A method, device, equipment, medium and product for estimating heavy oil migration velocity

Abstract

The present application discloses a method, device, equipment, medium and product for estimating the migration velocity of heavy oil, which relates to the field of exploration technology. The method comprises obtaining a basin structural geological model of a target basin; dividing the top surface of the transport layer in the low-angle slope area in the basin structural geological model into a grid structure, and determining the formation dip angle of each grid unit in the grid structure; the low-angle slope area is an area where the formation dip angle is within a set dip angle range; and calculating the migration velocity of heavy oil in each grid unit according to the formation dip angle, crude oil viscosity, crude oil permeability and capillary force of crude oil in the water layer of each grid unit. The present application can improve the accuracy of heavy oil migration velocity estimation and lay a foundation for the prediction of favorable crude oil potential accumulation areas.

Description

Technical Field

[0001] The present application relates to the field of exploration technology, and in particular to a method, device, equipment, medium and product for estimating the migration velocity of heavy oil. Background Art

[0002] The main driving force for the secondary migration of crude oil is the buoyancy it experiences in the transport layer, and the magnitude of the buoyancy is determined by the height of the oil column and the difference in oil-water density in the transport layer. When oil and gas migrate to the slope zone at the edge of the basin, the height of the oil column decreases significantly, and the newly generated hydrocarbons that migrate to the shallow part of the basin will lose their lighter components. Once these components are free, they will migrate faster, migrate or dissipate in the upward direction of the transport layer, leaving behind increasingly dense and viscous crude oil. Long-distance secondary migration may also increase the exposure of oil to biodegradation and water washing environments, thereby consuming the light hydrocarbon components of the oil and further increasing its viscosity. However, in the low-angle slope zone, the decrease in structural inclination leads to a decrease in the height of the oil column, and the salinity of the formation water decreases, which weakens the buoyancy, thereby affecting the migration rate of heavy oil. Under such special geological conditions, the migration of heavy oil in the transport layer is a non-Newtonian flow due to its high viscosity. The migration velocity estimation of conventional basin simulation methods usually relies on a comprehensive analysis of factors such as fluid potential, driving force and viscosity. The use of fluid potential method, radial method and Darcy seepage method to roughly estimate the migration velocity of crude oil at the edge of the basin has certain limitations and cannot accurately reflect the migration velocity of heavy oil in low-angle slope zones, which poses a great challenge to exploration deployment and reserve estimation. Summary of the invention

[0003] The purpose of this application is to provide a heavy oil migration velocity estimation method, device, equipment, medium and product, which can improve the accuracy of heavy oil migration velocity estimation and lay a foundation for the prediction of favorable crude oil potential accumulation areas.

[0004] To achieve the above objectives, this application provides the following solutions:

[0005] In a first aspect, the present application provides a method for estimating the migration velocity of heavy oil, comprising:

[0006] Obtaining a basin structural geological model of the target basin;

[0007] The top surface of the conductive layer in the low-angle slope area in the basin structural geological model is divided into a grid structure, and the formation dip angle of each grid unit in the grid structure is determined; the low-angle slope area is an area where the formation dip angle is within a set dip angle range;

[0008] The migration velocity of heavy oil in each grid cell is calculated based on the formation dip angle, crude oil viscosity, crude oil permeability and capillary force of crude oil in the water layer.

[0009] Optionally, the migration velocity of the heavy oil in each grid unit is calculated according to the formation dip angle of each grid unit, the crude oil viscosity, the crude oil permeability and the capillary force of the crude oil in the water layer, specifically including:

[0010] According to the formula Calculate the migration velocity of heavy oil in each grid cell;

[0011] in, For the i Line j The migration velocity of heavy oil in the grid cells of the column, For the i Line j The crude oil permeability in the grid cells of the column, For the i Line j The viscosity of crude oil in the grid cell of the column, is the fluid density difference, For the i Line j The formation dip of the grid cell in the column, For the i Line j Capillary force of crude oil in water layer within the grid cells of the column.

[0012] Alternatively, the capillary force of crude oil in a water layer is expressed as: ;

[0013] in, is the interfacial tension, is the wetting angle, For the i Line j The mesh cell throat radius of the column.

[0014] Optionally, after dividing the top surface of the transport layer in the low-angle slope area in the basin structural geological model into a grid structure and determining the formation dip angle of each grid unit in the grid structure, the heavy oil migration velocity estimation method further includes:

[0015] Calculate the formation temperature for each grid cell;

[0016] According to the relationship between formation temperature and crude oil viscosity, the crude oil viscosity of each grid unit is calculated.

[0017] Optionally, the formation temperature of each grid cell is calculated, specifically including:

[0018] According to the formula Calculate the formation temperature for each grid cell;

[0019] in, For the iLine j The formation temperature of the grid cells of the column, For the i Line j The surface temperature corresponding to the grid cells in the column, is the geothermal gradient, For the i Line j The buried depth of the conductive layer of the grid cells in the column.

[0020] Alternatively, the relationship between formation temperature and crude oil viscosity is expressed as: ;

[0021] in, For the i Line j The viscosity of crude oil in the grid cell of the column, and are constants, For the i Line j The formation temperature of the grid cells in the column.

[0022] In a second aspect, the present application provides a heavy oil migration velocity estimation device, the heavy oil migration velocity estimation device comprising:

[0023] A basin structural geological model acquisition module is used to obtain a basin structural geological model of a target basin;

[0024] A formation dip angle determination module is used to divide the top surface of the conductive layer in the low-angle slope area in the basin structural geological model into a grid structure, and determine the formation dip angle of each grid unit in the grid structure; the low-angle slope area is an area where the formation dip angle is within a set dip angle range;

[0025] The migration velocity calculation module is used to calculate the migration velocity of heavy oil in each grid unit according to the formation inclination of each grid unit, crude oil viscosity, crude oil permeability and capillary force of crude oil in the water layer.

[0026] In a third aspect, the present application provides a computer device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of any of the above-described methods for estimating the migration velocity of heavy oil.

[0027] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of any one of the above-mentioned methods for estimating the migration velocity of heavy oil.

[0028] In a fifth aspect, the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the steps of any one of the above-mentioned heavy oil migration velocity estimation methods.

[0029] According to the specific embodiments provided in the present application, the present application discloses the following technical effects: the present application provides a method, device, equipment, medium and product for estimating the migration velocity of heavy oil, which calculates the migration velocity of heavy oil in each grid unit according to the formation inclination of each grid unit, crude oil viscosity, crude oil permeability and capillary force of crude oil in the water layer, takes into account the influence of geological structure inclination on the migration velocity of heavy oil, improves the accuracy of heavy oil migration velocity estimation, and lays a foundation for predicting favorable potential crude oil accumulation areas. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0031] Figure 1 This is a diagram of the application environment of a heavy oil migration velocity estimation method in one embodiment of the present application.

[0032] Figure 2 A schematic diagram of an implementation flow of a heavy oil migration velocity estimation method provided in one embodiment of the present application.

[0033] Figure 3 A schematic diagram of a basin structural geological model provided in one embodiment of the present application.

[0034] Figure 4 A schematic diagram of the force relationship of heavy oil in a water-bearing formation provided in one embodiment of the present application.

[0035] Figure 5 A schematic diagram of viscosity-temperature relationship curve fitting provided in one embodiment of the present application.

[0036] Figure 6 A schematic cross-sectional diagram of input parameters and output parameters provided for an embodiment of the present application.

[0037] Figure 7 A schematic diagram of a plane view of formation dip angles provided in one embodiment of the present application.

[0038] Figure 8 A schematic diagram of the heavy oil migration velocity and favorable area distribution provided in one embodiment of the present application.

[0039] Fig. 9A schematic diagram of the structure of a computer device provided in one embodiment of the present application.

[0040] Figure numerals: 201 - oil-bearing area, 202 - water-bearing area, 203 - buoyancy, 204 - viscous force, 205 - capillary resistance, 206 - oil-water interface line, 207 - vertical height of oil column, 208 - hydrostatic pressure gradient line, 209 - oil column pressure gradient line, 210 - oil-water top height line, 211 - formation dip. DETAILED DESCRIPTION

[0041] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0042] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0043] The heavy oil migration velocity estimation method provided in the embodiment of the present application can be applied to Figure 1 In the application environment shown. Among them, the terminal 102 communicates with the server 104 through the network. The data storage system can store the data that the server 104 needs to process. The data storage system can be set up separately, integrated on the server 104, or placed on the cloud or other servers. The terminal 102 can send the basin structural geological model of the target basin to the server 104, and the server 104 receives the basin structural geological model of the target basin. For the basin structural geological model of the target basin, the server 104 obtains the basin structural geological model of the target basin; the top surface of the transport layer in the low-angle slope area in the basin structural geological model is divided into a grid structure, and the formation dip of each grid unit in the grid structure is determined; the low-angle slope area is an area where the formation dip is within the set dip range; the migration velocity of the heavy oil in each grid unit is calculated according to the formation dip of each grid unit, the crude oil viscosity, the crude oil permeability and the capillary force of the crude oil in the water layer. The server 104 can feedback the obtained migration velocity of the heavy oil for the target basin to the terminal 102. In addition, in some embodiments, the heavy oil migration velocity estimation method can also be implemented independently by the server 104 or the terminal 102. For example, the terminal 102 can directly estimate the heavy oil migration velocity for the basin structural geological model of the target basin, or the server 104 can obtain the basin structural geological model of the target basin from the data storage system and estimate the heavy oil migration velocity for the basin structural geological model of the target basin.

[0044] The terminal 102 may be, but is not limited to, various desktop computers, laptop computers, smart phones, tablet computers, IoT devices, and portable wearable devices. The IoT devices may be smart speakers, smart TVs, smart air conditioners, smart vehicle-mounted devices, etc. The portable wearable devices may be smart watches, smart bracelets, head-mounted devices, etc. The server 104 may be implemented as an independent server or a server cluster consisting of multiple servers, or may be a cloud server.

[0045] In an exemplary embodiment, Figure 2 As shown, a method for estimating the migration velocity of heavy oil is provided. The method is executed by a computer device, and can be executed by a computer device such as a terminal or a server alone, or by a terminal and a server together. In the embodiment of the present application, the method is applied to Figure 1 The server 104 in the example is used for explanation, and the steps include the following steps 1 to 3.

[0046] Step 1: Obtain the basin structural geological model of the target basin.

[0047] Step 2: Divide the top surface of the conductive layer in the low-angle slope area in the basin structural geological model into a grid structure, and determine the formation dip angle of each grid unit in the grid structure; the low-angle slope area is an area where the formation dip angle is within a set dip angle range.

[0048] Step 3: Calculate the migration velocity of heavy oil in each grid cell according to the formation dip angle, crude oil viscosity, crude oil permeability and capillary force of crude oil in the water layer.

[0049] The present application takes into account the influence of geological structure inclination on the migration velocity of heavy oil, thereby improving the accuracy of heavy oil migration velocity estimation.

[0050] The transport layer in this application is a water-containing transport layer, which includes an oil-containing area 201 and water-containing areas 202 at both ends of the oil-containing area 201. The force mechanism of heavy oil migration in the water-containing transport layer is as follows: Figure 4 The driving force is the upward buoyancy 203 generated by the vertical height 207 of the oil column, and the resistance is controlled by the capillary resistance 205 and the viscosity 204. The vertical height 207 of the oil column is the distance between the oil-water interface line 206 and the oil-water top height line 210. The formation dip 211 of the oil-bearing area 201 is shown in Figure 4 As shown, the hydrostatic pressure gradient line 208 and the oil-water pressure gradient line 209 are as shown in FIG. Figure 4 shown.

[0051] In step 1, seismic data and well data are used to perform geological modeling and construct the main geological framework, i.e., the basin structural geological model, such as Figure 3As shown in the figure, the dip angle and structural morphology of the strata are inferred, and the dip angle of the strata at different positions in the low-angle slope zone of the target basin is determined. , Figure 3 A, B, C, D, E, F and G are all drilling wellheads.

[0052] The tilt angle range is set to be greater than or equal to 1° and less than or equal to 4°.

[0053] The top surface of the conductive layer in the low-angle slope area of ​​the basin structural geological model is divided into a grid structure, specifically comprising: dividing the top surface of the conductive layer into a 100×100 meter square grid according to the structural map, calculating the formation dip angle of each grid unit on the top surface of the conductive layer, and forming a formation dip angle plane diagram of each formation dip angle, such as Figure 7 shown.

[0054] After step 2, the heavy oil migration velocity estimation method further includes: calculating the formation temperature of each grid unit; and calculating the crude oil viscosity of each grid unit according to the relationship between the formation temperature and the crude oil viscosity.

[0055] Assuming the surface temperature is 18°C ​​and the underground formation temperature gradient is 2.8°C / 100m, the formation temperature of each grid cell is calculated, including: According to the formula Calculate the formation temperature for each grid cell.

[0056] in, For the i Line j The formation temperature of the grid cell of the column, K; For the i Line j The surface temperature corresponding to the grid cell of the column, in °C; is the geothermal gradient, unit: °C / 100m; For the i Line j The depth of the conductive layer of the grid cells in the column, in meters.

[0057] Measure or estimate the viscosity and density of heavy oil. Through on-site sampling, measure the density and viscosity of heavy oil, and perform data fitting to establish the viscosity-temperature relationship, such as Figure 5 The dashed line is the viscosity-temperature relationship, and the expression of the dashed line is: y=9344.4x-18.167, R 2 =0.866, x represents temperature T, y is a value related to viscosity, specifically y= , R 2 is the determination coefficient.

[0058] According to the Arrhenius equation, we get .

[0059] in, For the i Line j The crude oil viscosity in the grid cell of the column is in mPa.s; A is a constant; R is the universal gas constant; is the formation temperature of the transport layer, unit K; △E is the activation energy of crude oil in the target basin, unit J / mol.

[0060] right Taking the logarithm of both sides, we can get the relationship between formation temperature and crude oil viscosity: .

[0061] Among them, W=3ln10+A, V=△E / R, according to the relationship between formation temperature and crude oil viscosity, establish With 1 / The linear relationship between the constants W and V is obtained. For the i Line j The formation temperature of the grid cells in the series is calculated, so as to predict the viscosity of crude oil at different burial depths.

[0062] According to the formula The obtained geothermal data is used to calculate the viscosity under different transport layer position conditions. The density of heavy oil in this embodiment adopts the average value, specifically 0.90g / cm 3 .

[0063] Estimate the crude oil permeability of the transport channel based on drilling core analysis and test data k , specifically including: calculating the formation permeability of the transmission layer at the location of the well point. According to the regional sedimentary phase characteristics and drilling data, the permeability of the sparse point is obtained, and then combined with the regional data, the embodiment data is interpolated to obtain the permeability value of each grid unit .

[0064] Estimate the capillary force of the grid unit of the transport channel based on the data of drilling core analysis and testing The capillary force of crude oil in the water layer is expressed as: .in, is the interfacial tension, is the wetting angle, For the i Line j The throat radius of the grid unit of the column, in mm. Considering that the present embodiment is mainly composed of fluvial sediments, the capillary force is mainly controlled by the interfacial tension and the pore radius. By conducting mercury injection experiments on cores of different sedimentary microfacies, the capillary force values ​​of discrete points are obtained, and interpolation processing is performed to obtain the capillary force of each grid unit.

[0065] Among them, step 3 specifically includes: according to the formula Calculate the migration velocity of heavy oil within each grid cell.

[0066] in, For the i Line j The migration velocity of heavy oil in the grid cell of the column, in mPa.s; For the i Line j Crude oil permeability in the grid cells of the column, in mD; For the i Line j The crude oil viscosity in the grid cell of the column, in mPa.s; is the fluid density difference, in g / cm 3 , the fluid density difference is the density difference between crude oil and water; For the i Line j The formation dip of the grid cell in the column, For the i Line j Capillary force of crude oil in water layer within the grid cell of column, in psi.

[0067] This application verifies the calculated migration velocity of heavy oil by drawing structural geological profiles, geothermal field profiles, fluid parameter profiles and migration velocity profiles along the tilt direction of the basin structure. Specifically, it includes: drawing input parameter and output parameter profiles for quality inspection. Draw a profile line from position O to position S along the up-dip direction of the top surface of the conducting layer, such as Figure 6 As shown in part (a), all input parameters and calculation results are projected on the profile. The input parameters include formation dip, formation temperature, crude oil density and crude oil viscosity. The calculation result, that is, the output parameter, is the migration velocity. The distribution of each parameter in the profile is checked to verify the rationality of the input parameters. Figure 6 The gray part in the middle (a) is the lower part of the conducting layer, which does not contain oil, and the yellow part is the crude oil area. The formation dip is as follows Figure 6 As shown in part (b), the formation temperature is Figure 6 As shown in part (c), the density of crude oil is Figure 6 As shown in part (d), the viscosity of crude oil is Figure 6 As shown in part (e), the migration speed is Figure 6As shown in the middle (f) section. The formation dip angles in this example range from more than 8° in the low part to 1° in the high part. The formation temperature decreases significantly from 60° near the basin sedimentation center to about 10° in front of the basin edge. As in many foreland basins, the density of oil increases rapidly toward the basin edge, and the corresponding oil viscosity increases. The heavy oil migration velocity along the profile is calculated, from 4000m / ma near the basin center to 5m / ma. Figure 6 In the green area in (a), the migration velocity decreases rapidly, forming a dynamic equilibrium accumulation, where the red line represents the fault.

[0068] According to the calculation results of the migration velocity of heavy oil, the structural map and the crude oil migration velocity plane map are drawn to evaluate the migration state of heavy oil and determine the low-speed state area of ​​crude oil migration. Specifically, the following are drawn: Figure 8 As shown, the favorable areas for reservoir formation are pointed out. In the hinterland where the basin is steeper, the oil is lighter and the viscosity is lower, the calculated velocity is greater than 2800m / ma, which is very short on the geological time scale. However, with the increase of the inclination angle, the velocity drops rapidly in the first 50km, and finally drops to a minimum of 5m / ma in the superstripping zone. Using the same method, the distribution map of oil and gas migration velocity near the transport layer in the whole area was calculated, which shows that the overall migration velocity is relatively low. In areas with large faults and angles, the velocity is relatively fast; in the transport layer of the slope belt with high fresh water content, high density of heavy oil and small formation inclination, the driving force buoyancy is very small, and only a small resistance can be applied to prevent the further migration of oil and gas and form a large number of accumulations, specifically: Figure 8 The part circled by the black dotted outline.

[0069] This application takes into account the influence of geological structural inclination on the migration velocity of heavy oil, can more accurately predict the migration characteristics of heavy oil, and improves the accuracy of heavy oil migration velocity. This application is suitable for geological conditions in low-angle slope zones and has high practical value and application prospects.

[0070] Based on the same inventive concept, the embodiment of the present application also provides a heavy oil migration velocity estimation device for implementing the above-mentioned heavy oil migration velocity estimation method. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above-mentioned method, so the specific limitations of one or more heavy oil migration velocity estimation device embodiments provided below can refer to the limitations of the heavy oil migration velocity estimation method above, and will not be repeated here.

[0071] In an exemplary embodiment, the present application provides a heavy oil migration velocity estimation device including the following modules.

[0072] The basin structural geological model acquisition module is used to obtain the basin structural geological model of the target basin.

[0073] The formation dip determination module is used to divide the top surface of the conductive layer in the low-angle slope area in the basin structural geological model into a grid structure and determine the formation dip of each grid unit in the grid structure; the low-angle slope area is an area where the formation dip is within a set dip range.

[0074] The migration velocity calculation module is used to calculate the migration velocity of heavy oil in each grid unit according to the formation inclination of each grid unit, crude oil viscosity, crude oil permeability and capillary force of crude oil in the water layer.

[0075] The present application provides a heavy oil migration velocity estimation device, which can automatically complete data input, calculation and result output, thereby improving the work efficiency of heavy oil migration velocity estimation.

[0076] In an exemplary embodiment, a computer device is provided. The computer device may be a server or a terminal. The internal structure diagram thereof may be as follows: Fig. 9 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store heavy oil migration velocity estimation data. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a heavy oil migration velocity estimation method is implemented.

[0077] Those skilled in the art will understand that Fig. 9 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components. In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the steps in the above-mentioned heavy oil migration velocity estimation method embodiments are implemented.

[0078] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program, and when the computer program is executed by a processor, the steps in the above-mentioned heavy oil migration velocity estimation method embodiments are implemented.

[0079] In an exemplary embodiment, a computer program product is provided, including a computer program, which implements the steps in the above-mentioned heavy oil migration velocity estimation method embodiments when executed by a processor.

[0080] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0081] A person of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment method can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned heavy oil migration velocity estimation method. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present 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, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

[0082] The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. The non-relational database may include a distributed database based on blockchain, etc., but is not limited thereto. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a data processing logic of a programmable logic device, etc., but is not limited thereto.

[0083] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0084] This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core ideas of this application. At the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A method for estimating the migration velocity of heavy oil, characterized in that: The heavy oil migration velocity estimation method comprises: Obtaining a basin structural geological model of the target basin; The top surface of the conductive layer in the low-angle slope area in the basin structural geological model is divided into a grid structure, and the formation dip angle of each grid unit in the grid structure is determined; the low-angle slope area is an area where the formation dip angle is within a set dip angle range; The migration velocity of heavy oil in each grid cell is calculated based on the formation dip angle, crude oil viscosity, crude oil permeability and capillary force of crude oil in the water layer of each grid cell; The migration velocity of heavy oil in each grid unit is calculated based on the formation dip angle, crude oil viscosity, crude oil permeability and capillary force of crude oil in the water layer of each grid unit, including: According to the formula Calculate the migration velocity of heavy oil in each grid cell; in, For the i Line j The migration velocity of heavy oil in the grid cells of the column, For the i Line j The crude oil permeability in the grid cells of the column, For the i Line j The viscosity of crude oil in the grid cell of the column, is the fluid density difference, For the i Line j The formation dip of the grid cell in the column, For the i Line j Capillary force of crude oil in water layer within the grid cells of the column.

2. The method for estimating the migration velocity of heavy oil according to claim 1, characterized in that: The capillary force of crude oil in the water layer is expressed as: ; in, is the interfacial tension, is the wetting angle, For the i Line j The throat radius of the mesh elements of the column.

3. The method for estimating the migration velocity of heavy oil according to claim 1, characterized in that: After dividing the top surface of the transport layer in the low-angle slope area in the basin structural geological model into a grid structure and determining the formation dip angle of each grid unit in the grid structure, the heavy oil migration velocity estimation method further includes: Calculate the formation temperature for each grid cell; According to the relationship between formation temperature and crude oil viscosity, the crude oil viscosity of each grid unit is calculated.

4. The method for estimating the migration velocity of heavy oil according to claim 3, characterized in that: Calculate the formation temperature for each grid cell, including: According to the formula Calculate the formation temperature for each grid cell; in, For the i Line j The formation temperature of the grid cells of the column, For the i Line j The surface temperature corresponding to the grid cells in the column, is the geothermal gradient, For the i Line j The buried depth of the conductive layer of the grid cells in the column.

5. The method for estimating the migration velocity of heavy oil according to claim 3, characterized in that: The relationship between formation temperature and crude oil viscosity is expressed as: ; in, For the i Line j The viscosity of crude oil in the grid cell of the column, and are constants, For the i Line j The formation temperature of the grid cells in the column.

6. A heavy oil migration velocity estimation device, characterized in that: The heavy oil migration velocity estimation device comprises: A basin structural geological model acquisition module is used to obtain a basin structural geological model of a target basin; A formation dip angle determination module is used to divide the top surface of the conductive layer in the low-angle slope area in the basin structural geological model into a grid structure, and determine the formation dip angle of each grid unit in the grid structure; the low-angle slope area is an area where the formation dip angle is within a set dip angle range; A migration velocity calculation module, used to calculate the migration velocity of heavy oil in each grid unit according to the formation inclination of each grid unit, crude oil viscosity, crude oil permeability and capillary force of crude oil in the water layer; The migration velocity of heavy oil in each grid unit is calculated based on the formation dip angle, crude oil viscosity, crude oil permeability and capillary force of crude oil in the water layer of each grid unit, including: According to the formula Calculate the migration velocity of heavy oil in each grid cell; in, For the i Line j The migration velocity of heavy oil in the grid cells of the column, For the i Line j The crude oil permeability in the grid cells of the column, For the i Line j The viscosity of crude oil in the grid cell of the column, is the fluid density difference, For the i Line j The formation dip of the grid cell in the column, For the i Line j Capillary force of crude oil in water layer within the grid cells of the column.

7. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the heavy oil migration velocity estimation method according to any one of claims 1 to 5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for estimating the heavy oil migration velocity according to any one of claims 1 to 5 is implemented.

9. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method for estimating the heavy oil migration velocity according to any one of claims 1 to 5 is implemented.

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