052] It is known that the original orientation of the core in the formation cannot be known when the core is taken to the ground. Meanwhile, the permeability is anisotropic, and the permeability in different directions is different. If the direction of the permeability experimental data is classified incorrectly, the permeability calculation result will be completely wrong. Therefore, the direction of the permeability experimental data needs to be classified.

[0053] For example, the direction of the permeability experimental data of a certain permeable layer section is classified by using the invasion factor corresponding to each sector of the permeable layer section. Correspondingly, in a specific embodiment, the direction of the permeability experimental data is classified, including the following implementation steps:

[0054] For a certain permeable layer section, the variation trend of the permeability experimental data at a certain phase angle is consistent with the variation trend of the invasion factor of a certain sector, and the permeability experimental data of the corresponding permeable layer section is classified to a certain direction by using the invasion factor, to obtain the permeability experimental data after direction classification.

[0055] In step S400, the classified permeability experimental data is fitted with the invasion factor of the sector corresponding to its own orientation, to generate a permeability calculation model. It should be understood that after the classified permeability experimental data is fitted with the invasion factor, a relationship between the invasion factor and the permeability is obtained. The relationship is taken as a function expression of the model, the invasion factor is taken as an input parameter of the model, and the permeability is taken as an output parameter of the model, so that the permeability calculation model is constructed.

[0056] In step S500, the permeability of the determined sector in the target formation is calculated by using the permeability calculation model.

[0057] It should be understood that the target formation can be a formation which needs to be calculated for permeability, or can be other permeable layer sections in the study formation which have not been evaluated for permeability. The determined sector can be one or more sectors. Therefore, after the permeable layer section in the target formation and the sector are selected, the permeability evaluation results of each sector of the longitudinally continuous permeable layer section can be obtained by step S500.

[0058] It is known that, by processing the oil-based mud electrical imaging logging data of the target borehole of the research formation, static images, dynamic images, low-frequency relative dielectric constants of all the polar plates, high-frequency relative dielectric constants and azimuth angles of all the polar plates can be obtained. In addition, each polar plate usually includes a plurality of measuring electrodes, so the low-frequency relative dielectric constant of a sector can be obtained by statistically analyzing the low-frequency relative dielectric constants of the electrodes belonging to the polar plate of the sector, and the high-frequency relative dielectric constant of the sector can be obtained by statistically analyzing the high-frequency relative dielectric constants of the electrodes belonging to the polar plate of the sector.

[0059] For example, in one specific embodiment, step S100, after processing the oil-based mud electrical imaging logging data of the target borehole of the research formation, the permeable layer section in the formation is determined, and the low-frequency relative dielectric constant and the high-frequency relative dielectric constant of each sector of the target borehole in the permeable layer section are determined, including the following implementation steps:

[0060] Step S110, processing the oil-based mud electrical imaging logging data of the target borehole of the research formation, obtaining the low-frequency relative dielectric constant, the high-frequency relative dielectric constant and the azimuth angle of all the polar plates.

[0061] Step S120, by comparing the difference between the low-frequency relative dielectric constant and the high-frequency relative dielectric constant of the same polar plate, the permeable layer section in the research formation is determined.

[0062] Step S130, sector division is performed on the target borehole, and the sector to which the polar plate belongs and the electrode sequence in the belonging sector are determined according to the azimuth angle of the polar plate.

[0063] It is known that, after sector division is performed on the target borehole, each sector has its own azimuth information, such as the size of the sector, the boundary angle of the sector, etc. According to the azimuth angle of the polar plate obtained in the previous step, the polar plate belonging to the sector and the electrode sequence on the polar plate located in the sector can be determined, and the polar plate belonging to the sector contributes to the low-frequency relative dielectric constant and the high-frequency relative dielectric constant of the sector.

[0064] Step S140, determining the low-frequency relative dielectric constant and the high-frequency relative dielectric constant of the sector itself according to the electrode sequence in the sector.

[0065] For example, when determining the low-frequency relative dielectric constant and the high-frequency relative dielectric constant of a sector itself according to the electrode sequence within the sector, for a certain sector, the low-frequency relative dielectric constant of all electrodes within the electrode sequence belonging to the sector can be statistically analyzed to obtain the low-frequency relative dielectric constant of the sector, for example, to obtain the average value and take the average value as the low-frequency relative dielectric constant of the sector; similarly, the high-frequency relative dielectric constant of all electrodes within the electrode sequence belonging to the sector can be statistically analyzed to obtain the high-frequency relative dielectric constant of the sector, for example, to obtain the average value and take the average value as the high-frequency relative dielectric constant of the sector.

[0066] As an improvement of the above embodiment, in order to quickly determine the electrode sequence located within a certain sector, in a specific embodiment, a method for quickly determining the electrode sequence based on the positional relationship between the azimuth angle of the electrode plate and the difference degree of the sector boundary or the sector bisector angle is proposed. Specifically, step S130, sector division is performed on the target wellbore, and the sector to which the electrode plate belongs and the electrode sequence within the belonging sector are determined according to the azimuth angle of the electrode plate, including the following implementation steps:

[0067] Step S1301, sector division is performed on the wellbore, and the azimuth information of each sector is calculated. The azimuth information of the sector includes the sector phase angle, the sector bisector angle, the left boundary angle of the sector in the clockwise direction, and the right boundary angle of the sector in the clockwise direction.

[0068] Step S1302, the sector to which the electrode plate belongs is determined according to the azimuth angle of the electrode plate and the azimuth information of the sector.

[0069] Step S1303, the electrode sequence on the electrode plate located in the sector to which the electrode plate belongs is determined according to the difference degree between the azimuth angle of the electrode plate and the sector boundary of the sector to which the electrode plate belongs or the positional relationship between the azimuth angle of the electrode plate and the sector bisector angle of the sector to which the electrode plate belongs.

[0070] The difference between the azimuth angle of the electrode plate and the sector boundary or the positional relationship between the azimuth angle of the electrode plate and the sector bisector angle is different, and the way of finding the electrode sequence on the electrode plate located in the sector to which the electrode plate belongs is different. Therefore, in a specific embodiment, step S1303, the electrode sequence on the electrode plate located in the sector to which the electrode plate belongs is determined according to the difference degree between the azimuth angle of the electrode plate and the sector boundary of the sector to which the electrode plate belongs or the positional relationship between the azimuth angle of the electrode plate and the sector bisector angle of the sector to which the electrode plate belongs, including the following implementation steps:

[0071] If the azimuth angle of the electrode plate coincides with the sector bisector angle of the sector to which the electrode plate belongs, it is determined that the electrode plate is the only contribution electrode plate of the high-frequency relative dielectric constant and the low-frequency relative dielectric constant of the sector to which the electrode plate belongs. The electrode sequence of the sector to which the electrode plate belongs is all the electrodes located on the electrode plate;

[0072] If the azimuth angle of the polar plate does not coincide with the sector bisector angle of the sector to which the polar plate belongs, it is determined that the polar plate is not the only contribution polar plate of the high-frequency relative dielectric constant and the low-frequency relative dielectric constant of the sector to which the polar plate belongs, that is, there is another polar plate in the sector; when the polar plate is a polar plate close to the left boundary of the sector to which the polar plate belongs, the angle between the azimuth angle of the polar plate and the left boundary of the sector to which the polar plate belongs is calculated, and the number of electrodes and the electrode index range of the polar plate located in the sector to which the polar plate belongs are determined according to the angle; when the polar plate is a polar plate close to the right boundary of the sector to which the polar plate belongs, the angle between the azimuth angle of the polar plate and the right boundary of the sector to which the polar plate belongs is calculated, and the number of electrodes and the electrode index range of the polar plate located in the sector to which the polar plate belongs are determined according to the angle.

[0073] As an improvement of the above embodiment, when there are two polar plates in a sector, the difference between the azimuth angle of the polar plate and the sector boundary of the sector to which the polar plate belongs determines the contribution degree of the relative dielectric constant measurement value of each electrode on the polar plate to the relative dielectric constant measurement value of the whole sector, the polar plate with a large difference degree has a larger number of electrodes included in the electrode sequence located in the sector to which the polar plate belongs, and the contribution weight of the polar plate can be increased at this time, and vice versa, the polar plate with a small difference degree has a smaller number of electrodes included in the electrode sequence located in the sector to which the polar plate belongs, and the contribution weight of the polar plate can be reduced at this time, so as to improve the accuracy of determining the low-frequency relative dielectric constant and the high-frequency relative dielectric constant of the sector according to the electrode sequence in the sector. Based on the above principle, in a specific embodiment, step S140, determining the low-frequency relative dielectric constant and the high-frequency relative dielectric constant of the sector according to the electrode sequence in the sector, comprises the following implementation steps:

[0074] Step S1401, determining the contribution weight of the polar plate to the high-frequency relative dielectric constant and the low-frequency relative dielectric constant of the sector according to the difference between the azimuth angle of the polar plate and the sector boundary of the sector to which the polar plate belongs or the positional relationship between the azimuth angle of the polar plate and the sector bisector angle of the sector to which the polar plate belongs, and calculating the average value of the high-frequency relative dielectric constant of each electrode in the electrode sequence belonging to the sector on the polar plate, and calculating the average value of the low-frequency relative dielectric constant of each electrode in the electrode sequence belonging to the sector on the polar plate.

[0075] Step S1402, for a certain sector, weighting the average value of the high-frequency relative dielectric constant corresponding to the polar plate itself according to the contribution weight corresponding to the polar plate itself to obtain a first weighted value, summing the first weighted values of all polar plates belonging to the sector to obtain the high-frequency relative dielectric constant of the sector, and weighting the average value of the low-frequency relative dielectric constant corresponding to the polar plate itself according to the contribution weight corresponding to the polar plate itself to obtain a second weighted value, and summing the second weighted values of all polar plates belonging to the sector to obtain the low-frequency relative dielectric constant of the sector.

[0076] Exemplarily, in one specific embodiment, the contribution weight of the high-frequency relative dielectric constant and the low-frequency relative dielectric constant of the sector to which the polar plate belongs to the sector is determined according to the difference between the azimuth angle of the polar plate and the sector boundary of the sector to which the polar plate belongs or the positional relationship with the sector bisector angle of the sector, including the following implementation steps:

[0077] If the azimuth angle of the polar plate coincides with the sector bisector angle of the sector to which the polar plate belongs, it is determined that the high-frequency relative dielectric constant and the low-frequency relative dielectric constant of the polar plate are the only contribution to the high-frequency relative dielectric constant and the low-frequency relative dielectric constant of the sector to which the polar plate belongs, and the contribution weight is 100%;

[0078] If the azimuth angle of the polar plate does not coincide with the sector bisector angle of the sector to which the polar plate belongs, it is determined that there is another polar plate contributing to the high-frequency relative dielectric constant and the low-frequency relative dielectric constant of the sector to which the polar plate belongs, and the contribution weight of the polar plate is the ratio of the difference between the azimuth angle of the polar plate and the sector boundary of the sector to which the polar plate belongs to the sum of the differences between the azimuth angles of all polar plates belonging to the sector and the sector boundary.

[0079] For example, assuming that the number of sectors divided by the target wellbore is m, the sector phase angle can be calculated by the following formula:

[0080] Wherein, δ represents the sector phase angle;

[0081] The sector bisector angle can be calculated by the following formula:

[0082] Wherein, k represents the number of the sector, 1≤k≤m, θ k represents the sector bisector angle;

[0083] The left boundary angle of the sector in the clockwise direction can be calculated by the following formula:

[0084] Wherein, αk represents the left boundary angle of the sector numbered k;

[0085] The right boundary angle of the sector in the clockwise direction can be calculated by the following formula:

[0086] Wherein, β k represents the right boundary angle of the sector numbered k.

[0087] When there is only one polar plate in the sector:

[0088] The high-frequency relative dielectric constant of the sector is the high-frequency relative dielectric constant of the polar plate, and the high-frequency relative dielectric constant of the polar plate is the average of the high-frequency relative dielectric constants of all electrodes on the polar plate, assuming that the high-frequency relative dielectric constant of the polar plate is E i,H , the high-frequency relative dielectric constant of the sector is Ek,H Then E i,H can be calculated by the following equation:

[0089] where i represents the number of the pad, N represents the number of electrodes on the pad, E H [s] represents the high-frequency relative dielectric constant of the s-th electrode on the i-th pad;

[0090] The low-frequency relative dielectric constant of the sector is the low-frequency relative dielectric constant of the pad, the low-frequency relative dielectric constant of the pad is the average of the low-frequency relative dielectric constants of all electrodes on the pad, and the low-frequency relative dielectric constant of the pad is assumed to be E i,L , the low-frequency relative dielectric constant of the sector is E k,L , and then E i,L can be calculated by the following equation:

[0091] where E L [s] represents the low-frequency relative dielectric constant of the s-th electrode on the i-th pad.

[0092] When there are two pads in the sector:

[0093] The contribution weight of the pad can be calculated by the following equation:

[0094] where θ left,k represents the difference value between the azimuth angle θ left of the pad close to the left boundary of the sector k and the sector left boundary of the sector k, θ right,k represents the difference value between the azimuth angle θ right of the pad close to the right boundary of the sector k and the sector right boundary of the sector k, W left,k represents the contribution weight of the pad close to the left boundary of the sector k, W right,k represents the contribution weight of the pad close to the right boundary of the sector k, represents half of the central angle θ (i) of the pad i, r represents the wellbore radius, N (i) represents the number of electrodes on the pad i, w (i) represents the width of a single electrode on the pad i;

[0095] The electrode sequence of the pad close to the left boundary of the sector to which it belongs is calculated by the following equation: end left = N (Equation 13);

[0096] where N represents the number of electrodes on the pad, round() represents the rounding function, θ represents the central angle of the pad, and N leftrepresents the number of electrodes on the plate within its sector k, start left represents the starting index of the electrodes on the plate within its sector k, end left represents the ending index of the electrodes on the plate within its sector k;

[0097] The sequence of electrodes on the plate within its sector k near the right boundary of the sector k is calculated by: start right = 1 (Equation 15);

[0098] where N right represents the number of electrodes on the plate within its sector k, start right represents the starting index of the electrodes on the plate within its sector k, end right represents the ending index of the electrodes on the plate within its sector k;

[0099] The low-frequency relative permittivity of the sector k is calculated by: k,L = mean L,left • W left,k + mean L,right • W right,k (Equation 17);

[0100] where E k,L represents the low-frequency relative permittivity of the sector k, mean L,left is the average of the low-frequency relative permittivities of the sequence of electrodes on the plate within the sector k near the left boundary of the sector k, and E L,left [s] represents the low-frequency relative permittivity of the s-th electrode on the plate within the sector k near the left boundary of the sector k, N left represents the number of electrodes on the plate within the sector k near the left boundary of the sector k, mean L,right is the average of the low-frequency relative permittivities of the sequence of electrodes on the plate within the sector k near the right boundary of the sector k, and E L,right [s] represents the low-frequency relative permittivity of the s-th electrode on the plate within the sector k near the right boundary of the sector k, N right represents the number of electrodes on the plate within the sector k near the right boundary of the sector k;

[0101] The high-frequency relative permittivity of the sector k is calculated by: k,H = mean H,left • W left,k + mean H,right • Wright,k (Equation 20);

[0102] wherein E k,H represents the high-frequency relative dielectric constant of the sector k, mean H,left represents the average value of the high-frequency relative dielectric constants of the electrode sequence within the sector k on the electrode plate close to the left boundary of the sector k, and E H,left [s] represents the high-frequency relative dielectric constant of the s-th electrode within the sector k on the electrode plate close to the left boundary of the sector k, N left represents the number of electrodes within the sector k on the electrode plate close to the left boundary of the sector k, mean H,right represents the average value of the high-frequency relative dielectric constants of the electrode sequence within the sector k on the electrode plate close to the right boundary of the sector k, and E H,right [s] represents the high-frequency relative dielectric constant of the s-th electrode within the sector k on the electrode plate close to the right boundary of the sector k, N right represents the number of electrodes within the sector k on the electrode plate close to the right boundary of the sector k.

[0103] The invasion factor of the sector can be represented as: I k = f(E k,H , E k,L , p mud , P p ) (Equation 23);

[0104] wherein I k represents the invasion factor of the sector k, p mud represents the mud density, P p represents the formation pressure coefficient, and f() represents the constructed invasion factor function.

[0105] As a modification of the above embodiment, the invasion factor of the sector is the product of the first ratio and the output value of the exponential decay function with the difference between the mud density and the formation pressure coefficient as the input, the first ratio being the ratio of the high-frequency relative dielectric constant and the low-frequency relative dielectric constant of the sector. For example, the sector invasion factor can be represented as:

[0106] Because the ratio of the high-frequency relative dielectric constant and the low-frequency relative dielectric constant of the sector has a positive correlation with the permeability of the formation, i.e., the greater the ratio, the greater the permeability, and at the same time, the permeability also presents an exponential decay characteristic with the increase of the difference between the mud density and the formation pressure coefficient, therefore, the sector invasion factor shown in Equation 24 is constructed, which has a very strong positive correlation with the permeability, so that the function expression accuracy of the permeability calculation model obtained by fitting is higher.

[0107] As a modification of the above embodiment, step S120, by comparing the difference between the low-frequency relative dielectric constant and the high-frequency relative dielectric constant of the same electrode plate, the permeable layer section in the research formation is determined, including the following implementation steps:

[0108] For a certain layer section, if the absolute difference between the high-frequency relative dielectric constant and the low-frequency relative dielectric constant of the same electrode plate and the ratio of the high-frequency relative dielectric constant are less than the first preset value, it is determined that the layer section is a non-permeable layer section, otherwise it is determined that the layer section is a permeable layer section.

[0109] When external interference causes the high-frequency relative dielectric constant and the low-frequency relative dielectric constant to deviate, compared to directly judging whether the layer section is a permeable layer section by the difference between the high-frequency relative dielectric constant and the low-frequency relative dielectric constant of the same electrode plate, the way of judging whether the layer section is a permeable layer section by the absolute difference between the high-frequency relative dielectric constant and the low-frequency relative dielectric constant and the ratio of the high-frequency relative dielectric constant can reduce the influence of interference on the judgment result, thereby improving the accuracy of permeable layer section identification.

[0110] To illustrate the effectiveness of the above embodiment, the target wellbore and the target formation wellbore of the research formation are both B well of an oilfield in Xinjiang, the permeability of the formation where B well is located is evaluated based on the above method, before that, research is carried out for A well of the oilfield in Xinjiang, to determine the difference between the low-frequency relative dielectric constant and the high-frequency relative dielectric constant of the same electrode plate when oil-based mud electrical imaging logging is carried out under different formation permeability, and both A well and B well use NGI logging instrument of Schlumberger for measurement, including steps A1 to A11, wherein A1 is for A well, and the remaining steps are for B well:

[0111] Step A1, research is carried out for A well, as shown in Figure 4, the results of oil-based mud electrical imaging logging for A well. From left to right, the first 3 channels are conventional logging curve channels, the 4th to 6th channels are static image, dynamic image, and gap image respectively, the 7th channel is depth channel, and the 8th to 15th channels are high-frequency relative dielectric constant curve (dashed line) and low-frequency relative dielectric constant curve (solid line) of A, B, C, D, E, F, G, H electrode plate respectively. As can be seen from the figure, in the mudstone and dense layer section, there is no oil-based mud invasion, so the high-frequency relative dielectric constant and the low-frequency relative dielectric constant are basically equal or have little difference, and from Figure 4 it can be seen that the two are basically coincident, therefore, when the layer section is mudstone or non-permeable layer, the relationship between the high-frequency relative dielectric constant and the low-frequency relative dielectric constant of the same electrode plate can be represented by the following formula: When the layer section is a permeable layer section, mud cake will be formed at the well wall due to the invasion of oil-based mud, and the flushing zone will be filtered by mud filtrate, thus causing a difference in the relative dielectric constant of the two, and the deeper the invasion, the greater the difference. As can be seen from Fig. 4, both the two permeable layer sections of 6909.5-6913 m and 6914-6915.2 m have cracks, and the dip angles and widths of the cracks are similar, but the density logging value of the permeable layer section of 6914-6915.2 m is lower, and the physical property is better, so the difference between the high-frequency and low-frequency relative dielectric constants is greater, and therefore, when the layer section is a permeable layer section, the relationship between the high-frequency and low-frequency relative dielectric constants of the same electrode plate can be represented by the following formula:

[0112] Step A2, processing the Schlumberger NGI oil-based mud electrical imaging logging data of well B to obtain static images, dynamic images, low-frequency relative dielectric constants and high-frequency relative dielectric constants of all electrode plates, and azimuth angles of all electrode plates; obtaining the mud density when the target wellbore of the research formation is developed by oil-based mud logging, and the formation pressure coefficient calculated by logging data.

[0113] Step A3, comparing the difference between the low-frequency relative dielectric constant and the high-frequency relative dielectric constant of the same electrode plate to determine the permeable layer section in the research formation, wherein the first preset value is set to 10%.

[0114] Step A4, annular piston sampling of the full-diameter core of at least one permeable layer section. The sampling principle is that four piston samples are taken for each depth, i.e. t is four, and the phase between different piston samples at each depth can be calculated by the following formula:

[0115] Therefore, four piston samples in the directions of 0°, 90°, 180° and 270° can be obtained at the same depth, as shown in Fig. 2. After obtaining the piston samples in different directions at different depths, the porosity and permeability of the samples are measured to obtain the porosity experimental data and the permeability experimental data.

[0116] Step A5, according to the wellbore size of well B and the electrode plate structure of the Schlumberger NGI oil-based mud electrical imaging logging instrument, the corresponding central angle of each electrode plate is calculated. It is known that the well diameter of well B is 8.5 in, the radius r = 8.5 / 2, the electrode width of each electrode plate of the NGI oil-based mud electrical imaging logging instrument is 0.13 in, and there are 24 electrodes on each electrode plate of the Schlumberger NGI oil-based mud electrical imaging logging instrument. Assuming that the wellbore is approximately circular, the calculation process of the corresponding central angle of an electrode plate is as follows:

[0117] Step A6, the wellbore of Well B is divided into 8 sectors as shown in Figure 3, and the phase angle and sector bisector angle of each sector are calculated, wherein the phase angle of the sector is 45°, and the bisector angles of the 8 sectors are 22.5°, 67.5°, 112.5°, 157.5°, 202.5°, 247.5°, 292.5° and 337.5° respectively. The sector bisector angle of No. 1 sector is 22.5°, the left boundary angle of No. 1 sector is 0°, and the right boundary angle of No. 1 sector is 45°.

[0118] Step A7, the electrode plate of the NGI oil-based mud electrical imaging logging instrument in No. 1 sector is in the state of Figure 5, that is: θ left = 2° and θ right = 47°, the difference value between the azimuth angle of the electrode plate close to the left boundary of No. 1 sector and the left boundary of No. 1 sector is calculated by Formula Seven, and the calculation process is as follows:

[0119] The difference value between the azimuth angle of the electrode plate close to the right boundary of No. 1 sector and the right boundary of No. 1 sector is calculated by Formula Eight, and the calculation process is as follows:

[0120] The contribution weight of the electrode plate close to the left boundary of No. 1 sector to the high-frequency relative permittivity and the low-frequency relative permittivity of No. 1 sector is calculated by Formula Nine, and the calculation process is as follows:

[0121] The contribution weight of the electrode plate close to the right boundary of No. 1 sector to the high-frequency relative permittivity and the low-frequency relative permittivity of No. 1 sector is calculated by Formula Ten, and the calculation process is as follows:

[0122] According to the difference between the azimuth angle of the electrode plate close to the left boundary of No. 1 sector and the left boundary of No. 1 sector, the number of electrodes and the electrode index range of the electrode plate located in No. 1 sector are calculated by using Formula Eleven to Formula Thirteen, and the specific calculation process is as follows: start left = N-N left +1 = 24-13+1 = 12; end left = 24;

[0123] According to the difference between the azimuth angle of the electrode plate close to the right boundary of No. 1 sector and the sector bisector angle of No. 1 sector, the number of electrodes and the electrode index range of the electrode plate located in No. 1 sector are calculated by using Formula Fourteen to Formula Sixteen, and the specific calculation process is as follows: start right = 1; end right = N right = 10;

[0124] The average value of the high-frequency relative dielectric constant of the electrode sequence of the pole plate close to the left boundary of the No. 1 sector in the No. 1 sector is calculated by using formula twenty-one, the average value of the low-frequency relative dielectric constant of the electrode sequence of the pole plate close to the left boundary of the No. 1 sector in the No. 1 sector is calculated by using formula eighteen, the average value of the high-frequency relative dielectric constant of the electrode sequence of the pole plate close to the right boundary of the No. 1 sector in the No. 1 sector is calculated by using formula twenty-two, and the average value of the low-frequency relative dielectric constant of the electrode sequence of the pole plate close to the right boundary of the No. 1 sector in the No. 1 sector is calculated by using formula nineteen;

[0125] The low-frequency relative dielectric constant of the No. 1 sector is calculated by using formula seventeen, and the high-frequency relative dielectric constant of the No. 1 sector is calculated by using formula twenty;

[0126] The invasion factor of the No. 1 sector is calculated by using formula twenty-four;

[0127] The invasion factors of all the sectors are calculated by repeating the above steps.

[0128] Step A8, depth homing is performed by using porosity experimental data and porosity curves.

[0129] Step A9, directional homing is performed on the permeability experimental data. In the application example, the directional homing of the permeability experimental data is performed by rotating the core, and the specific method is as follows: the permeability experimental data in the four directions of 0°, 90°, 180° and 270° are first compared with the invasion factors of the No. 1 sector, the No. 3 sector, the No. 5 sector and the No. 7 sector respectively in terms of trend, if the trend does not conform, the permeability experimental data in the four directions are rotated, and the trend comparison is performed with the invasion factors of the No. 2 sector, the No. 4 sector, the No. 6 sector and the No. 8 sector respectively, if the trend still has obvious difference, the permeability experimental data in the four directions are continuously rotated, and the trend comparison is performed with the invasion factors of the No. 3 sector, the No. 5 sector, the No. 7 sector and the No. 1 sector respectively, and so on, until the change trend of the permeability experimental data in all phase angles is consistent with the change trend of the invasion factor curve of a specific sector, that is, the directional homing is completed.

[0130] Step A10, the permeability calculation model is obtained by fitting the homed permeability experimental data and the corresponding invasion factor. As shown in FIG. 6, the function expression of the permeability calculation model obtained by fitting is: perm = 0.0048 × e 2.0601×I perm represents the output value of the permeability calculation model, that is, the calculated permeability value.

[0131] Step A11, the permeability of the determined sectors in the target formation is calculated by using the permeability calculation model. In the application example, the layer section in the well B which needs to be evaluated for permeability is determined by calculating the sector invasion factor based on the oil-based mud electrical imaging logging data of the well B in the above layer section, and the sector invasion factor is used as the input of the permeability calculation model. Figure 7 shows the comparison between the permeability evaluation results of the well B in the above layer section obtained by the permeability evaluation method based on the oil-based mud electrical imaging logging according to the embodiment of the present application and the permeability evaluation results obtained by the conventional nuclear magnetic COATES model. From left to right, the first to third columns are the conventional logging curve columns, the fourth to sixth columns are the static image, dynamic image and gap image respectively, the seventh column is the depth column, the eighth to fifteenth columns are the permeability evaluation curves of the first to eighth sectors respectively, the numbers in 4538-4539 are the average values of the permeability of the eight sectors in the reservoir section, and the rectangular scatter points are the core permeability experimental data in four directions, which are compared with the permeability calculated in the first, third, fifth and eighth sectors respectively. As can be seen from the figure, the permeability obtained based on the oil-based mud electrical imaging logging has good correspondence with the core experimental data, while the permeability obtained by the nuclear magnetic COATES model has no correspondence with the core experimental data at all, and the permeability calculated by the nuclear magnetic method has no directionality and cannot obtain the anisotropic permeability. At the same time, by focusing on the high permeability layer of 4538-4539, it can be seen that the permeability of the fourth sector and the fifth sector is the largest, which is 2-3 times of that of other sectors. It has been proved by oil and gas exploration that in the glutenite, the physical property of coarse sandstone is the best and the permeability is the best. From the static image and the dynamic image, it can be seen that the fourth sector and the fifth sector correspond to the areas containing gravel coarse sandstone. The first to third sectors and the sixth to eighth sectors are small glutenite with relatively coarse particle size, and the permeability is relatively poor. It can be seen that the above conclusion verifies the effectiveness of the permeability evaluation method based on the oil-based mud electrical imaging logging provided by the embodiment of the present application.

[0132] Device embodiment

[0133] Referring to Figure 8, corresponding to the permeability evaluation method based on the oil-based mud electrical imaging logging of the above embodiment, the embodiment of the present application provides a permeability evaluation device 400 based on the oil-based mud electrical imaging logging, which comprises sector relative permittivity determination module 410, sector invasion factor construction module 420, permeability experimental data homing module 430, model generation module 440 and permeability evaluation module 450 connected in sequence, wherein:

[0134] The sector relative permittivity determination module 410 is used to determine the permeable layer section in the formation after processing the oil-based mud electrical imaging logging data of the target wellbore of the research formation, and determine the low-frequency relative permittivity and high-frequency relative permittivity of each sector of the target wellbore in the permeable layer section;

[0135] The sector invasion factor construction module 420 is configured to construct an invasion factor of the sector according to the low-frequency relative dielectric constant, the high-frequency relative dielectric constant and a characteristic parameter of the sector, the invasion factor has a correlation with the formation permeability, and the characteristic parameter is a geological parameter and / or an engineering parameter associated with the depth of the oil-based mud invasion into the formation caused by the change of the formation permeability.

[0136] The permeability experimental data homing module 430 is configured to obtain permeability experimental data generated after measuring the permeability of the core of the permeable layer segment obtained by the annular sampling, and to homing the permeability experimental data in a direction.

[0137] The model generation module 440 is configured to fit the homed permeability experimental data with the invasion factor to generate a permeability calculation model.

[0138] The permeability evaluation module 450 is configured to calculate the permeability of the determined sector in the target formation by using the permeability calculation model. In one specific embodiment, the characteristic parameter includes the mud density and the formation pressure coefficient when the oil-based mud electrical imaging logging is performed on the target wellbore.

[0139] As an embodiment of the present application, the permeability evaluation device 400 based on the oil-based mud electrical imaging logging can realize the embodiment as shown in FIG. 1 and other related method embodiments of the present application.

[0140] The process of realizing the functions of each module in the mud pulse data encoding device provided by the embodiments of the present application is specifically referable to the description of the embodiment shown in FIG. 1 and other related method embodiments, which will not be repeated here.

[0141] It should be noted that the information interaction, execution process and the like between the above modules are based on the same concept as the method embodiments of the present application, and the specific functions and the technical effects brought by them are specifically referable to the method embodiments, which will not be repeated here. In addition, the above modules can be applied to a computing device comprising a memory and a processor.

[0142] On the other hand, the embodiments of the present application also provide a machine readable storage medium having a computer program stored thereon, the computer program is executed by a processor to realize the permeability evaluation method based on the oil-based mud electrical imaging logging as described in the above method embodiments.

[0143] In another aspect, the embodiment of the present application also provides a computer device which can be a terminal, and the internal structure diagram of the computer device can be shown in FIG. 9. The computer device comprises a processor A01, a network interface A02, a display screen A04, an input device A05 and a memory (not shown in the figure) which are connected through a system bus. The processor A01 of the computer device is used to provide computing and control capabilities. The memory of the computer device comprises an internal memory A03 and a non-volatile storage medium A06. The non-volatile storage medium A06 stores an operating system B01 and a computer program B02. The internal memory A03 provides an environment for the running of the operating system B01 and the computer program B02 in the non-volatile storage medium A06. The network interface A02 of the computer device is used to communicate with external terminals through network connection. The computer program is executed by the processor A01 to implement the permeability evaluation method based on oil-based mud electrical imaging logging. The display screen A04 of the computer device can be a liquid crystal display screen or an electronic ink display screen. The input device A05 of the computer device can be a touch layer overlaid on the display screen, or can be a key, trackball or touchpad arranged on the shell of the computer device, or can be an external keyboard, touchpad or mouse, etc.

[0144] In one embodiment, the device 400 for evaluating permeability based on oil-based mud electrical imaging logging provided by the present application can be implemented in the form of a computer program which can run on the computer device shown in FIG. 9. Each program module constituting the device 400 for evaluating permeability based on oil-based mud electrical imaging logging can be stored in the memory of the computer device. The computer program constituted by each program module enables the processor to execute the steps in the method for evaluating permeability based on oil-based mud electrical imaging logging described in the specification.

[0145] The embodiment of the present application also provides a computer program product which, when executed on a data processing device, is adapted to execute a program which has the following method steps:

[0146] The oil-based mud electrical imaging logging data of the target borehole of the research formation are processed to determine the permeable layer section in the formation and determine the low-frequency relative dielectric constant and the high-frequency relative dielectric constant of each sector of the target borehole in the permeable layer section;

[0147] The invasion factor of the sector is constructed according to the low-frequency relative dielectric constant, the high-frequency relative dielectric constant and the characteristic parameter of the sector. The invasion factor has a correlation with the formation permeability. The characteristic parameter is a geological parameter and / or an engineering parameter which is associated with the depth of the invasion of the oil-based mud into the formation caused by the change of the formation permeability.

[0148] The permeability experimental data generated after the permeability measurement of the core of the permeable layer section obtained by the annular sampling is acquired, and the permeability experimental data is directionally homed.

[0149] The permeability calculation model is generated by fitting the permeability data after homing with the invasion factor;

[0150] The permeability of the determined sector in the target formation is calculated by using the permeability calculation model.

[0151] The apparatus embodiments described above are merely illustrative, wherein the units as illustrated can or can not be physically separated, and the components as units can or can not be physical components, i.e., can be located in one place, or can be distributed on multiple network components. Part or all of the modules can be selected according to actual needs to achieve the purpose of the embodiments. Those skilled in the art can understand and implement without creative labor.

[0152] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0153] It should also be noted that the terms "comprising", "including", or any other variant thereof are intended to cover non-exclusive inclusions, so that processes, methods, articles, or devices that include a series of elements not only include those elements, but also include other elements not explicitly listed, or inherent to such processes, methods, articles, or devices. Without more limitations, the element defined by the statement "including a" does not exclude the presence of other identical elements in the process, method, article, or device that includes the element.

[0154] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit it; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that the technical solutions recorded in the foregoing embodiments can be modified, or some technical features can be replaced by equivalent ones; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A permeability evaluation method based on oil-based mud electrical imaging logging, characterized in that, The method comprises: processing oil-based mud electrical imaging logging data of a target borehole in a study formation to determine a permeable layer section in the formation and determine low-frequency relative dielectric constant and high-frequency relative dielectric constant of each sector of the target borehole in the permeable layer section; constructing an invasion factor of the sector according to the low-frequency relative dielectric constant, the high-frequency relative dielectric constant and a characteristic parameter of the sector, the invasion factor being correlated with formation permeability, and the characteristic parameter being a geological parameter and / or an engineering parameter associated with the depth of oil-based mud invasion into the formation caused by changes in formation permeability; obtaining permeability experimental data generated after measuring the permeability of a core of the permeable layer section obtained by annular sampling, and directionally homing the permeability experimental data; fitting the homed permeability experimental data with the invasion factor to generate a permeability calculation model; calculating the permeability of the determined sector in the target formation by using the permeability calculation model.

2. The oil-based mud electrical imaging log based permeability evaluation method of claim 1, wherein, The characteristic parameter comprises mud density and formation pressure coefficient when the oil-based mud electrical imaging logging is performed on the target borehole.

3. The oil-based mud electrical imaging log based permeability evaluation method of claim 2, wherein, The invasion factor is a product of a first ratio and an output value of an exponential decay function with the difference between the mud density and the formation pressure coefficient as input, the first ratio being a ratio of the high-frequency relative dielectric constant to the low-frequency relative dielectric constant of the sector.

4. The oil-based mud electrical imaging log based permeability evaluation method of claim 1, wherein, The processing of the oil-based mud electrical imaging logging data of the target borehole in the study formation to determine the permeable layer section in the formation and determine the low-frequency relative dielectric constant and the high-frequency relative dielectric constant of each sector of the target borehole in the permeable layer section comprises: processing the oil-based mud electrical imaging logging data of the target borehole in the study formation to obtain the low-frequency relative dielectric constant, the high-frequency relative dielectric constant and the azimuth angle of all the electrodes; determining the permeable layer section in the study formation by comparing the difference between the low-frequency relative dielectric constant and the high-frequency relative dielectric constant of the same electrode; dividing the target borehole into sectors and determining the sector to which each electrode belongs and the electrode sequence in the sector according to the azimuth angle of the electrode; determining the low-frequency relative dielectric constant and the high-frequency relative dielectric constant of the sector according to the electrode sequence in the sector.

5. The oil-based mud electrical imaging log based permeability evaluation method of claim 4, wherein, The determination of the permeable layer section in the study formation by comparing the difference between the low-frequency relative dielectric constant and the high-frequency relative dielectric constant of the same electrode comprises: for a certain layer section, if the absolute difference between the high-frequency relative dielectric constant and the low-frequency relative dielectric constant of the same electrode and the ratio of the high-frequency relative dielectric constant are less than a first preset value, the layer section is determined to be a non-permeable layer section, otherwise, the layer section is determined to be a permeable layer section.

6. The oil-based mud electrical imaging log based permeability evaluation method of claim 4, wherein, The division of the target borehole into sectors and the determination of the sector to which each electrode belongs and the electrode sequence in the sector according to the azimuth angle of the electrode comprise: dividing the borehole into sectors and calculating the azimuth information of each sector, the azimuth information of the sector including the sector phase angle, the sector bisector angle, the sector left boundary angle and the sector right boundary angle in the clockwise direction; determining the sector to which the electrode belongs according to the azimuth angle of the electrode and the azimuth information of the sector; determining the electrode sequence in the sector to which the electrode belongs according to the difference between the azimuth angle of the electrode and the sector boundary of the sector to which the electrode belongs or the positional relationship between the azimuth angle of the electrode and the sector bisector angle of the sector to which the electrode belongs.

7. The oil-based mud electrical imaging log based permeability evaluation method of claim 6, wherein, The method comprises the following steps: determining the electrode sequence in the sector according to the difference between the azimuth angle of the polar plate and the sector boundary of the sector to which the polar plate belongs or the positional relationship between the azimuth angle of the polar plate and the sector bisector of the sector to which the polar plate belongs. If the azimuth angle of the polar plate coincides with the sector bisector of the sector to which the polar plate belongs, the electrode sequence of the polar plate in the sector to which the polar plate belongs is determined as all the electrodes on the polar plate. If the azimuth angle of the polar plate does not coincide with the sector bisector of the sector to which the polar plate belongs and the polar plate is close to the left boundary of the sector to which the polar plate belongs, the included angle between the azimuth angle of the polar plate and the left boundary of the sector to which the polar plate belongs is calculated, and the electrode sequence of the polar plate in the sector to which the polar plate belongs is determined according to the calculated included angle. If the azimuth angle of the polar plate does not coincide with the sector bisector of the sector to which the polar plate belongs and the polar plate is close to the right boundary of the sector to which the polar plate belongs, the included angle between the azimuth angle of the polar plate and the right boundary of the sector to which the polar plate belongs is calculated, and the electrode sequence of the polar plate in the sector to which the polar plate belongs is determined according to the calculated included angle.

8. The oil-based mud electrical imaging logging based permeability evaluation method according to claim 6 or 7, characterized in that, The method comprises the following steps: determining the electrode sequence in the sector according to the difference between the azimuth angle of the polar plate and the sector boundary of the sector to which the polar plate belongs or the positional relationship between the azimuth angle of the polar plate and the sector bisector of the sector to which the polar plate belongs. The method comprises the following steps: determining the electrode sequence in the sector according to the difference between the azimuth angle of the polar plate and the sector boundary of the sector to which the polar plate belongs or the positional relationship between the azimuth angle of the polar plate and the sector bisector of the sector to which the polar plate belongs. For a certain sector, the average value of the high-frequency relative dielectric constant of each polar plate corresponding to the sector is weighted by using the contribution weight of the polar plate corresponding to the sector, to obtain a first weighted value, and the first weighted values of all the polar plates corresponding to the sector are summed to obtain the high-frequency relative dielectric constant of the sector; and the average value of the low-frequency relative dielectric constant of each polar plate corresponding to the sector is weighted by using the contribution weight of the polar plate corresponding to the sector, to obtain a second weighted value, and the second weighted values of all the polar plates corresponding to the sector are summed to obtain the low-frequency relative dielectric constant of the sector.

9. The oil-based mud electrical imaging log-based permeability evaluation method of claim 8, wherein, The method comprises the following steps: determining the electrode sequence in the sector according to the difference between the azimuth angle of the polar plate and the sector boundary of the sector to which the polar plate belongs or the positional relationship between the azimuth angle of the polar plate and the sector bisector of the sector to which the polar plate belongs. If the azimuth angle of the polar plate coincides with the sector bisector of the sector to which the polar plate belongs, the electrode sequence of the polar plate in the sector to which the polar plate belongs is determined as all the electrodes on the polar plate. If the azimuth angle of the polar plate does not coincide with the sector bisector of the sector to which the polar plate belongs and the polar plate is close to the left boundary of the sector to which the polar plate belongs, the included angle between the azimuth angle of the polar plate and the left boundary of the sector to which the polar plate belongs is calculated, and the electrode sequence of the polar plate in the sector to which the polar plate belongs is determined according to the calculated included angle. If the azimuth angle of the polar plate does not coincide with the sector bisector of the sector to which the polar plate belongs and the polar plate is close to the right boundary of the sector to which the polar plate belongs, the included angle between the azimuth angle of the polar plate and the right boundary of the sector to which the polar plate belongs is calculated, and the electrode sequence of the polar plate in the sector to which the polar plate belongs is determined according to the calculated included angle. The method comprises the following steps: determining the electrode sequence in the sector according to the difference between the azimuth angle of the polar plate and the sector boundary of the sector to which the polar plate belongs or the positional relationship between the azimuth angle of the polar plate and the sector bisector of the sector to which the polar plate belongs. If the azimuth angle of the polar plate coincides with the sector bisector of the sector to which the polar plate belongs, the electrode sequence of the polar plate in the sector to which the polar plate belongs is determined as all the electrodes on the polar plate. If the azimuth angle of the polar plate does not coincide with the sector bisector of the sector to which the polar plate belongs and the polar plate is close to the left boundary of the sector to which the polar plate belongs, the included angle between the azimuth angle of the polar plate and the left boundary of the sector to which the polar plate belongs is calculated, and the electrode sequence of the polar plate in the sector to which the polar plate belongs is determined according to the calculated included angle. If the azimuth angle of the polar plate does not coincide with the sector bisector of the sector to which the polar plate belongs and the polar plate is close to the right boundary of the sector to which the polar plate belongs, the included angle between the azimuth angle of the polar plate and the right boundary of the sector to which the polar plate belongs is calculated, and the electrode sequence of the polar plate in the sector to which the polar plate belongs is determined according to the calculated included angle. The method comprises the following steps: determining the electrode sequence in the sector according to the difference between the azimuth angle of the polar plate and the sector boundary of the sector to which the polar plate belongs or the positional relationship between the azimuth angle of the polar plate and the sector bisector of the sector to which the polar plate belongs. If the azimuth angle of the polar plate coincides with the sector bisector of the sector to which the polar plate belongs, the electrode sequence of the polar plate in the sector to which the polar plate belongs is determined as all the electrodes on the polar plate. If the azimuth angle of the polar plate does not coincide with the sector bisector of the sector to which the polar plate belongs and the polar plate is close to the left boundary of the sector to which the polar plate belongs, the included angle between the azimuth angle of the polar plate and the left boundary of the sector to which the polar plate belongs is calculated, and the electrode sequence of the polar plate in the sector to which the polar plate belongs is determined according to the calculated included angle. If the azimuth angle of the polar plate does not coincide with the sector bisector of the sector to which the polar plate belongs and the polar plate is close to the right boundary of the sector to which the polar plate belongs, the included angle between the azimuth angle of the polar plate and the right boundary of the sector to which the polar plate belongs is calculated, and the electrode sequence of the polar plate in the sector to which the polar plate belongs is determined according to the calculated included angle.

10. The oil-based mud electrical imaging logging based permeability evaluation method according to claim 9, wherein δ represents a sector phase angle, and m represents a number of sectors divided by the target borehole. The phase angle of the sector is calculated by the following equation: If the azimuth angle of the electrode plate does not coincide with the sector bisector angle of the sector to which the electrode plate belongs: The sector bisector angle is calculated by the following equation: where k represents the number of the sector, 1≤k≤m, θ k represents the sector bisecting angle; The sector left border angle in the clockwise direction is calculated by the following equation: wherein a k denotes the left boundary angle of the sector numbered k; The sector right boundary angle in the clockwise direction is calculated by the following equation: wherein β k denotes the right boundary angle of the sector numbered k; The direction of the permeability experimental data is returned, including: The contribution weight of the electrode plate near the left border of the sector to the high frequency relative dielectric constant and the low frequency relative dielectric constant of the sector is calculated by the following formula: The contribution weight of the electrode plate near the right boundary of the sector to the high-frequency relative dielectric constant and the low-frequency relative dielectric constant of the sector is calculated by the following formula: where θ left,k denotes the azimuth angle θ of the pole plate close to the left border of sector k left denotes the difference value, θ right,k denotes the azimuth angle θ of the pole plate close to the right border of sector k right denotes the difference value, W left,k denotes the contribution weight, W right,k denotes the contribution weight, W The central angle θ of the electrode plate (i) Half of, r represents the wellbore radius, N (i) w represents the number of electrodes on the plate. (i) The width of a single electrode on the plate is indicated by 'i', and the plate number is indicated by 'i'. The sequence of electrodes on the pole plate near the left border of the sector is calculated by the following formula: end left = N; wherein N denotes the number of electrodes on the pad, round() denotes the rounding function, θ denotes the central angle of the pad, N left denotes the number of electrodes on the pad which belong to its sector k, start left denotes the start index of the electrodes on the pad which belong to its sector k, end left denotes the end index of the electrodes on the pad which belong to its sector k; The sequence of electrodes on the plate closest to the right boundary of the sector that are located in the sector are calculated by the following formula: start right = 1; where N right represents the number of electrodes on the plate that belong to sector k, start right represents the starting index of the electrodes on the plate that belong to sector k, end right represents the ending index of the electrodes on the plate that belong to sector k.

11. The oil-based mud electrical imaging log based permeability evaluation method of claim 1, wherein, Obtaining the porosity experimental data generated after measuring the porosity of the core of the permeable layer obtained by annular sampling; Obtaining the porosity curve obtained by logging; The depth of the permeability experimental data layer is returned by comparing the porosity experimental data and the porosity curve; The direction of the permeability experimental data is returned by using the invasion factor according to the principle that the change trend of the permeability experimental data of a certain phase angle is consistent with the change trend of the invasion factor of a certain sector. The device comprises:

12. A permeability evaluation device based on electrical imaging logging of oil-based mud, characterized in that, A sector relative dielectric constant determination module is configured to process oil-based mud electrical imaging logging data of a target borehole in a study formation, determine a permeable layer in the formation, and determine low-frequency relative dielectric constant and high-frequency relative dielectric constant of each sector of the target borehole in the permeable layer. A sector invasion factor construction module is configured to construct an invasion factor of a sector according to low-frequency relative dielectric constant, high-frequency relative dielectric constant, and characteristic parameters of the sector, the invasion factor has a correlation with formation permeability, and the characteristic parameters are geological parameters and / or engineering parameters associated with the depth of oil-based mud invasion into the formation caused by changes in formation permeability. A permeability experimental data returning module is configured to obtain permeability experimental data generated after measuring the permeability of a core of a permeable layer obtained by annular sampling, and return the direction of the permeability experimental data. A model generation module is configured to fit the returned permeability experimental data and the invasion factor to generate a permeability calculation model. A permeability evaluation module is configured to calculate the permeability of a determined sector in a target formation by using the permeability calculation model. The processing of the oil-based mud electrical imaging logging data of the target borehole in the study formation, the determination of the permeable layer in the formation, and the determination of the low-frequency relative dielectric constant and the high-frequency relative dielectric constant of each sector of the target borehole in the permeable layer comprise:

13. The oil-based mud electrical imaging logging based permeability evaluation apparatus according to claim 12, wherein, Processing the oil-based mud electrical imaging logging data of the target borehole in the study formation to obtain low-frequency relative dielectric constant, high-frequency relative dielectric constant, and azimuth angle of all electrode plates; Determining the permeable layer in the study formation by comparing the difference between the low-frequency relative dielectric constant and the high-frequency relative dielectric constant of the same electrode plate; Dividing the target borehole into sectors and determining the sector to which the electrode plate belongs and the electrode sequence in the sector according to the azimuth angle of the electrode plate; Determining the low-frequency relative dielectric constant and the high-frequency relative dielectric constant of the sector itself according to the electrode sequence in the sector. The dividing of the target borehole into sectors and the determination of the sector to which the electrode plate belongs and the electrode sequence in the sector according to the azimuth angle of the electrode plate comprise:

14. The oil-based mud electrical imaging logging based permeability evaluation apparatus according to claim 13, wherein, Dividing the borehole into sectors and calculating the azimuth information of each sector, the azimuth information of the sector including a sector phase angle, a sector bisector angle, a left boundary angle, and a right boundary angle in the clockwise direction. ​ determining the sector to which the polar plate belongs according to the azimuth angle of the polar plate and the azimuth information of the sector; determining the electrode sequence on the polar plate that belongs to the sector according to the difference between the azimuth angle of the polar plate and the sector boundary of the sector to which the polar plate belongs or the positional relationship between the azimuth angle of the polar plate and the sector bisector angle of the sector to which the polar plate belongs.

15. The oil-based mud electrical imaging logging based permeability evaluation apparatus according to claim 13, wherein, determining the low-frequency relative dielectric constant and the high-frequency relative dielectric constant of the sector itself according to the electrode sequence in the sector, including: determining the contribution weight of the polar plate to the high-frequency relative dielectric constant and the low-frequency relative dielectric constant of the sector according to the difference between the azimuth angle of the polar plate and the sector boundary of the sector to which the polar plate belongs or the positional relationship between the azimuth angle of the polar plate and the sector bisector angle of the sector to which the polar plate belongs, and calculating the average value of the high-frequency relative dielectric constant of each electrode in the electrode sequence on the polar plate that belongs to the sector and the average value of the low-frequency relative dielectric constant of each electrode in the electrode sequence on the polar plate that belongs to the sector; for a certain sector, weighting the average value of the high-frequency relative dielectric constant corresponding to the polar plate itself according to the contribution weight corresponding to the polar plate itself to obtain a first weighted value, summing the first weighted values of all the polar plates belonging to the sector to obtain the high-frequency relative dielectric constant of the sector, and weighting the average value of the low-frequency relative dielectric constant corresponding to the polar plate itself according to the contribution weight corresponding to the polar plate itself to obtain a second weighted value, and summing the second weighted values of all the polar plates belonging to the sector to obtain the low-frequency relative dielectric constant of the sector.

16. A computer device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein, The processor executes the program to realize the oil-based mud electrical imaging logging-based permeability evaluation method in any one of claims 1 to 11.

17. A machine-readable storage medium having stored thereon a computer program, characterized in that The computer program is executed by the processor to realize the oil-based mud electrical imaging logging-based permeability evaluation method in any one of claims 1 to 11.

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