Well leakage type judgment method, device and equipment based on permeability comparison and medium

Abstract

The invention relates to the technical field of petroleum and natural gas development, in particular to a well leakage type judgment method and device based on permeability comparison and a medium. When the target leakage well section lacks imaging logging information, the rock porosity and the average particle radius are calculated by obtaining the logging information and the logging information, then the average permeability of the leakage stratum is inversed, the theoretical permeability is calculated by using the Kozeny-Carman model based on the assumption that the leakage stratum is a pure pore medium, and the permeability of the leakage stratum is calculated by using the Kozeny-Carman model. And comparing a relative error between the actually measured average permeability and the theoretical permeability with a preset threshold value to judge whether the leakage type is fractured or permeable leakage. The method does not need to depend on imaging logging information, and can quickly and quantitatively identify the well leakage type on an engineering site, so that targeted leakage prevention and plugging measures are adopted, and well drilling risks such as blowout are effectively reduced.

Description

Technical Field

[0001] This application relates to the field of oil and gas development technology, specifically to a method, device, and medium for determining well leakage type based on permeability comparison. Background Technology

[0002] In oil and gas drilling engineering, well leakage is one of the most common and complex downhole failures. Well leakage not only causes significant loss of drilling fluid and increases drilling costs and time, but may also induce serious accidents such as well collapse, stuck pipe, or even blowout. Accurately identifying the type of well leakage is a prerequisite for developing effective leakage prevention and plugging measures.

[0003] Currently, the main methods for determining well leakage types in engineering projects include imaging logging and core testing. Imaging logging (such as electrical imaging and acoustic imaging) can directly reflect formation fractures, pore structure, and other characteristics, thus helping to determine the nature of leakage channels; core analysis can provide direct evidence of rock physical parameters. However, these two methods are costly and time-consuming to implement, making them difficult to apply widely in all well sections, especially in scenarios with a large number of exploration or development wells, where economic efficiency and timeliness are limited.

[0004] In recent years, intelligent identification methods for well leakage types based on machine learning have gradually emerged. By integrating multi-source drilling and logging parameters to establish a predictive model, the identification efficiency has been improved to some extent. However, such methods usually lack the ability to analyze the physical mechanism of leakage and have poor interpretability.

[0005] Because it is difficult to accurately and quickly determine the shape of leakage channels after oil and gas well completion, and it is also impossible to quantify the parameters of leakage channels, the current judgment method in actual engineering sites often relies on inferring the nature of leakage channels based on leakage rate and experience, resulting in a lack of specificity in the selection of plugging solutions. Especially in the absence of imaging logging data, how to quickly and quantitatively identify the type of leakage based on conventional logging and well logging data remains a technical problem that urgently needs to be solved in the field.

[0006] Therefore, there is an urgent need for a well leakage type identification method that does not rely on imaging logging, can combine rock physics mechanisms, and is suitable for rapid decision-making in engineering sites, in order to make up for the shortcomings of existing technologies in terms of cost, timeliness, and mechanism interpretability. Summary of the Invention

[0007] The purpose of this application is to provide a method, device, and medium for determining well leakage type based on permeability comparison, in order to solve the problems in the prior art where well leakage type determination relies heavily on imaging logging data and the well leakage type determination is inaccurate and slow.

[0008] To achieve the above objectives, the first aspect of this application provides a method for determining well leakage type based on permeability comparison, comprising:

[0009] When imaging logging data is lacking for the target lost well section, obtain logging and well logging data for the target lost well section; The rock porosity of the target lost circulation section is determined based on well logging data, and the average radius of rock particles is determined based on the rock cuttings obtained from the target lost circulation section. Based on well logging data, the average permeability of the lost formation corresponding to the target lost well section is calculated by inversion. Assuming the lost formation is a purely porous medium, the theoretical permeability of the porous formation is determined based on the average radius of rock particles, rock porosity, and a preset tortuosity. Determine the relative error between the average permeability and the theoretical permeability; Based on the comparison between the relative error and the preset threshold, the leakage type of the target leakage section is determined to be either fracture leakage or permeability leakage.

[0010] In this embodiment of the application, determining whether the leakage type of the target leakage well section is fracture leakage or permeability leakage based on the comparison result of the relative error and the preset threshold includes: If the relative error is greater than or equal to a preset threshold, the leakage type of the target leakage well section is determined to be fracture leakage; If the relative error is less than a preset threshold, the leakage type of the target leakage well section is determined to be permeable leakage.

[0011] In this embodiment of the application, the average permeability of the lost formation corresponding to the target lost well section is determined based on the following formula inversion:

[0012]

[0013] in, The average permeability of the formation corresponding to the target lost circulation interval. q This represents the average leakage flow rate of the drilling fluid. μ For drilling fluid viscosity, r e For supply radius, r w The radius of the wellbore. h For the length of the missing segment, p For pressure difference, p m This refers to the static pressure of the drilling fluid column. p a For annular pressure loss, p p This represents the pore pressure of the original formation.

[0014] In this embodiment of the application, assuming the lost formation is a purely porous medium, the theoretical permeability of the porous formation is determined based on the average radius of rock particles, rock porosity, and a preset tortuosity, including: Assuming the lost formation is a purely porous medium and the rock is modeled as a parallel capillary bundle, the theoretical permeability is calculated based on the Kozeny-Carman equation, the average radius of rock particles, rock porosity, and a preset tortuosity.

[0015] In this embodiment, the theoretical penetration rate is determined according to the following formula:

[0016] in, K m Theoretical penetration rate, For rock porosity, r Where is the throat radius, τ For tortuosity; The relationship between the pore throat radius and the average radius of rock grains is as follows:

[0017] in, R The average radius of the rock particles; The specific surface area of ​​a rock is determined by the following formula.

[0018] Where S is the rock specific surface area; The theoretical permeability of the same specific surface based on the average radius of rock particles is determined by the following formula:

[0019] In this embodiment of the application, when the average penetration rate is greater than 100mD, the target threshold is set to 1000%; when the average penetration rate is greater than 10mD and less than 100mD, the target threshold is set to 500%; and when the average penetration rate is less than 10mD, the target threshold is set to 150%.

[0020] In this embodiment of the application, the method further includes: determining whether the logging data includes imaging logging data; if imaging logging data exists, determining whether the lost well section is a permeable loss or a fracture loss based on the imaging characteristics.

[0021] A second aspect of this application provides a well leakage type determination device based on permeability comparison, comprising: The data acquisition module is used to acquire logging and well logging data of the target lost well section when imaging logging data is lacking. The first calculation module is used to determine the rock porosity of the target lost well section based on well logging data, and to determine the average radius of rock particles based on the rock cuttings obtained from the target lost well section. The second calculation module is used to calculate the average permeability of the lost formation corresponding to the target lost well section based on well logging data. The third calculation module assumes that the lost formation is a pure porous medium and is used to determine the theoretical permeability of the porous formation based on the average radius of rock particles, rock porosity, and preset tortuosity. The error determination module is used to determine the relative error between the average permeability and the theoretical permeability; The type determination module is used to determine whether the leakage type of the target leakage well section is fracture leakage or permeability leakage based on the comparison result of the relative error and the preset threshold.

[0022] A third aspect of this application provides a well leakage type determination device based on permeability comparison, comprising: The memory is configured to store instructions; The processor is configured to retrieve instructions from memory and, when executing instructions, implement either of the following well leakage type determination methods based on permeability comparison.

[0023] A fourth aspect of this application provides a machine-readable storage medium storing instructions for causing a machine to execute any one of the well leakage type determination methods based on permeability comparison.

[0024] Through the above technical solution, when imaging logging data is lacking in the target lost circulation section, this application can obtain logging and well logging data, calculate rock porosity and average particle radius, invert the average permeability of the lost circulation formation, and calculate the theoretical permeability using the Kozeny-Carman model based on the assumption that the lost circulation layer is a pure porous medium. Then, by comparing the relative error between the measured average permeability and the theoretical permeability with a preset threshold, the type of loss can be determined as fractured or permeable loss. Even when imaging logging data is lacking at the engineering site, the type of well loss can be quickly and accurately identified, thereby guiding targeted loss prevention and plugging measures and effectively reducing drilling risks such as well blowouts.

[0025] Other features and advantages of the embodiments of this application will be described in detail in the following detailed description section. Attached Figure Description

[0026] The accompanying drawings are provided to further illustrate the embodiments of this application and form part of the specification. They are used together with the following detailed description to explain the embodiments of this application, but do not constitute a limitation on the embodiments of this application. In the drawings: Figure 1The illustration shows a flowchart of a well leakage type determination method based on permeability comparison according to an embodiment of this application; Figure 2 This illustration schematically shows a structural diagram of a well leakage type determination device based on permeability comparison according to an embodiment of this application; Figure 3 The diagram illustrates the structure of a well leakage type determination device based on permeability comparison according to an embodiment of this application. Detailed Implementation

[0027] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are only for illustration and explanation of the embodiments of this application and are not intended to limit the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0028] It should be noted that the acquisition, transmission, storage, use, and processing of data in the technical solution of this application all comply with relevant laws and regulations. In the embodiments of this application, certain existing industry solutions such as software, components, and models may be mentioned. These should be considered exemplary, intended only to illustrate the feasibility of implementing the technical solution of this application, and do not imply that the applicant has already used or necessarily used such solutions.

[0029] It should be noted that if the embodiments of this application involve directional indicators (such as up, down, left, right, front, back, etc.), the directional indicators are only used to explain the relative positional relationship and movement of each component in a certain specific posture (as shown in the figure). If the specific posture changes, the directional indicators will also change accordingly.

[0030] Furthermore, if the embodiments of this application involve descriptions such as "first" or "second," these descriptions are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, features defined with "first" or "second" may explicitly or implicitly include at least one of those features. Additionally, the technical solutions of various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. If the combination of technical solutions is contradictory or impossible to implement, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed in this application.

[0031] Figure 1The illustration schematically shows a flowchart of a well leakage type determination method based on permeability comparison according to an embodiment of this application. Figure 1 As shown in the embodiment of this application, a method for determining well leakage type based on permeability comparison is provided, which may include the following steps.

[0032] Step 110: When imaging logging data is lacking in the target lost well section, acquire logging data and well logging data for the target lost well section.

[0033] In this embodiment of the application, the logging data acquired by the processor includes data for calculating the porosity of the formation rock. The logging data includes the length of the lost circulation section, drilling fluid density, formation pore pressure, annular pressure loss, average lost circulation flow rate, drilling fluid viscosity, supply radius, and wellbore radius.

[0034] Specifically, logging data refers to data obtained downhole by logging instruments that reflects the physical properties of the formation; lost circulation length refers to the length of the well section where drilling fluid loss occurs; drilling fluid density refers to the mass per unit volume of drilling fluid, used to balance pressure; formation pore pressure refers to the pressure exerted on the fluid in the formation pores; annular pressure loss refers to the pressure loss caused by friction and other factors when drilling fluid flows in the annulus; average lost circulation rate refers to the average rate of drilling fluid loss per unit time, used to characterize the degree of loss; drilling fluid viscosity refers to the internal frictional resistance of drilling fluid flow, reflecting its fluidity; supply radius refers to the effective radius of influence of fluid flowing from the lost formation into the wellbore; and wellbore radius refers to the radius of the wellbore after drilling is completed.

[0035] The processor's acquisition of logging and well logging data of the target lost well section is beneficial for subsequent calculation of formation rock porosity, inversion of the average permeability of the lost formation, and provides basic data support for determining the type of well leakage.

[0036] Step 120: Determine the rock porosity of the target lost circulation section based on well logging data, and determine the average radius of rock particles based on the rock cuttings obtained from the target lost circulation section.

[0037] In this embodiment, the processor can invert the rock porosity of the target lost well section based on well logging data, and simultaneously determine the average radius of rock particles based on the backflow of rock cuttings from the target lost well section.

[0038] Specifically, in this embodiment of the application, a laser particle size analyzer can be used to quickly determine the particle size composition of the returned rock cuttings, thereby obtaining the average radius of the rock particles; or, based on the lithological characteristics of the returned rock cuttings, the corresponding particle size range can be queried, thereby determining the average radius of the rock particles.

[0039] Determining the average radius of rock particles can provide key parameters for subsequent calculations of the theoretical permeability of porous formations based on the Kozeny-Carman equation.

[0040] Step 130: Based on well logging data, calculate the average permeability of the lost formation corresponding to the target lost well section.

[0041] In this embodiment, the processor determines the average permeability of the lost formation corresponding to the target lost well section based on the following formula:

[0042]

[0043] in, The average permeability of the formation corresponding to the target lost circulation interval. q This represents the average leakage flow rate of the drilling fluid. μ For drilling fluid viscosity, r e For supply radius, r w The radius of the wellbore. h For the length of the missing segment, p For pressure difference, p m This refers to the static pressure of the drilling fluid column. p a For annular pressure loss, p p This refers to the original formation pore pressure. It's understandable that the static pressure of the drilling fluid column is determined by the drilling fluid density and well depth, while the original formation pore pressure is the pressure of the formation itself, which can be measured on-site.

[0044] Darcy's formula for radial flow in a plane can be used to invert and calculate the average permeability of lost formations. It can effectively utilize conventional field logging data and quantitatively characterize the seepage capacity of lost formations in the absence of imaging logging data, providing a basis for subsequent comparison with the theoretical permeability of porous formations.

[0045] Step 140: Assuming the lost formation is a purely porous medium, determine the theoretical permeability of the porous formation based on the average radius of rock particles, rock porosity, and the preset tortuosity.

[0046] In this embodiment, assuming the lost circulation formation is a purely porous medium and the rock is modeled as a parallel capillary bundle, the processor calculates the theoretical permeability based on the Kozeny-Carman equation, according to the average radius of rock particles, rock porosity, and a preset tortuosity. A lost circulation formation refers to a formation in which drilling fluid is lost during drilling. Depending on the loss mechanism, it can be classified as permeable loss, fracture loss, and cavern loss. This application only addresses the first two types and is limited to clastic rock formations. The parallel capillary bundle model is an idealized physical model used to simplify the flow characteristics of porous media. The model equates the actual complex and irregular rock pore structure to a set of parallel, identical, or proportionally distributed straight circular capillaries in which fluid flows axially. In this model, rock particles can be approximated as spheres of equal diameter, thus allowing the pore throat radius to be estimated using the particle radius. The Kozeny-Carman equation is a classic empirical formula describing the relationship between the permeability of porous media and pore structure parameters (such as porosity, specific surface area, and tortuosity). In this application, it is used to convert parameters such as the average radius of rock particles into theoretical permeability.

[0047] Furthermore, in the embodiments of this application, the theoretical penetration rate is determined according to the following formula:

[0048] in, K m Theoretical penetration rate, For rock porosity, r Where is the throat radius, τ For tortuosity; The relationship between the pore throat radius and the average radius of rock grains is as follows:

[0049] in, R The average radius of the rock particles; The specific surface area of ​​a rock is determined by the following formula.

[0050] Where S is the rock specific surface area; The theoretical permeability of the same specific surface based on the average radius of rock particles is determined by the following formula:

[0051] In one embodiment of this application, an optional implementation is to use a default value of 1.4 for the tortuosity.

[0052] The pore throat radius can be obtained based on the average radius of rock particles at the same specific surface. In the embodiments of this application, the theoretical permeability can be completely determined by the porosity obtained from well logging and the average radius of rock particles measured by cuttings, without the need for additional experiments or imaging data, thus meeting the needs of rapid identification in engineering sites.

[0053] Step 150: Determine the relative error between the average permeability and the theoretical permeability.

[0054] In this embodiment, the relative error between the average permeability and the theoretical permeability can be determined according to the following formula:

[0055] Where, Δ K This is a relative error. K m Theoretical penetration rate, This represents the average penetration rate.

[0056] By determining the relative error, the deviation between the average permeability and the theoretical permeability assumed to be a pure porous medium can be quantified, thereby verifying whether the assumption in the previous step is correct.

[0057] Step 160: Based on the comparison between the relative error and the preset threshold, determine whether the leakage type of the target leakage section is fracture leakage or permeability leakage.

[0058] In this embodiment of the application, if the relative error is greater than or equal to a preset threshold, the processor determines that the leakage type of the target leakage well section is fracture leakage; if the relative error is less than the preset threshold, the processor determines that the leakage type of the target leakage well section is permeable leakage.

[0059] Specifically, in this application embodiment, when the average penetration rate is greater than 100mD, the target threshold is set to 1000%; when the average penetration rate is greater than 10mD and less than 100mD, the target threshold is set to 500%; and when the average penetration rate is less than 10mD, the target threshold is set to 150%.

[0060] mD is an abbreviation for millidarcy, a commonly used unit of permeability used to measure the ability of porous media (such as rocks) to allow fluid to pass through, derived from Darcy's law. Permeability leakage occurs in purely porous media, where fluid flows through the tiny pores between rock particles. This flow conforms to the pore structure model described by the Kozeny-Carman equations, and its permeability is mainly determined by porosity, particle radius, and tortuosity. Fracture leakage, on the other hand, occurs in formations with natural or induced fractures. Fracture channels are much larger than pore throats, possessing extremely high conductivity, resulting in the actual measured average formation permeability being significantly higher than the theoretical permeability calculated solely from pore structure.

[0061] By identifying the type of leakage in the target lost well section, on-site engineers can be provided with a clear understanding of the leakage mechanism, enabling them to select appropriate prevention or plugging measures. For permeable leakage, conventional methods such as bridging plugging and particle-graded plugging can be used. For fracture leakage, flexible materials, gel-based or high-fluid-loss plugging slurries that adapt to fracture propagation characteristics are required to effectively improve the success rate of plugging, reduce drilling fluid consumption, shorten non-productive time, and reduce well control risks induced by well leakage.

[0062] This application, in the absence of imaging logging data, can obtain rock porosity and determine the average particle radius of cuttings from logging data, and then invert the average permeability of the lost-flow formation using logging data. Simultaneously, assuming the formation is a purely porous medium, the theoretical permeability is calculated using the Kozeny-Carman model. By comparing the relative error between the measured average permeability and the theoretical permeability, and comparing it with a preset threshold, the type of loss can be determined as fracture-related or permeable loss. This application has low requirements for logging data and can efficiently identify well leakage types on-site, thus providing a basis for targeted leakage prevention and plugging measures, effectively reducing drilling risks such as well blowouts.

[0063] In this embodiment of the application, the well leakage type determination method based on permeability comparison further includes determining whether the logging data includes imaging logging data. If imaging logging data exists, the leakage well section is determined to be permeable leakage or fracture leakage based on the imaging characteristics.

[0064] When imaging logging data is available, the type of lost well section can be determined directly based on imaging features, which can quickly, intuitively and with high accuracy identify the distribution characteristics of fractures or pore structures in the formation.

[0065] Figure 2 The diagram illustrates the structure of a well leakage type determination device based on permeability comparison according to an embodiment of this application. Figure 2 As shown in the embodiment of this application, a well leakage type determination device 200 for permeability comparison includes: The data acquisition module 210 is used to acquire logging data and well logging data of the target lost well section when imaging logging data is lacking. The first calculation module 220 is used to determine the rock porosity of the target lost well section based on well logging data, and to determine the average radius of rock particles based on the rock cuttings obtained from the target lost well section. The second calculation module 230 is used to calculate the average permeability of the lost formation corresponding to the target lost well section based on logging data. The third calculation module 240, assuming the lost formation is a pure porous medium, is used to determine the theoretical permeability of the porous formation based on the average radius of rock particles, rock porosity, and preset tortuosity. Error determination module 250 is used to determine the relative error between average permeability and theoretical permeability; The type determination module 260 is used to determine whether the leakage type of the target leakage well section is fracture leakage or permeability leakage based on the comparison result of the relative error and the preset threshold.

[0066] Figure 3 The diagram schematically illustrates a structural block diagram of a well leakage type determination device based on permeability comparison according to an embodiment of this application. Figure 3 As shown in the figure, this application provides a well leakage type determination device 300 based on permeability comparison, which may include: Memory 310 is configured to store instructions; The processor 320 is configured to retrieve instructions from the memory 310 and, when executing the instructions, to implement the aforementioned well leakage type determination method based on permeability comparison.

[0067] This application also provides a machine-readable storage medium storing instructions that cause a machine to execute the above-described well leakage type determination method based on permeability comparison.

[0068] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied 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.

[0069] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0070] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0071] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0072] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0073] Memory may include non-persistent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0074] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0075] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0076] The above are merely embodiments of this application and are not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A method for determining well leakage type based on permeability comparison, characterized in that, The method includes: When imaging logging data is lacking for the target lost well section, logging and well logging data for the target lost well section are obtained; The rock porosity of the target lost circulation section is determined based on the well logging data, and the average radius of the rock particles is determined based on the rock cuttings obtained from the target lost circulation section. Based on the logging data, the average permeability of the lost formation corresponding to the target lost well section is calculated by inversion. Assuming the lost formation is a purely porous medium, the theoretical permeability of the porous formation is determined based on the average radius of the rock particles, the porosity of the rock, and the preset tortuosity. Determine the relative error between the average permeability and the theoretical permeability; Based on the comparison between the relative error and the preset threshold, the leakage type of the target leakage well section is determined to be either fracture leakage or permeability leakage.

2. The method according to claim 1, characterized in that, The step of determining whether the leakage type of the target leakage well section is fracture leakage or permeability leakage based on the comparison result of the relative error and the preset threshold includes: If the relative error is greater than or equal to the preset threshold, the leakage type of the target leakage well section is determined to be fracture leakage; If the relative error is less than the preset threshold, the leakage type of the target leakage well section is determined to be permeable leakage.

3. The method according to claim 1, characterized in that, The average permeability of the lost formation corresponding to the target lost well section is determined based on the following inversion formula: in, The average permeability of the formation corresponding to the target lost-flow well section. q This represents the average leakage flow rate of the drilling fluid. μ For drilling fluid viscosity, r e For supply radius, r w The radius of the wellbore. h For the length of the missing segment, p For pressure difference, p m This refers to the static pressure of the drilling fluid column. p a For annular pressure loss, p p This represents the pore pressure of the original formation.

4. The method according to claim 1, characterized in that, Assuming the leaking formation is a purely porous medium, the theoretical permeability of the porous formation is determined based on the average radius of the rock particles, the porosity of the rock, and a preset tortuosity, including: Assuming the lost formation is a pure porous medium and the rock is a parallel capillary bundle model, the theoretical permeability is calculated based on the Kozeny-Carman equation, according to the average radius of the rock particles, the porosity of the rock, and the preset tortuosity. The average radius of the rock particles is obtained by analyzing rock cuttings with a laser particle size analyzer or by querying the rock lithology.

5. The method according to claim 4, characterized in that, The theoretical penetration rate is determined according to the following formula: in, K m The theoretical penetration rate is... The porosity of the rock is... r Where is the throat radius, τ For tortuosity; The relationship between the pore throat radius and the average radius of the rock particles is as follows: in, R The average radius of the rock particles; The specific surface area of ​​a rock is determined by the following formula. Where S is the rock specific surface area; The theoretical permeability of the same specific surface area based on the average radius of the rock particles is determined according to the following formula: 。 6. The method according to claim 2, characterized in that, When the average penetration rate is greater than 100 mD, the target threshold is set to 1000%; when the average penetration rate is greater than 10 mD and less than 100 mD, the target threshold is set to 500%; when the average penetration rate is less than 10 mD, the target threshold is set to 150%.

7. The method according to claim 1, characterized in that, The method further includes: Determine whether the logging data includes imaging logging data; If the imaging logging data is available, the lost well section is determined to be either permeable or fractured based on the imaging characteristics.

8. A well leakage type determination device based on permeability comparison, characterized in that, include: The data acquisition module is used to acquire logging and well logging data of the target lost well section when imaging logging data is lacking. The first calculation module is used to determine the rock porosity of the target lost circulation section based on the well logging data, and to determine the average radius of rock particles based on the rock cuttings obtained from the target lost circulation section. The second calculation module is used to calculate the average permeability of the lost formation corresponding to the target lost well section based on the logging data. The third calculation module, assuming the lost formation is a pure porous medium, is used to determine the theoretical permeability of the porous formation based on the average radius of the rock particles, the porosity of the rock, and the preset tortuosity. An error determination module is used to determine the relative error between the average permeability and the theoretical permeability; The type determination module is used to determine whether the leakage type of the target leakage well section is fracture leakage or permeability leakage based on the comparison result of the relative error and the preset threshold.

9. A well leakage type determination device based on permeability comparison, characterized in that, include: The memory is configured to store instructions; The processor is configured to retrieve the instructions from the memory and, when executing the instructions, to implement the well leakage type determination method based on permeability comparison according to any one of claims 1 to 7.

10. A machine-readable storage medium, characterized in that, The machine-readable storage medium stores instructions for causing the machine to perform the well leakage type determination method based on permeability comparison according to any one of claims 1 to 7.

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