Sleeve transformation risk grade division method and device, electronic equipment and storage medium

Abstract

The invention discloses a casing deformation risk grade division method and device, electronic equipment and a storage medium. The method comprises the following steps: collecting a three-dimensional seismic data volume of a work area, and predicting distribution characteristics and scales of natural fractures in the three-dimensional seismic data volume to obtain a fracture distribution scale; loading the actual drilling trajectory of the horizontal well to be fractured into a predetermined three-dimensional geologic model, and determining the stress difference values of different positions and the relative position relation of natural fractures; and according to the crack distribution scale, the stress difference value and the relative position relation of the natural cracks, casing deformation risk grades are divided. According to the technical scheme, on the basis of pre-fracturing earthquake and geological data, the engineering risks of different well sections can be accurately evaluated, so that the casing deformation risk in the fracturing process is effectively reduced, and powerful support is provided for unconventional oil and gas resource benefit development.

Description

Technical Field

[0001] The present invention relates to the technical field of unconventional oil and gas resource development, and in particular to a method, device, electronic equipment and storage medium for classifying risk levels of casing changes. Background Art

[0002] With the development of unconventional oil and gas resource exploration and development at home and abroad, China has achieved leapfrog development in shale gas exploration and development, becoming the third country to achieve industrialized production of shale gas after the United States and Canada. my country's shale gas reservoirs have the characteristics of poor reservoir properties, strong heterogeneity, and low natural production capacity, and hydraulic fracturing must be carried out before production. Horizontal well volume fracturing technology can effectively improve the seepage characteristics of the wellbore and increase the production capacity of a single well. Due to my country's special tectonic background, the structural activity of shale gas development areas is relatively strong, and my country's shale gas development faces serious casing changes to varying degrees. Casing changes will not only cause the bridge plug to fail to be seated in place, resulting in multi-stage combined pressure or even loss of stages, affecting the fracturing effect, but also increase construction costs and difficulty, shorten the life cycle of the wellbore, and thus reduce the overall economic benefits of shale gas development.

[0003] In the prior art, some researchers regard multiple fracturing sections as different areas, and calculate the slope of the frequency-magnitude distribution relationship of seismic events in a certain area respectively, so as to obtain the continuous change characteristics of the slope of the frequency-magnitude distribution relationship of seismic events in a certain area along the horizontal well section, and use the continuous change characteristics of the slope of the frequency-magnitude distribution relationship of seismic events in a certain area to identify fault activation information, which is used to judge and warn of casing deformation.

[0004] However, for researchers, this method can only be implemented during the fracturing process. By analyzing the changes in the slope of the frequency-magnitude distribution relationship of earthquake events in a certain area, it can be determined which section induced fault activity during the fracturing process. However, the fault activity may have already caused casing deformation and cannot play a role in early prediction of casing deformation. Summary of the invention

[0005] The present invention provides a casing change risk level classification method, device, electronic equipment and storage medium, which can accurately evaluate the engineering risks of different well sections based on pre-fracturing seismic and geological data, thereby effectively reducing the casing change risk during fracturing, thereby providing strong support for the efficient development of unconventional oil and gas resources.

[0006] According to one aspect of the present invention, a method for classifying risk levels of a change is provided, the method comprising:

[0007] Collecting three-dimensional seismic data of the work area, and predicting the distribution characteristics and scale of natural fractures in the three-dimensional seismic data to obtain the distribution scale of fractures;

[0008] Load the actual drilling trajectory of the horizontal well to be fractured into a pre-determined three-dimensional geological model to determine the stress difference at different positions and the relative position relationship of the natural fractures;

[0009] The casing deformation risk level is divided according to the crack distribution scale, stress difference and relative position relationship of natural cracks.

[0010] According to another aspect of the present invention, a device for classifying risk levels of a set change is provided, the device comprising:

[0011] A fracture distribution scale obtaining module is used to collect three-dimensional seismic data volumes of the work area, and predict the distribution characteristics and scale of natural fractures in the three-dimensional seismic data volumes to obtain the fracture distribution scale;

[0012] A module for determining the relative position relationship between stress difference and natural fractures, which is used to load the actual drilling trajectory of the horizontal well to be fractured into a predetermined three-dimensional geological model to determine the relative position relationship between stress difference and natural fractures at different positions;

[0013] The casing change risk level classification module is used to classify casing change risk levels according to the crack distribution scale, stress difference and relative position relationship of natural cracks.

[0014] According to another aspect of the present invention, there is provided an electronic device, the electronic device comprising:

[0015] at least one processor; and

[0016] a memory communicatively connected to the at least one processor; wherein,

[0017] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute a method for classifying set change risk levels as described in any embodiment of the present invention.

[0018] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement a method for classifying set change risk levels as described in any embodiment of the present invention when executed.

[0019] The technical solution of the embodiment of the present invention collects three-dimensional seismic data of the work area, predicts the distribution characteristics and scale of natural fractures in the three-dimensional seismic data, obtains the scale of fracture distribution, and then loads the actual drilling trajectory of the horizontal well to be fractured into a predetermined three-dimensional geological model to determine the stress difference at different positions and the relative position relationship of natural fractures, and divides the casing change risk level according to the fracture distribution scale, stress difference and the relative position relationship of natural fractures. This technical solution can accurately evaluate the engineering risks of different well sections based on pre-fracturing seismic and geological data, thereby effectively reducing the risk of casing change during fracturing, thereby providing strong support for the efficient development of unconventional oil and gas resources.

[0020] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0022] Figure 1 This is a flow chart of a method for classifying risk levels of a change of a set of equipment provided in accordance with the first embodiment of the present invention;

[0023] Figure 2 The natural fracture prediction result map of the study area provided in Example 1 of the present application;

[0024] Figure 3 The horizontal well logging interpretation data and results provided in Example 1 of this application;

[0025] Figure 4 The horizontal stress difference model of the study area provided in Example 1 of the present application;

[0026] Figure 5 The risk level classification result of the research area provided in Example 1 of this application;

[0027] Figure 6 This is a schematic diagram of the structure of a device for classifying risk levels of a change of a set of equipment provided according to the second embodiment of the present invention;

[0028] Figure 7 It is a structural schematic diagram of an electronic device for implementing a method for classifying risk levels of a set change according to an embodiment of the present invention. DETAILED DESCRIPTION

[0029] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0030] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0031] Embodiment 1

[0032] Figure 1 This is a flow chart of a casing change risk level classification method provided according to the first embodiment of the present invention. This embodiment can be applied to the case of evaluating casing change risk levels of different depth sections before horizontal well fracturing. The method can be executed by a casing change risk level classification device, which can be implemented in the form of hardware and / or software. The casing change risk level classification device can be configured in a device. For example, the device can be a background server or other device with communication and computing capabilities. Figure 1 As shown, the method includes:

[0033] S110, collecting a three-dimensional seismic data volume of the work area, and predicting the distribution characteristics and scale of natural fractures in the three-dimensional seismic data volume to obtain the distribution scale of fractures.

[0034] In this scheme, the three-dimensional seismic data volume of the work area can be collected through seismic exploration technology, and then the fracture prediction technology can be used to predict the distribution characteristics and scale of natural fractures in the study area.

[0035] Optionally, after obtaining the crack distribution scale, the method further includes:

[0036] Determines how horizontal stress differences are calculated.

[0037] Specifically, mechanical parameters and horizontal stress differences are simulated and calculated based on relevant geological and logging data.

[0038]

[0039]

[0040] Among them, V p 、V s is the speed of sound of longitudinal and transverse waves (ft / us).

[0041] The dynamic elastic parameters are calculated according to the following formula:

[0042]

[0043] E d =2V s 2 ρ(1+μ d );

[0044] Where, μ is the dynamic Poisson’s ratio, which has no unit; E is the dynamic elastic modulus (GPa); ρ is the logging rock density (g / cm 3 ).

[0045] Furthermore, the calculation method of horizontal stress difference is determined, including:

[0046] The following formula is used to describe the horizontal stress difference;

[0047]

[0048]

[0049] σ HD =σ H -σ h ;

[0050] Among them, σ HD is the horizontal stress difference, σ h is the minimum horizontal stress difference, σ H is the maximum horizontal stress difference, μ is the dynamic Poisson’s ratio, S v is the overlying formation pressure, α is the Boit coefficient, P P is the pore pressure value that changes with time, E is the dynamic elastic modulus, ε h With ε H Construct stress coefficient values ​​for the horizontal stress directions.

[0051] S120, loading the actual drilling trajectory of the horizontal well to be fractured into a predetermined three-dimensional geological model, and determining the stress difference at different positions and the relative position relationship of the natural fractures.

[0052] In this scheme, the actual drilling trajectory of the horizontal well to be fractured is loaded into a predetermined three-dimensional geological model. Based on the stress difference calculation formula in the three-dimensional geological model and other analysis methods, the stress difference at different positions and the relative position relationship of the natural fractures can be determined.

[0053] S130. Classify casing change risk levels according to the crack distribution scale, stress difference and relative position relationship of natural cracks.

[0054] In this scheme, the risk level of housing change includes the first-level housing change risk level, the second-level housing change risk level, the third-level housing change risk level, the fourth-level housing change risk level and the fifth-level housing change risk level. Among them, the first-level housing change risk is expressed as a high risk level, the second-level housing change risk is expressed as a medium-high risk level, the third-level housing change risk is expressed as a medium risk level, the fourth-level housing change risk is expressed as a medium-low risk level and the fifth-level housing change risk is expressed as a low risk level.

[0055] Furthermore, the casing deformation risk is evaluated by comprehensively considering the crack distribution scale, horizontal stress difference and relative position relationship.

[0056] Optionally, the casing deformation risk level is divided according to the relative position relationship of the crack distribution scale, stress difference and natural cracks, including:

[0057] Based on the crack distribution scale, the comparison result of the stress difference with the preset threshold value and the relative position relationship of the natural cracks, the casing change risk level is divided.

[0058] Among them, the preset threshold can be divided according to the risk level of the change.

[0059] In this embodiment, the relative position relationship of the natural fractures may refer to the position relationship between the natural fractures and the wellbore, including intersection and non-intersection. That is, the relative position relationship of the natural fractures is that the natural fractures and the wellbore intersect or do not intersect.

[0060] Specifically, the risk level of casing deformation can be divided by comprehensively analyzing the crack distribution scale, the comparison results of the stress difference with the preset threshold, and the relative position relationship of the natural cracks.

[0061] By evaluating the casing change risk level at different depths before horizontal well fracturing, it is helpful to reduce the casing change rate of horizontal wells while ensuring the post-fracturing production, providing technical support for the efficient development of unconventional oil and gas resources.

[0062] Optionally, based on the crack distribution scale, the comparison result of the stress difference with the preset threshold value and the relative position relationship of the natural cracks, the casing change risk level is divided, including:

[0063] When the crack distribution scale is greater than a preset first threshold, the stress difference is greater than a preset second threshold, and the natural crack intersects with the wellbore, the casing change risk level is classified as a first-level casing change risk;

[0064] When the crack distribution scale is greater than a preset first threshold, the stress difference is less than a preset second threshold, and the natural crack intersects with the wellbore, the casing change risk level is classified as a secondary casing change risk;

[0065] When the crack distribution scale is smaller than the preset first threshold, the stress difference is smaller than the preset second threshold, and the natural crack intersects with the wellbore, the casing change risk level is classified as the third-level casing change risk;

[0066] When the crack distribution scale is smaller than the preset first threshold, the stress difference is smaller than the preset second threshold, and the natural cracks do not intersect the wellbore, the casing change risk level is classified as level 4 casing change risk;

[0067] When the crack distribution scale is undeveloped and the stress difference is less than the preset second threshold, the casing change risk level is classified as level five casing change risk.

[0068] In this solution, the first threshold can be set to 100m, and the second threshold can be set to 20Mpa.

[0069] Specifically, the first-level casing change risk section division standard is: the scale of fracture development is greater than 100m, the stress difference is greater than 20MPa, and the natural fractures intersect with the wellbore; the second-level casing change risk section division standard is: the scale of fracture development is greater than 100m, the stress difference is less than 20MPa, and the natural fractures intersect with the wellbore; the third-level casing change risk section division standard is: the scale of fracture development is less than 100m, the stress difference is less than 20MPa, and the natural fractures intersect with the wellbore; the fourth-level casing change risk section division standard is: the scale of fracture development is less than 100m, the stress difference is less than 20MPa, and the natural fractures do not intersect with the wellbore; the fifth-level casing change risk section division standard is: no fractures are developed, and the stress difference is less than 20MPa.

[0070] By evaluating the casing change risk level at different depths before horizontal well fracturing, it is helpful to reduce the casing change rate of horizontal wells while ensuring the post-fracturing production, providing technical support for the efficient development of unconventional oil and gas resources.

[0071] Optionally, the horizontal well fracturing parameters include a first horizontal well fracturing parameter, a second horizontal well fracturing parameter, a third horizontal well fracturing parameter, a fourth horizontal well fracturing parameter and a fifth horizontal well fracturing parameter;

[0072] Accordingly, after classifying the risk levels of the change, the method further includes:

[0073] According to the association between the predetermined casing change risk level and the fracturing construction parameters of different well sections of the horizontal well, the horizontal well fracturing parameters corresponding to the casing change risk level are determined.

[0074] In this embodiment, the fracturing construction parameters of different sections of horizontal wells are optimized for different casing change risk levels. Among them, the horizontal well fracturing parameters corresponding to the first casing change risk level are the first horizontal well fracturing parameters; the horizontal well fracturing parameters corresponding to the second casing change risk level are the second horizontal well fracturing parameters; the horizontal well fracturing parameters corresponding to the third casing change risk level are the third horizontal well fracturing parameters; the horizontal well fracturing parameters corresponding to the fourth casing change risk level are the fourth horizontal well fracturing parameters; and the horizontal well fracturing parameters corresponding to the fifth casing change risk level are the fifth horizontal well fracturing parameters.

[0075] Specifically, the optimization of the parameters and construction suggestions for the risk section of the first-stage transformer: the liquid strength is 25m 3 / m, liquid volume 1500m 3 , sand adding strength 2t / m, sand quantity 120t, 70 / 140 mesh quartz sand 80t, 40 / 70 mesh ceramsite 40t, construction displacement 14-16m 3 / min, and throw the ball twice, each time 12 19mm temporary plugging balls are thrown in, and then 260kg of temporary plugging agent is thrown in, and the construction pressure is controlled to be ≤120MPa. Parameter optimization and construction suggestions for the risk section of the secondary casing change: Liquid strength 25m 3 / m, liquid volume 1500m 3 , sand adding strength 2t / m, sand quantity 120t, 70 / 140 mesh quartz sand 80t, 40 / 70 mesh ceramsite 40t, construction displacement 16-18m 3 / min, and throw the ball twice, each time 12 19mm temporary plugging balls are thrown, and then 260kg of temporary plugging agent is thrown, and the construction pressure is controlled to be ≤120MPa. Parameter optimization and construction suggestions for the risk section of the third-level casing change: liquid strength 30m 3 / m, liquid volume 1800m 3 , sand adding strength 2t / m, sand quantity 120t, 70 / 140 mesh quartz sand 80t, 40 / 70 mesh ceramsite 40t, construction displacement 16-18m 3 / min, drop the ball twice, 12 19mm temporary plugging balls are dropped each time, a total of 24 balls, and the construction pressure is controlled to be ≤120MPa. Parameter optimization and construction suggestions for the risk section of the fourth-level casing transformer: Liquid strength 35m 3 / m, liquid volume 2100m 3 , sand adding strength 3t / m, sand quantity 180t, 70 / 140 mesh quartz sand 100t, 40 / 70 mesh ceramsite 80t, construction displacement 16-18m 3 / min, with two balls, 12 19mm temporary plugging balls each time, a total of 24 balls, and the construction pressure is controlled to be ≤120MPa. Parameter optimization and construction suggestions for the risk section of the five-stage casing transformer: Liquid strength 35m 3 / m, liquid volume 2100m 3 , sand adding strength 3t / m, sand quantity 180t, 70 / 140 mesh quartz sand 100t, 40 / 70 mesh ceramsite 80t, construction displacement not less than 18m 3 / min, with 12 19mm temporary plugging balls thrown in twice, each time, for a total of 24 balls, and the construction pressure was controlled to be ≤120MPa.

[0076] By comprehensively considering geomechanics, fracture prediction results, and the relative position relationship between fracture development characteristics and wellbore, the risk levels of different depths in the horizontal section are divided, and different pumping programs are designed for different well sections. The displacement, liquid volume, construction scale and other engineering parameters corresponding to different risk levels are quantitatively characterized to optimize the fracturing plan. Through the pre-fracturing risk level assessment, the risk level of different locations can be accurately assessed before the fracturing operation, effectively reducing the risk of casing change, while ensuring the production capacity effect of horizontal wells after fracturing, providing technical guidance for the efficient development of unconventional oil and gas reservoirs.

[0077] The technical solution of the embodiment of the present invention collects three-dimensional seismic data of the work area, predicts the distribution characteristics and scale of natural fractures in the three-dimensional seismic data, obtains the scale of fracture distribution, and then loads the actual drilling trajectory of the horizontal well to be fractured into a predetermined three-dimensional geological model to determine the stress difference at different positions and the relative position relationship of natural fractures, and divides the casing change risk level according to the fracture distribution scale, stress difference and the relative position relationship of natural fractures. By implementing this technical solution, on the basis of pre-fracturing seismic and geological data, the engineering risks of different well sections can be accurately evaluated, thereby effectively reducing the risk of casing change during fracturing, thereby providing strong support for the efficient development of unconventional oil and gas resources.

[0078] In this plan, Block A is located in the southern Sichuan low fold belt, indicating that the Silurian Longmaxi Formation in this block has rich shale gas resources. The thickness of the Wufeng Formation-Longyi 1 sub-member I+II reservoirs is distributed between 30-65 meters. The shale gas reservoirs of the Wufeng Formation-Longmaxi Formation in the work area are mainly buried at a depth of 3500-4200m, which is a deep shale gas reservoir.

[0079] Furthermore, Figure 2 The natural fracture prediction result map of the study area provided in Example 1 of this application is based on the single well imaging logging interpretation and combined with the seismic attribute curvature body as the three-dimensional spatial constraint of the fracture to improve the accuracy of three-dimensional fracture modeling. The regional fracture prediction is as follows: Figure 2As shown in the figure, the development of fractures in this area is mainly controlled by micro-structures. The degree of fracture development is significantly correlated with the curvature anomaly. The three-dimensional natural fracture model has a high degree of consistency with the curvature anomaly body. There are many large-scale fracture zones crossing the AH3 platform. It is necessary to optimize the fracturing construction plan to reduce the risks of casing damage and pressure channeling.

[0080] Furthermore, Figure 3 The horizontal well logging interpretation data and results provided in Example 1 of this application are as follows: the horizontal section of well AH3-4 is 1808m long, and the drilling encounter is Long-1 2 , Dragon 1 1 The length of the Wufeng Formation is 98.4%. The logging shows that Longmaxi has been shown 3 times, and the drilling fluid density is 2.13g / cm2 for oil-based mud. 3 , the highest temperature: 135.2℃ (5486.1m), the maximum value of total hydrocarbon is 41.5%. Taking into account the geomechanics, fracture prediction results and the relative position relationship between fracture development characteristics and wellbore, the risk level of AH3-4 well is divided into 5 levels, and different pumping procedures are designed for different well sections to optimize the fracturing plan. At the same time, the geological sweet spot evaluation of AH3-4 well is carried out. The evaluation results are as follows: Figure 3 shown.

[0081] In this embodiment, Figure 4 The horizontal stress difference model of the study area provided in Example 1 of this application is: Figure 5 The risk level classification results of the research area provided in Example 1 of this application are combined with the crack prediction results and the horizontal stress difference model ( Figure 4 ), the formation drilling situation is divided into risk levels. Among them, the first-level casing change risk is represented as a high risk level, the second-level casing change risk is represented as a medium-high risk level, the third-level casing change risk is represented as a medium risk level, the fourth-level casing change risk is represented as a medium-low risk level, and the fifth-level casing change risk is represented as a low risk level. AH3-4 well is divided into 28 sections, such as Figure 5 As shown in Table 1, there are 3 high-risk sections, 3 medium-high-risk sections, 5 medium-risk sections, 4 medium-low-risk sections, and 13 low-risk sections. The well risk level assessment classification table is shown in Table 1.

[0082] Table 1

[0083]

[0084]

[0085] Furthermore, based on the results of the risk level classification and combined with the recommended fracturing construction parameters for different risk levels, the fracturing scheme of the AH3-4 well was optimized and constructed. No casing change occurred during the fracturing construction of the well, and the construction was smooth.

[0086] Embodiment 2

[0087] Figure 6 FIG. 1 is a schematic diagram of a device for classifying risk levels of a set change according to a second embodiment of the present invention. Figure 6 As shown, the device comprises:

[0088] The fracture distribution scale obtaining module 610 is used to collect the three-dimensional seismic data volume of the work area, and predict the distribution characteristics and scale of natural fractures in the three-dimensional seismic data volume to obtain the fracture distribution scale;

[0089] The module 620 for determining the relative position relationship between stress difference and natural fractures is used to load the actual drilling trajectory of the horizontal well to be fractured into a predetermined three-dimensional geological model to determine the relative position relationship between stress difference and natural fractures at different positions;

[0090] The casing change risk level classification module 630 is used to classify casing change risk levels according to the fracture distribution scale, stress difference and relative position relationship of natural fractures.

[0091] Optionally, the risk level classification module 630 includes:

[0092] The casing change risk level classification submodule is used to classify the casing change risk level based on the crack distribution scale, the comparison result of the stress difference and the preset threshold value, and the relative position relationship of the natural cracks.

[0093] Optional, the risk level classification submodule is used to:

[0094] When the crack distribution scale is greater than a preset first threshold, the stress difference is greater than a preset second threshold, and the natural crack intersects with the wellbore, the casing change risk level is classified as a first-level casing change risk;

[0095] When the crack distribution scale is greater than a preset first threshold, the stress difference is less than a preset second threshold, and the natural crack intersects with the wellbore, the casing change risk level is classified as a secondary casing change risk;

[0096] When the crack distribution scale is smaller than the preset first threshold, the stress difference is smaller than the preset second threshold, and the natural crack intersects with the wellbore, the casing change risk level is classified as the third-level casing change risk;

[0097] When the crack distribution scale is smaller than the preset first threshold, the stress difference is smaller than the preset second threshold, and the natural cracks do not intersect the wellbore, the casing change risk level is classified as level 4 casing change risk;

[0098] When the crack distribution scale is undeveloped and the stress difference is less than the preset second threshold, the casing change risk level is classified as level five casing change risk.

[0099] Optionally, the horizontal well fracturing parameters include a first horizontal well fracturing parameter, a second horizontal well fracturing parameter, a third horizontal well fracturing parameter, a fourth horizontal well fracturing parameter and a fifth horizontal well fracturing parameter;

[0100] Accordingly, the device further comprises:

[0101] The horizontal well fracturing parameter determination module is used to determine the horizontal well fracturing parameters corresponding to the casing change risk level according to the association relationship between the predetermined casing change risk level and the fracturing construction parameters of different well sections of the horizontal well.

[0102] Optionally, the device further comprises:

[0103] The module for determining the calculation method of the horizontal stress difference is used to determine the calculation method of the horizontal stress difference.

[0104] Optionally, a module for determining a method for calculating a horizontal stress difference is used to:

[0105] The following formula is used to describe the horizontal stress difference;

[0106]

[0107]

[0108] σ HD =σ H -σ h ;

[0109] Among them, σ HD is the horizontal stress difference, σ h is the minimum horizontal stress difference, σ H is the maximum horizontal stress difference, μ is the dynamic Poisson’s ratio, S v is the overlying formation pressure, α is the Boit coefficient, P P is the pore pressure value that changes with time, E is the dynamic elastic modulus, ε h With ε H Construct stress coefficient values ​​for the horizontal stress directions.

[0110] A set change risk level classification device provided in an embodiment of the present invention can execute a set change risk level classification method provided in any embodiment of the present invention, and has corresponding functional modules and beneficial effects of the execution method.

[0111] Embodiment 3

[0112] Figure 7A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0113] like Figure 7 As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0114] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0115] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as a set of risk level classification methods.

[0116] In some embodiments, a set-change risk level classification method may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the set-change risk level classification method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform a set-change risk level classification method in any other appropriate manner (e.g., by means of firmware).

[0117] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0118] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0119] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0120] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0121] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0122] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0123] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0124] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for classifying risk levels of a set of changes, characterized in that: include: Collecting three-dimensional seismic data of the work area, and predicting the distribution characteristics and scale of natural fractures in the three-dimensional seismic data to obtain the distribution scale of fractures; Load the actual drilling trajectory of the horizontal well to be fractured into a pre-determined three-dimensional geological model to determine the stress difference at different positions and the relative position relationship of the natural fractures; The casing deformation risk level is divided according to the crack distribution scale, stress difference and relative position relationship of natural cracks.

2. The method according to claim 1, characterized in that According to the distribution scale of the cracks, the stress difference and the relative position of the natural cracks, the casing change risk level is divided into: Based on the crack distribution scale, the comparison result of the stress difference with the preset threshold value and the relative position relationship of the natural cracks, the casing change risk level is divided.

3. The method according to claim 2, characterized in that Based on the crack distribution scale, the comparison result of the stress difference with the preset threshold value and the relative position relationship of the natural cracks, the casing change risk level is divided, including: When the crack distribution scale is greater than a preset first threshold, the stress difference is greater than a preset second threshold, and the natural crack intersects with the wellbore, the casing change risk level is classified as a first-level casing change risk; When the crack distribution scale is greater than a preset first threshold, the stress difference is less than a preset second threshold, and the natural crack intersects with the wellbore, the casing change risk level is classified as a secondary casing change risk; When the crack distribution scale is smaller than the preset first threshold, the stress difference is smaller than the preset second threshold, and the natural crack intersects with the wellbore, the casing change risk level is classified as the third-level casing change risk; When the crack distribution scale is smaller than the preset first threshold, the stress difference is smaller than the preset second threshold, and the natural cracks do not intersect the wellbore, the casing change risk level is classified as level 4 casing change risk; When the crack distribution scale is undeveloped and the stress difference is less than the preset second threshold, the casing change risk level is classified as level five casing change risk.

4. The method according to claim 3, characterized in that The horizontal well fracturing parameters include a first horizontal well fracturing parameter, a second horizontal well fracturing parameter, a third horizontal well fracturing parameter, a fourth horizontal well fracturing parameter and a fifth horizontal well fracturing parameter; Accordingly, after classifying the risk levels of the asset change, the method further includes: According to the association between the predetermined casing change risk level and the fracturing construction parameters of different well sections of the horizontal well, the horizontal well fracturing parameters corresponding to the casing change risk level are determined.

5. The method according to claim 1, characterized in that: After obtaining the crack distribution scale, the method further includes: Determines how horizontal stress differences are calculated.

6. The method according to claim 5, characterized in that Determine the method for calculating horizontal stress difference, including: The following formula is used to describe the horizontal stress difference; s HD =s H -s h ; Among them, σ HD is the horizontal stress difference, σ h is the minimum horizontal stress difference, σ H is the maximum horizontal stress difference, μ is the dynamic Poisson’s ratio, S v is the overlying formation pressure, α is the Boit coefficient, P P is the pore pressure value that changes with time, E is the dynamic elastic modulus, ε h With ε H Construct stress coefficient values ​​for the horizontal stress directions.

7. A device for classifying risk levels of a set change, characterized in that: include: A fracture distribution scale obtaining module is used to collect three-dimensional seismic data of the work area, and predict the distribution characteristics and scale of natural fractures in the three-dimensional seismic data to obtain the fracture distribution scale; A module for determining the relative position relationship between stress difference and natural fractures, which is used to load the actual drilling trajectory of the horizontal well to be fractured into a predetermined three-dimensional geological model to determine the relative position relationship between stress difference and natural fractures at different positions; The casing change risk level classification module is used to classify casing change risk levels according to the crack distribution scale, stress difference and relative position relationship of natural cracks.

8. The device according to claim 7, characterized in that The module for classifying risk levels of asset changes includes: The casing change risk level classification submodule is used to classify the casing change risk level based on the crack distribution scale, the comparison result of the stress difference and the preset threshold value, and the relative position relationship of the natural cracks.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory in communication with the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute a method for classifying set change risk levels according to any one of claims 1 to 6.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement a method for classifying set change risk levels according to any one of claims 1 to 6 when executing the computer instructions.

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