Cluster spacing dual-objective optimization method and system based on crack propagation form and productivity

Abstract

The invention provides a cluster spacing dual-objective optimization method and system based on fracture propagation form and productivity, and the method comprises the steps: building fracturing geologic models of a target reservoir, and carrying out the fracture propagation simulation of each fracturing geologic model based on different perforation cluster spacing; calculating a crack propagation uniformity coefficient based on the crack propagation form data, and preferably selecting a first cluster spacing range by taking the crack propagation uniformity degree as a target; setting a plurality of productivity simulation cluster spacing based on the first cluster spacing range, establishing a corresponding productivity simulation geologic model by combining the data of the target reservoir to carry out a productivity simulation process, and preferably selecting a second cluster spacing range according to a simulation result by taking productivity maximization as a principle; and solving an intersection of the first cluster spacing range and the second cluster spacing range as a final optimized cluster spacing range of the target reservoir. According to the method, the crack expansion uniformity and the oil and gas well after-pressure productivity are both considered, the optimization precision is further improved on the basis of a previous perforation cluster spacing optimization method, and the optimization efficiency is high.

Description

Technical Field

[0001] The present invention relates to the technical field of oil and gas production increase optimization, and in particular to a cluster spacing dual-objective optimization method and system based on fracture extension morphology and production capacity. Background Art

[0002] Unconventional natural gas reservoirs have the characteristics of low porosity and low permeability, and it is extremely difficult for gas to flow naturally in such reservoirs. Hydraulic fracturing technology is an effective means to transform unconventional reservoirs. It forms a complex fracture network in the underground reservoir and effectively supports it by injecting fracturing fluid and proppant and other materials into the ground, thereby building a "highway" for unconventional reservoirs to assist the flow of oil and gas. Unconventional reservoir transformation usually adopts multi-cluster perforation. If the same fracturing parameters as conventional reservoir transformation are used, complex inter-fracture interference between different fractures is prone to occur during the fracture expansion process, making some fractures unable to expand effectively, reducing the fracture control area, and affecting the fracturing transformation effect and oil and gas production capacity. Therefore, before implementing hydraulic fracturing, a series of optimizations of the fracturing scheme are required, including the number of clusters, cluster spacing, fracturing fluid pumping rate, construction fluid volume, etc., in order to maximize the gas well production capacity.

[0003] In the prior art, some technicians conduct formation fracturing induced stress analysis on different cluster spacings and select cluster spacings that meet the requirements of induced stress changes. For example, patent document CN103527163B proposes a volume fracturing process for horizontal wells in tight reservoirs. By collecting data such as the size and direction of in situ stress, the orientation and length of the horizontal well, the Young's modulus of the reservoir, the Poisson's ratio and the logging interpretation results, the data are used as the basic parameters of induced stress required for calculating complex fractures generated by volume fracturing of horizontal wells in tight reservoirs; according to the physical properties of the reservoir, the changes in the induced stress difference under different fracturing sequences of 3 or more perforation clusters in the same fracturing section are compared, and the fracture initiation sequence of the perforation clusters is optimized with the maximum induced stress difference as the target; the perforation cluster spacing is optimized to promote the formation of complex fractures by fracturing in the same fracturing section of the horizontal well, so as to achieve the transformation of the complex fracture morphology of the fracturing horizontal well. Although this solution can improve the effect of horizontal well fracturing to a certain extent, it is based on the analysis of fracturing-induced stress and ignores the impact of interaction with the reservoir during the fracturing process. The analysis results cannot reflect the actual fracturing status data and lack accuracy.

[0004] The information disclosed in the background technology section of the present invention is only intended to deepen the understanding of the general background technology of the present invention, and should not be regarded as acknowledging or suggesting in any form that the information constitutes the prior art known to those skilled in the art. Summary of the invention

[0005] To solve the above problems, the present invention provides a dual-objective optimization method for cluster spacing based on crack extension morphology and productivity. In one embodiment, the method includes:

[0006] Steps for constructing a fracturing geological model: obtaining reservoir geological engineering parameters of the target reservoir according to requirements, and establishing a number of fracturing geological models matching the target reservoir based on the parameters;

[0007] Fracture propagation simulation step: setting a perforation cluster spacing list, and performing fracture propagation simulation based on the fracturing geological model and the set process parameters;

[0008] Crack morphology optimization step: After the crack extension simulation is completed, the crack extension uniformity coefficient is calculated according to the crack extension morphology data, and the first cluster spacing set is optimized with the crack extension uniformity coefficient as the target;

[0009] Capacity simulation cluster spacing setting step: filling in gaps and extending based on the first cluster spacing set to form a continuous capacity simulation cluster spacing range;

[0010] Geological capacity simulation steps: after establishing corresponding production geological models for different cluster spacings within the capacity simulation cluster spacing range based on the basic data of the target reservoir, the capacity simulation is carried out using the production simulation system;

[0011] Production capacity optimization step: according to the production capacity simulation results of each production geological model, the second cluster spacing set is optimized based on the principle of maximizing production capacity;

[0012] The target cluster spacing optimization step is: taking the intersection of the first cluster spacing set and the second cluster spacing set obtained as the final optimized cluster spacing range of the target reservoir cluster spacing.

[0013] Preferably, in some embodiments, the reservoir geological engineering parameters include: porosity, permeability, maximum horizontal principal stress, minimum horizontal principal stress, Young's modulus, Poisson's ratio, and the angle between the maximum horizontal principal stress and the wellbore of the target reservoir.

[0014] Furthermore, in an optional embodiment, the fracture morphology data of the extended simulation includes final fracture distribution and fracture geometric parameters.

[0015] Further, in an optional embodiment, in the fracture propagation simulation step, a technician sets a perforation cluster spacing list according to the fracturing construction parameters of a historical reservoir whose geological parameters match the target reservoir.

[0016] In an optional embodiment, in the crack extension simulation step, the dynamic induced stress field corresponding to each cluster of cracks is calculated according to the fracturing process parameters corresponding to different perforation cluster spacings, and then based on the dynamic induced stress field, a phase field method crack damage evolution model is used to implement complex dynamic crack extension simulation to obtain the final fracture morphology data for each different perforation cluster spacing scheme.

[0017] Further, in an optional embodiment, in the fracture propagation simulation step, the process of calculating the dynamic induced stress field corresponding to each cluster of fractures according to the fracturing process parameters corresponding to different perforation cluster spacings includes:

[0018] The geological parameters of the geological model and the information of different perforation cluster spacing are input into the multi-cluster fracture flow distribution model, and the fracturing process parameters of each cluster fracture in different perforation cluster spacing schemes are analyzed, including dynamic injection flow and fracture mouth pressure;

[0019] The fracturing process parameters of each cluster of fractures are taken as boundary conditions, and the fluid-solid coupling stress field model of fractures is used to calculate the dynamic induced stress field of each cluster of fractures corresponding to different cluster spacings.

[0020] Specifically, in a preferred embodiment, in the crack morphology optimization step, the crack extension uniformity coefficient is calculated according to the crack geometric parameters of the extension simulation according to the following formula:

[0021]

[0022] Where: ξ is the crack extension uniformity coefficient; ω i is the crack width of the i-th crack, a i is the length of the i-th crack unit, m; n min Represents the minimum number of crack units, dimensionless, n max Indicates the maximum number of elements in each crack, dimensionless, ω i,min represents the minimum width of each crack in the i-th unit, m, ω i,max represents the maximum width of each crack in the i-th unit, m, and h represents the crack height, m.

[0023] Furthermore, in a preferred embodiment, in the capacity simulation cluster spacing setting step, the cluster spacings are extended forward and backward respectively according to a set ratio according to the number of cluster spacings in the first cluster spacing set.

[0024] In actual application, the forward and backward extension ratios can be the same or different, and can be set separately according to actual conditions and needs, thereby achieving flexible and scientifically reasonable capacity cluster spacing range settings.

[0025] In an optional embodiment, in the geological productivity simulation step, the process of establishing corresponding production geological models for different cluster spacings within the productivity simulation cluster spacing range based on the basic data of the target reservoir includes:

[0026] The reservoir logging data is analyzed to determine the reservoir parameters and fracture parameters related to the production, and a production geological model corresponding to different cluster spacings is established based on the reservoir parameters and fracture parameters, wherein the reservoir characteristic parameters include the formation pressure, porosity, permeability, water saturation, effective thickness of the reservoir and horizontal well section length, and the fracture parameters include fracture half-length, fracture width and fracture conductivity.

[0027] Based on the application aspects of the method described in any one or more of the above embodiments, the present invention also provides a dual-objective optimization system for cluster spacing based on crack extension morphology and productivity, which executes the method described in any one or more of the above embodiments.

[0028] Compared with the closest prior art, the present invention has the following beneficial effects:

[0029] The present invention provides a dual-objective optimization method and system for cluster spacing based on fracture extension morphology and productivity. The method establishes a fracturing geological model of a target reservoir, simulates fracture extension for each fracturing geological model based on different perforation cluster spacings, and then calculates the fracture extension uniformity coefficient based on fracture extension morphology data, and optimizes the first cluster spacing range with fracture extension uniformity as the target; the data can reflect the real impact of the fracture extension process on the fracture morphology data;

[0030] Multiple capacity simulation cluster spacings are set based on the first cluster spacing range, which saves data setting operations and can accurately determine the cluster spacing range for capacity simulation, so as not to perform redundant production simulation work and not to miss cluster spacing data that may have a high capacity probability;

[0031] Then, a corresponding capacity simulation geological model is established in combination with the data of the target reservoir, the capacity simulation process is carried out according to the set capacity simulation parameters, and the second cluster spacing range is optimized based on the simulation results and the principle of maximizing capacity; the intersection of the first cluster spacing range and the second cluster spacing range is obtained as the final optimized cluster spacing range of the target reservoir; the uniformity of fracture expansion and the post-pressure capacity of oil and gas wells are taken into consideration, and the optimization accuracy is further improved on the basis of the traditional perforation cluster spacing optimization method; the present invention can adapt to the cluster spacing optimization of various reservoirs, has strong operability and high optimization efficiency.

[0032] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the description, claims and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0034] Figure 1 It is a flow chart of a dual-objective optimization method for cluster spacing based on crack extension morphology and productivity provided by an embodiment of the present invention;

[0035] Figure 2 It is a schematic diagram of a reservoir fracturing geological model according to a dual-objective optimization method of cluster spacing based on fracture extension morphology and productivity provided in an embodiment of the present invention;

[0036] Figure 3 This is an example diagram of uniformity coefficient statistics of a dual-objective optimization method for cluster spacing based on crack extension morphology and productivity provided in an embodiment of the present invention;

[0037] Figure 4 This is an example diagram of cumulative gas production statistics of a dual-objective optimization method for cluster spacing based on fracture extension morphology and productivity provided by an embodiment of the present invention;

[0038] Figure 5 It is a schematic structural diagram of a dual-objective optimization system for cluster spacing based on crack extension morphology and productivity provided by another embodiment of the present invention. DETAILED DESCRIPTION

[0039] The following will describe the implementation methods of the present invention in detail in conjunction with the accompanying drawings and embodiments, so that the implementers of the present invention can fully understand how the present invention applies technical means to solve technical problems and achieve the implementation process of technical effects and implement the present invention specifically according to the above implementation process. It should be noted that as long as there is no conflict, the various embodiments and various features of the embodiments in the present invention can be combined with each other, and the technical solutions formed are all within the protection scope of the present invention.

[0040] Although the flowcharts describe the operations as sequential processes, many of the operations may be performed in parallel, concurrently, or simultaneously. The order of the operations may be rearranged. A process may be terminated when its operations are completed, but may also have additional steps not included in the accompanying drawings. A process may correspond to a method, function, procedure, subroutine, subprogram, etc.

[0041] Computer devices include user devices and network devices. Among them, user devices or clients include but are not limited to computers, smart phones, PDAs, etc.; network devices include but are not limited to a single network server, a server group consisting of multiple network servers, or a cloud composed of a large number of computers or network servers based on cloud computing. Computer devices can be operated alone to implement the present invention, or they can be connected to the network and implement the present invention through interactive operations with other computer devices in the network. The network where the computer device is located includes but is not limited to the Internet, wide area network, metropolitan area network, local area network, VPN network, etc.

[0042] The terms "first", "second", etc. may be used herein to describe various units, but these units should not be limited by these terms, and these terms are used only to distinguish one unit from another unit. The term "and / or" used herein includes any and all combinations of one or more of the listed associated items. When a unit is referred to as being "connected" or "coupled" to another unit, it can be directly connected or coupled to the other unit, or there can be intermediate units.

[0043] The terms used herein are only for describing specific embodiments and are not intended to limit exemplary embodiments. Unless the context clearly indicates otherwise, the singular forms "one", "one" and "item" used herein are also intended to include plural numbers. It should also be understood that the terms "include" and / or "comprise" used herein specify the existence of stated features, integers, steps, operations, units and / or components, without excluding the existence or addition of one or more other features, integers, steps, operations, units, components and / or combinations thereof.

[0044] Unconventional natural gas reservoirs have the characteristics of low porosity and low permeability, and it is extremely difficult for gas to flow naturally in such reservoirs. Hydraulic fracturing technology is an effective means to transform unconventional reservoirs. It forms a complex fracture network in the underground reservoir and effectively supports it by injecting fracturing fluid and proppant and other materials into the ground, thereby building a "highway" for unconventional reservoirs to assist the flow of oil and gas. Unconventional reservoir transformation usually adopts multi-cluster perforation. If the same fracturing parameters as conventional reservoir transformation are used, complex inter-fracture interference between different fractures is prone to occur during the fracture expansion process, making some fractures unable to expand effectively, reducing the fracture control area, and affecting the fracturing transformation effect and oil and gas production capacity. Therefore, before implementing hydraulic fracturing, a series of optimizations of the fracturing scheme are required, including the number of clusters, cluster spacing, fracturing fluid pumping rate, construction fluid volume, etc., in order to maximize the gas well production capacity.

[0045] In the prior art, some technicians conduct formation fracturing induced stress analysis on different cluster spacings and select cluster spacings that meet the requirements of induced stress changes. For example, patent document CN103527163B proposes a volume fracturing process for horizontal wells in tight reservoirs. By collecting data such as the size and direction of in situ stress, the orientation and length of the horizontal well, the Young's modulus of the reservoir, the Poisson's ratio and the logging interpretation results, the data are used as the basic parameters of induced stress required for calculating complex fractures generated by volume fracturing of horizontal wells in tight reservoirs; according to the reservoir physical properties, the changes in the induced stress difference under different fracturing sequences of 3 or more perforation clusters in the same fracturing section are compared, and the fracture initiation sequence of the perforation clusters is optimized with the maximum induced stress difference as the target; the perforation cluster spacing is optimized to promote the formation of complex fractures by fracturing in the same fracturing section of the horizontal well, so as to achieve the transformation of the complex fracture morphology of the fracturing horizontal well. Although this solution can improve the effect of horizontal well fracturing to a certain extent, it is based on the analysis of fracturing-induced stress and ignores the impact of interaction with the reservoir during the fracturing process. The analysis results cannot reflect the actual fracturing status data and lack accuracy.

[0046] In addition, some technicians use numerical simulation of fracture extension to optimize cluster spacing. By comparing fracture morphology under different cluster spacing, the high-quality cluster spacing range is determined with fracture extension morphology as the optimization target. However, the fracturing operation parameters are a collection of multiple parameters. The cluster spacing optimized by this method is difficult to take into account the impact of oil and gas well production process, and cannot guarantee the optimal production capacity after reservoir transformation. Moreover, the gap between the upper and lower limits of cluster spacing may be large, and a more accurate cluster spacing range cannot be selected.

[0047] To solve the above problems, the present invention provides a dual-objective optimization method and system for cluster spacing based on crack extension morphology and productivity, which adopts the following technical ideas:

[0048] Establish a reservoir fracturing geological model of the target reservoir according to the reservoir geological engineering parameters of the target reservoir;

[0049] The fracture propagation simulation with different perforation cluster spacing is carried out through the reservoir fracturing geological model, and the fracture propagation simulation results are obtained;

[0050] The crack extension uniformity coefficient is calculated based on the crack extension simulation results, and a cluster spacing range is optimized based on the crack extension uniformity.

[0051] In addition, geological models under different cluster spacings are established based on the basic data of the target reservoir;

[0052] Through the geological models under different cluster spacings, the capacity simulation under different cluster spacings is carried out to obtain various capacity simulation results. According to the various capacity simulation results, another cluster spacing range is selected based on the principle of maximizing capacity.

[0053] The intersection of the two selected cluster spacing ranges is taken as the final optimized cluster spacing range of the target reservoir cluster spacing.

[0054] This method is used to further improve the optimization accuracy based on the previous perforation cluster spacing optimization method.

[0055] Next, the detailed process of the method of the embodiment of the present invention is described in detail based on the accompanying drawings. The steps shown in the flowchart of the accompanying drawings can be executed in a computer system including a set of computer executable instructions. Although the logical order of each step is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than here.

[0056] Embodiment 1

[0057] Figure 1 FIG. 1 shows a schematic flow chart of a dual-objective optimization method for cluster spacing based on crack extension morphology and productivity provided in the first embodiment of the present invention, referring to FIG. Figure 1 It can be seen that the method includes the following steps.

[0058] Steps for constructing a fracturing geological model: obtaining reservoir geological engineering parameters of the target reservoir according to requirements, and establishing a number of fracturing geological models matching the target reservoir based on the parameters;

[0059] Fracture propagation simulation step: setting a perforation cluster spacing list, and performing fracture propagation simulation based on the fracturing geological model and the set process parameters;

[0060] Crack morphology optimization step: After the crack extension simulation is completed, the crack extension uniformity coefficient is calculated according to the crack extension morphology data, and the first cluster spacing set is optimized with the crack extension uniformity coefficient as the target;

[0061] Capacity simulation cluster spacing setting step: filling in gaps and extending based on the first cluster spacing set to form a continuous capacity simulation cluster spacing range;

[0062] Geological capacity simulation steps: after establishing corresponding production geological models for different cluster spacings within the capacity simulation cluster spacing range based on the basic data of the target reservoir, the capacity simulation is carried out using the production simulation system;

[0063] Production capacity optimization step: according to the production capacity simulation results of each production geological model, the second cluster spacing set is optimized based on the principle of maximizing production capacity;

[0064] The target cluster spacing optimization step is to take the intersection of the obtained first cluster spacing set and the second cluster spacing set as the final optimized cluster spacing range of the target reservoir cluster spacing.

[0065] The dual-objective optimization method of the embodiment of the present invention can take into account both the uniformity of fracture expansion and the post-pressure production capacity of oil and gas wells, further improve the accuracy of cluster spacing optimization settings, and can adapt to cluster spacing optimization for various reservoirs. It has strong practicality and operability and high optimization efficiency.

[0066] Optionally, in one embodiment, in the fracturing geological model construction step, the reservoir geological engineering parameters include: porosity, permeability, maximum horizontal principal stress, minimum horizontal principal stress, Young's modulus, Poisson's ratio, and the angle between the maximum horizontal principal stress and the wellbore of the target reservoir.

[0067] Further, in one embodiment, the fracture morphology data of the fracture extension simulation in the fracture extension simulation step includes final fracture distribution and fracture geometric parameters;

[0068] Optionally, in one embodiment, in the fracture extension simulation step, a technician sets a perforation cluster spacing list according to the fracturing construction parameters of a historical reservoir whose geological parameters match the target reservoir.

[0069] Preferably, in one embodiment, in the crack extension simulation step, the dynamic induced stress field corresponding to each cluster of cracks is calculated according to the fracturing process parameters corresponding to different perforation cluster spacings, and then based on the dynamic induced stress field, a phase field method crack damage evolution model is used to implement complex dynamic crack extension simulation to obtain the final fracture morphology data for each different perforation cluster spacing scheme.

[0070] Furthermore, in one embodiment, in the fracture propagation simulation step, the process of calculating the dynamic induced stress field corresponding to each cluster of fractures according to the fracturing process parameters corresponding to different perforation cluster spacings includes:

[0071] The geological parameters of the geological model and the information of different perforation cluster spacing are input into the multi-cluster fracture flow distribution model, and the fracturing process parameters of each cluster fracture in different perforation cluster spacing schemes are analyzed, including dynamic injection flow and fracture mouth pressure;

[0072] The fracturing process parameters of each cluster of fractures are taken as boundary conditions, and the fluid-solid coupling stress field model of fractures is used to calculate the dynamic induced stress field of each cluster of fractures corresponding to different cluster spacings.

[0073] In practical applications, the crack propagation simulation process in the crack propagation simulation step includes the following operations:

[0074] The multi-cluster fracture flow distribution model is used to calculate the dynamic injection flow and fracture mouth pressure of each fracture cluster in different perforation cluster spacing schemes.

[0075] The dynamic injection flow rate and the fracture mouth pressure of each fracture cluster are used as boundary conditions, and the dynamic induced stress field of each fracture cluster is calculated using the fracture fluid-solid coupling stress field model.

[0076] According to the dynamic induced stress field of each cluster of cracks, the phase field method fracture damage evolution model is used to simulate the complex dynamic fracture propagation, and the final fracture morphology and fracture geometric parameters of different perforation cluster spacing schemes are obtained.

[0077] Furthermore, in a preferred embodiment, in the crack morphology optimization step, the crack extension uniformity coefficient is calculated according to the crack geometric parameters of the extension simulation according to the following formula:

[0078]

[0079] Where: ξ is the crack extension uniformity coefficient; ω i is the crack width of the i-th crack, a i is the length of the i-th crack unit, m; n min Represents the minimum number of crack units, dimensionless, n max Indicates the maximum number of elements in each crack, dimensionless, ω i,min represents the minimum width of each crack in the i-th unit, m, ω i,max represents the maximum width of each crack in the i-th unit, m, and h represents the crack height, m.

[0080] Specifically, in an optional embodiment, in the capacity simulation cluster spacing setting step, the cluster spacing in the first cluster spacing set is extended forward and backward according to a set ratio. In actual application, the forward and backward extension ratios may be the same or different, and may be set according to actual conditions and needs, thereby achieving flexible and scientifically reasonable capacity cluster spacing range settings.

[0081] Optionally, in one embodiment, in the geological productivity simulation step, the process of establishing corresponding production geological models for different cluster spacings within the productivity simulation cluster spacing range based on the basic data of the target reservoir includes:

[0082] The reservoir logging data is analyzed to determine the reservoir parameters and fracture parameters related to the production, and a production geological model corresponding to different cluster spacings is established based on the reservoir parameters and fracture parameters, wherein the reservoir characteristic parameters include the formation pressure, porosity, permeability, water saturation, effective thickness of the reservoir and horizontal well section length, and the fracture parameters include fracture half-length, fracture width and fracture conductivity.

[0083] In actual application, the production simulation system used is a virtual production simulation system on the computer side, which can automatically obtain the production cycle records and cycle capacity data corresponding to different production pressure difference parameters and different production cycle (time) parameters, and calculate the cumulative capacity as the capacity simulation result based on the cycle capacity data. In actual application, when the capacity geological model corresponding to different perforation cluster spacing is used for capacity simulation, the production pressure difference parameters used are consistent.

[0084] In addition, in order to comprehensively simulate the impact of different production pressure differences on capacity simulation, in an optional embodiment, multiple groups of capacity simulation processes can be performed for different feasible production pressure differences, and capacity data corresponding to multiple production pressure difference parameters can be obtained for each cluster spacing. The extreme values ​​of the difference that reach the set conditions are removed, and the average value is obtained as the final capacity simulation result.

[0085] The dual-objective optimization method for cluster spacing based on fracture extension morphology and productivity provided by the present invention can take into account both the uniformity of fracture extension and the productivity of oil and gas wells after pressure reduction, and further improve the optimization accuracy on the basis of the previous perforation cluster spacing optimization method; the present invention can adapt to the cluster spacing optimization of various reservoirs, has strong operability and high optimization efficiency.

[0086] The present invention is further described below in conjunction with examples of implementation. The scope of the present invention is not limited by the examples, but is set forth in the claims.

[0087] For a certain target reservoir, when the dual-objective optimization method of cluster spacing based on fracture extension morphology and productivity of the present invention is adopted, the following steps are specifically included:

[0088] Step 1: Collect reservoir geological engineering parameters of the target work area (Table 1);

[0089] Table 1

[0090] parameter Numeric parameter Numeric Porosity, % 7 Permeability, mD 0.2 Maximum horizontal principal stress, MPa 75 Minimum horizontal principal stress, MPa 65 Young's modulus, GPa 23 Poisson's ratio 0.23 Angle between maximum horizontal principal stress and wellbore,° 70

[0091] Step 2: Based on the reservoir geological engineering parameters in Table 1, set the horizontal wellbore and perforation clusters to establish Figure 2 The reservoir fracturing geological model is shown;

[0092] Step 3: Setting simulation parameters of reservoir fracturing geological model (Table 2);

[0093] Table 2

[0094] Cluster spacing Displacement Liquid volume 8 <![CDATA[12m 3 / min]]> <![CDATA[1000m 3 ]]> 9 <![CDATA[12m 3 / min]]> <![CDATA[1000m 3 ]]> 10 <![CDATA[12m 3 / min]]> <![CDATA[1000m 3 ]]> 11 <![CDATA[12m 3 / min]]> <![CDATA[1000m 3 ]]>

[0095] Step 4: Based on the simulation parameters in Table 2, the fracture propagation simulation is performed on the reservoir fracturing geological model to simulate the complex fracture propagation morphology under different simulation parameter schemes;

[0096] Step 5: Calculate the crack extension uniformity coefficient for each simulation result (e.g. Figure 3 As shown), and the preferred cluster spacing range is (9-11m);

[0097] Step 6: According to the basic data of the target reservoir, establish horizontal well models with different cluster spacings and set simulation parameters (see Table 3);

[0098] Table 3

[0099] parameter Numeric parameter Numeric Horizontal section length, m 1000 Production time, year 3 Porosity, % 7 Permeability, mD 0.2 Crack half length, m 150 Fracture conductivity, D·cm 5 Cluster spacing, m 8、9、10、11

[0100] Step 7: Conduct capacity simulation to obtain the cumulative output at different times (such as Figure 4 As shown), the preferred cluster spacing range is (8-10m);

[0101] Step 8: Take the intersection of the cluster spacing optimized for the fracture extension morphology and the cluster spacing optimized for the productivity simulation to obtain the final cluster spacing range (9-10m).

[0102] For the above-mentioned method embodiments, for the sake of simplicity, they are all described as a series of action combinations, but those skilled in the art should know that the present invention is not limited by the order of the actions described, because according to the present invention, some steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present invention.

[0103] It should be pointed out that in other embodiments of the present invention, the method can also obtain a new fracturing cluster spacing optimization method by combining one or several of the above embodiments to achieve accurate optimal setting of the fracturing cluster spacing.

[0104] It should be noted that, based on the method in any one or more of the above embodiments of the present invention, the present invention also provides a storage medium, which stores program code that can implement the method as described in any one or more of the above embodiments, and when the code is executed by the operating system, it can implement the above-mentioned dual-objective optimization method of cluster spacing based on crack extension morphology and production capacity.

[0105] Embodiment 2

[0106] The method is described in detail in the embodiments disclosed in the present invention. The method of the present invention can be implemented by various devices or systems. Therefore, based on other aspects of the method described in any one or more embodiments, the present invention also provides a dual-objective optimization system for cluster spacing based on crack extension morphology and productivity. The system is used to execute the dual-objective optimization method for cluster spacing based on crack extension morphology and productivity described in any one or more embodiments. Specific embodiments are given below for detailed description.

[0107] Specifically, Figure 5 FIG. 4 is a schematic diagram showing a dual-objective optimization system for cluster spacing based on crack extension morphology and productivity provided in an embodiment of the present invention. Figure 5 As shown, the system includes:

[0108] A fracturing geological model building module, which is configured to obtain reservoir geological engineering parameters of a target reservoir according to requirements, and to establish a number of fracturing geological models matching the target reservoir based on the parameters;

[0109] A fracture extension simulation module, which is configured to set a perforation cluster spacing list and perform fracture extension simulation based on the fracturing geological model according to set process parameters;

[0110] A crack morphology optimization module is configured to calculate the crack extension uniformity coefficient according to the crack extension morphology data after the crack extension simulation is completed, and to optimize the first cluster spacing set with the crack extension uniformity coefficient as the target;

[0111] A capacity simulation cluster spacing setting module, configured to fill in gaps and extend the first cluster spacing set to form a continuous capacity simulation cluster spacing range;

[0112] A geological capacity simulation module is configured to establish corresponding production geological models for different cluster spacings within the capacity simulation cluster spacing range based on basic data of the target reservoir, and then use the production simulation system to carry out capacity simulation;

[0113] A capacity optimization module is configured to optimize the second cluster spacing set based on the capacity simulation results of each production geological model and the principle of maximizing capacity;

[0114] The target cluster spacing optimization module is configured to take the intersection of the obtained first cluster spacing set and the second cluster spacing set as the final optimized cluster spacing range of the target reservoir cluster spacing.

[0115] Preferably, in some embodiments, the reservoir geological engineering parameters are set to include: porosity, permeability, maximum horizontal principal stress, minimum horizontal principal stress, Young's modulus, Poisson's ratio, and the angle between the maximum horizontal principal stress and the wellbore of the target reservoir.

[0116] Furthermore, in an optional embodiment, the fracture morphology data of the extended simulation includes final fracture distribution and fracture geometric parameters.

[0117] Further, in an optional embodiment, the fracture extension simulation module is configured to set a perforation cluster spacing list according to the fracturing construction parameters of the historical reservoir whose geological parameters match the target reservoir.

[0118] In an optional embodiment, the crack extension simulation module is configured as follows: according to the fracturing process parameters corresponding to different perforation cluster spacings, the dynamic induced stress field corresponding to each cluster of cracks is calculated; then based on the dynamic induced stress field, a phase field method crack damage evolution model is used to implement complex dynamic crack extension simulation, and the final crack morphology data for each different perforation cluster spacing scheme is obtained.

[0119] Further, in an optional embodiment, the fracture propagation simulation module is configured to calculate the dynamic induced stress field corresponding to each cluster of fractures according to the fracturing process parameters corresponding to different perforation cluster spacings by performing the following operations:

[0120] The geological parameters of the geological model and the information of different perforation cluster spacing are input into the multi-cluster fracture flow distribution model, and the fracturing process parameters of each cluster fracture in different perforation cluster spacing schemes are analyzed, including dynamic injection flow and fracture mouth pressure;

[0121] The fracturing process parameters of each cluster of fractures are taken as boundary conditions, and the fluid-solid coupling stress field model of fractures is used to calculate the dynamic induced stress field of each cluster of fractures corresponding to different cluster spacings.

[0122] Specifically, in a preferred embodiment, the crack morphology optimization module calculates the crack extension uniformity coefficient according to the crack geometric parameters of the extension simulation according to the following formula:

[0123]

[0124] Where: ξ is the crack extension uniformity coefficient; ω i is the crack width of the i-th crack, a i is the length of the i-th crack unit, m; n min Represents the minimum number of crack units, dimensionless, n max Indicates the maximum number of elements in each crack, dimensionless, ω i,min represents the minimum width of each crack in the i-th unit, m, ω i,max represents the maximum width of each crack in the i-th unit, m, and h represents the crack height, m.

[0125] Furthermore, in a preferred embodiment, the capacity simulation cluster spacing setting module is configured to: extend forward and backward respectively according to a set ratio based on the number of cluster spacings in the first cluster spacing set.

[0126] In actual application, the forward and backward extension ratios can be the same or different, and can be set separately according to actual conditions and needs, thereby achieving flexible and scientifically reasonable capacity cluster spacing range settings.

[0127] In an optional embodiment, the geological productivity simulation module is configured to perform the following operations to establish corresponding production geological models for different cluster spacings within the productivity simulation cluster spacing range based on the basic data of the target reservoir:

[0128] The reservoir logging data is analyzed to determine the reservoir parameters and fracture parameters related to the production, and a production geological model corresponding to different cluster spacings is established based on the reservoir parameters and fracture parameters, wherein the reservoir characteristic parameters include the formation pressure, porosity, permeability, water saturation, effective thickness of the reservoir and horizontal well section length, and the fracture parameters include fracture half-length, fracture width and fracture conductivity.

[0129] In the dual-objective optimization system for cluster spacing based on crack extension morphology and productivity provided by the embodiment of the present invention, each module or unit structure can operate independently or in combination according to actual parameter setting requirements and simulation data processing requirements to achieve corresponding technical effects.

[0130] It should be understood that the embodiments disclosed in the present invention are not limited to the specific structures, processing steps or materials disclosed herein, but should be extended to equivalent substitutions of these features understood by ordinary technicians in the relevant field. It should also be understood that the terms used herein are only used for the purpose of describing specific embodiments and are not meant to be limiting.

[0131] The "one embodiment" mentioned in the specification means that a particular feature, structure or characteristic described in conjunction with the embodiment is included in at least one embodiment of the present invention. Therefore, the phrase "one embodiment" appearing in various places throughout the specification does not necessarily refer to the same embodiment.

[0132] Although the embodiments disclosed in the present invention are as above, the above contents are only embodiments adopted for facilitating the understanding of the present invention and are not intended to limit the present invention. Any technician in the technical field to which the present invention belongs can make any modifications and changes in the form and details of the implementation without departing from the spirit and scope disclosed in the present invention, but the patent protection scope of the present invention shall still be subject to the scope defined in the attached claims.

Claims

1. A dual-objective optimization method for cluster spacing based on crack extension morphology and productivity, characterized in that: The method comprises: Steps for constructing a fracturing geological model: obtaining reservoir geological engineering parameters of the target reservoir according to requirements, and establishing a number of fracturing geological models matching the target reservoir based on the parameters; Fracture propagation simulation step: setting a perforation cluster spacing list, and performing fracture propagation simulation based on the fracturing geological model and the set process parameters; Crack morphology optimization step: After the crack extension simulation is completed, the crack extension uniformity coefficient is calculated according to the crack extension morphology data, and the first cluster spacing set is optimized with the crack extension uniformity coefficient as the target; Capacity simulation cluster spacing setting step: filling in gaps and extending based on the first cluster spacing set to form a continuous capacity simulation cluster spacing range; Geological capacity simulation steps: after establishing corresponding production geological models for different cluster spacings within the capacity simulation cluster spacing range based on the basic data of the target reservoir, the capacity simulation is carried out using the production simulation system; Production capacity optimization step: according to the production capacity simulation results of each production geological model, the second cluster spacing set is optimized based on the principle of maximizing production capacity; The target cluster spacing optimization step is: taking the intersection of the first cluster spacing set and the second cluster spacing set obtained as the final optimized cluster spacing range of the target reservoir cluster spacing.

2. The method according to claim 1, characterized in that The reservoir geological engineering parameters include: porosity, permeability, maximum horizontal principal stress, minimum horizontal principal stress, Young's modulus, Poisson's ratio, and the angle between the maximum horizontal principal stress and the wellbore of the target reservoir.

3. The method according to claim 1, characterized in that The fracture morphology data of the extended simulation includes final fracture distribution and fracture geometric parameters.

4. The method according to claim 1, characterized in that In the fracture propagation simulation step, a technician sets a perforation cluster spacing list according to the fracturing construction parameters of a historical reservoir whose geological parameters match the target reservoir.

5. The method according to claim 1, characterized in that In the crack extension simulation step, the dynamic induced stress field corresponding to each cluster of cracks is calculated according to the fracturing process parameters corresponding to different perforation cluster spacings, and then based on the dynamic induced stress field, the phase field method crack damage evolution model is used to realize complex dynamic crack extension simulation, and the final fracture morphology data of each different perforation cluster spacing scheme is obtained.

6. The method according to claim 5, characterized in that In the fracture propagation simulation step, the process of calculating the dynamic induced stress field corresponding to each cluster of fractures according to the fracturing process parameters corresponding to different perforation cluster spacings includes: The geological parameters of the geological model and the information of different perforation cluster spacing are input into the multi-cluster fracture flow distribution model, and the fracturing process parameters of each cluster fracture in different perforation cluster spacing schemes are analyzed, including dynamic injection flow and fracture mouth pressure; The fracturing process parameters of each cluster of fractures are taken as boundary conditions, and the fluid-solid coupling stress field model of fractures is used to calculate the dynamic induced stress field of each cluster of fractures corresponding to different cluster spacings.

7. The method according to claim 1, characterized in that In the crack morphology optimization step, the crack extension uniformity coefficient is calculated according to the crack geometric parameters of the extension simulation according to the following formula: Where: ξ is the crack extension uniformity coefficient; ω i is the crack width of the i-th crack, a i is the length of the i-th crack unit, m; n min Represents the minimum number of crack units, dimensionless, n max Indicates the maximum number of units in each crack, dimensionless, ω i,min represents the minimum width of each crack in the i-th unit, m, ω i,max represents the maximum width of each crack in the i-th unit, m, and h represents the crack height, m.

8. The method according to claim 1, characterized in that: In the capacity simulation cluster spacing setting step, the cluster spacings in the first cluster spacing set are extended forward and backward respectively according to a set ratio. In actual application, the forward and backward extension ratios can be the same or different, and can be set separately according to actual conditions and needs, thereby achieving flexible and scientifically reasonable capacity cluster spacing range settings.

9. The method according to claim 1, characterized in that: In the geological productivity simulation step, the process of establishing corresponding production geological models for different cluster spacings within the productivity simulation cluster spacing range based on the basic data of the target reservoir includes: The reservoir logging data is analyzed to determine the reservoir parameters and fracture parameters related to the production, and a production geological model corresponding to different cluster spacings is established based on the reservoir parameters and fracture parameters, wherein the reservoir characteristic parameters include the formation pressure, porosity, permeability, water saturation, effective thickness of the reservoir and horizontal well section length, and the fracture parameters include fracture half-length, fracture width and fracture conductivity.

10. A dual-objective optimization system for cluster spacing based on crack extension morphology and productivity, characterized in that: The system executes the method according to any one of claims 1 to 9.

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