A fracturing operation equipment scheduling method and device based on digital twinning, an electronic device and a medium

Abstract

This invention relates to a method, device, electronic equipment, and medium for scheduling fracturing equipment based on digital twins, belonging to the field of resource optimization technology in petroleum exploration operations. The method applies digital twin technology to the scheduling of fracturing equipment. By constructing a twin well site, selecting a scheduling scheme, and conducting simulations and iterations, a better scheduling scheme is obtained. Combined with manual intervention, historical database analysis, and access control, this improves the efficiency of fracturing equipment management, reducing idle time caused by relying on manual experience, minimizing blind spots in fracturing resource scheduling, lowering costs, and increasing operational efficiency. The device, electronic equipment, and medium based on this invention improve the application efficiency of the method and expand its applicability. It is suitable for scheduling fracturing equipment.

Description

Technical Field

[0001] This invention belongs to the field of resource optimization technology for petroleum exploration operations, specifically a method and device for scheduling fracturing equipment, electronic equipment, and media based on digital twins. Background Technology

[0002] Fracturing is an important operation that involves injecting high-pressure fluid to fracture underground rock formations, thereby promoting the flow of oil and gas. The operation involves the configuration and management of various equipment resources. The rational arrangement and allocation of equipment resources is one of the key links to ensure that the operation can be carried out smoothly and efficiently.

[0003] Traditional fracturing equipment scheduling typically relies on the experience of on-site operators and their real-time perception and judgment of the working environment. While this scheduling method offers some flexibility in certain special circumstances, allowing for adjustments to adapt to changing on-site conditions, it also presents numerous problems and challenges. First, traditional scheduling methods generally lack comprehensive monitoring and precise analysis of on-site data, resulting in a lack of scientific basis for equipment scheduling and leaving many pieces of equipment idle or operating inefficiently during operations. This low equipment utilization not only reduces production efficiency but also wastes significant resources and time. Second, scheduling methods relying on human experience are slow to react to emergencies or changes in demand, making it difficult to quickly adjust work arrangements and resource allocation, causing delays in work progress and impacting overall work efficiency and schedule. Furthermore, due to the lack of precise cost management and control methods, scheduling decisions often fail to achieve optimal resource allocation and effective cost control during operations, significantly reducing the overall economic efficiency of the operation and ultimately failing to achieve the expected cost-effectiveness and economic returns. Therefore, traditional scheduling methods have significant limitations in improving efficiency, reducing costs, and optimizing resource allocation. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention first establishes a digital twin system to simulate, iteratively optimize, execute, and monitor the scheduling schemes for individual equipment resources. Then, it collects data on individual equipment scheduling schemes, analyzes and summarizes historical schemes, and optimizes them to form an overall scheduling scheme, ultimately improving equipment scheduling efficiency and optimizing resource allocation.

[0005] Another objective of this invention is to provide an apparatus, electronic device, and computer-readable storage medium based on the above-described digital twin-based fracturing equipment scheduling method.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0007] A method for scheduling fracturing equipment based on digital twins, comprising the following steps performed sequentially:

[0008] S1. Constructing a twin well site: Utilizing digital twin technology to construct a digital twin system of the fracturing operation well site, serving as the twin well site;

[0009] S2. Select a scheduling scheme: Input a fracturing operation equipment scheduling scheme that includes equipment types and quantities of each type of equipment; simulate the scheduling scheme in a digital twin system, and use an objective function to iteratively output a scheduling scheme α that minimizes equipment cost and maximizes operation efficiency;

[0010] The objective function includes a cost function and an efficiency function.

[0011] Cost function

[0012] In the formula, This represents the cost of using the i-th type of equipment, where n is the total number of equipment. It is the cost of equipment energy consumption; It is the cost of equipment operation time;

[0013] Efficiency function

[0014] In the formula, Q total This is the total fracturing fluid injection volume; T total This is the total time required to complete the fracturing operation;

[0015] S3. Execution and monitoring of scheduling plan: Execute scheduling plan α at the fracturing well site and monitor the operation results;

[0016] The operational effectiveness includes equipment utilization rate and equipment usage time.

[0017] As a limitation of the present invention, the objective function is constrained by the equipment working capacity or the equipment operation sequence.

[0018] The expression for the equipment's working capacity as a constraint is: In the formula, P i (t) is the actual operating power of the i-th type of equipment. and These are the minimum and maximum power of the i-th type of device, respectively;

[0019] Equipment operation sequence as a constraint refers to the existence of an operational sequence between different pieces of equipment. For example, a sand mixing truck can only start sand mixing operations after the sand supply equipment is ready, which is represented by the logical relation S. i j , among which, S i and S j These represent the operating steps for different equipment.​

[0020] The equipment includes core equipment for fracturing operations and non-core equipment to assist fracturing operations.

[0021] The core equipment includes raw material equipment, mixing equipment, high-pressure equipment, pumping equipment, and manifold equipment; the non-core equipment is determined based on the number of core equipment and other conditions and requirements such as on-site personnel, and includes central control equipment, power supply equipment, and living equipment.

[0022] As another limitation of the present invention, the set of device types E = {E} rw E cx E hy E pm E mf E gc E ey E lv The set of the number of devices N = {N} rw N cx N hy N pm N mf N gc N ey N lv The number of devices is always a non-negative number.

[0023] Among them, E rw E represents the set of types of raw material equipment. cx E represents the set of types of mixed equipment. hy E represents the set of types of high-voltage equipment. pm E represents a collection of types of pumping equipment. mf E represents the set of types of manifold equipment. gc E represents the set of types of central control equipment. ey E represents the set of types of energy supply equipment. lv This refers to a collection of different types of daily necessities.

[0024] N rw N represents the set of quantities of raw material equipment. cx N represents the set of quantities of mixed equipment. hy N represents the set of quantities of high-voltage equipment. pm N represents the set of quantities of pumping equipment. mf N represents the set of the number of manifold equipment. gc N represents the set of all control equipment. ey N represents the set of energy supply equipment. lv This represents the set of quantities of daily necessities.

[0025] As a third limitation of the present invention, when monitoring the operation effect, the constraints are adjusted manually based on the operation effect, and the scheduling scheme α is manually modified to obtain the actual execution scheduling scheme β.

[0026] As a further limitation of the present invention, for the scheduling of equipment for multiple fracturing operations, after constructing twin well sites, selecting scheduling schemes, and executing and monitoring the scheduling schemes, the following steps are also included in sequence:

[0027] Data Acquisition and Classification: Collect all scheduling schemes, operational effects, and equipment performance of the twin well sites, classify them according to equipment type, and obtain a historical database of equipment scheduling;

[0028] Results Comparison and Feedback: Using a comparative indicator system, the differences and corresponding operational effects of scheduling scheme α and scheduling scheme β in the equipment scheduling history database are compared and analyzed. Resource assessment of the equipment is performed, and a report file containing the resource assessment results and the expected effects of the scheduling scheme is generated. This report is then fed back to the digital twin system to optimize the scheduling scheme and output the results.

[0029] The comparative indicator system includes the differences in equipment idle rate, the differences in work completion time, and the differences in cost.

[0030] As a further limitation of the present invention, the equipment scheduling history database is equipped with a usage permission control program; the objects of the resource evaluation include equipment performance, equipment maintenance status, equipment failure rate, and equipment usage frequency; and a predictive model of scheduling scheme and expected operation effect is generated using report files to predict equipment failure and equipment maintenance events.

[0031] As a further limitation of the present invention, the simulation algorithm adopts a discrete event simulation algorithm.

[0032] The present invention also provides a fracturing operation equipment scheduling device based on digital twin, comprising:

[0033] The twin well site construction module is used to construct twin well sites based on the fracturing operation well sites;

[0034] The scheduling scheme selection module is used to store and optimize scheduling schemes, analyze and output scheduling scheme α based on the report file;

[0035] The scheduling scheme execution module is used to execute the scheduling scheme;

[0036] The scheduling scheme monitoring module is used to monitor the operation results;

[0037] The data acquisition and classification module is used to collect data, classify it, and obtain a historical database of equipment scheduling.

[0038] The results comparison and feedback module is used to generate report files, feed the report files back to the digital twin system to optimize the scheduling scheme and output them.

[0039] The present invention also provides an electronic device for a fracturing operation equipment scheduling method based on digital twins, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the above-mentioned fracturing operation equipment scheduling method based on digital twins.

[0040] The present invention also provides a computer-readable storage medium storing a computer program that executes the above-described digital twin-based fracturing equipment scheduling method.

[0041] By adopting the above-described technical solution, the beneficial effects achieved by this invention compared to the prior art are as follows:

[0042] (1) The fracturing operation equipment scheduling method based on digital twin of the present invention uses digital twin technology to establish a twin well field of fracturing operation well field (physical well field), realizes the synchronization and interaction between physical entity and virtual model, and ensures the real-time and accuracy of scheduling scheme. This synchronous interaction mechanism enables the scheduling scheme to be dynamically adjusted according to actual operation conditions and equipment status, thereby improving resource utilization and operation response speed. By constructing twin well fields, selecting scheduling schemes and performing simulation and iteration, a better scheduling scheme is obtained. With the help of manual intervention, historical database analysis and permission management, the idle rate of some fracturing equipment caused by carrying fracturing equipment based on manual experience is reduced, the blindness in fracturing operation resource scheduling is reduced, and the cost is reduced and the operation efficiency is improved.

[0043] (2) The fracturing equipment scheduling method based on digital twin of the present invention adjusts the constraints by manual intervention based on the operation effect and adjusts the scheduling scheme in combination with the actual physical well site. The method of combining manual intervention and automatic optimization makes the scheduling scheme more accurate and efficient, and can cope with complex and ever-changing operation scenarios, achieve optimal resource allocation and smooth execution of operation process. By setting up a usage permission control program, different types of personnel can quickly view the functions of the corresponding equipment area according to their own permissions, improve the monitoring and management effect, speed up the operation response speed, and ensure the continuity and stability of operation.

[0044] (3) The fracturing equipment scheduling method based on digital twin of the present invention can provide the best equipment scheduling scheme with the lowest equipment cost and the highest operation efficiency for a single operation. Through simulation, iteration and scheduling scheme execution and monitoring, it can accurately match operation requirements and equipment capabilities, ensure that each operation can be completed efficiently and economically, reduce equipment idleness, avoid resource waste, and improve the continuity and stability of the operation.

[0045] (4) The fracturing equipment scheduling method based on digital twin of the present invention also provides a scheduling scheme for multiple fracturing operations on the basis of a single operation. By collecting all the scheduling schemes in the twin well site, a historical database of equipment scheduling is obtained. Through comparative analysis and resource evaluation, the equipment resources are optimized and configured. Based on the report document obtained from the analysis of historical data, the maximum utilization of resources is achieved, the efficiency of the entire operation process is improved, and the overall operating cost is reduced.

[0046] The apparatus, electronic equipment, and computer-readable storage medium of the fracturing operation equipment scheduling method based on digital twins can improve the efficiency of the scheduling method of the present invention and provide a foundation for multi-scenario applications. Attached Figure Description

[0047] Figure 1 This is a flowchart illustrating a fracturing equipment scheduling method based on digital twins according to Embodiment 1 of the present invention.

[0048] Figure 2 This is a flowchart illustrating a method for multiple scheduling of fracturing equipment based on digital twins, according to Embodiment 2 of the present invention. Detailed Implementation

[0049] The present invention will be further described in detail below with reference to specific embodiments and accompanying drawings. It should be understood that the described embodiments are only used to explain the present invention and do not limit the present invention.

[0050] Example 1: A fracturing equipment scheduling method based on digital twins

[0051] This embodiment designs the optimal scheduling scheme for a well site in a certain area that requires a single fracturing operation, based on the single-operation equipment scheduling, as follows:

[0052] S1. Constructing a twin well site:

[0053] (1) Information collection

[0054] Utilizing multiple sensors, such as pressure sensors, position sensors, and flow sensors, comprehensive information about the target well site for fracturing operations is collected, such as... Figure 1 Specifically, it collects physical data, environmental parameters, derived data, and expert advice and assessment conclusions of the equipment operating parameters; among them, the fracturing equipment data in the physical data is recorded according to the equipment type such as pump truck, sand mixing truck and instrument truck, recording its model, performance parameters and working status information; for environmental parameters, meteorological conditions and geological data including stratigraphic structure and rock characteristics are collected.

[0055] (2) Establish sub-model

[0056] Modeling software based on CAD and BIM technology platforms uses collected information to construct a twin well site sub-model of the target well site, including a geometric model, a behavioral model, a physical model, and a rule model. Among them, the behavioral model is used to reflect the changes in the working status of equipment in real time, such as the pressure output curve of the pump truck and the changes in the sand-liquid mixing ratio of the sand mixing truck.

[0057] (3) Forming a digital twin system

[0058] All the obtained sub-models are integrated to construct a digital twin system. The accuracy of the models is calibrated and optimized by comparing them with actual well site operational data, ensuring a high degree of consistency between the digital twin system and the real system. Specifically, the energy consumption data of the equipment in the digital twin system is compared with the actual energy consumption data, and the error is controlled within a certain range to ensure the reliability of the digital twin system.

[0059] S2. Select a scheduling scheme:

[0060] The input includes the set of device types E = {E} rw E cx E hy E pm E mf E gc E ey E lv} and the set of the number of devices N = {N rw N cx N hy N pm N mf N gc N ey N lv A fracturing equipment scheduling scheme is proposed. In the digital twin system, a discrete event simulation algorithm is used to discretize the fracturing operation process into equipment start-up, stop, and material transport events, simulating them in the order they occur. At each event, the system state is updated based on the equipment status and operating rules, and the objective function is calculated.

[0061] The objective function includes a cost function and an efficiency function.

[0062] Cost function

[0063] In the formula, This represents the cost of using the i-th type of equipment, where n is the total number of equipment. It is the cost of equipment energy consumption; It is the cost of equipment operation time;

[0064] Efficiency function

[0065] In the formula, Q total This is the total fracturing fluid injection volume; T total This is the total time required to complete the fracturing operation;

[0066] The objective function is constrained by either the equipment's working capacity or the equipment's operating sequence.

[0067] The expression for the equipment's working capacity as a constraint is: In the formula, P i (t) is the actual operating power of the i-th type of equipment. and These are the minimum and maximum power of the i-th type of device, respectively;

[0068] In each simulation, different device scheduling sequences are randomly generated, and the corresponding cost and efficiency values ​​are calculated. After multiple iterations, the scheduling scheme α with the minimum device cost and the highest efficiency is selected as the optimal scheme.

[0069] Scheduling scheme α is E rw It consists of 100xi, 2 pieces in total, and is made of raw sand and water; E cx 35xi, 1 piece in total; E hy There are 2 units totaling 15xi, one for electric drive and one for diesel drive; E pm 5xi, 1 piece in total; E mf There are 2 pieces, one 50xi and one high-pressure component; E gc 5yi, 1 item in total; E ey There are 2 pieces totaling 15xi, consisting of a transformer and a frequency converter; E lv The value is 15yi, and there is 1 piece in total; where xi is the wellhead volume parameter and yi is the number of workers.

[0070] in, rw Indicates raw material equipment, cx Indicates mixed equipment. hy Indicates high-voltage equipment, pm Indicates pumping equipment, mf Indicates manifold equipment, gc Indicates the central control equipment. ey Indicates power supply equipment, lv It refers to daily necessities.

[0071] S3. Scheduling Scheme Execution and Monitoring:

[0072] The scheduling scheme α was executed at the target well site for fracturing operations. The operation effect was monitored, and the equipment utilization rate was 100% with an equipment usage time of 7.5 days. In the fracturing operation, the usage time of the mixed equipment was too long, which led to the extension of the project period. Therefore, it is necessary to increase the number of corresponding equipment, manually modify the scheduling scheme, and output the actual executed scheduling scheme β.

[0073] Scheduling scheme β is: E rw It consists of 100xi, 2 pieces in total, and is made of raw sand and water; E cx 35xi, 2 pieces in total; E hy There are 2 units totaling 15xi, one for electric drive and one for diesel drive; E pm 5xi, 1 piece in total; E mf There are 2 pieces, one 50xi and one high-pressure component; E gc 5yi, 1 item in total; E ey There are 2 pieces totaling 15xi, consisting of a transformer and a frequency converter; E lv The value is 15yi, and there is 1 piece in total; where xi is the wellhead volume parameter and yi is the number of workers.

[0074] Further monitoring of operational effectiveness revealed 100% equipment utilization and a 3.5-day equipment usage period, reducing equipment operating costs, energy costs, and equipment operation time costs. Therefore, the method of this invention, through manual modification, adapts to changes in actual on-site needs. This flexibility further enhances the adaptability and practicality of the scheduling scheme, enabling it to more accurately meet the needs of actual operations. The method of this invention not only improves equipment utilization efficiency in fracturing operations but also enhances overall operational performance through precise resource allocation.

[0075] Example 2: A fracturing equipment scheduling method based on digital twins

[0076] This embodiment performs multiple equipment scheduling operations at the target well site for fracturing operations in Embodiment 1, designs the optimal scheduling scheme, and obtains scheduling scheme α and scheduling scheme β based on Embodiment 1, and further performs the following steps:

[0077] Data Acquisition and Classification: Collect all scheduling schemes, including scheduling scheme α and scheduling scheme β, from the twin well sites, as well as the operational effects and equipment performance of the fracturing operation well sites. Classify the equipment according to its type and set up access control procedures based on operator permissions to obtain a historical database of equipment scheduling.

[0078] Results Comparison and Feedback: Using a comparative indicator system with equipment idle rate difference, job completion time difference, and cost difference as the main indicators, the differences and corresponding operational effects of scheduling scheme α and scheduling scheme β in the equipment scheduling history database are compared and analyzed. A comparison document showing the specific differences in cost-effectiveness and operational effects between different scheduling schemes is generated. At the same time, resource assessments are performed on the equipment involved, including equipment performance, equipment maintenance status, equipment failure rate, and equipment usage frequency. A report document containing resource assessment results and expected effects of scheduling schemes is generated and fed back to the digital twin system to optimize and output the scheduling scheme.

[0079] The gradient descent-based optimization algorithm adjusts the scheduling scheme. If the difference in equipment idle rate is greater than 0, it indicates that the equipment idleness has worsened, requiring a reduction in the waiting time of some equipment or optimization of their startup sequence. If the difference in job completion time is greater than 0, the operation speed of equipment on the critical path is accelerated or the job flow is adjusted. If the cost difference is greater than 0, the usage frequency of high-cost equipment is reduced or a more economical alternative is sought. Through continuous iterative comparison and feedback adjustments, the system gradually approaches the optimal scheduling scheme, thereby continuously improving system performance.

[0080] Both comparison documents and report documents can be exported for manual analysis, enabling flexible processing and enhanced monitoring and management of equipment.

[0081] In other implementations, the report file is used to generate a predictive model of the scheduling scheme and expected operational results, which is used to predict equipment failures and equipment maintenance events.

[0082] Example 3: A computer device

[0083] This embodiment provides a computer device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, to implement a fracturing operation equipment scheduling method based on digital twins according to Embodiment 1.

[0084] This memory is used to store non-transitory computer-readable instructions. Specifically, the memory may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may, for example, include random access memory (RAM) and / or cache memory. The non-volatile memory may, for example, include read-only memory (ROM), hard disk, flash memory, etc.

[0085] The processor may be a central processing unit (CPU) or other form of processing unit with data processing and / or instruction execution capabilities, and may control other components in the electronic device to perform desired functions. The processor is used to execute computer-readable instructions stored in the memory.

[0086] Those skilled in the art will understand that, in order to solve the technical problem of how to achieve a good user experience, this embodiment may also include well-known structures such as communication buses and interfaces, and these well-known structures should also be included within the protection scope of this disclosure.

[0087] For a detailed description of this embodiment, please refer to the corresponding descriptions in the foregoing embodiments, which will not be repeated here.

[0088] Example 4: A computer-readable storage medium

[0089] This embodiment provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements a fracturing equipment scheduling method based on digital twins according to Embodiment 1.

[0090] The computer-readable storage medium stores non-transitory computer-readable instructions thereon. When the non-transitory computer-readable instructions are executed by a processor, all or part of the steps of the methods of the foregoing embodiments are performed.

[0091] The aforementioned computer-readable storage media include, but are not limited to: optical storage media (e.g., CD-ROM and DVD), magneto-optical storage media (e.g., MO), magnetic storage media (e.g., magnetic tape or portable hard drive), media with built-in rewritable non-volatile memory (e.g., memory card), and media with built-in ROM (e.g., ROM cartridge).

[0092] Example 5: A fracturing equipment scheduling device based on digital twin

[0093] This embodiment provides a fracturing operation equipment scheduling device based on digital twins, which consists of the following main modules:

[0094] The twin well site construction module is used to construct twin well sites based on the fracturing operation well sites;

[0095] The scheduling scheme selection module is used to store and optimize scheduling schemes, analyze and output scheduling scheme α based on the report file;

[0096] The scheduling scheme execution module is used to execute the scheduling scheme;

[0097] The scheduling scheme monitoring module is used to monitor the operation results;

[0098] The data acquisition and classification module is used to collect data, classify it, and obtain a historical database of equipment scheduling.

[0099] The results comparison and feedback module is used to generate report files, feed the report files back to the digital twin system to optimize the scheduling scheme and output them.

[0100] It should be noted that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art can still modify the technical solutions described in the above embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the claims of the present invention.

Claims

1. A method for scheduling fracturing equipment based on digital twins, characterized in that, This includes the following steps performed sequentially: S1. Constructing a twin well site: Utilizing digital twin technology to construct a digital twin system of the fracturing operation well site, serving as the twin well site; S2. Select a scheduling scheme: Input a fracturing operation equipment scheduling scheme that includes equipment types and quantities of each type of equipment; simulate the scheduling scheme in a digital twin system, and use an objective function to iteratively output a scheduling scheme α that minimizes equipment cost and maximizes operation efficiency; The objective function includes a cost function and an efficiency function. Cost function In the formula, This represents the cost of using the i-th type of equipment, where n is the total number of equipment. It is the cost of equipment energy consumption; It is the cost of equipment operation time; Efficiency function In the formula, Q total This is the total fracturing fluid injection volume; T total This is the total time required to complete the fracturing operation; S3. Execution and monitoring of scheduling plan: Execute scheduling plan α at the fracturing well site and monitor the operation results; The operational effectiveness includes equipment utilization rate and equipment usage time.

2. The fracturing equipment scheduling method based on digital twin according to claim 1, characterized in that, The objective function is constrained by the equipment's working capacity or the equipment's operating sequence. The expression for the equipment's working capacity as a constraint is: In the formula, P i (t) is the actual operating power of the i-th type of equipment. and These are the minimum and maximum power of the i-th type of equipment, respectively; the equipment includes core equipment for fracturing operations and non-core equipment for assisting fracturing operations.

3. The fracturing equipment scheduling method based on digital twin according to claim 2, characterized in that, The set of device types E = {E} rw E cx E hy E pm E mf E gc E ey E lv The set of the number of devices N = {N} rw N cx N hy N pm N mf N gc N ey N lv The number of devices is always a non-negative number. in, rw Indicates raw material equipment, cx Indicates mixed equipment. hy Indicates high-voltage equipment, pm Indicates pumping equipment, mf Indicates manifold equipment, gc Indicates the central control equipment. ey Indicates power supply equipment, lv It refers to daily necessities.

4. A method for scheduling fracturing equipment based on digital twins according to claim 1, 2, or 3, characterized in that, When monitoring the operation results, the constraints are adjusted manually based on the operation results, and the scheduling scheme α is manually modified to obtain the actual executed scheduling scheme β.

5. A method for scheduling fracturing equipment based on digital twins according to claim 4, characterized in that, For equipment scheduling in multiple fracturing operations, after constructing twin well sites, selecting scheduling schemes, and executing and monitoring the scheduling schemes, the following steps are also included in sequence: Data Acquisition and Classification: Collect all scheduling schemes, operational effects, and equipment performance of the twin well sites, classify them according to equipment type, and obtain a historical database of equipment scheduling; Results Comparison and Feedback: Using a comparative indicator system, the differences and corresponding operational effects of scheduling scheme α and scheduling scheme β in the equipment scheduling history database are compared and analyzed. Resource assessment of the equipment is performed, and a report file containing the resource assessment results and the expected effects of the scheduling scheme is generated. This report is then fed back to the digital twin system to optimize the scheduling scheme and output the results. The comparative indicator system includes the differences in equipment idle rate, the differences in work completion time, and the differences in cost.

6. A method for scheduling fracturing equipment based on digital twins according to claim 5, characterized in that, The equipment scheduling history database is equipped with a usage permission control program; The objects of the resource assessment include equipment performance, equipment maintenance status, equipment failure rate, and equipment usage frequency; The report files are used to generate a predictive model of scheduling schemes and expected operational results, which can be used to predict equipment failures and equipment maintenance events.

7. A fracturing equipment scheduling method based on digital twin according to any one of claims 1 to 3, 5 or 6, characterized in that, The simulation algorithm used is a discrete event simulation algorithm.

8. A fracturing operation equipment scheduling device based on digital twin according to claim 7, characterized in that, include: The twin well site construction module is used to construct twin well sites based on the fracturing operation well sites; The scheduling scheme selection module is used to store and optimize scheduling schemes, analyze and output scheduling scheme α based on the report file; The scheduling scheme execution module is used to execute the scheduling scheme; The scheduling scheme monitoring module is used to monitor the operation results; The data acquisition and classification module is used to collect data, classify it, and obtain a historical database of equipment scheduling. The results comparison and feedback module is used to generate report files, feed the report files back to the digital twin system to optimize the scheduling scheme and output them.

9. An electronic device for a fracturing operation equipment scheduling method based on digital twins, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements a fracturing equipment scheduling method based on digital twins as described in any one of claims 1-8.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that executes a digital twin-based fracturing equipment scheduling method according to any one of claims 1-8.

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