A reservoir parameter direct inversion method and system

Abstract

The present invention provides a reservoir parameter direct inversion method and system, the method comprising the steps of: S10, establishing a rock physics model, and calculating the density, bulk modulus, and shear modulus of the minerals and fluids in the reservoir; S20, extracting seismic wavelets and establishing a reservoir parameter model; S30, calculating the reservoir initial elastic parameter model based on the density, bulk modulus, and shear modulus of the minerals and fluids in the reservoir and the reservoir parameter model. S40, performing prestack inversion using the initial elastic parameter model to obtain an inverted elastic parameter model; S50, characterizing the lithology, morphology, physical properties, and oil and gas content of the reservoir through the inverted elastic parameter model and the density, bulk modulus, and shear modulus of the minerals and fluids. The present invention can directly predict reservoir lithology, reservoir physical properties, and oil and gas content.

Description

Technical Field

[0001] The invention relates to seismic exploration and development of oil, gas and coal-bed methane, and in particular to a reservoir parameter direct inversion method and system. Background Art

[0002] Reservoir parameters are the basis for reservoir prediction, description and evaluation. Reservoirs are usually characterized from four aspects: lithology, morphology, physical properties and hydrocarbon content. Reservoir lithology is an element used to describe the composition of the reservoir. It directly or indirectly reflects the reservoir performance and reservoir characteristics of the rock formation. Reservoir morphology is an important parameter for describing the geometric shape of the reservoir. Commonly used descriptive parameters include the distribution range of the reservoir, the structural morphology of the reservoir top interface, and the reservoir thickness. The parameters describing the physical properties of the reservoir are mainly porosity and permeability. The description of the hydrocarbon content of the reservoir mainly includes whether the reservoir contains fluid, the type of fluid contained in the reservoir, and the hydrocarbon saturation.

[0003] Through logging data and rock core analysis, the lithology of oil and gas reservoirs can be obtained more accurately, including mineral type, cementation type, mineral content, reservoir geometric parameters, such as reservoir thickness, reservoir physical properties and oil and gas content. However, since wells are sparsely distributed in space, the reservoir parameters obtained from logging data are often at local points in space.

[0004] In actual work, reservoir prediction is mainly based on seismic information, and other data (geology, well logging, rock physics, etc.) are used as constraints to predict the geometric characteristics, lithology, physical properties and oil and gas content of oil and gas reservoirs. Reservoir prediction based on seismic data includes: seismic attribute method and seismic inversion method. The seismic attribute method first calculates or extracts the amplitude, phase, frequency, waveform, coherence and other attributes of the seismic data of the target layer, and then establishes the relationship between these reservoir parameters to predict the distribution range of reservoir rock formations, reservoir characteristics, etc. The seismic inversion method first uses seismic data for inversion to obtain reservoir wave impedance, or elastic parameters such as longitudinal and transverse wave velocity, density, and Poisson's ratio. At the same time, well logging calibration seismic is used to establish the relationship between reservoir elastic parameters and reservoir parameters, and then the inverted elastic parameters are used to predict reservoir parameters, thereby achieving the purpose of reservoir prediction. This is usually achieved through prestack inversion, including prestack AVO inversion and prestack elastic wave impedance inversion. The general process is: using some superimposed seismic data and well data (shear wave velocity, compressional wave velocity, density and other elastic parameter information), and inverting using different approximate formulas to obtain a variety of elastic parameters related to lithology and oil and gas content, and then use these elastic parameters to further predict reservoir lithology, reservoir physical properties and oil and gas content.

[0005] It can be seen that the steps of reservoir prediction are very cumbersome. Summary of the invention

[0006] Features and advantages of the invention are set forth in part in the following description, or may be obvious from the description, or may be learned through practice of the invention.

[0007] In order to overcome the problems of the prior art, the present invention provides a reservoir parameter direct inversion method and system, which uses seismic pre-stack data and logging interpretation data for direct inversion to obtain reservoir lithology, porosity, hydrocarbon content and saturation, thereby achieving direct prediction of reservoir lithology, reservoir physical properties and hydrocarbon content.

[0008] The technical solution adopted by the present invention to solve the above technical problems is as follows:

[0009] According to one aspect of the present invention, a reservoir parameter direct inversion method is provided, comprising:

[0010] S10, establishing a rock physics model and calculating the density, bulk modulus and shear modulus of minerals and fluids in the reservoir;

[0011] S20, extracting seismic wavelets and establishing a reservoir parameter model;

[0012] S30, calculating an initial elastic parameter model of the reservoir according to the density, bulk modulus and shear modulus of the minerals and fluids in the reservoir and the reservoir parameter model;

[0013] S40, performing prestack inversion using the initial elastic parameter model to obtain an elastic parameter model after inversion;

[0014] S50, characterizing the lithology, morphology, physical properties and oil and gas content of the reservoir through the inverted elastic parameter model and the density, bulk modulus and shear modulus of the mineral and fluid.

[0015] Preferably, the step S10 includes:

[0016] S11. Determine the approximate type of reservoir based on the geological knowledge of the target layer in the target exploration area and the logging interpretation results;

[0017] S12. Select the rock physical relationship between elastic parameters and reservoir parameters.

[0018] Preferably, the step S12 comprises:

[0019] The Voigt-Reuss-Hill formula, Wood formula, and Gassmann formula are used to calculate the density, bulk modulus, and shear modulus of minerals and fluids in the reservoir;

[0020] The relationship between P-wave and S-wave velocities is statistically calculated from the P-wave and S-wave logging curves.

[0021] Preferably, the step S20 includes:

[0022] Using the time-depth relationship between well seismic data, we can obtain the longitudinal and transverse wave velocity curves, density curves and reservoir parameter curves at the seismic scale.

[0023] The corresponding bulk modulus and shear modulus of the well logging are calculated from the longitudinal and shear wave velocities and density.

[0024] Preferably, in step S30, the reservoir parameter model is characterized by reservoir parameters, and the reservoir parameters are continuous values ​​between 0 and 1.

[0025] Preferably, the step S40 includes: constructing an objective function using the reflection coefficient formula, wavelet and observation data, and using an optimization algorithm to find an optimal solution that minimizes the objective function value as an inversion result, thereby obtaining an elastic parameter model after inversion.

[0026] Preferably, step S50 includes: calculating reservoir parameters such as reservoir mineral content saturation using rock physics relationships based on the elastic parameter model obtained by prestack inversion, the density, bulk modulus and shear modulus of each mineral component in the reservoir, to characterize the lithology, morphology, physical properties and oil and gas content of the reservoir.

[0027] The present invention provides a reservoir parameter direct inversion system, comprising:

[0028] The first calculation module is used to establish a rock physics model and calculate the density, bulk modulus, and shear modulus of minerals and fluids in the reservoir;

[0029] A reservoir parameter model building module is used to extract seismic wavelets and build a reservoir parameter model;

[0030] The elastic parameter model calculation module is used to calculate the initial elastic parameter model of the reservoir according to the density, bulk modulus and shear modulus of the minerals and fluids in the reservoir and the reservoir parameter model.

[0031] The inversion module is used to perform prestack inversion using the initial elastic parameter model to obtain an inverted elastic parameter model.

[0032] The second calculation module is used to describe the lithology, morphology, physical properties and oil and gas content of the reservoir through the inverted elastic parameter model and the density, bulk modulus and shear modulus of the mineral and fluid.

[0033] Preferably, the reservoir parameter model is characterized by reservoir parameters, and the reservoir parameters are continuous values ​​between 0 and 1.

[0034] The present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores at least one computer-executable program, and when the at least one program is executed by the computer, the computer executes the steps in any one of the above-mentioned methods.

[0035] The present invention provides a reservoir parameter direct inversion method and system, which can directly invert reservoir lithology, porosity, oil and gas content and saturation at the same time.

[0036] By reading the specification, ordinary technicians in this field will have a better understanding of the characteristics and contents of these technical solutions. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The present invention will be described in detail below with reference to the accompanying drawings and in combination with examples, and the advantages and implementation methods of the present invention will become more obvious. The contents shown in the accompanying drawings are only used to explain the present invention and do not constitute any limitation to the present invention in any sense. In the accompanying drawings:

[0038] Figure 1 Schematic diagram of the flow of the direct inversion method of reservoir parameters according to an embodiment of the present invention.

[0039] Figure 2 Schematic diagram of the structure of a reservoir parameter direct inversion system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0040] The data required for use in the present invention include well data and seismic data, wherein the well data include various conventional logging curves and interpretation results, especially mineral content (volume percentage), porosity, and fluid (oil, gas, and water) saturation; the seismic data include pre-stack seismic data, post-stack seismic data, and structural interpretation results.

[0041] Based on the above well data and seismic data, Figure 1 As shown, the present invention provides a reservoir parameter direct inversion method, comprising the steps of:

[0042] S10. Establish a rock physics model and calculate the relationship between the density, bulk modulus, shear modulus and longitudinal and transverse wave velocities of minerals and fluids in the reservoir.

[0043] S20, extracting seismic wavelets and establishing a reservoir parameter model.

[0044] The seismic wavelet is used for calibration and inversion, wherein calibration refers to the process of establishing a connection between well data and seismic data.

[0045] S30, calculating an initial elastic parameter model of the reservoir according to the density, bulk modulus and shear modulus of the minerals and fluids in the reservoir and the reservoir parameter model.

[0046] S40, performing prestack inversion using the initial elastic parameter model to obtain an inverted elastic parameter model.

[0047] S50, characterizing the lithology, morphology, physical properties and oil and gas content of the reservoir through the inverted elastic parameter model and the density, bulk modulus and shear modulus of the mineral and fluid.

[0048] Wherein, the step S10 specifically includes:

[0049] S11. Determine the approximate type of reservoir based on the geological knowledge of the target layer in the target exploration area and the logging interpretation results;

[0050] The general types of reservoirs include sandstone, clastic rock, carbonate rock, etc.

[0051] S12, selecting a rock physical relationship between elastic parameters and reservoir parameters;

[0052] In this embodiment, the Voigt-Reuss-Hill formula, Wood formula, and Gassmann formula are used. Of course, it is also feasible to use other formulas. At the same time, the relationship between the longitudinal and shear wave velocities in this area is statistically calculated from the longitudinal and shear wave logging curves.

[0053] Voigt-Reuss-Hill formula:

[0054] Where M represents the shear modulus μ or the bulk modulus K,

[0055] M V =f Q ·M Q +f F ·M F +f C ·M C +…+f w ·M w +f O ·M O +f G ·M G ;

[0056]

[0057] Where f represents the volume content of each mineral component, for example: f Q represents the volume content of quartz in reservoir rocks, M Q Then the shear modulus μ of quartz Q Or the bulk modulus K Q .

[0058] Wood's formula: ρ=f Q ·ρQ +f F ·ρ F +f C ·ρ C +…+f w ·ρ w +f O ·ρ O +f G ·ρ G .

[0059] Where ρ represents the density.

[0060] When there are pores in the reservoir, we first use the above formula to calculate the modulus and density of the reservoir rock skeleton and fluid respectively:

[0061]

[0062] M V_0 =f Q ·M Q +f F ·M F +f C ·M C +…,M r_fl =f w ·M w +f O ·M O +f G ·M G

[0063]

[0064] ρ0=f Q ·ρ Q +f F ·ρ F +f C ·ρ C +...,ρ fl =f w ·ρ w +f O ·ρ O +f G ·ρ G

[0065] Then use the following formulas to calculate the longitudinal and transverse wave velocities of the reservoir rock skeleton and fluid respectively:

[0066] For example:

[0067] Finally, considering the influence of porosity φ, the following formulas are used to calculate the P-wave velocity, S-wave velocity and density of the reservoir rock:

[0068]

[0069] It should be noted that if there are no pores, the last step of considering the porosity f is not necessary.

[0070] Gassmann formula:

[0071] in is the bulk modulus of dry rock. φ C It is the critical porosity, which is generally taken as 0.4.

[0072] In the step S20, it specifically includes: well seismic calibration. In this calibration process, it is not only necessary to establish the well seismic time-depth relationship and extract sub-waves, but also to use the well seismic time-depth relationship to obtain the longitudinal wave velocity curve of the reservoir at the seismic wave scale. And using the relationship between the longitudinal and transverse wave velocities obtained in step S10, the transverse wave velocity at the seismic wave scale is calculated from the longitudinal wave velocity at the seismic wave scale. In this way, the longitudinal and transverse wave velocity curves, density curves and reservoir parameter curves at the seismic scale are obtained by using the well seismic time-depth relationship. The corresponding bulk modulus and shear modulus can be calculated from the longitudinal and transverse wave velocities and density using the following formula.

[0073]

[0074]

[0075] Among them, V P_b 、V s_b is the reservoir P-wave velocity obtained from logging, ρ b is the density, K b is the reservoir bulk modulus, μ b is the reservoir shear modulus.

[0076] It can be seen that the Voigt-Reuss-Hill formula in step S1 is used to calculate the modulus of the rock based on the mineral component content of the rock and the modulus of the corresponding mineral, while here the modulus of the rock is calculated using the longitudinal and transverse wave velocities and density of the rock obtained by well logging.

[0077] Assuming that the elastic parameters such as bulk modulus and shear modulus of minerals are the same at the same depth (layer), the elastic parameter curves such as reservoir bulk modulus and shear modulus curves and reservoir parameter curves obtained from multiple wells can be used to calculate the elastic parameter curves such as density, bulk modulus and shear modulus curves of each mineral component in the reservoir from rock physical relationships.

[0078] It should be noted that the application of these formulas in different situations includes:

[0079] ① The bulk modulus and shear modulus of the rock are calculated from the P- and S-wave velocities and density obtained from logging. The density of the rock is equal to the logging density.

[0080] ② The bulk modulus, shear modulus, density of the rock, porosity and mineral volume content obtained by logging are used to calculate the bulk modulus, shear modulus and density of the mineral (including flow diagram) using the Voigt-Reuss-Hill formula, Wood formula and Gassmann formula.

[0081] Take three framework minerals as an example:

[0082]

[0083]

[0084]

[0085] in

[0086] K V_0 =f Q ·K Q +f F ·K F +f C ·K C , K V_fl =f w ·K w +f O ·K O +f G ·K G

[0087]

[0088] For example, when there are more than 6 well logging density curves r b，i , and the corresponding porosity curve φ i , mineral volume content f Q，i , f F，i , f C，i and the fluid saturation f w，i , f o，i , f G，i , then at each depth (layer), there can be more than 6 following formulas:

[0089]

[0090] Thus, the density of minerals and fluids can be solved: ρ Q , ρ F , ρ C , ρ w , ρ o , ρG In the process of solving the problem, constraints can be added based on the laboratory measurement results in the work area: for example, the density of water:

[0091] 1.0≤ρ w ≤1.1, crude oil density 0.8≤ρ w ≤1.0.

[0092] Similarly, the bulk modulus K of the mineral can be obtained Q , K F , K C and shear modulus μ Q , μ F , μ C , the bulk modulus K of the fluid w , K o , K G .

[0093] In step S30, the corresponding data on the well is interpolated or extrapolated under the constraints of the seismic structural interpretation results, but it is different from the initial model in the conventional inversion. The initial model in the conventional inversion is an elastic parameter model, while the model in the present invention is a reservoir parameter model characterized by reservoir parameters such as mineral content (volume percentage), porosity, and fluid (oil, gas, and water) saturation. These parameters are continuous values ​​between 0 and 1, and are not an identifier like lithology. The initial reservoir model and the parameters such as density, bulk modulus, and shear modulus of each mineral component in the reservoir obtained in step S10 can be used to calculate the initial elastic parameter model of the reservoir using rock physics relationships.

[0094] In step S40, the initial elastic parameter model is used to perform prestack inversion. Based on different formulas (the specific formulas need to be specifically considered, for example, the following gives different formulas for prestack elastic wave impedance inversion and prestack synchronous inversion), different inversion results can be obtained: P-wave velocity, S-wave velocity, density; or P-wave impedance, S-wave impedance, density. For example, the prestack elastic wave impedance inversion uses the following formula to obtain P-wave velocity, S-wave velocity, and density:

[0095] Where i represents the layer number. EI(θ) represents the elastic wave impedance of the formation when the incident angle is θ. EI (θ) represents the reflection coefficient when the incident angle is θ.

[0096]

[0097] Where: k = (Vs / Vp) 2

[0098] Prestack synchronous inversion can use the following Fatti formula to obtain P-wave impedance, S-wave impedance, and density:

[0099]

[0100] Generally, part of the superimposed data is used as the observation data, and the objective function is constructed using the above reflection coefficient formula, wavelet and observation data, and then the optimization algorithm is used to find the optimal solution that minimizes the objective function value as the inversion result. Thus, the elastic parameter model after inversion is obtained.

[0101] In step S50, the elastic parameter model obtained by prestack inversion, the density, bulk modulus and shear modulus of each mineral component in the reservoir, and the rock physics relationship (i.e., the elastic parameters of the rock, the density, bulk modulus and shear modulus of each mineral component) are used to calculate the reservoir parameters such as the mineral content (volume percentage), porosity, and fluid (oil, gas and water) saturation of the reservoir. This allows the characterization of the lithology, morphology, physical properties and oil and gas content of the reservoir. For example, the longitudinal wave velocity V of the reservoir rock is obtained by inversion. P_b , shear wave velocity V S_b , density ρ b Later, the shear modulus μ of the reservoir rock can be calculated b and bulk modulus K b Density of minerals and fluids obtained in step S3: ρ Q , ρ F , ρ C , ρ W , ρ O , ρ G , the bulk modulus K of the mineral Q , K F , K C and shear modulus μ Q , μ F , μ C Bulk modulus K of the fluid w , K o , K G , to obtain the porosity φ, the volume content of the mineral components: f Q 、f C and fluid saturation: f w 、f hydr . This enables the characterization of the reservoir's lithology, morphology, physical properties and oil and gas content.

[0102] For example, suppose the stratum is a sandstone-mudstone section, that is, it contains only two minerals, and the fluid in the pores is two-phase saturated, namely water and oil and gas. Then the density of oil and gas is ρ0, ρ G Merge into: hydr , the bulk modulus K of oil and gas o , K G Merge into K hydr , and also the volume component of oil and gas f o , f GThe merger is denoted as f hydr Then, the three elastic parameters V obtained by inversion are P_b 、V S_b , b And the following three equations:

[0103]

[0104]

[0105]

[0106] in

[0107] K V_0 =f Q ·K Q +f C ·K C , K V__fl =f w ·K w +f hydr ·K hydr

[0108]

[0109] Then there are two constraint equations:

[0110] f Q +f C =1

[0111] f w +f hydr =1

[0112] At each depth point (layer), the above five equations can be used to solve the unknown variables contained in the equations: porosity φ, volume content of mineral components: f Q 、f C and fluid saturation: f w 、f hydr . This enables the characterization of the reservoir's lithology, morphology, physical properties and oil and gas content.

[0113] The present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores at least one computer-executable program, and when the at least one program is executed by the computer, the computer executes the steps in any one of the above-mentioned methods.

[0114] like Figure 2 As shown, a reservoir parameter direct inversion system comprises:

[0115] The first calculation module 10 is used to establish a rock physics model and calculate the density, bulk modulus, and shear modulus of minerals and fluids in the reservoir; more specifically, the first calculation module 10 is used to implement the above step S10, which will not be repeated here.

[0116] The reservoir parameter model building module 20 is connected to the first calculation module 10 and is used to extract seismic wavelets and build a reservoir parameter model; more specifically, the reservoir parameter model building module 20 is used to implement the above step S20, which will not be repeated here.

[0117] The elastic parameter model calculation module 30 is connected to the reservoir parameter model establishment module 20, and is used to calculate the initial elastic parameter model of the reservoir according to the density, bulk modulus and shear modulus of the minerals and fluids in the reservoir and the reservoir parameter model. More specifically, the elastic parameter model calculation module 30 is used to implement the above step S30, which will not be described in detail here.

[0118] The inversion module 40 is connected to the elastic parameter model calculation module 30 and is used to perform prestack inversion using the initial elastic parameter model to obtain an inverted elastic parameter model. More specifically, the inversion module 40 is used to implement the above step S40, which will not be described in detail herein.

[0119] The second calculation module 50 is connected to the inversion module 40 and is used to describe the lithology, morphology, physical properties and hydrocarbon content of the reservoir through the elastic parameter model after inversion and the density, bulk modulus and shear modulus of the mineral and fluid. More specifically, the second calculation module 50 is used to implement the above step S50, which will not be described in detail here.

[0120] The present invention uses seismic pre-stack data and logging interpretation data for direct inversion to obtain reservoir lithology, porosity, oil and gas content and saturation. The present invention uses a small amount of data and is simple to calculate, and can directly predict reservoir lithology, reservoir physical properties and oil and gas content.

[0121] The preferred embodiments of the present invention are described above with reference to the accompanying drawings. A person skilled in the art may implement the present invention in a variety of variations without departing from the scope and essence of the present invention. For example, a feature shown or described as part of one embodiment may be used in another embodiment to obtain another embodiment. The above are only preferred feasible embodiments of the present invention, and do not limit the scope of rights of the present invention. Any equivalent changes made using the contents of the present specification and the accompanying drawings are included in the scope of rights of the present invention.

Claims

1. A reservoir parameter direct inversion method, characterized in that: include: S10, establishing a rock physics model and calculating the density, bulk modulus and shear modulus of minerals and fluids in the reservoir; S20, extracting seismic wavelets and establishing a reservoir parameter model; S30, calculating an initial elastic parameter model of the reservoir according to the density, bulk modulus and shear modulus of the minerals and fluids in the reservoir and the reservoir parameter model; S40, performing prestack inversion using the initial elastic parameter model to obtain an elastic parameter model after inversion; S50, characterizing the lithology, morphology, physical properties and oil and gas content of the reservoir through the inverted elastic parameter model and the density, bulk modulus and shear modulus of the mineral and fluid.

2. The reservoir parameter direct inversion method according to claim 1, characterized in that: The step S10 comprises: S11. Determine the approximate type of reservoir based on the geological knowledge of the target layer in the target exploration area and the logging interpretation results; S12. Select the rock physical relationship between elastic parameters and reservoir parameters.

3. The reservoir parameter direct inversion method according to claim 2, characterized in that: The step S12 comprises: The Voigt-Reuss-Hill formula, Wood formula, and Gassmann formula are used to calculate the density, bulk modulus, and shear modulus of minerals and fluids in the reservoir; The relationship between P-wave and S-wave velocities is statistically calculated from the P-wave and S-wave logging curves.

4. The reservoir parameter direct inversion method according to claim 1, characterized in that: The step S20 comprises: Using the time-depth relationship between well seismic data, we can obtain the longitudinal and transverse wave velocity curves, density curves and reservoir parameter curves at the seismic scale. The corresponding bulk modulus and shear modulus of the well logging are calculated from the longitudinal and shear wave velocities and density.

5. The reservoir parameter direct inversion method according to claim 1, characterized in that: In step S30, the reservoir parameter model is characterized by reservoir parameters, and the reservoir parameters are continuous values ​​between 0 and 1.

6. The reservoir parameter direct inversion method according to claim 1, characterized in that: The step S40 includes: constructing an objective function using the reflection coefficient formula, wavelet and observation data, and using an optimization algorithm to find the optimal solution that minimizes the objective function value as the inversion result, thereby obtaining an elastic parameter model after inversion.

7. The reservoir parameter direct inversion method according to claim 1, characterized in that: The step S50 includes: using the elastic parameter model obtained by prestack inversion, the density, bulk modulus and shear modulus of each mineral component in the reservoir, and using rock physical relationships to calculate the reservoir mineral content, porosity, and fluid saturation, so as to characterize the lithology, morphology, physical properties and oil and gas content of the reservoir.

8. A reservoir parameter direct inversion system, characterized in that: include: The first calculation module is used to establish a rock physics model and calculate the density, bulk modulus, and shear modulus of minerals and fluids in the reservoir; A reservoir parameter model building module is used to extract seismic wavelets and build a reservoir parameter model; An elastic parameter model calculation module, used to calculate an initial elastic parameter model of the reservoir according to the density, bulk modulus and shear modulus of the minerals and fluids in the reservoir and the reservoir parameter model; An inversion module, used for performing prestack inversion using the initial elastic parameter model to obtain an inverted elastic parameter model; The second calculation module is used to describe the lithology, morphology, physical properties and oil and gas content of the reservoir through the inverted elastic parameter model and the density, bulk modulus and shear modulus of the mineral and fluid.

9. The reservoir parameter direct inversion system according to claim 8, characterized in that: The reservoir parameter model is characterized by reservoir parameters, and the reservoir parameters are continuous values ​​between 0 and 1.

10. A computer-readable storage medium storing at least one computer-executable program, characterized in that: When the at least one program is executed by the computer, the computer executes the steps of the method according to any one of claims 1 to 7.

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