Reservoir volume fracturing effect evaluation method and system, electronic equipment and storage medium

Abstract

The invention belongs to the technical field of petroleum and natural gas engineering, and provides a reservoir volume fracturing effect evaluation method and system, electronic equipment and a storage medium, and the method comprises the following steps: obtaining single mineral content, actual Young modulus and single mineral Young modulus in a rock sample; calculating the mineral dispersity, Young modulus difference degree and mineral adhesion degree of the rock sample according to the single mineral Young modulus of the rock sample in combination with the single mineral content and the actual Young modulus; calculating the fracture potential degree of the reservoir where the rock sample is located according to the Young modulus difference degree and the mineral adhesion degree; according to the mineral dispersity and the fracture potential degree of the reservoir, the fracture network complex index of the reservoir is calculated, and the volume fracturing effect of the reservoir is evaluated according to the fracture network complex index. The reservoir volume fracturing effect is evaluated by comprehensively considering the complexity of the natural fracture and the complexity of the fracture network formed by reservoir transformation, and the precision and accuracy of fracturing effect evaluation are improved.

Description

Technical Field

[0001] This disclosure belongs to the field of oil and gas engineering technology, and particularly relates to a method, system, electronic equipment and storage medium for evaluating the effect of reservoir volumetric fracturing. Background Technology

[0002] It is extremely rich in tight oil and gas resources with huge development potential, making it a strategic alternative to oil and a major force for increasing oil and gas reserves and production in the future.

[0003] Large-scale, segmented, multi-cluster volumetric fracturing in horizontal wells is a key technology for the efficient development of unconventional tight oil and gas, accelerating the pace of reserve and production increases in various oilfields. However, tight gas reservoirs are highly heterogeneous, and core sampling from horizontal wells confirms extremely uneven distribution of sand bodies in both longitudinal and transverse directions. Furthermore, due to previous tectonic movements, reservoirs typically develop natural fractures, but the accuracy of current testing methods for their occurrence and distribution falls far short of the requirements for quantitative characterization. This leads to extremely complex competition for fracture initiation and propagation among multiple fracture clusters, with unclear control mechanisms, posing a significant challenge to the evaluation of fracturing effectiveness.

[0004] Despite the adoption of advanced fracturing technology, the lack of an optimized parameter system that matches reservoir characteristics has led to significant differences in the stimulation effects of different horizontal wells within the same block, resulting in underutilization of reservoir productivity. Furthermore, numerous and complex factors influence the effectiveness of unconventional tight gas volumetric fracturing.

[0005] The existing technical solutions to the above problems are as follows: (1) In the journal Petroleum and Natural Gas Geology, Issue 5, 2021, Jiao Fangzheng published "Research on Fracture Network Sweep in Shale Oil in Ordos Basin and Its Application in Volume Development". The article proposes a subdivided volumetric fracture network sweep volume calculation model, and uses the multiple linear regression method to establish the relationship between key geological engineering parameters and microseismic cover volume. The relationship is further corrected using actual mine production data, and an empirical formula for quantitative characterization of fracture network sweep volume is established. Then, a correlation chart between it and production capacity is drawn to provide guidance for the optimization of volumetric fracturing engineering parameters. (2) Patent No.: CN201810759973.1, Patent Name: A Comprehensive Evaluation Method for Completion Efficiency of Multi-stage Fracturing Horizontal Wells in Tight Oil and Gas Reservoirs. This method first uses the analytic hierarchy process (AHP) to comprehensively consider the unique reservoir physical parameters and hydraulic fracturing construction parameters of multi-stage fractured horizontal wells, and establishes a multi-level evaluation system for factors affecting completion efficiency. Secondly, it uses the grey relational analysis method to calculate the weight coefficients of each influencing factor with the horizontal well production capacity as the target, and sorts each influencing factor according to the size of the weight coefficient to clarify the main controlling factors affecting completion efficiency. Finally, it calculates the comprehensive evaluation factor of completion efficiency based on the weight coefficients, and sorts and classifies them. The higher the comprehensive evaluation factor, the higher the completion efficiency and the better the reservoir stimulation effect, thereby achieving the purpose of comprehensive evaluation of the completion efficiency of multi-stage fractured horizontal wells in tight oil and gas reservoirs. (3) In the journal Special Oil and Gas Reservoirs, in issue 2 of 2015, Wang Rui published an analysis of the influencing factors of volumetric fracturing effect of horizontal wells in tight oil reservoirs. The article selected seven factors affecting the volumetric fracturing effect of horizontal wells in tight oil test areas, analyzed the magnitude and causes of the influence of each factor on oil production at different post-fracturing periods, and proposed an improved process. This method takes into account reservoir physical parameters and fracturing operation parameters, but does not take into account key production dynamic parameters such as formation pressure.

[0006] The existing technologies mentioned above all rely on comprehensive evaluation of fracturing effects based on geological and engineering parameters after volumetric fracturing. However, for highly heterogeneous reservoirs, the simulated evaluation results often deviate significantly from actual results. Furthermore, none of these technologies effectively address the evaluation of fracturing effects in key reservoir characteristics, such as the degree of natural fracture development and the potential for forming complex fracture networks in volumetric fracturing, which significantly impact single-well production in unconventional tight gas. Therefore, it is necessary to propose new methods for evaluating the effectiveness of tight gas volumetric fracturing to provide crucial theoretical support for the efficient development of unconventional resources. Summary of the Invention

[0007] To address the aforementioned issues, this disclosure provides a method and system for evaluating the effectiveness of reservoir volumetric fracturing. It comprehensively considers both the complexity of natural fractures and the complexity of the fracture network formed by reservoir stimulation to evaluate the effectiveness of reservoir volumetric fracturing, thereby improving the precision and accuracy of fracturing effectiveness evaluation.

[0008] This application is achieved through the following technical solution:

[0009] Methods for evaluating the effectiveness of reservoir volumetric fracturing include:

[0010] Obtain the content of single minerals, actual Young's modulus, and Young's modulus of single minerals in the rock sample;

[0011] Based on the Young's modulus of a single mineral in the rock sample, combined with the content of the single mineral and the actual Young's modulus, the mineral dispersion, Young's modulus difference, and mineral adhesion of the rock sample are calculated.

[0012] The fracture potential of the reservoir where the rock sample is located is calculated based on Young's modulus difference and mineral adhesion.

[0013] Based on mineral dispersion and reservoir fracture potential, the fracture network complexity index of the reservoir is calculated, and the reservoir volumetric fracturing effect is evaluated based on the fracture network complexity index.

[0014] Furthermore, before obtaining the single mineral content, actual Young's modulus, and theoretical Young's modulus of the rock sample, the process also includes drying the rock sample to constant weight.

[0015] Furthermore, based on the Young's modulus of a single mineral in the rock sample, combined with the content of that single mineral and the actual Young's modulus, the mineral dispersion of the rock sample is calculated, including:

[0016]

[0017] In the formula, Ew is the optimal dispersion, dimensionless; Ei is the Young's modulus of a single mineral, MPa; ki is the content of a single mineral, %; n is the number of types of single minerals in the rock sample; Ec is the actual Young's modulus, MPa; and Ef is the mineral dispersion of the rock sample, dimensionless.

[0018] Furthermore, based on the Young's modulus of the rock sample, combined with the content of the single mineral and the actual Young's modulus, the Young's modulus discrepancy of the rock sample is calculated, including:

[0019] Sort the Young's moduli of individual minerals in ascending order, and assign subscripts to the Young's moduli of individual minerals according to the sorting. The larger the Young's modulus of an individual mineral, the larger its subscript. Calculate the Young's modulus variation of the rock samples, including:

[0020]

[0021] In the formula, Eij represents the Young's modulus difference of the rock sample, which is dimensionless; Ei and Ej represent the Young's modulus of a single mineral, where the Young's modulus of a single mineral with subscript i is greater than the Young's modulus of a single mineral with subscript j, in MPa.

[0022] Furthermore, based on the Young's modulus of the single mineral in the rock sample, combined with the content of the single mineral and the actual Young's modulus, the mineral adhesion of the rock sample is calculated, including:

[0023] k ij =ki k j (i≥2,j <i)

[0024] In the formula, kij represents the mineral adhesion degree of the rock sample, which is dimensionless; ki and kj represent the content of a single mineral, where the Young's modulus of a single mineral with subscript i is greater than that of a single mineral with subscript j, and is dimensionless.

[0025] Furthermore, the fracture potential of the reservoir where the rock sample is located is calculated based on the Young's modulus difference and mineral adhesion, including:

[0026] The fracture potential of rock samples is calculated based on Young's modulus difference and mineral adhesion, including:

[0027] G ij =E ij k ij (i≥2,j <i)

[0028] In the formula, Gij represents the fracture potential of the rock sample, which is dimensionless;

[0029] Based on the fracture potential of the rock sample, the fracture potential of the reservoir containing the rock sample is calculated as follows:

[0030]

[0031] In the formula, Gz represents the fracture potential of the reservoir, which is dimensionless.

[0032] Furthermore, based on mineral dispersion and reservoir fracture potential, the reservoir fracture network complexity index is calculated, and the reservoir volumetric fracturing effect is evaluated based on the fracture network complexity index, including:

[0033] B Q =G z E f

[0034] In the formula, BQ is the mesh complexity index, which is dimensionless;

[0035] The higher the fracture network complexity index (BQ), the better the reservoir volume fracturing effect.

[0036] Reservoir volume pressure effect evaluation system, the system includes,

[0037] The acquisition module is used to acquire the content of single minerals, the actual Young's modulus, and the Young's modulus of single minerals in rock samples.

[0038] The rock sample calculation module is used to calculate the mineral dispersion, Young's modulus difference, and mineral adhesion of the rock sample based on the Young's modulus of the single mineral, combined with the single mineral content and the actual Young's modulus.

[0039] The reservoir calculation module calculates the fracture potential of the reservoir where the rock sample is located based on the Young's modulus difference and mineral adhesion; and calculates the fracture network complexity index of the reservoir based on mineral dispersion and the fracture potential of the reservoir.

[0040] The effect evaluation module evaluates the reservoir volume fracturing effect based on the fracture network complexity index.

[0041] Compared with the prior art, this disclosure has the following advantages:

[0042] The evaluation of reservoir volumetric fracturing effect takes into account both the complexity of natural fractures and the complexity of fracture networks formed by reservoir stimulation, thereby improving the accuracy and precision of fracturing effect evaluation.

[0043] Other features and advantages of this disclosure will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the disclosure. The objects and other advantages of this disclosure may be realized and obtained by means of the structures pointed out in the description, claims and drawings. Attached Figure Description

[0044] To more clearly illustrate the technical solutions in the embodiments of this disclosure or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this disclosure. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0045] Figure 1 A schematic diagram of the process for evaluating the effectiveness of reservoir volumetric fracturing is shown.

[0046] Figure 2 A schematic diagram of the functional flow of a reservoir volume fracturing effect evaluation system according to an embodiment of the present disclosure is shown;

[0047] Figure 3 A mineral dispersion comparison diagram is shown according to an embodiment of this disclosure;

[0048] Figure 4 A comparison chart of stitch complexity indices according to embodiments of this disclosure is shown. Detailed Implementation

[0049] To make the objectives, technical solutions, and advantages of the embodiments of this disclosure clearer, the technical solutions of the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this disclosure, and not all embodiments. Based on the embodiments of this disclosure, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this disclosure.

[0050] Terminology Explanation:

[0051] Constant weight: In geological and materials science experiments, a sample is dried at a certain temperature until it reaches "constant weight," meaning that the sample's weight no longer changes significantly during continuous weighing. Specifically, "constant weight" means that the sample has completely lost its free water and some bound water, reaching a state of stable moisture content.

[0052] X-ray diffractometer: Based on the diffraction phenomenon produced by the interaction of X-rays with crystals, it can provide information about the atomic arrangement inside the material.

[0053] A triaxial rock mechanics testing system is a device used in rock mechanics experiments that applies pressure in different directions to rock samples, simulating the stress conditions of rocks in their natural environment. The main feature of this system is its ability to simultaneously apply axial loads (along the length of the rock sample) and confining pressures (lateral pressures acting around the rock sample). This testing environment allows researchers to study the mechanical properties of rocks under complex stress states under controlled conditions, such as compressive strength, shear strength, elastic modulus (including Young's modulus), and Poisson's ratio.

[0054] Young's modulus, also known as tensile modulus or elastic modulus, is a physical quantity used to measure a material's resistance to tensile or compressive deformation. Young's modulus is an inherent property of a material, reflecting its stiffness. For rocks, a higher Young's modulus means the rock is harder and deforms less under the same stress.

[0055] Example 1

[0056] This disclosure discloses a method for evaluating the volumetric fracturing effect of tight gas reservoirs, comprising:

[0057] Rock sample preparation: Take 3 rocks from the tight gas reservoir where the horizontal well is located, prepare rock samples with a diameter of 2.5 cm and a length of 5 cm, assign them the rock sample numbers S1, S2 and S3, and dry them in a 100℃ oven until constant weight.

[0058] Obtaining rock sample parameters: The content of single minerals ki in the rock sample was calculated using an X-ray diffractometer, and the actual Young's modulus Ec of the rock sample was obtained using a triaxial rock mechanics testing system. Six minerals were selected for testing, and the value of n was set to 6. The basic parameters of single minerals were obtained, as shown in Table 1.

[0059] Table 1. Basic parameters of single minerals in rock samples

[0060]

[0061] The Young's modulus of six single minerals was obtained, and the single minerals were sorted according to the size of the Young's modulus, as shown in Table 2.

[0062] In this embodiment, the Young's modulus of a single mineral is the theoretical Young's modulus of a single mineral in the rock sample.

[0063] Table 2 Young's Modulus of Single Minerals

[0064] Single mineral composition Young's modulus of a single mineral (MPa) Pyrite 283056.36 dolomite 105309.01 quartz 95942.54 calcite 78010.81 Feldspar 64838.72 clay 21914.15

[0065] Based on the Young's modulus of the single minerals, they are ordered as follows: pyrite E6, dolomite E5, quartz E4, calcite E3, feldspar E2, and clay minerals E1.

[0066] The assemblage state of rock samples is evaluated based on the Young's modulus of each individual mineral. A state where individual minerals are not dispersed—that is, where minerals such as quartz and feldspar each occupy a separate area without mixing with other minerals—is called an undispersed state. Conversely, a state where each mineral uniformly intrudes into other minerals is called a fully dispersed state. The Young's modulus of minerals in near-fully dispersed states is calculated using the formula... Calculate the optimal dispersion Ew of the rock sample; when the actual Young's modulus Ec of the rock sample is close to or greater than the optimal dispersion Ew, the mineral dispersion inside the rock sample is the most uniform.

[0067] Then the formula The ore dispersion of the rock sample was calculated to evaluate the complexity of the natural fractures. A higher ore dispersion indicates a greater complexity of the natural fractures in the rock sample, as shown in Table 3. Figure 1 As shown.

[0068] It should be noted that when the single mineral is dispersed too uniformly inside the rock sample, a new mixed mineral will be formed, causing the actual Young's modulus of the rock sample to be greater than the optimal dispersion Ew, resulting in the mineral dispersion Ef being greater than 1. This is normal.

[0069] Table 3 Mineral Dispersion of Rock Samples

[0070]

[0071] Using formula The Young's modulus difference of the rock sample is calculated. The Young's modulus difference is the difference in Young's modulus between each pair of individual minerals. The larger the Young's modulus difference, the more fragile the bond between the two individual minerals is under stress. As shown in Table 4, the vertical column is E5 and the horizontal column is E6, which represents the difference in Young's modulus between mineral E6 and mineral E5.

[0072] Table 4. Difference in Young's Modulus of Single Minerals

[0073]

[0074] Using the formula k ij = k i k j (i≥2, j < i) to calculate the mineral adhesion degree of the rock sample, and the mineral adhesion degree is the adhesion degree between pairwise different single minerals. And using the formula G ij = E ij k ij (i≥2, j < i) to combine the Young's modulus difference degree and the mineral adhesion degree to calculate the crack potential degree between single minerals. The calculation results are shown in Tables 5, 6, and 7. In the tables, the vertical column is E5 and the horizontal column is E6, which represents the crack potential degree between mineral E6 and mineral E5.

[0075] Table 5 Single Mineral Crack Potential Degree Table of Rock Sample S1

[0076] Rock sample S1 E6 E5 E4 E3 E2 E1 E6 — 0.0032 0.0018 0.0039 0.0040 0.052 E5 — — 0.0017 0.0100 0.0141 0.3185 E4 — — — 0.0031 0.0052 0.1338 E3 — — — — 0.0036 0.1696 E2 — — — — — 0.1035 E1 — — — — — —

[0077] Table 6 Single Mineral Crack Potential Degree Table of Rock Sample S2

[0078]

[0079] Table 7 Single Mineral Crack Potential Degree Table of Rock Sample S3

[0080] Rock sample S3 E6 E5 E4 E3 E2 E1 E6 — 0.0068 0.0043 0.0058 0.0121 0.0906 E5 — — 0.0022 0.0077 0.0223 0.2896 E4 — — — 0.0028 0.0095 0.1413 E3 — — — — 0.0040 0.1074 E2 — — — — — 0.1341 E1 — — — — — —

[0081] According to the formula calculate the crack potential degree of the reservoir where the rock sample is located. For example, the reservoir crack potential degree of rock sample S1 is the sum of the data in Table 5, and the calculation methods for rock samples S2 and S3 are the same.

[0082] According to the formula B Q = G z E f Combine the mineral dispersion degree of the rock sample and the crack potential degree of the reservoir where the rock sample is located to calculate the fracture network complexity index of the reservoir where the rock sample is located, as shown in Table 8 and Appendix Figure 2 as shown.

[0083] Table 8 Fracture Network Complexity Index Table of Reservoirs Where Rock Samples S1 - S3 are Located

[0084]

[0085] Based on the above data, the volumetric fracturing effect of the reservoirs where the rock samples are located is evaluated. The larger the fracture network complexity index, the better the fracturing effect. The fracture network complexity indices of rock samples S1, S2, and S3 are 0.9025, 0.8489, and 0.7901, respectively. The volumetric fracturing effect of the reservoirs corresponding to the rock samples is ranked as follows: rock sample S1 > rock sample S2 > rock sample S3.

[0086] Based on the above method, this disclosure also provides a reservoir volume pressure effect evaluation system corresponding to the above method, such as... Figure 2 As shown, the reservoir volume pressure effect evaluation device includes,

[0087] The acquisition module is used to acquire the content of single minerals, the actual Young's modulus, and the Young's modulus of single minerals in rock samples.

[0088] The rock sample calculation module is used to calculate the mineral dispersion, Young's modulus difference, and mineral adhesion of the rock sample based on the Young's modulus of a single mineral, the content of the single mineral, and the actual Young's modulus.

[0089] The reservoir calculation module calculates the fracture potential of the reservoir where the rock sample is located based on the Young's modulus difference and the mineral adhesion; and calculates the fracture network complexity index of the reservoir based on the mineral dispersion and the fracture potential of the reservoir.

[0090] The effect evaluation module evaluates the reservoir volume fracturing effect based on the fracture network complexity index.

[0091] Based on the same inventive concept as the above disclosure, this disclosure also provides an electronic device. The electronic device of this disclosure includes at least one processor electrically connected to the processor and at least one memory electrically connected to the processor. The memory stores instructions executable by the at least one processor, which, when executed, enable the at least one processor to perform the method described above.

[0092] It should be noted that the electrical connection between the above-mentioned units does not necessarily mean the connection between lines. The indirect connection method can be applied to the embodiments of this disclosure as long as it achieves the purpose of this disclosure.

[0093] Based on the same inventive concept, this disclosure also provides a computer storage medium storing a computer program that, when executed by a processor, implements the above-described method for evaluating the effect of reservoir volume pressure.

[0094] Although the present disclosure has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present disclosure.

Claims

1. A method for evaluating the effectiveness of reservoir volumetric fracturing, characterized in that, The method includes, Obtain the content of single minerals, actual Young's modulus, and Young's modulus of single minerals in the rock sample; Based on the Young's modulus of the single mineral in the rock sample, combined with the content of the single mineral and the actual Young's modulus, the mineral dispersion, Young's modulus difference, and mineral adhesion of the rock sample are calculated. The fracture potential of the reservoir where the rock sample is located is calculated based on the Young's modulus difference and the mineral adhesion; the fracture network complexity index of the reservoir is calculated based on the mineral dispersion and the fracture potential of the reservoir. The reservoir volumetric fracturing effect is evaluated based on the fracture network complexity index.

2. The method according to claim 1, characterized in that, Before obtaining the single mineral content, actual Young's modulus, and single mineral Young's modulus in the rock sample, the method further includes drying the rock sample to constant weight.

3. The method according to claim 1, characterized in that, Based on the Young's modulus of the single mineral in the rock sample, combined with the content of the single mineral and the actual Young's modulus, the mineral dispersion of the rock sample is calculated, including: Where: Ew is the optimal dispersion, dimensionless; Ei is the Young's modulus of the single mineral, MPa; ki is the content of the single mineral, %; n is the number of types of single minerals in the rock sample; Ec is the actual Young's modulus, MPa; Ef is the mineral dispersion of the rock sample, dimensionless.

4. The method according to claim 3, characterized in that, Based on the Young's modulus of the single mineral in the rock sample, combined with the content of the single mineral and the actual Young's modulus, the Young's modulus difference of the rock sample is calculated, including, The Young's moduli of the individual minerals are sorted in ascending order, and subscripts for the Young's moduli are set according to the sorting, with larger subscripts for larger Young's moduli. The Young's modulus difference of the rock samples is calculated, including: Where: Eij is the Young's modulus difference of the rock sample, dimensionless; Ei and Ej are the Young's modulus of a single mineral, where the Young's modulus of a single mineral with subscript i is greater than the Young's modulus of a single mineral with subscript j, in MPa.

5. The method according to claim 4, characterized in that, Based on the Young's modulus of the single mineral in the rock sample, combined with the content of the single mineral and the actual Young's modulus, the mineral adhesion of the rock sample is calculated, including: k ij =k i k j (i≥2,j<i), Where: kij represents the mineral adhesion of the rock sample, which is dimensionless; ki and kj represent the content of a single mineral, where the Young's modulus of a single mineral with subscript i is greater than that of a single mineral with subscript j, which is dimensionless.

6. The method according to claim 5, characterized in that, The fracture potential of the reservoir containing the rock sample is calculated based on the Young's modulus difference and the mineral adhesion, including: The fracture potential of the rock sample is calculated based on the Young's modulus difference and the mineral adhesion, including: G ij =E ij k ij (i≥2,j <i), Where: Gij is the fracture potential of the rock sample, which is dimensionless; Based on the fracture potential of the rock sample, the fracture potential of the reservoir containing the rock sample is calculated as follows: Wherein: Gz is the fracture potential of the reservoir, which is dimensionless.

7. The method according to claim 6, characterized in that, Based on the mineral dispersion and reservoir fracture potential, the fracture network complexity index of the reservoir is calculated. The reservoir volumetric fracturing effect is then evaluated based on the fracture network complexity index, including: B Q =G z E f , Among them: B Q The complexity index of the sewing mesh is dimensionless. Its stitching complexity index B Q The larger the reservoir volume, the better the fracturing effect.

8. A reservoir volume pressure effect evaluation system, characterized in that, The system includes, The acquisition module is used to acquire the content of single minerals, the actual Young's modulus, and the Young's modulus of single minerals in rock samples. The rock sample parameter calculation module is used to calculate the mineral dispersion, Young's modulus difference, and mineral adhesion of the rock sample based on the Young's modulus of a single mineral, the content of the single mineral, and the actual Young's modulus. The reservoir parameter calculation module calculates the fracture potential of the reservoir where the rock sample is located based on the Young's modulus difference and the mineral adhesion; and calculates the fracture network complexity index of the reservoir based on the mineral dispersion and the fracture potential of the reservoir. The effect evaluation module evaluates the reservoir volume fracturing effect based on the fracture network complexity index.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the method as described in any one of claims 1-7.

10. A computer storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the method as described in any one of claims 1-7.

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