A method and apparatus for determining reservoir recovery

Abstract

The application provides a reservoir recovery rate determination method and device, and the method comprises the following steps: determining a fractal dimension of a target reservoir; determining a volume fraction of pores with a pore diameter less than a preset pore diameter threshold in a core sample of the target reservoir; determining a T2 cutoff value of the target reservoir according to the fractal dimension of the target reservoir and the volume fraction; and determining a contribution degree of imbibition and displacement to the recovery rate of the target reservoir according to the T2 cutoff value of the target reservoir. The T2 cutoff value of the target reservoir is determined through the above scheme, and the nuclear magnetic resonance spectrum is divided based on the determined T2 cutoff value, so that the contribution degrees of the production capacities of different oil production methods can be accurately determined, thereby solving the technical problem that the existing technology cannot quantitatively characterize imbibition and displacement, and achieving the technical effect of quantitatively characterizing imbibition and displacement.

Description

Technical Field

[0001] This application belongs to the field of oil and gas extraction technology, and in particular relates to a method and apparatus for determining reservoir recovery rate. Background Technology

[0002] Reservoir stimulation technology based on large-scale volumetric fracturing in horizontal wells can create a large number of artificial fractures, which can effectively achieve initial-scale recovery of tight oil / shale oil. However, since tight oil / shale oil reservoirs are mostly terrestrial sedimentary, most reservoirs mainly develop micro- and nano-scale pore-throat structures, and multi-scale natural fractures are well-developed. Conventional water injection to replenish formation energy is prone to water channeling along the fractures, resulting in low recovery rates of the large amount of remaining oil in the matrix.

[0003] In actual oilfield development, the development effect can be improved by combining capillary pressure adsorption with pressure differential displacement. That is, by effectively utilizing the adsorption and displacement effects between matrix fractures, the development effect of tight oil / shale oil can be improved. However, in the current water injection development process, adsorption and displacement effects cannot be quantitatively characterized.

[0004] Regarding how to quantitatively characterize osmosis and displacement, the above-mentioned solutions are currently effective. Summary of the Invention

[0005] The purpose of this application is to provide a method and apparatus for determining reservoir recovery, which can achieve quantitative characterization of percolation and displacement.

[0006] This application provides a method for quantitatively characterizing osmosis and displacement as follows:

[0007] A method for determining reservoir recovery rate, the method comprising:

[0008] Determine the fractal dimension of the target reservoir;

[0009] Determine the volume fraction of pores with a pore size smaller than a preset pore size threshold in the core sample of the target reservoir;

[0010] The T2 cutoff value of the target reservoir is determined based on the fractal dimension and the volume fraction of the target reservoir.

[0011] Based on the T2 cutoff value of the target reservoir, determine the contribution of infiltration and displacement to the recovery rate of the target reservoir.

[0012] In one implementation, determining the T2 cutoff value of the target reservoir based on the fractal dimension and the volume fraction includes:

[0013] The T2 cutoff value of the target reservoir is calculated using the following formula:

[0014] lgS av = (3-D)lgT2+(D-3)lgT 2max

[0015] Among them, S av T represents the volume fraction of pores in the core sample with a pore size smaller than a preset pore size threshold, D represents the fractal dimension of the target reservoir, and T represents the volume fraction of pores with a pore size smaller than a preset pore size threshold in the core sample. 2max This represents the maximum T2 value, where T2 represents the T2 cutoff value of the target reservoir.

[0016] In one embodiment, determining the volume fraction of pores with a pore size smaller than a preset pore size threshold in a core sample of the target reservoir includes:

[0017] The cumulative volume of pores with a diameter smaller than the preset pore diameter threshold in the core sample is determined according to the following formula:

[0018]

[0019] Among them, V r This represents the cumulative volume of pores with a half-aperture diameter smaller than the preset pore diameter threshold, where A” is a proportionality constant and r min Indicates the minimum pore radius; r max Let represent the maximum pore radius, A represent the fractal factor, f(r) represent the density function of the pore radius, and D represent the fractal dimension.

[0020] The cumulative volume of pores in the core sample is determined using the following formula:

[0021]

[0022] Among them, V t r represents the cumulative pore volume in the core sample. max Indicates the maximum pore radius;

[0023] The volume fraction of pores with a pore size smaller than a preset pore size threshold in the core sample of the target reservoir is determined using the following formula:

[0024]

[0025] Among them, S av This represents the volume fraction of pores in the core sample of the target reservoir whose pore size is smaller than a preset pore size threshold.

[0026] In one embodiment, determining the volume fraction of pores with a pore size smaller than a preset pore size threshold in a core sample of the target reservoir includes:

[0027] The volume fraction of pores with a pore size smaller than a preset pore size threshold in the core sample of the target reservoir is determined using the following formula:

[0028]

[0029] Among them, S av This represents the volume fraction of pores with a pore size smaller than a preset pore size threshold in the core sample of the target reservoir, where r represents the preset pore size threshold. max V represents the maximum pore radius, D represents the fractal dimension, and V represents the maximum pore radius. r V represents the cumulative volume of pores with a half-aperture smaller than the preset aperture threshold. t This represents the cumulative volume of pores in the core sample.

[0030] In one implementation, the contribution of adsorption and displacement to the recovery rate of the target reservoir is determined based on the T2 cutoff value of the target reservoir, including:

[0031] Obtain the nuclear magnetic resonance spectrum of the target reservoir;

[0032] Based on the T2 cutoff value of the target reservoir, the nuclear magnetic resonance spectrum is segmented, wherein the segmentation is performed in the manner of percolation and oil displacement on the left and displacement and oil displacement on the right.

[0033] Based on the segmentation results, determine the recovery rate of the seepage effect and the recovery rate of the displacement effect;

[0034] The contribution of percolation and displacement to the recovery rate of the target reservoir is determined based on the recovery rates from percolation and displacement.

[0035] In one implementation, determining the fractal dimension of the target reservoir includes:

[0036] To obtain the critical point of oil recovery mode based on the difference in pore structure in the target reservoir;

[0037] The critical value corresponding to the critical point is taken as the fractal dimension of the target reservoir.

[0038] An apparatus for determining reservoir recovery rate, comprising:

[0039] The first determining module is used to determine the fractal dimension of the target reservoir;

[0040] The second determining module is used to determine the volume fraction of pores with a pore size smaller than a preset pore size threshold in the core sample of the target reservoir.

[0041] The third determining module is used to determine the T2 cutoff value of the target reservoir based on the fractal dimension and the volume fraction of the target reservoir;

[0042] The fourth determining module is used to determine the contribution of percolation and displacement to the recovery rate of the target reservoir based on the T2 cutoff value of the target reservoir.

[0043] An electronic device includes a processor and a memory for storing processor-executable instructions, wherein the processor, when executing the instructions, implements the steps of the method described above.

[0044] A computer-readable storage medium having a computer program / instructions stored thereon, which, when executed by a processor, implement the steps of the above-described method.

[0045] A computer program product includes a computer program / instructions that, when executed by a processor, implement the steps of the above-described method.

[0046] This application provides a method and apparatus for determining reservoir recovery. It determines the T2 cutoff value of the target reservoir by determining the fractal dimension of the target reservoir and the volume fraction of pores with pore sizes smaller than a preset pore size threshold in the core sample of the target reservoir. Furthermore, based on the T2 cutoff value of the target reservoir, it determines the contribution of permeation and displacement to the recovery rate of the target reservoir. This solution solves the technical problem of low accuracy in determining the contribution of permeation and displacement due to the inability to quantitatively characterize these processes, achieving the technical effect of quantitatively characterizing permeation and displacement to accurately determine the contribution of recovery. Attached Figure Description

[0047] To more clearly illustrate the technical solutions in the embodiments of this application 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 only some embodiments recorded in this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0048] Figure 1 This is a flowchart of one embodiment of the method for determining reservoir recovery provided in this application;

[0049] Figure 2 This is a hardware structure block diagram of an electronic device for a method of determining reservoir recovery rate provided in this application;

[0050] Figure 3 This is a schematic diagram of the module structure of one embodiment of the reservoir recovery determination device provided in this application. Detailed Implementation

[0051] To enable those skilled in the art to better understand the technical solutions in this application, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of this application.

[0052] To address the current inability to quantitatively characterize the seepage and displacement processes during water injection development, this paper proposes a method for quantitatively characterizing these processes. This method aims to effectively analyze the seepage mechanism of water-driven seepage and provide theoretical and technical support for reservoir development planning and oil recovery enhancement.

[0053] Figure 1 This is a flowchart of one embodiment of the method for determining reservoir recovery provided in this application. Although this application provides method operation steps or apparatus structures as shown in the following embodiments or figures, more or fewer operation steps or module units may be included in the method or apparatus based on conventional or non-inventive effort. In steps or structures where there is no logically necessary causal relationship, the execution order of these steps or the module structure of the apparatus is not limited to the execution order or module structure described in the embodiments and figures of this application. When the method or module structure is applied in actual devices or end products, it can be executed sequentially or in parallel according to the method or module structure shown in the embodiments or figures (e.g., in a parallel processor or multi-threaded processing environment, or even a distributed processing environment).

[0054] Specifically, such as Figure 1 As shown, the method for determining reservoir recovery rate described above may include the following steps:

[0055] Step 101: Determine the fractal dimension of the target reservoir;

[0056] Step 102: Determine the volume fraction of pores with a pore size smaller than a preset pore size threshold in the core sample of the target reservoir;

[0057] Step 103: Determine the T2 cutoff value of the target reservoir based on the fractal dimension and the volume fraction;

[0058] Step 104: Determine the contribution of percolation and displacement to the recovery rate of the target reservoir based on the T2 cutoff value of the target reservoir.

[0059] Specifically, in implementation, the T2 cutoff value of the target reservoir can be calculated using the following formula:

[0060] lgS av = (3-D)lgT2+(D-3)lgT 2max

[0061] Among them, S av T represents the volume fraction of pores in the core sample with a pore size smaller than a preset pore size threshold, D represents the fractal dimension of the target reservoir, and T represents the volume fraction of pores with a pore size smaller than a preset pore size threshold in the core sample. 2max This represents the maximum T2 value, where T2 represents the T2 cutoff value of the target reservoir.

[0062] To determine the volume fraction of pores with pore sizes smaller than a preset pore size threshold in the core sample of the target reservoir, the cumulative volume of pores with pore sizes smaller than the preset pore size threshold in the core sample and the cumulative volume of pores in the core sample can be determined first, and then the volume fraction of pores with pore sizes smaller than the preset pore size threshold in the core sample of the target reservoir can be determined.

[0063] For example, the cumulative volume of pores with a diameter smaller than the preset pore diameter threshold in the core sample can be determined first using the following formula:

[0064]

[0065] Among them, V r This represents the cumulative volume of pores with a half-aperture diameter smaller than the preset pore diameter threshold, where A” is a proportionality constant and r min Indicates the minimum pore radius; r max Let represent the maximum pore radius, A represent the fractal factor, f(r) represent the density function of the pore radius, and D represent the fractal dimension.

[0066] The cumulative volume of pores in the core sample is then determined using the following formula:

[0067]

[0068] Among them, V t r represents the cumulative pore volume in the core sample. max Indicates the maximum pore radius;

[0069] Finally, the volume fraction of pores with a pore size smaller than a preset pore size threshold in the core sample of the target reservoir is determined according to the following formula:

[0070]

[0071] Among them, S av This represents the volume fraction of pores in the core sample of the target reservoir whose pore size is smaller than a preset pore size threshold.

[0072] Furthermore, considering the presence of r in tight / shale reservoirs min It is much smaller than rmax Therefore, the volume fraction of pores with a pore size smaller than a preset pore size threshold in the core sample of the target reservoir can be determined using the following simplified formula:

[0073]

[0074] Among them, S av This represents the volume fraction of pores with a pore size smaller than a preset pore size threshold in the core sample of the target reservoir, where r represents the preset pore size threshold. max V represents the maximum pore radius, D represents the fractal dimension, and V represents the maximum pore radius. r V represents the cumulative volume of pores with a half-aperture smaller than the preset aperture threshold. t This represents the cumulative volume of pores in the core sample.

[0075] In step 104 above, determining the contribution of adsorption and displacement to the recovery rate of the target reservoir based on the T2 cutoff value of the target reservoir may include:

[0076] S1: Obtain the nuclear magnetic resonance spectrum of the target reservoir;

[0077] S2: The nuclear magnetic resonance spectrum is segmented according to the T2 cutoff value of the target reservoir, wherein the segmentation is performed in the manner of percolation and oil displacement on the left and displacement and oil displacement on the right.

[0078] S3: Based on the segmentation results, determine the production rate of the percolation and displacement processes;

[0079] S4: Determine the contribution of permeation and displacement to the recovery rate of the target reservoir based on the production rate of permeation and displacement.

[0080] The fractal dimension of the target reservoir can be determined as follows: Obtain the critical points of different oil recovery methods based on the pore structure of the target reservoir; use the critical values ​​corresponding to these critical points as the fractal dimension of the target reservoir. That is, the fractal dimension is determined based on the critical points of different oil recovery methods for different types of reservoir pore structures. Small pores are dominated by permeation / absorption, large pores by displacement, and the critical value for the intermediate development methods is the fractal dimension boundary.

[0081] The above method will be described below with reference to a specific embodiment. It should be noted that this specific embodiment is only for better illustration of this application and does not constitute an improper limitation of this application.

[0082] Current research on water-driven seepage mainly focuses on dynamic seepage recovery mechanisms and theoretical models, applicable reservoir types and microscopic influence mechanisms, seepage dynamics characteristics, and influencing factors. However, these methods often employ conventional displacement physics simulation devices, which can only measure fluid conditions at the inlet and outlet ends and evaluate oil displacement effects by calculating macroscopic parameters from data collected at both ends of the clamp. However, since the flow process inside the core is a "black box," it is impossible to effectively measure the volume of crude oil discharged through seepage and displacement, especially for tight oil / shale oil cores, where experimental results have larger errors, limiting the quantitative evaluation and research of seepage and displacement. Currently, some studies use microfluidic model experiments, numerical simulation methods, and field experiments to study the seepage and displacement dynamics of tight oil / shale oil. However, due to differences from actual reservoirs and the large scale of some studies, these methods cannot precisely characterize the magnitude of seepage and displacement and the microscopic fluid dynamics during water injection development.

[0083] To address the problems with existing processing methods, this example introduces nuclear magnetic resonance (NMR) technology to quantitatively assess the distribution of fluids in different pores and the microscopic dynamic characteristics within the core. Currently, there are also some methods that calculate the recovery rate changes of different oil production methods by analyzing the gray value differences in NMR MRI images. Although MRI technology can intuitively and continuously reflect the distribution of oil and water within the rock and the changes in the fluid saturation field during water injection development, these methods can only analyze the percolation and displacement effects from a qualitative and semi-quantitative perspective. They cannot accurately and quantitatively characterize the contribution of different oil production methods (percolation and displacement) to the recovery rate and the changes in core signals.

[0084] Based on this, in this example, we utilize the self-similarity characteristics of porous media to construct a dynamic infiltration-drainage coupling online physical simulation based on nuclear magnetic resonance fractal theory to compensate for the shortcomings of MRI imaging technology. This allows for accurate, quantitative, and continuous characterization of infiltration and displacement within the core during water injection development.

[0085] Specifically, this example presents a dynamic online physical simulation method for water displacement coupling based on nuclear magnetic resonance (NMR) fractal theory. This method enables online NMR simulation of various reservoir rock samples under different injection media and conditions. Through quantitative and qualitative analysis of the magnitude of water absorption and displacement during micro-water injection development and the contribution mechanism of different oil recovery methods to the recovery rate, it provides theoretical support for efficient development decisions in tight / shale oil. Currently, there is no dynamic online physical simulation method for water displacement coupling based on NMR fractal theory, thus lacking quantitative research on the magnitude of different oil recovery methods (water absorption and displacement) under micro-conditions and their contribution mechanism to the recovery rate. This example provides a method for quantitatively determining the contribution of different utilization methods.

[0086] Specifically, a dynamic infiltration-flooding coupled online physical simulation experimental method based on nuclear magnetic resonance (NMR) fractal theory was established. By selecting core samples to conduct dynamic infiltration-flooding experiments, the multiphase flow and migration behavior of crude oil during the oil displacement experiment were monitored in real-time using NMR, thereby obtaining NMR spectra under different conditions. Considering that the T2 value can characterize the distribution and mobility of fluids in pores of different scales, the T2 cutoff value of the target reservoir was quantitatively determined. Based on the determined T2 cutoff value, the NMR spectra were segmented. After segmentation, the left region represents infiltration-flooding (small pores), and the right region represents displacement-flooding (large pores). Furthermore, by calculating the recovery rate of different oil production methods (infiltration and displacement), the contribution of infiltration and displacement during water injection development can be quantitatively evaluated. After quantitatively evaluating the contributions of percolation and displacement during water injection development, the dynamic evolution and seepage characteristics of percolation and displacement oil production over development time can be analyzed by combining key injection and production parameters. This provides crucial support for development scheme design, injection and production pressure optimization, and development process tracking and adjustment. Consequently, it provides a theoretical basis for the pore throat activation mechanism and dynamic development characteristics of reservoirs at different development stages under the matrix-fracture coupling mode, aiming to efficiently leverage the synergistic effect between the matrix and fractures, improve the degree of matrix crude oil activation, reduce the residual oil saturation distribution, and further enhance oil recovery.

[0087] In implementation, nuclear magnetic resonance fractal dimension data analysis methods may include:

[0088] Based on low-field nuclear magnetic resonance (NMR) theory, considering that NMR occurs when hydrogen-containing protons are immersed in a static magnetic field and exposed to a second oscillating magnetic field, and that the NMR amplitude is proportional to the number of hydrogen protons under the same NMR parameters, this principle allows for the quantitative evaluation of changes in the saturation of hydrogen-containing fluids within rock samples. The transverse relaxation time T2 in the NMR spectrum can be used as a characteristic parameter expressing the magnitude of fluid energy transfer, and also as an effective indicator of the structural characteristics of flow channels and the strength of fluid-structure interaction: that is, the molecular surface forces acting on the fluid at the walls of large pores and in small pores are more significant, resulting in smaller T2 values. Conversely, in larger pores and fractures, the molecular surface forces are smaller, resulting in larger T2 values. The T2 spectrum of saturated oil in the core can be obtained through NMR testing and the successive iterative reconstruction (SIRT) algorithm.

[0089] Specifically, the T2 relaxation time can be expressed as:

[0090]

[0091] Where T2 represents the relaxation time, in milliseconds (ms), and T... 2B T represents the relaxation time of the filling fluid itself, in milliseconds (ms). 2S T represents the relaxation time of rock particle surfaces, measured in milliseconds (ms).2D The relaxation time of fluid molecule diffusion in the magnetic field gradient is expressed in milliseconds (ms). M(t) represents the inversion of the total signal quantity, which is dimensionless. i T represents the cumulative total signal amplitude, dimensionless. 2i Let represent the i-th relaxation time, in milliseconds; t represents time, in milliseconds.

[0092] Among them, T 2B and T 2D In actual testing, the surface relaxation time T of rock particles can often be ignored. 2S The transverse relaxation time in porous media can be approximately characterized, and the surface relaxation time mostly occurs at the fluid-structure interaction interface, which is closely related to the structural characteristics of the porous media. Therefore, the T2 relaxation time can be expressed as:

[0093]

[0094] Where ρ represents the surface relaxation intensity, μm / ms; S represents the pore surface area, cm². 2 V represents the pore volume, in cm. 3 ;F S Denotes the aperture geometry factor (spherical aperture, F) S =3; columnar pore, F S =2; Crack, F S =1), r is the aperture in μm; C represents the conversion factor, which is dimensionless.

[0095] As can be seen from Formula 3 above, the transverse relaxation time of the nuclear magnetic resonance curve can approximately characterize the size and distribution of pores at different scales in porous media.

[0096] The pore-throat structure of oil reservoir rocks is a natural porous medium with self-similar characteristics. Therefore, by combining fractal geometry theory with nuclear magnetic resonance transverse relaxation time (T2) spectra, the irregularity of pores at different scales and the self-similar characteristics of pore throats during water-driven seepage development can be effectively evaluated, thereby classifying the activation modes of pore throats at different levels. Based on the principles of fractal geometry, the number of pores with a diameter greater than r can be characterized by the following formula:

[0097]

[0098] Where, N r It is the number of pores with a diameter greater than r, where r is the pore radius in μm. max Let represent the maximum pore radius in μm, A represent the fractal factor, f(r) represent the density function of the pore radius in %, and D represent the fractal dimension, which is dimensionless.

[0099] The fractal dimension D can be determined based on the critical points of different oil recovery methods for different types of reservoir pore structures. Small pores are dominated by permeation and adsorption, while large pores are dominated by displacement. Correspondingly, the critical value of the intermediate development method is the fractal dimension limit.

[0100] Therefore, based on Formula 4 above, the cumulative volume of pores with a pore radius smaller than r can be expressed as:

[0101]

[0102] Among them, V r This represents the cumulative volume of pores with a radius smaller than r, in cm. 3 "A" is a proportionality constant; r min Let r represent the minimum pore radius, in μm, where r can be the actual pore size value obtained from the core sample, for example, the value of r can be determined by high pressure mercury intrusion or nuclear magnetic resonance.

[0103] Based on Formula 5 above, the cumulative volume fraction of pores with a pore radius less than r in the reservoir can be expressed as:

[0104]

[0105] Among them, S av It is the cumulative volume fraction of pores with a radius smaller than r, expressed as %.

[0106] Due to the tight / shale reservoirs, r min Much smaller than r max Formula 6 above can be simplified to:

[0107]

[0108] Combining Formula 3 above, taking the logarithm of Formula 7 yields:

[0109] lgS av = (3-D)lgT2+(D-3)lgT 2max (Formula 8)

[0110] Therefore, based on the differences in fluid production methods within pores of different levels, the T2 cutoff value of the lateral relaxation time of pore throats at different levels, dominated by the two oil production methods of percolation and displacement, can be determined using fractal dimensions.

[0111] Based on Equation 8 above, the following quantitative characterization of water-driven percolation based on nuclear magnetic resonance fractal dimension can be established:

[0112] lgS avi =(3-D i )lgT 2i +(D i -3)lgT2max (Formula 9)

[0113] Among them, S avi This indicates a time less than the lateral relaxation time T. 2i The cumulative signal amplitude percentage, %; D i Let T be the lateral relaxation time. 2i The fractal dimension below is dimensionless, and i represents different types of reservoirs.

[0114] That is, Formula 9 above uses the fractal dimension D corresponding to different types of reservoirs. i By determining the corresponding T2 cutoff value, and then using this T2 cutoff value as a boundary, the contribution of pore oil production to the recovery rate dominated by different oil production methods (permeation and displacement) can be quantitatively characterized.

[0115] Based on the quantitative characterization method for water-driven adsorption-displacement based on the fractal dimension of nuclear magnetic resonance established above, online nuclear magnetic resonance experiments on dynamic adsorption in water-driven oil recovery can be conducted to obtain nuclear magnetic resonance spectra under different development states. By determining the critical fractal dimension D of adsorption and displacement, i The corresponding T2 cutoff value, as a boundary, allows for the quantitative characterization of the contribution of different oil recovery methods (percolation and displacement) to the oil recovery rate, thereby quantitatively evaluating the magnitude of percolation and displacement during water injection development. Simultaneously, combining nuclear magnetic resonance spectra with injection-production pressure, injection-production fluid volume, and other injection-production development parameters in the percolation process serves as key data for calculating oil displacement efficiency and recovery rate. This enables qualitative and quantitative analysis of the dynamic development characteristics and microscopic seepage mechanisms of percolation and displacement, further optimizing integrated percolation and displacement development methods and related parameters.

[0116] In the example above, a dynamic online physical simulation experiment method integrating infiltration and displacement was established based on nuclear magnetic resonance (NMR) technology. This method can simulate water-driven infiltration experiments under different injection and production conditions within the formation, and dynamically monitor the multiphase flow and migration behavior of crude oil during the oil displacement experiment using NMR in real time, thereby obtaining NMR spectra under different conditions. A T2 cutoff value was determined using NMR fractal dimension theory to segment the NMR spectra, allowing for quantitative characterization of infiltration and displacement effects by combining different injection and production parameters, injection and production fluid volumes, and recovery rates. By analyzing the contribution mechanism, dynamic development characteristics, and microscopic seepage mechanism of different oil production methods during water injection development, this method provides a reference for the formulation of subsequent reservoir development plans, optimization of injection and production processes, and selection of measures to improve oil recovery.

[0117] Specifically, in implementation, a constant-temperature oil bath heating circulation control system and core encapsulation method can be used for experiments to ensure that the experimental core and fluid reach the temperature and pressure under simulated formation conditions. The specially designed nuclear magnetic resonance (NMR) core holder can be made of S2 glass fiber and PEEK high-strength composite materials, significantly enhancing pressure resistance and improving coil sensitivity. Furthermore, by combining heat-shrink tubing and fluoropolymer sleeves, direct contact between acidic corrosive fluids and fluoropolymer oils and the core is avoided, extending the lifespan of experimental materials while ensuring experimental accuracy. Online NMR scanning avoids testing errors caused by stress changes or placement variations during core removal, achieving, to a certain extent, the physical simulation of water-driven percolation development under high-temperature and high-pressure conditions based on online NMR testing.

[0118] Furthermore, based on online nuclear magnetic resonance (NMR), by changing different injection and production conditions, methods, and displacement parameters (injection pressure, injection rate, injection-production pressure difference, permeability, and core type), integrated simulation of seepage-drive coupling under various development conditions can be achieved, and the changes in nuclear magnetic signal in the core can be monitored in real time during the displacement process. Based on the fractal dimension theory of NMR, the NMR spectrum was finely divided. Combined with the calculation of key injection and production parameters and recovery rate during the displacement process, the seepage and displacement effects in water-driven seepage were quantitatively characterized. This allowed for qualitative and quantitative analysis of the dynamic development characteristics and microscopic seepage mechanism of seepage and displacement, further optimizing the integrated seepage-drive development method and related parameters, and providing a theoretical basis for the efficient development of shale oil.

[0119] A specific example is given below: Three shale samples (S1, S2, and S3) from the target study area were obtained. Online nuclear magnetic resonance (NMR) experiments were conducted on these three shale samples under water-driven percolation. NMR tests were performed on key nodes during the displacement process. Combined with injection and production parameters and other data from the experiment, the measured NMR spectra were plotted. Furthermore, a quantitative characterization method for water-driven percolation based on NMR fractal dimension was developed. According to Formula 8 above, the pore fractal dimension D controlled by different oil recovery methods (percolation and displacement) was obtained. i=2, correspondingly, the T2 cutoff value corresponding to the critical fractal dimension is determined to be 10ms. Therefore, the saturated oil distribution pores in the core can be divided into pores dominated by percolation and pores controlled by displacement, using 10ms as the boundary. The pores dominated by percolation are smaller in scale, and the fluid inside them is more strongly controlled by percolation (capillary pressure). The pores controlled by displacement are larger in scale, and the fluid inside them is more strongly controlled by displacement (viscous force). Therefore, the contribution of different oil recovery methods to the recovery rate of the three cores under different displacement pressures can be calculated. Specifically, based on the obtained nuclear magnetic resonance T2 spectra, it can be seen that the T2 peak decreases with the increase of displacement time, indicating that crude oil in the core can be effectively recovered under a certain pressure difference. The permeability levels of samples S1, S2, and S3 were basically the same. The recovery rates of sample S1 at 3 MPa, sample S2 at 10 MPa, and sample S3 at 15 MPa were 34.68%, 40.47%, and 36.35%, respectively. As the displacement pressure increased, the recovery rate first increased and then decreased, indicating that the displacement pressure in the water-driven percolation experiment is not necessarily better the higher it is, and there is an optimal range of values.

[0120] Therefore, it can be seen that the T2 spectrum of nuclear magnetic resonance combined with injection and production parameters can better reflect the overall signal changes of the core during the experiment. The recovery rate calculated based on the signal changes can correspond well with the recovery rate obtained by oil-water metering. The trend of recovery rate change reflected is more intuitive and continuous, which can effectively assist in the qualitative and quantitative characterization of crude oil production and its contribution to recovery rate in dynamic displacement coupling experiments under microscopic conditions.

[0121] By comparing the contributions of different oil recovery methods to the recovery rate, it can be seen that the degree of percolation recovery decreases with increasing displacement pressure, from 29.92% to 4.31%, while the degree of displacement recovery increases rapidly and then slowly with increasing displacement pressure. That is, when the displacement pressure is low, the viscous force is low, and the core percolation process is close to spontaneous percolation. Water can slowly reach the small pores in the matrix, and the percolation process is in the equilibrium zone between capillary pressure and viscous force. At this time, the percolation effect of capillary pressure on small pores is the main oil discharge mechanism. However, the low pressure makes it difficult for the viscous driving force to overcome the capillary pressure of most small pore throats, making it difficult to effectively exert the displacement effect. Moreover, the amount of water injected in the same time is limited, which cannot guarantee efficient percolation, resulting in a low overall recovery rate. When the displacement pressure increases to 10 MPa, the displacement pressure increases, and the viscous force also increases. Under the action of capillary pressure percolation and displacement viscous force, the crude oil percolated into large pores or fractures can be quickly displaced and discharged by viscous force, resulting in a higher overall recovery rate. When the displacement pressure continues to rise to 15 MPa, viscous force becomes the dominant force for oil drainage. However, the water in the fractures is discharged before it can undergo percolation and exchange with the crude oil in the matrix, limiting the percolation effect of the matrix and resulting in poor percolation efficiency. Simultaneously, high displacement pressure leads to greater viscous force. When the viscous force exceeds the capillary pressure, fingering will occur, drastically shortening the breakthrough time and causing instability at the oil-water front, potentially leading to severe water channeling and consequently, low recovery rates under high injection pressure. Therefore, the precise quantitative evaluation of different oil recovery methods based on nuclear magnetic resonance fractal dimension directly and quantitatively characterizes the dynamic evolution and seepage characteristics of percolation and displacement oil production over development time during water injection development.

[0122] In summary, by establishing a dynamic seepage-displacement coupling online physical simulation experimental method based on nuclear magnetic resonance fractal theory, a direct and quantitative evaluation of seepage and displacement during water injection development can be effectively conducted. In actual production experiments, a comprehensive analysis of the aforementioned nuclear magnetic resonance spectra can be performed to dynamically characterize and analyze the contribution and mechanism of different oil recovery methods to enhanced oil recovery from multiple aspects, qualitatively and quantitatively. This yields the dynamic development characteristics and microscopic seepage mechanisms of the corresponding water injection development process, providing a reference for the formulation of subsequent reservoir development plans, optimization of injection and production processes, and selection of enhanced oil recovery measures.

[0123] The methods and embodiments provided in the above-described embodiments of this application can be executed in a mobile terminal, computer terminal, or similar computing device. Taking its operation on an electronic device as an example... Figure 2 This is a hardware block diagram of an electronic device for a method of determining reservoir recovery rate provided in this application. (See diagram for example.) Figure 2As shown, the electronic device 10 may include one or more (only one is shown in the figure) processors 02 (processors 02 may include, but are not limited to, microprocessors MCUs or programmable logic devices FPGAs, etc.), a memory 04 for storing data, and a transmission module 06 for communication functions. Those skilled in the art will understand that... Figure 2 The structure shown is for illustrative purposes only and does not limit the structure of the electronic device described above. For example, electronic device 10 may also include... Figure 2 The more or fewer components shown, or having the same Figure 2 The different configurations shown.

[0124] The memory 04 can be used to store software programs and modules of application software, such as the program instructions / modules corresponding to the reservoir recovery determination method in the embodiments of this application. The processor 02 executes various functional applications and data processing by running the software programs and modules stored in the memory 04, thereby realizing the reservoir recovery determination method of the above-mentioned application. The memory 04 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 04 may further include memory remotely located relative to the processor 02, and these remote memories can be connected to the electronic device 10 via a network. Examples of the above-mentioned networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0125] The transmission module 06 is used to receive or send data via a network. Specific examples of the network described above may include a wireless network provided by the communication provider of the electronic device 10. In one example, the transmission module 06 includes a Network Interface Controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, the transmission module 06 may be a Radio Frequency (RF) module, used for wireless communication with the Internet.

[0126] At the software level, the aforementioned reservoir recovery determination device can be as follows: Figure 3 As shown, it includes:

[0127] The first determining module 301 is used to determine the fractal dimension of the target reservoir;

[0128] The second determining module 302 is used to determine the volume fraction of pores with a pore size smaller than a preset pore size threshold in the core sample of the target reservoir.

[0129] The third determining module 303 is used to determine the T2 cutoff value of the target reservoir based on the fractal dimension of the target reservoir and the volume fraction.

[0130] The fourth determining module 304 is used to determine the contribution of percolation and displacement to the recovery rate of the target reservoir based on the T2 cutoff value of the target reservoir.

[0131] In one implementation, the third determining module 303 can specifically calculate the T2 cutoff value of the target reservoir according to the following formula:

[0132] lgS av = (3-D)lgT2+(D-3)lgT 2max

[0133] Among them, S av T represents the volume fraction of pores in the core sample with a pore size smaller than a preset pore size threshold, D represents the fractal dimension of the target reservoir, and T represents the volume fraction of pores with a pore size smaller than a preset pore size threshold in the core sample. 2max This represents the maximum T2 value, where T2 represents the T2 cutoff value of the target reservoir.

[0134] In one embodiment, the second determining module 302 can specifically determine the cumulative volume of pores in the core sample with pore sizes smaller than the preset pore size threshold according to the following formula:

[0135]

[0136] Among them, V r This represents the cumulative volume of pores with a half-aperture diameter smaller than the preset pore diameter threshold, where A” is a proportionality constant and r min Indicates the minimum pore radius; r max Let represent the maximum pore radius, A represent the fractal factor, f(r) represent the density function of the pore radius, and D represent the fractal dimension.

[0137] The cumulative volume of pores in the core sample is determined using the following formula:

[0138]

[0139] Among them, V t r represents the cumulative pore volume in the core sample. max Indicates the maximum pore radius;

[0140] The volume fraction of pores with a pore size smaller than a preset pore size threshold in the core sample of the target reservoir is determined using the following formula:

[0141]

[0142] Among them, S avThis represents the volume fraction of pores in the core sample of the target reservoir whose pore size is smaller than a preset pore size threshold.

[0143] In one embodiment, the second determining module 302 can specifically determine the volume fraction of pores with a pore size smaller than a preset pore size threshold in the core sample of the target reservoir according to the following formula:

[0144]

[0145] Among them, S av This represents the volume fraction of pores with a pore size smaller than a preset pore size threshold in the core sample of the target reservoir, where r represents the preset pore size threshold. max V represents the maximum pore radius, D represents the fractal dimension, and V represents the maximum pore radius. r V represents the cumulative volume of pores with a half-aperture smaller than the preset aperture threshold. t This represents the cumulative volume of pores in the core sample.

[0146] In one embodiment, the fourth determining module 304 can specifically acquire the nuclear magnetic resonance spectrum of the target reservoir; segment the nuclear magnetic resonance spectrum according to the T2 cutoff value of the target reservoir, wherein the segmentation is performed in a manner where the left side represents adsorption-induced oil production and the right side represents displacement-induced oil production; determine the production volume of adsorption-induced oil production and the production volume of displacement-induced oil production based on the segmentation results; and determine the contribution of adsorption-induced oil production and displacement-induced oil production to the recovery rate of the target reservoir based on the production volume of adsorption-induced oil production and the production volume of displacement-induced oil production.

[0147] In one embodiment, the first determining module 301 can specifically obtain the critical point of the differential oil recovery mode in the pore structure of the target reservoir; and use the critical value corresponding to the critical point as the fractal dimension of the target reservoir.

[0148] The embodiments of this application also provide a specific implementation of an electronic device capable of implementing all steps in the reservoir recovery determination method in the above embodiments. The electronic device specifically includes: a processor, a memory, a communication interface, and a bus; wherein the processor, memory, and communication interface communicate with each other via the bus; the processor is used to call a computer program in the memory, and when the processor executes the computer program, it implements all steps in the reservoir recovery determination method in the above embodiments. For example, when the processor executes the computer program, it implements the following steps:

[0149] Step 1: Determine the fractal dimension of the target reservoir;

[0150] Step 2: Determine the volume fraction of pores with a pore size smaller than a preset pore size threshold in the core sample of the target reservoir;

[0151] Step 3: Determine the T2 cutoff value of the target reservoir based on the fractal dimension and the volume fraction;

[0152] Step 4: Determine the contribution of percolation and displacement to the recovery rate of the target reservoir based on the T2 cutoff value of the target reservoir.

[0153] Embodiments of this application also provide a computer-readable storage medium capable of implementing all steps of the reservoir recovery determination method in the above embodiments. The computer-readable storage medium stores a computer program that, when executed by a processor, implements all steps of the reservoir recovery determination method in the above embodiments. For example, when the processor executes the computer program, it implements the following steps:

[0154] Step 1: Determine the fractal dimension of the target reservoir;

[0155] Step 2: Determine the volume fraction of pores with a pore size smaller than a preset pore size threshold in the core sample of the target reservoir;

[0156] Step 3: Determine the T2 cutoff value of the target reservoir based on the fractal dimension and the volume fraction;

[0157] Step 4: Determine the contribution of percolation and displacement to the recovery rate of the target reservoir based on the T2 cutoff value of the target reservoir.

[0158] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to interchangeably. Each embodiment focuses on its differences from other embodiments. In particular, hardware + program embodiments are relatively simple in description because they are fundamentally similar to method embodiments; relevant parts can be referred to the descriptions in the method embodiments.

[0159] The foregoing has described specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0160] While this application provides the method operation steps as described in the embodiments or flowcharts, more or fewer operation steps may be included based on conventional or non-inventive labor. The order of steps listed in the embodiments is merely one possible execution order among many and does not represent the only execution order. In actual device or client product execution, the methods shown in the embodiments or drawings can be executed sequentially or in parallel (e.g., in a parallel processor or multi-threaded processing environment).

[0161] While this specification provides method operation steps as described in the embodiments or flowcharts, more or fewer operation steps may be included based on conventional or non-inventive means. The order of steps listed in the embodiments is merely one possible execution order among many and does not represent the only execution order. In actual device or end product execution, the methods shown in the embodiments or drawings may be executed sequentially or in parallel (e.g., in a parallel processor or multi-threaded processing environment, or even a distributed data processing environment). The terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, product, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, product, or apparatus. Without further limitations, the presence of other identical or equivalent elements in the process, method, product, or apparatus that includes said elements is not excluded.

[0162] For ease of description, the above devices are described in terms of function, divided into various modules. Of course, in implementing the embodiments of this specification, the functions of each module can be implemented in one or more software and / or hardware components, or a module that performs the same function can be implemented by a combination of multiple sub-modules or sub-units. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division; in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces, or indirect coupling or communication connection between devices or units, and may be electrical, mechanical, or other forms.

[0163] Those skilled in the art will also know that, besides implementing the controller using purely computer-readable program code, the same functions can be achieved by logically programming the method steps, making the controller function as logic gates, switches, application-specific integrated circuits (ASICs), programmable logic controllers (PLCs), and embedded microcontrollers. Therefore, such a controller can be considered a hardware component, and the devices within it used to implement various functions can also be considered structures within that hardware component. Alternatively, the devices used to implement various functions can be considered as both software modules implementing the method and structures within a hardware component.

[0164] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0165] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0166] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0167] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0168] Memory may include non-persistent storage in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0169] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0170] Those skilled in the art will understand that the embodiments of this specification can be provided as methods, systems, or computer program products. Therefore, the embodiments of this specification can take the form of entirely hardware embodiments, entirely software embodiments, or embodiments combining software and hardware aspects. Furthermore, the embodiments of this specification can take the form of computer program products implemented on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0171] The embodiments described in this specification can be described in the general context of computer-executable instructions, such as program modules, that are executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform a specific task or implement a specific abstract data type. The embodiments of this specification can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0172] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, system embodiments are basically similar to method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments. In the description of this specification, the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the embodiments in this specification. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described can be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0173] The above description is merely an embodiment of the present specification and is not intended to limit the embodiments of the present specification. For those skilled in the art, various modifications and variations can be made to the embodiments of the present specification. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principle of the embodiments of the present specification should be included within the scope of the claims of the embodiments of the present specification.

Claims

1. A method for determining reservoir recovery rate, characterized in that, The method includes: Determine the fractal dimension of the target reservoir; Determine the volume fraction of pores with a pore size smaller than a preset pore size threshold in the core sample of the target reservoir; The T2 cutoff value of the target reservoir is determined based on the fractal dimension and the volume fraction of the target reservoir. Based on the T2 cutoff value of the target reservoir, determine the contribution of infiltration and displacement to the recovery rate of the target reservoir.

2. The method according to claim 1, characterized in that, Determining the T2 cutoff value of the target reservoir based on its fractal dimension and volume fraction includes: The T2 cutoff value of the target reservoir is calculated using the following formula: lgS av =(3-D)lgT2+(D-3)lgT 2max Among them, S av T represents the volume fraction of pores in the core sample with a pore size smaller than a preset pore size threshold, D represents the fractal dimension of the target reservoir, and T represents the volume fraction of pores with a pore size smaller than a preset pore size threshold in the core sample. 2max This represents the maximum T2 value, where T2 represents the T2 cutoff value of the target reservoir.

3. The method according to claim 1, characterized in that, Determining the volume fraction of pores with a pore size smaller than a preset pore size threshold in the core sample of the target reservoir includes: The cumulative volume of pores with a diameter smaller than the preset pore diameter threshold in the core sample is determined according to the following formula: Among them, V r This represents the cumulative volume of pores with a half-aperture diameter smaller than the preset pore diameter threshold, where A” is a proportionality constant and r min Indicates the minimum pore radius; r max Let represent the maximum pore radius, A represent the fractal factor, f(r) represent the density function of the pore radius, and D represent the fractal dimension. The cumulative volume of pores in the core sample is determined using the following formula: Among them, V t r represents the cumulative pore volume in the core sample. max Indicates the maximum pore radius; The volume fraction of pores with a pore size smaller than a preset pore size threshold in the core sample of the target reservoir is determined using the following formula: Among them, S av This represents the volume fraction of pores in the core sample of the target reservoir whose pore size is smaller than a preset pore size threshold.

4. The method according to claim 1, characterized in that, Determining the volume fraction of pores with a pore size smaller than a preset pore size threshold in the core sample of the target reservoir includes: The volume fraction of pores with a pore size smaller than a preset pore size threshold in the core sample of the target reservoir is determined using the following formula: Among them, S av This represents the volume fraction of pores with a pore size smaller than a preset pore size threshold in the core sample of the target reservoir, where r represents the preset pore size threshold. max V represents the maximum pore radius, D represents the fractal dimension, and V represents the maximum pore radius. r V represents the cumulative volume of pores with a half-aperture smaller than the preset aperture threshold. t This represents the cumulative volume of pores in the core sample.

5. The method according to claim 1, characterized in that, Based on the T2 cutoff value of the target reservoir, determine the contribution of adsorption and displacement to the recovery rate of the target reservoir, including: Obtain the nuclear magnetic resonance spectrum of the target reservoir; Based on the T2 cutoff value of the target reservoir, the nuclear magnetic resonance spectrum is segmented, wherein the segmentation is performed in the manner of percolation and oil displacement on the left and displacement and oil displacement on the right. Based on the segmentation results, determine the recovery rate of the seepage effect and the recovery rate of the displacement effect; The contribution of percolation and displacement to the recovery rate of the target reservoir is determined based on the recovery rates from percolation and displacement.

6. The method according to claim 1, characterized in that, Determining the fractal dimension of the target reservoir includes: To obtain the critical point of oil recovery mode based on the difference in pore structure in the target reservoir; The critical value corresponding to the critical point is taken as the fractal dimension of the target reservoir.

7. A device for determining reservoir recovery rate, characterized in that, include: The first determining module is used to determine the fractal dimension of the target reservoir; The second determining module is used to determine the volume fraction of pores with a pore size smaller than a preset pore size threshold in the core sample of the target reservoir. The third determining module is used to determine the T2 cutoff value of the target reservoir based on the fractal dimension and the volume fraction of the target reservoir; The fourth determining module is used to determine the contribution of percolation and displacement to the recovery rate of the target reservoir based on the T2 cutoff value of the target reservoir.

8. An electronic device comprising a processor and a memory for storing processor-executable instructions, characterized in that, When the processor executes the instructions, it implements the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program / instructions stored thereon, characterized in that, When the computer program / instructions are executed by the processor, they implement the steps of the method described in any one of claims 1 to 6.

10. A computer program product comprising a computer program / instructions, characterized in that, When the computer program / instructions are executed by the processor, they implement the steps of the method described in any one of claims 1 to 6.

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