A well logging response simulation method and device, electronic equipment and storage medium

Abstract

The application belongs to the technical field of complex reservoir exploration and development, and particularly relates to a well logging response simulation method, device, electronic equipment and storage medium. The well logging response simulation method comprises the following steps: obtaining wellbore parameters and fracture-cave body geological parameters of a target area; constructing a wellbore model based on the wellbore parameters and constructing a fracture-cave body geological model based on the fracture-cave body geological parameters; establishing a fracture-cave body three-dimensional well logging geometric model based on the wellbore model and the fracture-cave body geological model; setting preset physical properties of limestone and fillers in the fracture-cave body three-dimensional well logging geometric model to obtain a target fracture-cave body three-dimensional well logging physical model; and performing well logging response simulation based on the target fracture-cave body three-dimensional well logging physical model to obtain well logging response simulation numerical values. The well logging response simulation data in the application is matched with the geological conditions of the fracture-cave body, and the interpretation effect of the well logging response is better improved.

Description

Technical Field

[0001] This invention belongs to the technical field of complex reservoir exploration and development, and specifically relates to a well logging response simulation method, device, electronic equipment and storage medium. Background Technology

[0002] Fractured-cavitary bodies are a crucial aspect of exploration and development. Due to the difficulty of coring these bodies, core calibration analysis of logging responses is impractical. Therefore, numerical simulation analysis of logging responses in fractured-cavitary bodies is essential. Previous research has explored numerical simulation of logging responses in fractured-cavitary bodies. However, past results relied on predefined parameters in the simulation models, lacking a direct correlation with specific geological parameters. Furthermore, these studies primarily focused on single logging simulation methods, employing relatively simple models to analyze the relationship between individual logging responses and model parameters. This approach fails to accurately reflect the geological conditions of fractured-cavitary bodies and hinders comparative analysis between multiple logging responses, thus impairing the effectiveness of logging interpretation. Summary of the Invention

[0003] To address the aforementioned technical problems, this invention proposes a well logging response simulation method, apparatus, electronic device, and storage medium. This application combines a wellbore model and a fractured-cavity geological model to form a three-dimensional geometric model of the fractured-cavity. Based on the parameters of the wellbore model and the fractured-cavity geological model, the physical properties of the three-dimensional geometric model of the fractured-cavity are preset. Finally, well logging response simulation is performed on the three-dimensional geometric model with the preset physical properties to obtain well logging response simulation data. The well logging response simulation data in this application matches the geological conditions of the fractured-cavity, thus improving the interpretation effect of the well logging response.

[0004] To solve the above-mentioned technical problems, the technical solution adopted by the present invention includes four aspects.

[0005] In a first aspect, a well logging response simulation method is provided, comprising: acquiring wellbore parameters and fracture-cavity geological parameters of a target area; constructing a wellbore model based on the wellbore parameters and a fracture-cavity geological model based on the fracture-cavity geological parameters; establishing a three-dimensional well logging geometric model of the fracture-cavity based on the wellbore model and the fracture-cavity geological model; setting preset physical properties for limestone and filling material in the three-dimensional well logging geometric model of the fracture-cavity to obtain a three-dimensional well logging physical model of the target fracture-cavity; and performing well logging response simulation based on the three-dimensional well logging physical model of the target fracture-cavity to obtain well logging response simulation values.

[0006] In some embodiments, the method further includes: establishing a correspondence between the simulated logging response values ​​and the three-dimensional logging geometric model of the fractured cavity.

[0007] In some embodiments, the wellbore parameters include: wellbore diameter, wellbore angle, and wellbore filling material; the fractured cavity geological parameters include: fractured cavity type, fractured cavity filling material, and fractured cavity size; the step of constructing a wellbore model based on the wellbore parameters and a fractured cavity geological model based on the fractured cavity geological parameters includes: establishing the wellbore model based on the wellbore diameter, wellbore angle, and wellbore filling material; and establishing the fractured cavity geological model based on the fractured cavity type, fractured cavity filling material, and fractured cavity size.

[0008] In some embodiments, the wellbore parameters further include: drilling encounter relationship; the step of establishing a three-dimensional logging geometric model of the fractured cavity based on the wellbore model and the fractured cavity geological model includes: combining the wellbore model and the fractured cavity geological model according to the drilling encounter relationship to form a three-dimensional logging geometric model of the fractured cavity.

[0009] In some embodiments, the preset physical properties include: preset acoustic transit time, preset neutron, preset density, and preset resistivity; setting preset physical properties for limestone and filling material in the three-dimensional logging geometry model of the fractured cavity to obtain the target three-dimensional logging physical model of the fractured cavity includes: setting preset acoustic transit time, preset neutron, preset density, and preset resistivity for the filling material of the fractured cavity, the wellbore filling material, and the limestone to obtain the target three-dimensional logging physical model of the fractured cavity.

[0010] In some embodiments, the simulated logging response values ​​include: acoustic transit-time logging simulated response values, neutron logging simulated response values, density logging simulated response values, and resistivity logging simulated response values; the step of performing logging response simulation based on the three-dimensional logging physical model of the target fractured cavity to obtain the simulated logging response values ​​includes: performing acoustic transit-time logging response simulation on the three-dimensional logging physical model of the target fractured cavity using the three-dimensional finite difference method to obtain the acoustic transit-time logging simulated response values; performing neutron and density logging response simulation on the three-dimensional logging physical model of the target fractured cavity using the Monte Carlo method to obtain the neutron logging simulated response values ​​and the density logging simulated response values; and performing resistivity logging response simulation on the three-dimensional logging physical model of the target fractured cavity using the three-dimensional finite element method to obtain the resistivity logging simulated response values.

[0011] In some embodiments, the simulated logging response values ​​include: simulated response values ​​of sonic transit time logging, simulated response values ​​of neutron logging, simulated response values ​​of density logging, and simulated response values ​​of resistivity logging. Establishing the correspondence between the simulated logging response results and the three-dimensional logging geometric model of the fractured cavity includes: establishing the correspondence between the simulated response values ​​of sonic transit time logging, simulated response values ​​of neutron logging, simulated response values ​​of density logging, and simulated response values ​​of resistivity logging and the three-dimensional logging geometric model of the fractured cavity.

[0012] Secondly, this application provides a well logging response simulation device, comprising: a first acquisition module for acquiring wellbore parameters and fracture-cavity geological parameters of a target area; a first establishment module for constructing a wellbore model based on the wellbore parameters and a fracture-cavity geological model based on the fracture-cavity geological parameters; a second establishment module for establishing a three-dimensional well logging geometric model of the fracture-cavity based on the wellbore model and the fracture-cavity geological model; a first preset module for setting preset physical properties for the dense limestone and filling material in the three-dimensional well logging geometric model of the fracture-cavity to obtain a three-dimensional well logging physical model of the target fracture-cavity; and a first execution module for performing well logging response simulation based on the three-dimensional well logging physical model of the target fracture-cavity to obtain well logging response simulation values.

[0013] A third aspect provides an electronic device including a storage device and a processor, the storage device storing a computer program, the processor executing the computer program to implement the steps of a well logging response simulation method.

[0014] The fourth aspect provides a storage medium storing a computer program that can be executed by one or more processors, the computer program being able to implement the steps of any of the well logging response simulation methods in the first aspect.

[0015] The beneficial effects of this invention are as follows: This application combines a wellbore model and a fractured-cavity geological model to form a three-dimensional geometric model of the fractured-cavity. Based on the parameters of the wellbore model and the fractured-cavity geological model, the physical properties of the three-dimensional geometric model of the fractured-cavity are preset. Finally, well logging response simulation is performed on the three-dimensional geometric model with preset physical properties to obtain well logging response simulation data. The well logging response simulation data in this application matches the geological conditions of the fractured-cavity, thus improving the interpretation effect of the well logging response. Attached Figure Description

[0016] The scope of this disclosure can be better understood by reading the following detailed description of exemplary embodiments in conjunction with the accompanying drawings. The accompanying drawings are:

[0017] Figure 1 This is a flowchart illustrating a well logging response simulation method provided in Embodiment 1 of this application;

[0018] Figure 2 This is a flowchart illustrating a well logging response simulation method provided in Embodiment 2 of this application;

[0019] Figure 3 This is a schematic block diagram of a well logging simulation device provided in Embodiment 3 of this application;

[0020] Figure 4 This is a schematic block diagram of a well logging simulation device provided in Embodiment 4 of this application. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings. The described embodiments should not be regarded as limitations on this application. All other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0022] In the following description, references are made to “some embodiments,” which describe a subset of all possible embodiments. However, it is understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0023] If the application documents contain similar descriptions such as "first, second, third", the following explanation shall be added: In the following description, the terms "first, second, third" are used only to distinguish similar objects and do not represent a specific order of objects. It is understood that "first, second, third" may be interchanged in a specific order or sequence where permitted, so that the embodiments of this application described herein can be implemented in an order other than that illustrated or described herein.

[0024] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0025] Example 1:

[0026] In view of the problems existing in the background technology, such as Figure 1 As shown, this application provides a well logging response simulation method, which is applied to an electronic device, such as a server, mobile terminal, computer, or cloud platform. The functions implemented by the device data processing provided in this application embodiment can be achieved by the processor of the electronic device calling program code, wherein the program code can be stored in a computer storage medium. The well logging response simulation method includes:

[0027] Step S1: Obtain wellbore parameters and fractured cavern geological parameters for the target area.

[0028] Step S2: Construct a wellbore model based on the wellbore parameters, and construct a fractured-cavity geological model based on the fractured-cavity geological parameters.

[0029] The wellbore parameters include: wellbore diameter, wellbore angle, and wellbore filling material. The geological parameters of the fractured cavity include: fractured cavity type, fractured cavity filling material, and fractured cavity dimensions. The wellbore diameter is typically 120.65 mm or 149.2 mm. The wellbore angle is between 0 and 90°. The wellbore filling material is mud.

[0030] The types of cavities include: fissure-type cavities, cave-type cavities, and fracture-type cavities. The filling material for each type of cavity is different, and each type of cavity has its own required dimensions.

[0031] In some embodiments, step S2, "Constructing a wellbore model based on the wellbore parameters and constructing a fractured-cavity geological model based on the fractured-cavity geological parameters," includes:

[0032] Step 21: Establish the wellbore model based on the wellbore diameter, wellbore angle, and wellbore filling material.

[0033] Step S22: Establish the geological model of the fracture cavity based on the fracture cavity type, fracture cavity filling material, and fracture cavity size.

[0034] Therefore, a wellbore model can be established based on the wellbore diameter, wellbore angle, and wellbore filling material.

[0035] When establishing geological models of fracture-cavities, different types of fracture-cavities will form different types of geological models. Specifically, fracture-type fracture-cavities form fracture geological models, cave-type fracture-cavities form cave geological models, and fault-type fracture-cavities form fault geological models.

[0036] The fracture geological model includes dense limestone and fractures. The cave geological model includes dense limestone and caves. The fault geological model includes dense limestone and faults. Therefore, when establishing a fracture-cavity geological model, the time-developing fracture-cavity is simulated based on the relevant parameters of the dense limestone and fracture-cavity types. It is required that the selection of relevant parameters for the dense limestone and fracture-cavity types conforms to the geological characteristics of the fracture-cavity.

[0037] The shape of dense limestone is massive. Dense limestone consists of a limestone framework and pores, which are filled with formation water. Therefore, the relevant parameter for dense limestone here is its porosity, which is generally between 0.1% and 2%.

[0038] Different types of fracture-cavity bodies correspond to different types of fracture-cavity geological models. When the fracture-cavity geological model is a fracture geological model, the relevant parameters to consider include: fracture dip angle, fracture width, fracture length, number of fractures, fracture interval, and fracture filling material. The fracture dip angle is between 0-90°. The fracture width is between 0.01mm-100mm. When establishing a fracture geological model, the fracture length needs to reflect the differences in radial detection depth between different logging methods. This difference in radial detection depth will lead to differences in logging response, so the fracture projection radial length range includes: 0.1m, 0.25m, 0.75m, 1m, and infinite length. The number of fractures should be between 1-9. If there are multiple fractures, the fracture interval should be set as an integer multiple of the logging sampling point (0.125m). The filling material in the fractures is one of mud, mudstone, or calcite.

[0039] When the fractured-cavity geological model is a cave geological model, the relevant parameters to consider include: the ratio of the cave's major and minor axes and the cave's filling material. When the ratio of the cave's major and minor axes is 1:1, the cave geological model is spherical. When the cave geological model is spherical, the radius of the cave should be within the detection depth range of the well logging method (0.5-5m). When the ratio of the cave's major and minor axes is other values, the cave shape is ellipsoidal. The minor radius of the ellipsoidal cave geological model should be between 0.5-5m. The cave filling material can be one or a mixture of several of the following: mud, sandstone, mudstone, breccia, and calcite. When multiple filling materials are combined to fill the cave geological model, each filling material is placed in parallel layers within the cave. Sandstone consists of a sandstone skeleton and pores, with the pores containing oil and water. Breccia is formed from the collapse of the cave walls, so breccia includes breccia fragments and the pores between them, with mud filling the pores between the fragments. When the filling material in the cave geological model is sandstone and breccia, it is necessary to determine the porosity of the filling material, which is between 2% and 4%. When the filling material in the cave geological model is other materials, it is not necessary to determine the porosity of the filling material.

[0040] When the geological model of the fractured cavity is a fracture geological model, the relevant parameters of the fracture geological model include: fracture width, fracture infill material, porosity of the fracture infill material, and fracture dip angle, since the fracture shape is a straight plate. The fracture width should be between 1-10m, taking into account the detection depth of well logging methods. The fracture infill material, like that in the cavity, can be of various types. When the infill material includes sandstone or breccia, the porosity of the fracture infill material needs to be considered. The fracture dip angle is between 45° and 90°.

[0041] Step S3: Establish a three-dimensional logging geometric model of the fractured cavity based on the wellbore model and the fractured cavity geological model.

[0042] In some embodiments, the wellbore parameters further include: drilling encounter relationship. The drilling encounter relationship refers to the relationship between the wellbore and the fractured-cavity geological model, including the distance from the wellbore to the boundary of the fractured-cavity geological model. There are two types of drilling encounter relationships: the wellbore model encountering the fractured-cavity geological model and the wellbore model not encountering the fractured-cavity geological model. The case where the wellbore model does not encounter the fractured-cavity geological model is not discussed here. When the wellbore model encounters the fractured-cavity geological model, the boundary length between the wellbore model and the fractured-cavity geological model must be less than or equal to half the width of the fractured-cavity geological model. This requirement is beneficial for meeting the detection depth and resolution requirements of different logging methods.

[0043] Step S3, "Establishing a three-dimensional logging geometric model of the fractured cavity based on the wellbore model and the fractured cavity geological model," includes:

[0044] Step S31: Combine the wellbore model and the fractured cavity geological model according to the drilling encounter relationship to form a three-dimensional logging geometric model of the fractured cavity.

[0045] Therefore, based on the drilling encounter relationship between the wellbore model and the fractured-cavity geological model, a relationship is established between the wellbore model and the fractured-cavity geological model. This relationship satisfies the drilling encounter relationship, thus forming a three-dimensional logging geometric model of the fractured-cavity.

[0046] Step S4: Set preset physical properties for the dense limestone and filling material in the three-dimensional logging geometric model of the fractured cavity to obtain the three-dimensional logging physical model of the target fractured cavity.

[0047] In some embodiments, the preset physical properties include: preset acoustic transit time, preset neutrons, preset density, and preset resistivity. These physical properties include: preset physical properties of dense limestone and preset physical properties of the infill material. The preset physical properties of the infill material include: preset physical properties of the wellbore model infill material and preset physical properties of the fractured cavity geological model.

[0048] (1) Therefore, the acoustic transit time, neutrons, and density of dense limestone are determined using the following formula:

[0049]

[0050]

[0051]

[0052] In the formula: and The sonic transit times (μs / ft) for dense limestone, formation water, and limestone framework are respectively. and The values ​​can be 185 μs / ft and 47.5 μs / ft, or empirical values ​​recognized in the study area can be used; and Neutrons, v / v, representing dense limestone, formation water, and the limestone framework, respectively. and It can be 1 or 0, or it can be an empirical value recognized in the study area; and The densities, in g / cm³, are those of dense limestone, formation water, and the limestone skeleton, respectively. and It is possible; V represents the porosity of dense limestone, v / v.

[0053] The resistivity value of dense limestone was determined by deducing the formation formula from actual well logging data. When the porosity of dense limestone is set at 2%, its corresponding resistivity is... When the porosity of dense limestone is 0%, the corresponding study area has a maximum resistivity of [missing information]. This results in the following formula:

[0054]

[0055] In the formula: Ω·m represents the resistivity of dense limestone.

[0056] (2) For the filling material of the fracture geological model, the filling material of the cave geological model, the filling material of the fault geological model and the filling material of the wellbore model, the preset physical properties are related to the type of filling material.

[0057] The filling material for the fracture geological model is one of mud, mudstone, and calcite. The filling material for the fault geological model and the cave geological model is one or more of mud, sandstone, mudstone, breccia, and calcite. The filling material for the wellbore model is mud. Therefore, determining the preset physical properties of the fracture geological model, cave geological model, fault geological model, and wellbore model is equivalent to determining the physical properties of mud, sandstone, mudstone, breccia, and calcite.

[0058] The density of the mud is determined by statistically studying the average or median mud density of the block. If the mud density of each well is not much different, the average value is used; if the mud density of the wells differs greatly, the median value is used.

[0059] The resistivity of mud is determined by using the following formula to calculate the resistivity value of mud in each well in the study area at the bottom hole temperature of the well, and then averaging the values ​​to obtain the mud resistivity.

[0060] =

[0061] In the formula: t is a certain temperature, in °C; and denoted as t℃, where t is the resistivity of the mud at 18℃ and t℃, in ohm.m.

[0062] For acoustic transit time logging of mud, the mud acoustic transit time value provided in the array acoustic data is selected. For neutrons in the mud, the maximum neutron value of the enlarged section in the actual logging data is selected.

[0063] The acoustic transit time, neutron density, and resistivity of sandstone are determined by the following formulas.

[0064]

[0065]

[0066]

[0067]

[0068] In the formula: and Sonic transit times for sandstone, sandstone skeleton, and oil, respectively, in μs / ft; and Neutrons, v / v, for sandstone, sandstone framework, and oil, respectively; and The densities of sandstone, sandstone framework, and oil are respectively, in g / cm³. 3 ; The porosity of sandstone is v / v. This represents the water saturation of the sandstone.

[0069] The presupposed physical properties of mudstone are the average values ​​of acoustic transit time, neutron, density, and resistivity logging data for mud-filled cavities at depths of 5 meters or more in the well.

[0070] The acoustic transit time, neutron density, and resistivity of breccia are determined by the following formulas.

[0071]

[0072]

[0073]

[0074]

[0075] In the formula: , where represents the acoustic transit time of the breccia, in μs / ft; For neutrons in breccia, v / v; Density of breccia, g / cm³ 3 ; and V represents the porosity between breccia and the porosity of the breccia.

[0076] Calcite is a pure limestone, almost without any pores. The acoustic transit time, neutron, density and resistivity values ​​of the limestone skeleton were selected.

[0077] Therefore, in some embodiments, step S4, "setting preset physical properties for the dense limestone and filling material in the three-dimensional logging geometric model of the fractured cavity to obtain the target three-dimensional logging physical model of the fractured cavity," includes:

[0078] Step S41: Set preset acoustic transit time, preset neutron, preset density and preset resistivity for the fractured cavity filling material, the wellbore filling material and the dense limestone to obtain a three-dimensional logging physical model of the target fractured cavity.

[0079] Based on the type of filler material in the fractured cavity, the corresponding preset acoustic transit time, preset neutron, preset solution, and preset resistivity are determined and set on the filler material of the fractured cavity geological model. Then, the preset physical properties of the dense limestone and the preset physical properties of the wellbore model are determined. This transforms the three-dimensional logging geometric model of the fractured cavity into the three-dimensional logging physical model of the target fractured cavity.

[0080] Step S5: Perform well logging response simulation based on the three-dimensional well logging physical model of the target fracture cavity to obtain the well logging response simulation values.

[0081] This application combines a wellbore model and a fractured-cavity geological model to form a three-dimensional geometric model of the fractured-cavity. Based on the parameters of the wellbore model and the fractured-cavity geological model, the physical properties of the three-dimensional geometric model of the fractured-cavity are preset. Finally, well logging response simulation is performed on the three-dimensional geometric model with preset physical properties to obtain well logging response simulation data. The well logging response simulation data in this application matches the geological conditions of the fractured-cavity, thus improving the interpretation effect of the well logging response.

[0082] After establishing the three-dimensional logging physical model of the target fracture cavity, different logging methods were used to simulate the logging response of the model. The simulated logging response values ​​were obtained. These simulated values ​​can better interpret the logging response.

[0083] Commonly used logging methods include: sonic transit time logging, neutron logging, density logging, and dual lateral logging. The corresponding values ​​obtained are the sonic transit time logging response values, neutron logging response values, density logging response values, and resistivity logging response values.

[0084] Therefore, in some embodiments, the simulated logging response values ​​include: simulated response values ​​of sonic transit time logging, simulated response values ​​of neutron logging, simulated response values ​​of density logging, and simulated response values ​​of resistivity logging.

[0085] Furthermore, step S5, "Based on the three-dimensional logging physical model of the target fracture cavity, perform logging response simulation to obtain logging response simulation values," includes:

[0086] Step S51: Use the three-dimensional finite difference method to simulate the acoustic time-of-flight logging response of the three-dimensional logging physical model of the target fracture cavity, and obtain the simulation response value of the acoustic time-of-flight logging.

[0087] Step S52: Use the Monte Carlo method to simulate the neutron and density logging responses of the three-dimensional logging physical model of the target fracture cavity, and obtain the neutron logging simulation response values ​​and the density logging simulation response values.

[0088] Step S53: Use the three-dimensional finite element method to simulate the resistivity logging response of the three-dimensional logging physical model of the target fracture cavity, and obtain the simulated resistivity logging response value.

[0089] In order to make the final well logging response simulation results easier to interpret, it is necessary to unify the recording points of each well logging method at a single depth point.

[0090] This application integrates the geological model, physical properties, numerical simulation methods for various logging responses, and multiple logging responses of fractured-cavitary reservoirs into a holistic approach for logging response analysis, making the logging responses more closely approximate the geological conditions of fractured-cavitary reservoirs. The data used in the method can be obtained from logging data, core data, formation water data, and mud data, exhibiting strong operability and wide applicability. The results can effectively analyze the logging responses of fractured-cavitary reservoirs and provide rich and accurate data for artificial intelligence research on logging in fractured-cavitary reservoirs, possessing significant practical value in the exploration and development of complex reservoirs such as fractured-cavitary reservoirs.

[0091] The above method can be used in the exploration field to perform field modeling on the data of the exploration area, obtain well logging response simulation values, and improve the success rate of exploration.

[0092] Example 2:

[0093] like Figure 2 As shown, this application provides a well logging response simulation method, which is applied to an electronic device, such as a server, mobile terminal, computer, or cloud platform. The functions implemented by the device data processing provided in this application embodiment can be achieved by the processor of the electronic device calling program code, wherein the program code can be stored in a computer storage medium. The well logging response simulation method includes:

[0094] Step S1: Obtain wellbore parameters and fractured cavern geological parameters for the target area.

[0095] Step S2: Construct a wellbore model based on the wellbore parameters, and construct a fractured-cavity geological model based on the fractured-cavity geological parameters.

[0096] The wellbore parameters include: wellbore diameter, wellbore angle, and wellbore filling material. The geological parameters of the fractured cavity include: fractured cavity type, fractured cavity filling material, and fractured cavity dimensions. The wellbore diameter is typically 120.65 mm or 149.2 mm. The wellbore angle is between 0 and 90°. The wellbore filling material is mud.

[0097] The types of cavities include: fissure-type cavities, cave-type cavities, and fracture-type cavities. The filling material for each type of cavity is different, and each type of cavity has its own required dimensions.

[0098] In some embodiments, step S2, "Constructing a wellbore model based on the wellbore parameters and constructing a fractured-cavity geological model based on the fractured-cavity geological parameters," includes:

[0099] Step 21: Establish the wellbore model based on the wellbore diameter, wellbore angle, and wellbore filling material.

[0100] Step S22: Establish the geological model of the fracture cavity based on the fracture cavity type, fracture cavity filling material, and fracture cavity size.

[0101] Therefore, a wellbore model can be established based on the wellbore diameter, wellbore angle, and wellbore filling material.

[0102] When establishing geological models of fracture-cavities, different types of fracture-cavities will form different types of geological models. Specifically, fracture-type fracture-cavities form fracture geological models, cave-type fracture-cavities form cave geological models, and fault-type fracture-cavities form fault geological models.

[0103] The fracture geological model includes dense limestone and fractures. The cave geological model includes dense limestone and caves. The fault geological model includes dense limestone and faults. Therefore, when establishing a fracture-cavity geological model, the time-developing fracture-cavity is simulated based on the relevant parameters of the dense limestone and fracture-cavity types. It is required that the selection of relevant parameters for the dense limestone and fracture-cavity types conforms to the geological characteristics of the fracture-cavity.

[0104] The shape of dense limestone is massive. Dense limestone consists of a limestone framework and pores, which are filled with formation water. Therefore, the relevant parameter for dense limestone here is its porosity, which is generally between 0.1% and 2%.

[0105] Different types of fracture-cavity bodies correspond to different types of fracture-cavity geological models. When the fracture-cavity geological model is a fracture geological model, the relevant parameters to consider include: fracture dip angle, fracture width, fracture length, number of fractures, fracture interval, and fracture filling material. The fracture dip angle is between 0-90°. The fracture width is between 0.01mm-100mm. When establishing a fracture geological model, the fracture length needs to reflect the differences in radial detection depth between different logging methods. This difference in radial detection depth will lead to differences in logging response, so the fracture projection radial length range includes: 0.1m, 0.25m, 0.75m, 1m, and infinite length. The number of fractures should be between 1-9. If there are multiple fractures, the fracture interval should be set as an integer multiple of the logging sampling point (0.125m). The filling material in the fractures is one of mud, mudstone, or calcite.

[0106] When the fractured-cavity geological model is a cave geological model, the relevant parameters to consider include: the ratio of the cave's major and minor axes and the cave's filling material. When the ratio of the cave's major and minor axes is 1:1, the cave geological model is spherical. When the cave geological model is spherical, the radius of the cave should be within the detection depth range of the well logging method (0.5-5m). When the ratio of the cave's major and minor axes is other values, the cave shape is ellipsoidal. The minor radius of the ellipsoidal cave geological model should be between 0.5-5m. The cave filling material can be one or a mixture of several of the following: mud, sandstone, mudstone, breccia, and calcite. When multiple filling materials are combined to fill the cave geological model, each filling material is placed in parallel layers within the cave. Sandstone consists of a sandstone skeleton and pores, with the pores containing oil and water. Breccia is formed from the collapse of the cave walls, so breccia includes breccia fragments and the pores between them, with mud filling the pores between the fragments. When the filling material in the cave geological model is sandstone and breccia, it is necessary to determine the porosity of the filling material, which is between 2% and 4%. When the filling material in the cave geological model is other materials, it is not necessary to determine the porosity of the filling material.

[0107] When the geological model of the fractured cavity is a fracture geological model, the relevant parameters of the fracture geological model include: fracture width, fracture infill material, porosity of the fracture infill material, and fracture dip angle, since the fracture shape is a straight plate. The fracture width should be between 1-10m, taking into account the detection depth of well logging methods. The fracture infill material, like that in the cavity, can be of various types. When the infill material includes sandstone or breccia, the porosity of the fracture infill material needs to be considered. The fracture dip angle is between 45° and 90°.

[0108] Step S3: Establish a three-dimensional logging geometric model of the fractured cavity based on the wellbore model and the fractured cavity geological model.

[0109] In some embodiments, the wellbore parameters further include: drilling encounter relationship. The drilling encounter relationship refers to the relationship between the wellbore and the fractured-cavity geological model, including the distance from the wellbore to the boundary of the fractured-cavity geological model. There are two types of drilling encounter relationships: the wellbore model encountering the fractured-cavity geological model and the wellbore model not encountering the fractured-cavity geological model. The case where the wellbore model does not encounter the fractured-cavity geological model is not discussed here. When the wellbore model encounters the fractured-cavity geological model, the boundary length between the wellbore model and the fractured-cavity geological model must be less than or equal to half the width of the fractured-cavity geological model. This requirement is beneficial for meeting the detection depth and resolution requirements of different logging methods.

[0110] Step S3, "Establishing a three-dimensional logging geometric model of the fractured cavity based on the wellbore model and the fractured cavity geological model," includes:

[0111] Step S31: Combine the wellbore model and the fractured cavity geological model according to the drilling encounter relationship to form a three-dimensional logging geometric model of the fractured cavity.

[0112] Therefore, based on the drilling encounter relationship between the wellbore model and the fractured-cavity geological model, a relationship is established between the wellbore model and the fractured-cavity geological model. This relationship satisfies the drilling encounter relationship, thus forming a three-dimensional logging geometric model of the fractured-cavity.

[0113] Step S4: Set preset physical properties for the dense limestone and filling material in the three-dimensional logging geometric model of the fractured cavity to obtain the three-dimensional logging physical model of the target fractured cavity.

[0114] In some embodiments, the preset physical properties include: preset acoustic transit time, preset neutrons, preset density, and preset resistivity. These physical properties include: preset physical properties of dense limestone and preset physical properties of the infill material. The preset physical properties of the infill material include: preset physical properties of the wellbore model infill material and preset physical properties of the fractured cavity geological model.

[0115] (1) Therefore, the acoustic transit time, neutrons, and density of dense limestone are determined using the following formula:

[0116]

[0117]

[0118]

[0119] In the formula: and The sonic transit times (μs / ft) for dense limestone, formation water, and limestone framework are respectively. and The values ​​can be 185 μs / ft and 47.5 μs / ft, or empirical values ​​recognized in the study area can be used; and Neutrons, v / v, representing dense limestone, formation water, and the limestone framework, respectively. and It can be 1 or 0, or it can be an empirical value recognized in the study area; and The densities, in g / cm³, are those of dense limestone, formation water, and the limestone skeleton, respectively. and It is possible; V represents the porosity of dense limestone, v / v.

[0120] The resistivity value of dense limestone was determined by deducing the formation formula from actual well logging data. When the porosity of dense limestone is set at 2%, its corresponding resistivity is... When the porosity of dense limestone is 0%, the corresponding study area has a maximum resistivity of [missing information]. This results in the following formula:

[0121]

[0122] In the formula: Ω·m represents the resistivity of dense limestone.

[0123] (2) For the filling material of the fracture geological model, the filling material of the cave geological model, the filling material of the fault geological model and the filling material of the wellbore model, the preset physical properties are related to the type of filling material.

[0124] The filling material for the fracture geological model is one of mud, mudstone, and calcite. The filling material for the fault geological model and the cave geological model is one or more of mud, sandstone, mudstone, breccia, and calcite. The filling material for the wellbore model is mud. Therefore, determining the preset physical properties of the fracture geological model, cave geological model, fault geological model, and wellbore model is equivalent to determining the physical properties of mud, sandstone, mudstone, breccia, and calcite.

[0125] The density of the mud is determined by statistically studying the average or median mud density of the block. If the mud density of each well is not much different, the average value is used; if the mud density of the wells differs greatly, the median value is used.

[0126] The resistivity of mud is determined by using the following formula to calculate the resistivity value of mud in each well in the study area at the bottom hole temperature of the well, and then averaging the values ​​to obtain the mud resistivity.

[0127] =

[0128] In the formula: t is a certain temperature, in °C; and denoted as t℃, where t is the resistivity of the mud at 18℃ and t℃, in ohm.m.

[0129] For acoustic transit time logging of mud, the mud acoustic transit time value provided in the array acoustic data is selected. For neutrons in the mud, the maximum neutron value of the enlarged section in the actual logging data is selected.

[0130] The acoustic transit time, neutron density, and resistivity of sandstone are determined by the following formulas.

[0131]

[0132]

[0133]

[0134]

[0135] In the formula: and Sonic transit times for sandstone, sandstone skeleton, and oil, respectively, in μs / ft; and Neutrons, v / v, for sandstone, sandstone framework, and oil, respectively; and The densities of sandstone, sandstone framework, and oil are respectively, in g / cm³. 3 ; The porosity of sandstone is v / v. This represents the water saturation of the sandstone.

[0136] The presupposed physical properties of mudstone are the average values ​​of acoustic transit time, neutron, density, and resistivity logging data for mud-filled cavities at depths of 5 meters or more in the well.

[0137] The acoustic transit time, neutron density, and resistivity of breccia are determined by the following formulas.

[0138]

[0139]

[0140]

[0141]

[0142] In the formula: , where represents the acoustic transit time of the breccia, in μs / ft; For neutrons in breccia, v / v; Density of breccia, g / cm³ 3 ; and V represents the porosity between breccia and the porosity of the breccia.

[0143] Calcite is a pure limestone, almost without any pores. The acoustic transit time, neutron, density and resistivity values ​​of the limestone skeleton were selected.

[0144] Therefore, in some embodiments, step S4, "setting preset physical properties for the dense limestone and filling material in the three-dimensional logging geometric model of the fractured cavity to obtain the target three-dimensional logging physical model of the fractured cavity," includes:

[0145] Step S41: Set preset acoustic transit time, preset neutron, preset density and preset resistivity for the fractured cavity filling material, the wellbore filling material and the dense limestone to obtain a three-dimensional logging physical model of the target fractured cavity.

[0146] Based on the type of filler material in the fractured cavity, the corresponding preset acoustic transit time, preset neutron, preset solution, and preset resistivity are determined and set on the filler material of the fractured cavity geological model. Then, the preset physical properties of the dense limestone and the preset physical properties of the wellbore model are determined. This transforms the three-dimensional logging geometric model of the fractured cavity into the three-dimensional logging physical model of the target fractured cavity.

[0147] Step S5: Perform well logging response simulation based on the three-dimensional well logging physical model of the target fracture cavity to obtain the well logging response simulation values.

[0148] This application combines a wellbore model and a fractured-cavity geological model to form a three-dimensional geometric model of the fractured-cavity. Based on the parameters of the wellbore model and the fractured-cavity geological model, the physical properties of the three-dimensional geometric model of the fractured-cavity are preset. Finally, well logging response simulation is performed on the three-dimensional geometric model with preset physical properties to obtain well logging response simulation data. The well logging response simulation data in this application matches the geological conditions of the fractured-cavity, thus improving the interpretation effect of the well logging response.

[0149] After establishing the three-dimensional logging physical model of the target fracture cavity, different logging methods were used to simulate the logging response of the model. The simulated logging response values ​​were obtained. These simulated values ​​can better interpret the logging response.

[0150] Commonly used logging methods include: sonic transit time logging, neutron logging, density logging, and dual lateral logging. The corresponding values ​​obtained are the sonic transit time logging response values, neutron logging response values, density logging response values, and resistivity logging response values.

[0151] Therefore, in some embodiments, the simulated logging response values ​​include: simulated response values ​​of sonic transit time logging, simulated response values ​​of neutron logging, simulated response values ​​of density logging, and simulated response values ​​of resistivity logging.

[0152] Furthermore, step S5, "Based on the three-dimensional logging physical model of the target fracture cavity, perform logging response simulation to obtain logging response simulation values," includes:

[0153] Step S51: Use the three-dimensional finite difference method to simulate the acoustic time-of-flight logging response of the three-dimensional logging physical model of the target fracture cavity, and obtain the simulation response value of the acoustic time-of-flight logging.

[0154] Step S52: Use the Monte Carlo method to simulate the neutron and density logging responses of the three-dimensional logging physical model of the target fracture cavity, and obtain the neutron logging simulation response values ​​and the density logging simulation response values.

[0155] Step S53: Use the three-dimensional finite element method to simulate the resistivity logging response of the three-dimensional logging physical model of the target fracture cavity, and obtain the simulated resistivity logging response value.

[0156] In order to make the final well logging response simulation results easier to interpret, it is necessary to unify the recording points of each well logging method at a single depth point.

[0157] After step S5, the method further includes:

[0158] Step S6: Establish the correspondence between the simulated logging response values ​​and the three-dimensional logging geometric model of the fractured cavity.

[0159] The simulated logging response values ​​include: simulated response values ​​of sonic transit time logging, simulated response values ​​of neutron logging, simulated response values ​​of density logging, and simulated response values ​​of resistivity logging.

[0160] Therefore, step S6, "Establishing the correspondence between the well logging response simulation results and the three-dimensional well logging geometric model of the fractured cavity," includes:

[0161] Step S61: Establish the correspondence between the simulated response values ​​of acoustic time-of-flight logging, neutron logging, density logging, and resistivity logging and the three-dimensional logging geometric model of the fractured cavity.

[0162] In this embodiment, multiple simulations can be performed, setting different preset physical properties for the three-dimensional logging geometry model of the fractured cavity. A correspondence is then established between the simulated logging response values ​​obtained from each simulation and the three-dimensional logging geometry model of the fractured cavity, ultimately forming a correspondence table between the three-dimensional logging geometry model and the simulated logging response values. When relevant parameters of the target area are obtained, the corresponding simulated logging response values ​​can be retrieved through the correspondence table, improving the exploration efficiency of the target area. Similarly, the corresponding three-dimensional logging geometry model can be retrieved from the correspondence table based on the actual logging response values ​​of the target area, thereby obtaining various relevant parameters in the target area.

[0163] Example 3:

[0164] Based on the foregoing embodiments, this application provides a well logging response simulation device. The various modules and units included in the device can be implemented by a processor in a computer device; of course, they can also be implemented by specific logic circuits. In the implementation process, the processor can be a central processing unit (CPU), a microprocessor unit (MPU), a digital signal processor (DSP), or a field programmable gate array (FPGA), etc.

[0165] like Figure 3 As shown, the second aspect provides a well logging response simulation device, including: a first acquisition module, a first establishment module, a second establishment module, a first preset module, and a first execution module.

[0166] The first acquisition module is used to acquire wellbore parameters and fracture-cavity geological parameters of the target area. The first establishment module is used to construct a wellbore model based on the wellbore parameters and a fracture-cavity geological model based on the fracture-cavity geological parameters. The second establishment module is used to establish a three-dimensional logging geometric model of the fracture-cavity based on the wellbore model and the fracture-cavity geological model. The first preset module is used to set preset physical properties for the limestone and filling material in the three-dimensional logging geometric model of the fracture-cavity, obtaining a three-dimensional logging physical model of the target fracture-cavity. The first execution module is used to perform logging response simulation based on the three-dimensional logging physical model of the target fracture-cavity, obtaining simulated logging response values.

[0167] In some embodiments, the first establishment module includes a third establishment module and a fourth establishment module.

[0168] The third module is used to create a wellbore model based on the wellbore diameter, wellbore angle, and wellbore filling material. The fourth module is used to create a geological model of the fractured cavity based on the fractured cavity type, fractured cavity filling material, and fractured cavity size.

[0169] In some embodiments, the second establishment module includes a fifth establishment module. The fifth establishment module is used to combine the wellbore model and the fractured-cavity geological model according to the drilling encounter relationship to form a three-dimensional logging geometric model of the fractured-cavity.

[0170] In some embodiments, the first preset module includes a second preset module. The second preset module is used to set preset acoustic transit time, preset neutron, preset density, and preset resistivity for the fractured cavity filling material, the wellbore filling material, and the dense limestone to obtain a three-dimensional logging physical model of the target fractured cavity.

[0171] In some embodiments, the first execution module includes: a second execution module, a third execution module, and a fourth execution module.

[0172] The second execution module is used to simulate the acoustic time-of-flight logging response of the three-dimensional logging physical model of the fractured cavity using the three-dimensional finite difference method, and obtain the simulated acoustic time-of-flight logging response values. The third execution module is used to simulate the neutron and density logging responses of the target fractured cavity three-dimensional logging physical model using the Monte Carlo method, and obtain the simulated neutron logging response values ​​and the simulated density logging response values. The fourth execution module is used to simulate the resistivity logging response of the target fractured cavity three-dimensional logging physical model using the three-dimensional finite element method, and obtain the simulated resistivity logging response values.

[0173] This application integrates the geological model, physical properties, numerical simulation methods for various logging responses, and multiple logging responses of fractured-cavitary reservoirs into a holistic approach for logging response analysis, making the logging responses more closely approximate the geological conditions of fractured-cavitary reservoirs. The data used in the method can be obtained from logging data, core data, formation water data, and mud data, exhibiting strong operability and wide applicability. The results can effectively analyze the logging responses of fractured-cavitary reservoirs and provide rich and accurate data for artificial intelligence research on logging in fractured-cavitary reservoirs, possessing significant practical value in the exploration and development of complex reservoirs such as fractured-cavitary reservoirs.

[0174] Example 4:

[0175] On the logging response simulation device of the above embodiment 3, such as Figure 4 As shown, it may also include: a sixth creation module.

[0176] The sixth module is used to establish the correspondence between the simulated logging response values ​​and the three-dimensional logging geometric model of the fractured cavity.

[0177] In some embodiments, the sixth establishment module includes: a seventh establishment module.

[0178] The seventh module is used to establish the correspondence between the simulated response values ​​of acoustic time-of-flight logging, neutron logging, density logging, and resistivity logging and the three-dimensional logging geometric model of the fractured cavity.

[0179] The seventh module is also used to generate a correspondence table between the three-dimensional logging geometric model and the logging response simulation values.

[0180] In some embodiments, the logging response device further includes a query module.

[0181] The query module is used to obtain the corresponding well logging response simulation values ​​by querying the corresponding relationship table when the relevant parameters of the target area are obtained, thereby improving the exploration efficiency of the target area.

[0182] The query module can also be used to query the corresponding three-dimensional logging geometric model in the corresponding relationship table based on the actual logging response values ​​of the target area, thereby obtaining various relevant parameters in the target area.

[0183] The modules in the aforementioned well logging response simulation device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of the device in hardware form or independently of it, or stored in the memory of the processing device in software form, so that the processor can call and execute the operations corresponding to each module. It should be noted that the module division in this embodiment is illustrative and only represents a logical functional division; in actual implementation, there may be other division methods.

[0184] Example 5:

[0185] The third aspect provides an electronic device including a storage device and a processor, wherein the storage device stores a computer program, and the processor executes the computer program to implement the steps of a well logging response simulation method.

[0186] Example 6:

[0187] The fourth aspect provides a storage medium storing a computer program that can be executed by one or more processors, the computer program being able to implement the steps of any of the well logging response simulation methods in the first aspect.

[0188] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, or optical storage, etc. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0189] It should be understood that the phrase "one embodiment" or "an embodiment" throughout the specification means that a specific feature, structure, or characteristic related to the embodiment is included in at least one embodiment of this application. Therefore, "in one embodiment" or "in an embodiment" appearing throughout the specification does not necessarily refer to the same embodiment. Furthermore, these specific features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. It should be understood that in the various embodiments of this application, the sequence numbers of the above-described processes do not imply a sequential order of execution; the execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application. The sequence numbers of the above-described embodiments are merely descriptive and do not represent the superiority or inferiority of the embodiments.

[0190] It should be noted that, in this document, 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 a 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.

[0191] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods, such as: multiple units or components can be combined, or integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the various components shown or discussed can be through some interfaces, and the indirect coupling or communication connection between devices or units can be electrical, mechanical, or other forms.

[0192] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units. They may be located in one place or distributed across multiple network units. Some or all of the units may be selected to achieve the purpose of this embodiment according to actual needs.

[0193] In addition, each functional unit in the various embodiments of this application can be integrated into one processing unit, or each unit can be a separate unit, or two or more units can be integrated into one unit; the integrated unit can be implemented in hardware or in the form of hardware plus software functional units.

[0194] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media that can store program code, such as mobile storage devices, read-only memory (ROM), magnetic disks, or optical disks.

[0195] Alternatively, if the integrated units described above are implemented as software functional modules and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the embodiments of this application, or the parts that contribute to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a controller to execute all or part of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, ROMs, magnetic disks, or optical disks.

[0196] The above description is merely an embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A well logging response simulation method, characterized in that, include: Obtain wellbore parameters and fractured cavern geological parameters for the target area; A wellbore model is constructed based on the wellbore parameters, and a fractured cavity geological model is constructed based on the fractured cavity geological parameters. A three-dimensional logging geometric model of the fractured cavity was established based on the wellbore model and the geological model of the fractured cavity. Preset physical properties are set for the dense limestone and filling material in the three-dimensional logging geometric model of the fractured cavity to obtain the three-dimensional logging physical model of the target fractured cavity. Based on the three-dimensional logging physical model of the target fracture cavity, logging response simulation was performed to obtain logging response simulation values.

2. The well logging response simulation method according to claim 1, characterized in that, The method further includes: Establish the correspondence between the simulated logging response values ​​and the three-dimensional logging geometric model of the fractured cavity.

3. The well logging response simulation method according to claim 1, characterized in that, The wellbore parameters include: wellbore diameter, wellbore angle, and wellbore filling material; the fractured cavity geological parameters include: fractured cavity type, fractured cavity filling material, and fractured cavity size; the construction of a wellbore model based on the wellbore parameters and a fractured cavity geological model based on the fractured cavity geological parameters includes: The wellbore model is established based on the wellbore diameter, wellbore angle, and wellbore filling material. A geological model of the fracture cavity is established based on the cavity type, cavity filling material, and cavity size.

4. The well logging response simulation method according to claim 1, characterized in that, The wellbore parameters also include: drilling encounter relationships; the establishment of a three-dimensional logging geometric model of the fractured cavity based on the wellbore model and the fractured cavity geological model includes: Based on the drilling encounter relationship, the wellbore model and the fractured cavity geological model are combined to form a three-dimensional logging geometric model of the fractured cavity.

5. The well logging response simulation method according to claim 3, characterized in that, The preset physical properties include: preset acoustic transit time, preset neutron, preset density, and preset resistivity; setting preset physical properties for the dense limestone and filling material in the three-dimensional logging geometric model of the fractured cavity to obtain the target fractured cavity three-dimensional logging physical model includes: A three-dimensional logging physical model of the target fracture cavity is obtained by setting preset acoustic transit time, preset neutron, preset density and preset resistivity for the cavity filling material, the wellbore filling material and the dense limestone.

6. The well logging response simulation method according to claim 2, characterized in that, The simulated logging response values ​​include: simulated response values ​​for sonic transit time logging, neutron logging, density logging, and resistivity logging; the simulated logging response values ​​obtained by performing logging response simulation based on the three-dimensional logging physical model of the target fracture cavity include: The acoustic time-of-flight logging response of the three-dimensional well logging physical model of the fractured cavity was simulated using the three-dimensional finite difference method, and the numerical values ​​of the acoustic time-of-flight logging simulation response were obtained. The Monte Carlo method was used to simulate the neutron and density logging responses of the three-dimensional logging physical model of the target fractured cavity, and the numerical values ​​of the neutron logging simulation response and the density logging simulation response were obtained. The resistivity logging response of the target fracture cavity was simulated using the three-dimensional finite element method to obtain the simulated resistivity logging response values.

7. The well logging response simulation method according to claim 6, characterized in that, The simulated logging response values ​​include: simulated response values ​​for sonic transit time logging, neutron logging, density logging, and resistivity logging. Establishing the correspondence between the simulated logging response results and the three-dimensional logging geometric model of the fractured cavity includes: Establish the correspondence between the simulated response values ​​of acoustic time-of-flight logging, neutron logging, density logging, and resistivity logging and the three-dimensional logging geometric model of the fractured cavity.

8. A well logging response simulation device, characterized in that, include: The first acquisition module is used to acquire wellbore parameters and fractured cavern geological parameters of the target area; The first module is used to construct a wellbore model based on the wellbore parameters and a fractured-cavity geological model based on the fractured-cavity geological parameters. The second module is used to establish a three-dimensional logging geometric model of the fractured cavity based on the wellbore model and the fractured cavity geological model. The first preset module is used to set preset physical properties for the dense limestone and filling material in the three-dimensional logging geometric model of the fractured cavity to obtain the target three-dimensional logging physical model of the fractured cavity. The first execution module is used to perform well logging response simulation based on the three-dimensional well logging physical model of the target fracture cavity to obtain well logging response simulation values.

9. An electronic device, characterized in that, include: The system includes a memory and a processor, wherein the memory stores a computer program that, when executed by the processor, performs a well logging response simulation method as described in any one of claims 1 to 7.

10. A storage medium, characterized in that, The computer program stored in the storage medium can be executed by one or more processors, and the computer program can be used to implement the steps of a well logging response simulation as described in any one of claims 1 to 7.

Images