Fracturing equipment integrated tool design method and device based on offshore mobile platform

Abstract

The invention discloses a fracturing equipment integrated tool design method and device based on an offshore mobile platform. The method comprises the steps that an optimized parameter system composed of fracturing equipment parameters, tool structure parameters, platform adaptation parameters and operation constraint parameters is constructed; constructing an objective function with maximization of the space utilization rate and the fracturing displacement standard-reaching rate as an objective and a constraint function covering structure safety, operation functions and platform adaptation; and solving the parameters based on SACS modeling, CFD simulation and a hybrid optimization algorithm to obtain an integrated tool with an optimal configuration, and the like. The total weight of the fracturing equipment integrated tool can be obviously reduced, the installation time of the device on an offshore mobile platform can be obviously shortened, the installation difficulty of the device can be obviously reduced, and therefore the cost of the fracturing equipment integrated tool is obviously reduced.

Description

Technical Field

[0001] This invention belongs to the field of offshore oil and gas development equipment optimization technology, specifically relating to a design method and device for integrated tooling of fracturing equipment based on an offshore mobile platform. Background Technology

[0002] my country possesses abundant offshore shale oil resources, with proven reserves in the Beibu Gulf and Bohai Sea regions of the South China Sea reaching hundreds of millions of tons, representing a crucial strategic reserve for ensuring national energy security. With the advancement of shale oil extraction technology, large-scale fracturing operations have become the core technological path to enhance oil recovery, with the core demand manifested in "large displacement (≥10m³)". 3 "High-volume fracturing (thousand cubic meters per minute), high-volume fracturing (thousand cubic meters per minute), long-term continuous operation"—both domestic and international industry practices clearly indicate a trend towards dense cutting and high-power fracturing technology.

[0003] However, the inherent characteristics of offshore mobile platforms impose multiple stringent constraints on fracturing operations, becoming a key bottleneck restricting the large-scale development of offshore shale oil, specifically in the following three aspects: Extreme spatial constraints: The available deck area of ​​the platform is limited. Taking a conventional 2500-type fracturing pump as an example, the layout of 6 units requires approximately 580m² of deck space. 2 The maximum usable area of ​​most drilling ships' main deck plus cantilever deck is only 450m². 2 ~500m 2 The space constraints of the jacket platform are more prominent, which cannot meet the equipment deployment requirements of large-scale fracturing. The crowded equipment layout leads to insufficient operating space and is also prone to safety hazards.

[0004] Load-bearing capacity varies: The unit area load threshold differs significantly (1.2t / m²) in different areas of the platform deck (pipe rack area, non-pipe rack area, and under the cantilever beam). 2 ~2.0t / m 2 The traditional heavy-duty integrated fracturing equipment, when laid out in a flat manner, is prone to local load exceeding the standard, which not only affects the structural safety of the platform, but also makes it difficult to increase the scale of operations by simply increasing the number of equipment, thus limiting the efficiency of fracturing operations.

[0005] Lack of integrated technology: Existing equipment lacks targeted modular design, and small auxiliary equipment (liquid injection pumps, generator skids) are mixed with large fracturing pumps and sand tanks, further wasting space; at the same time, the hoisting of equipment is limited by the working range of cantilever beams and the capacity of cranes, and the space utilization rate of some areas is less than 30% due to poor hoisting accessibility. It also leads to problems such as low heat dissipation efficiency (temperatures exceeding 85°C in densely populated equipment areas) and chaotic pipeline layout, which increases the difficulty of equipment maintenance and the risk of operational failure.

[0006] Mature onshore high-density fracturing technology cannot be directly transferred to offshore platforms due to their unique spatial, load-bearing, and hoisting requirements. Currently, the industry lacks specialized tooling technologies with three-dimensional layouts, modular integration, and efficient placement adapted to offshore scenarios, making it difficult to meet the demands of large-scale offshore fracturing operations. Therefore, developing highly adaptable, safe, and efficient integrated tooling optimization solutions for fracturing equipment has become a core requirement for overcoming the bottlenecks in offshore shale oil development. Summary of the Invention

[0007] This invention addresses the challenges of fracturing operations on offshore platforms due to limited space, varying load-bearing capacities, and a lack of integrated technology. Specifically, it addresses issues such as low space utilization, poor load-bearing capacity, difficulty in equipment placement, and insufficient operational efficiency in fracturing operations on mobile offshore platforms. The aim is to provide a design method and apparatus for integrated fracturing equipment based on a mobile offshore platform.

[0008] This invention is achieved through the following technical solution: A method for designing integrated tooling for fracturing equipment based on a mobile offshore platform includes the following steps: S1. Construct an optimized parameter system; S2. Construct the objective function and constraint functions; S3. Solve the optimization parameter system constructed in step S1 based on the objective function and constraint function established in step S2 to obtain the integrated tooling with the optimal configuration.

[0009] In the above technical solution, the optimized parameter system includes fracturing equipment parameters, tooling structure parameters, platform adaptation parameters, and operational constraint parameters.

[0010] In the above technical solution, the fracturing equipment parameters include the number of core equipment and the external dimensions, weight, center of gravity coordinates, and working load of each core equipment; the tooling structure parameters include the number of modular tooling layers, the net height between modular tooling layers, the cross-sectional dimensions of the support beams, the type of connection nodes, the length of the slide rails, and the traction force parameters of the sliding mechanism; the platform adaptation parameters include the available deck area, the bearing threshold of different areas, the operating radius of the cantilever beam, the maximum lifting capacity of the crane, and the capacity of the mud pit; the operational constraint parameters include the target fracturing displacement, the equipment operation and maintenance space threshold, the minimum curvature radius of the pipeline, and the upper limit of the safe load.

[0011] In the above technical solution, the objective function has two objectives: maximizing space utilization and maximizing the fracturing discharge rate. The mathematical expression for the objective function is: ; in: ; .

[0012] In the above technical solution, the constraint function is a triple constraint system composed of structural safety constraints, operational function constraints, and platform adaptation constraints; The structural safety constraints include the support beam stress utilization factor UC≤1, the maximum Z-direction displacement of the node ≤ beam span / 240, the equipment hoisting load ≤ the crane rated load, and the total tooling load ≤ the deck area safety load. The operational constraints include equipment spacing ≥ 0.65m, air velocity in the fracturing pump heat dissipation channel ≥ 3m / s, and traction force of the sliding mechanism ≤ rated pulling force of the winch; The platform adaptation constraints include that the tooling dimensions do not exceed the deck boundary, the equipment center of gravity projection falls within the range of the platform's main load-bearing beam, and the pipeline layout does not conflict with the platform's existing facilities.

[0013] In the above technical solution, the parameter solution in step S3 adopts a multi-algorithm joint solution based on SACS modeling, CFD simulation and hybrid optimization algorithm.

[0014] In the above technical solution, step S3 specifically includes the following steps: S31. Based on the engineering practice rules for the layout of offshore oil engineering equipment, and combined with the constraint boundary of the optimization parameter system constructed in step S1, multiple sets of feasible initial layout schemes are automatically generated through integrated tools. S32. Establish a mechanical model of the tooling structure to simulate the stress of the tooling under working load and hoisting load, and output the core structural data; analyze the heat dissipation characteristics of the equipment and output the key heat dissipation data; use the Kriging proxy model to perform dimensionality reduction modeling on the high-dimensional combination of the core structural data, key heat dissipation data and optimization parameter system. S33. The optimal integrated tooling configuration is obtained by using a hybrid optimization strategy of steepest descent method and genetic algorithm.

[0015] In the above technical solution, the production quantity of the initial layout scheme conforms to the conventional quantity for multi-scheme comparison in marine engineering, and the production quantity of the initial layout scheme is 30 to 100 sets.

[0016] In the above technical solution, the mechanical model of the tooling structure is established using SACS software, which is mature and widely used in the field of marine engineering; the core structural data includes the stress utilization factor of the support beam, the Z-direction displacement of the nodes, the overall weight of the tooling, and the adaptability parameters of the cross-sectional dimensions of the support beam. The analysis of the equipment's heat dissipation characteristics was performed using the integrated ANSYS Fluent CFD simulation module; the key heat dissipation data included the average temperature of the densely populated equipment area, the wind speed distribution in the heat dissipation channels, the location and temperature of hot spots, and the power requirements for the fans.

[0017] An integrated tooling design device for fracturing equipment based on a mobile offshore platform for implementing the aforementioned method includes: The parameter selection module is configured to select an optimization parameter system and supports data import; The function building module is configured to build objective functions and constraint functions; The optimization execution module is configured to solve for the optimal configuration through modeling, simulation, and algorithms. The verification module is configured to perform strength, hoisting, and compatibility verifications.

[0018] In the above technical solution, the optimization execution module integrates the SACS structural modeling plugin, the CFD simulation module, and the hybrid optimization strategy of steepest descent method + genetic algorithm, with a solution time of ≤30 minutes and parameter optimization accuracy of ≥99%.

[0019] The beneficial effects of this invention are: This invention provides a design method and apparatus for integrated tooling of fracturing equipment based on a marine mobile platform. It is applicable to large-scale fracturing operation equipment deployment scenarios on marine carriers such as drilling ships and jacket platforms. By constructing a multi-parameter optimization model and realizing three-dimensional layout and modular integration, it maximizes the utilization of platform space and fracturing operation capacity while meeting structural safety and operational functions. It provides technical support for large-scale offshore fracturing operations, reduces operating costs, and ensures safe and stable operation.

[0020] This is achieved through the design method of the present invention: Significantly improved space utilization: Through three-dimensional layout and modular integration, the deck space utilization rate has increased from 95% in the traditional flat layout to 117.7%, reaching 458.25m. 2 Eight fracturing pumps can be deployed on the deck area, which increases the number of equipment by 33% compared with the traditional solution. This fully taps the potential of the platform space, solves the problem of limited space on offshore platforms, and makes it possible to deploy large-scale fracturing equipment. Operational capabilities fully meet standards: Optimized fracturing displacement reaches 10.4m³. 3 / min, meeting the needs of large-scale fracturing operations of "ten thousand cubic meters of liquid and one thousand cubic meters of sand", improving single-well fracturing efficiency by 49%, significantly increasing offshore fracturing output, shortening operation cycle, and improving project economic benefits; High safety and reliability: The UC value of the support beam is ≤0.89 and the maximum Z-direction displacement of the node is 0.437cm, both of which meet the specifications and ensure the safety and stability of the tooling structure; the safety risks during equipment hoisting, sliding and operation are reduced by 60%, reducing the probability of safety accidents during operation and ensuring the safety of operators and equipment; Wide adaptability: Parameters can be flexibly adjusted according to different platform deck conditions and load-bearing capacity, adapting to various types of drilling vessels and jacket platforms such as Nanhai No. 4 and 945. There is no need to design tooling separately for different platforms, reducing design costs, increasing tooling reuse rate, and enhancing the promotion and application value of the technology. Improved construction efficiency: Modular tooling supports prefabrication on land and rapid assembly at sea. Combined with the sliding mechanism, equipment can be in place within 4 hours, reducing the installation and commissioning cycle from 7-10 days to 3-5 days, reducing offshore construction time and lowering the risks of offshore operations; operating costs are reduced by 21%, saving companies a lot of manpower, material resources and financial resources, and enhancing market competitiveness. Attached Figure Description

[0021] Figure 1 This is a flowchart of the method of the present invention; Figure 2 This is a three-dimensional structural schematic diagram of the optimized tooling in Embodiment 1 of the present invention; Figure 3 This is a schematic diagram of the hinge point structure of the optimized tooling in Embodiment 1 of the present invention (111000 in the figure represents the hinge node). Figure 4 This is an exploded view of the integrated tooling for the fracturing equipment in Embodiment 1 of the present invention; Figure 5 This is a schematic diagram of the equipment layout on a mobile offshore platform according to Embodiment 1 of the present invention; Figure 6 This is a schematic diagram of the overall layout of the mobile platform at sea according to Embodiment 1 of the present invention.

[0022] in: 1. Support structure; 2. Fracturing equipment structural base; 3. Attached secondary platform; 4. Fracturing equipment; 5. Integrated tooling for fracturing equipment; 6. Stacking tooling; 7. Platform deck.

[0023] For those skilled in the art, other related figures can be obtained from the above figures without any creative effort. Detailed Implementation

[0024] To enable those skilled in the art to better understand the technical solution of the present invention, the technical solution of the present invention will be further described below with reference to the accompanying drawings and specific embodiments.

[0025] Example 1 like Figure 1 As shown, a method for designing integrated tooling for fracturing equipment based on a mobile offshore platform includes the following steps: S1. Construct an optimized parameter system; The optimized parameter system includes fracturing equipment parameters, tooling structure parameters, platform adaptation parameters, and operational constraint parameters; The fracturing equipment parameters include the number of core equipment (N) and the external dimensions (length × width × height), weight (G), center of gravity coordinates (X, Y, Z) and working load (P) of each core equipment. The fracturing equipment parameters ensure that they fully reflect the core characteristics of the equipment and provide accurate basic data for subsequent optimization. The core equipment includes a 2500-type fracturing pump, a liquid injection pump, and a generator skid; The single-pump displacement range of the fracturing pump is 1.0 m³ / s. 3 / min~1.3m 3 / min, The tooling structure parameters include the number of modular tooling layers (n), the net height between modular tooling layers (h), the cross-sectional dimensions or model of the support beam (such as H440 I-beam), the connection node type (hinged / rigid connection), the slide rail length (L), and the traction force parameters of the sliding mechanism (F). By clarifying the key parameters of the tooling structure, the overall stability and functionality of the tooling are ensured. The platform adaptation parameters are: available deck area (S), bearing threshold for different areas ([q1,q2]), cantilever beam operating radius (R), maximum crane lifting capacity (Q), and mud pit capacity (V). The platform adaptation parameters are based on the platform's laser scanning data. Relying on accurate platform data, the tooling is highly compatible with the platform's characteristics, avoiding problems such as exceeding load limits.

[0026] The operational constraint parameters include the target fracturing displacement (Q≥10m). 3 The parameters for operation constraints, including the minimum radius of curvature of the pipeline (≥1.5D, where D is the pipe diameter), the equipment operation and maintenance space threshold (≥0.65m), the minimum radius of curvature of the pipeline (≥1.5D, where D is the pipe diameter), and the upper limit of the safe load ([Q1,Q2]), are based on the actual needs of the operation to ensure that the optimized tooling meets the operational functions and safety requirements.

[0027] In this embodiment, the specific parameters of the fracturing equipment are as follows: 8 Type 2500 fracturing pumps (10.8m×2.4m×2.8m, 34.8t / unit), 1 liquid injection pump (3m×1.2m×1.98m, 2t), 1 generator skid (2.5m×1.1m×1.8m, 2.5t), and 1 set of 30m 3 Sand pot, 4 sets of 50m 3 The liquid tank has detailed and clear equipment parameters to ensure the accuracy of subsequent modeling and optimization; The specific platform adaptation parameters are as follows: using the Nanhai No. 4 drilling vessel as the carrier, the usable deck area is 458.25m². 2 (Main deck 225.75m) 2 +Cantilever beam deck 232.5m 2 The bearing capacity of the pipe rack area is 2t / m. 2The cantilever crane has a maximum lifting capacity of 46t, and the platform parameters are based on actual measurements and surveys and are highly consistent with the actual situation of the platform. The specific operational constraint parameters are: target displacement 10m³ / h 3 / min, equipment operating space ≥0.65m, total tooling load ≤900t, and operation constraint parameters are set according to the actual needs of offshore fracturing operations to ensure operational functionality and safety.

[0028] S2. Construct the objective function and constraint functions; The objective function adopts a multi-objective optimization model, with the dual objectives of maximizing space utilization (core objective) and maximizing fracturing displacement compliance rate; The mathematical expression for the objective function is: in: For space utilization rate, it intuitively reflects the efficiency of space utilization; To ensure the displacement compliance rate and the fracturing operation capacity meet the standards, the dual objectives of space utilization and operation efficiency are taken into account, which meets the core requirements of offshore fracturing operations. The constraint function is a triple constraint system to ensure the feasibility of the optimization results, including structural safety constraints, operational function constraints, and platform adaptation constraints. The structural safety constraints include: the stress utilization factor of the support beam UC≤1 (compliant with API RP 2A-WSD specifications), the maximum Z-direction displacement of the node ≤L / 240 (L is the beam span), the equipment hoisting load ≤ the rated load of the crane, and the total load of the tooling ≤ the safe load of the deck area; The operational constraints include: equipment spacing ≥ 0.65m (meeting the operating space requirements of GB 50183-2004), fracturing pump heat dissipation channel wind speed ≥ 3m / s (ensuring equipment operating temperature ≤ 80℃), and sliding mechanism traction force ≤ winch rated pulling force; The platform adaptation constraints include: the tooling dimensions do not exceed the deck boundary, the equipment center of gravity projection falls within the range of the platform's main load-bearing beam (offset ≤ 0.3m), and the pipeline layout does not conflict with the platform's existing facilities.

[0029] S3. Based on the objective function and constraint function established in step S2, the optimization parameter system constructed in step S1 is solved through modeling, simulation and hybrid optimization algorithms.

[0030] The parameters in step S3 are solved using a multi-algorithm joint solution based on SACS modeling, CFD simulation, and hybrid optimization algorithm. Step S3 specifically includes the following steps: S31. Solution Generation Stage: Based on engineering practice rules for the layout of offshore oil engineering equipment (such as "heavy equipment close to the main load-bearing beam, high-frequency operation equipment arranged in easily accessible areas, and pipelines following the shortest path"), and combined with constraints such as equipment size, platform load-bearing capacity, and lifting capacity in the parameter system, N sets (N=30-100 sets, which is in line with the conventional number of multi-scheme comparisons in marine engineering) of feasible initial layout schemes are automatically generated through integrated tools. All schemes meet the prerequisites of "no structural safety hazards, basic operating space meeting standards, and feasible lifting paths", avoiding invalid schemes from wasting computing resources, and the generation logic is completely consistent with the actual design process of marine engineering.

[0031] In this embodiment, based on the layout rules of marine engineering equipment, 50 initial feasible schemes are automatically generated. All schemes meet the basic requirements of structural safety, working space and hoisting path, providing sufficient candidate samples for subsequent multi-algorithm solutions. S32, Modeling Stage: The SACS software, a mature application in marine engineering (widely used for platform structural strength analysis), was used to establish a mechanical model of the tooling structure. This model accurately simulates the stress on the tooling under operational and lifting loads, outputting core structural data such as the stress utilization factor (UC value) of the support beam, the Z-direction displacement of the nodes, the overall weight of the tooling, and the adaptability parameters of the support beam cross-sectional dimensions. The ANSYS Fluent CFD simulation module (a common tool for heat dissipation analysis of marine equipment) was integrated to analyze the equipment's heat dissipation characteristics, outputting key heat dissipation data such as the average temperature in densely populated areas, the wind speed distribution in heat dissipation channels, the location and temperature of hot spots, and the power requirements of the fans. A Kriging surrogate model was used to reduce the dimensionality of the high-dimensional combination of the above structural data, heat dissipation data, and optimization parameter system, thus reducing computational load. This modeling method has become a standardized application process in the optimization design of marine platform equipment, ensuring technical feasibility.

[0032] In this embodiment, the modeling data output is as follows: The initial structural mechanics model is established using SACS software, outputting the UC value of the supporting beam (0.72-1.05), the Z-direction displacement of the nodes (0.31-0.87cm), and the overall weight of the tooling (42t~65t) for each scheme; Through ANSYS Fluent CFD simulation, the average temperature of the equipment-dense area (68℃~83℃), the air velocity of the heat dissipation channel (2.8m / s~3.9m / s), and the temperature of the hot spot area (75℃~89℃) for each scheme are output, providing accurate input parameters for the steepest descent method. S33, Solution Stage: A hybrid optimization strategy combining the steepest descent method and genetic algorithm, commonly used in marine engineering optimization design, is adopted. This combined algorithm has been verified to be effective in scenarios such as offshore platform equipment layout and pipeline optimization. The specific execution logic and core input parameters are as follows: S331, Steepest Descent Method with Multiple Starting Points Executed in Parallel (Core Input: SACS Structure Core Data + CFD Key Heat Dissipation Parameters): S331. Parallel execution of the steepest descent method from multiple starting points: Ten evenly distributed initial points are randomly selected from 50 initial schemes (covering 3 tooling layers: 1, 2, and 3 layers; 4 equipment layout modes: main deck centralized arrangement, main deck + cantilever beam separate placement, symmetrical arrangement of upper and lower layers, and core equipment close to the load-bearing beam), and the steepest descent method iteration is started in parallel. S3311, Parameter Mapping Association: Establish a one-to-one correspondence between the UC values ​​and nodal displacements output by SACS and the tooling structural parameters (support beam section type, inter-story clearance, nodal type). Establish a mapping relationship between the equipment area temperature and heat dissipation velocity output by CFD and the equipment layout parameters (equipment spacing, number of tooling layers, heat dissipation channel size) to form an "optimization parameter-performance index" correlation matrix. Clarify the influence weight of each parameter on structural safety and heat dissipation effect (e.g., the support beam section type accounts for 60% of the weight of the UC value, and the equipment spacing accounts for 45% of the weight of the heat dissipation velocity). S3312, Initial Point Selection and Parallel Startup: In the initial N feasible solutions, 8 to 12 evenly distributed initial points are randomly selected based on the correlation matrix (covering 3 to 4 types of tooling layers, 5 to 6 types of support beam specifications, and 4 to 5 types of equipment layout modes) to ensure that the initial points cover different parameter combination scenarios. For each initial point, the local optimization criteria are "UC value ≤ 0.95, node displacement ≤ L / 280, maximum equipment temperature ≤ 78℃, and heat dissipation wind speed ≥ 3.2m / s" (stricter than the constraint function threshold to improve the quality of local optimal solutions), and the steepest descent method iteration is started in parallel. S3313, Local optimal region convergence calculation: Using the gradient of the objective function (space utilization rate η, displacement compliance rate γ) as the search direction, 1-2 key parameters are adjusted in each iteration (prioritizing parameters with a weight ratio ≥40%, such as support beam cross-section and equipment layout). Simultaneously, SACS structural data and CFD heat dissipation parameters are substituted for feasibility verification. When the change in the objective function value is ≤0.5% in 3 consecutive iterations, and the structural and heat dissipation parameters meet the local optimization criteria, the iteration at that starting point is stopped, and the local optimal solution corresponding to that starting point is determined. The parameter range constitutes a local optimal region (e.g., "2 tooling layers, H440×300 series support beam cross-section, 0.65m~0.8m equipment spacing, 3.2m / s~3.8m / s heat dissipation channel wind speed"). Finally, through parallel calculation at multiple starting points, 5-8 non-overlapping local optimal regions are obtained, forming a candidate interval set for the optimal solution. This solves the problem that the steepest descent method with a single starting point is prone to getting trapped in local optima, ensuring that the candidate interval set covers the range of potential global optimal solutions. This embodiment is specifically as follows: For the initial point of "2-layer tooling + main deck + cantilever beam separation", the criteria of "UC value ≤ 0.95, node displacement ≤ 0.5cm, maximum equipment temperature ≤ 78℃, and heat dissipation wind speed ≥ 3.2m / s" were used to prioritize the adjustment of the support beam cross section (from H380×280 to H440×300) and equipment spacing (from 0.65m to 0.7m). After 6 iterations, the change in the objective function value was ≤ 0.4%, forming a local optimum region: "2-layer tooling, H440×300 series support beam cross section, 0.65m~0.8m equipment spacing, 3.2m / s~3.8m / s heat dissipation channel wind speed, 110%~120% space utilization rate, and 100%~105% displacement compliance rate". After iterating through 10 initial points, 6 non-overlapping local optimal regions are obtained, forming a set of candidate intervals for the optimal solution. Tooling modeling optimization: Based on 6 locally optimal regions, a final 2-layer modular tooling model was established using SACS software. The hydraulic injection pump and generator skid were integrated into the upper tooling (layer height 2.5m). 8 fracturing pumps were placed on the main deck (6 units) and in the extended area below the cantilever beam (2 units), and were slid into position via 12m long slide rails. The heat dissipation channel layout was optimized using ANSYS Fluent CFD simulation, and 2 explosion-proof axial flow fans (displacement 68,000 m³ / h) were added to the top of the tooling. 3 / h), ensuring that the airflow velocity in the heat dissipation channel reaches 3.5m / s; Parametric dimensionality reduction modeling: The Kriging model is used to reduce the dimensionality of eight key parameters, including support beam specifications, inter-story clear height, equipment spacing, and heat dissipation channel size. The high-dimensional parameter combination is transformed into three principal component factors, which reduces the search dimension of the genetic algorithm and improves the solution efficiency. S332. Genetic Algorithm Quadratic Search and Global Comparison (Core Input: Optimal Solution Candidate Interval Set + Objective-Constraint Function): S3321, Interval parameter encoding: Using the parameter range of each local optimal region as the boundary, the core parameters of the tooling are binary encoded (chromosome length = number of parameters × encoding precision, encoding precision is taken as 0.01m / 0.1t level to ensure parameter precision), for example, "number of tooling layers (2 layers: 10), cross section of support beam (H440×300: 011), equipment spacing (0.7m: 101101), heat dissipation channel size (1.2m×0.8m: 11001000)", each chromosome corresponds to a complete set of tooling configuration parameters; S3322, Initial Population Generation: Parameter combinations are randomly selected from 5 to 8 local optimal regions to generate an initial population of 50 to 80 (8 to 10 groups are selected from each region to ensure that the population covers all candidate intervals). Each parameter combination in the population must meet the bottom line requirements of the constraint function such as "UC value ≤ 1, node displacement ≤ L / 240, equipment temperature ≤ 80℃" and invalid chromosomes are removed. Specifically, in this embodiment, the parameters of the six local optimal regions are binary encoded, the chromosome length is 32 bits (8 parameters × 4 bits of encoding precision), an initial population of size 60 is generated, two sets of invalid chromosomes with UC values ​​> 1.0 are removed, and 58 sets of valid populations are retained. S3323, Genetic operation iteration: The iteration count is set to 30-50 generations, with a crossover probability of 0.7-0.8 and a mutation probability of 0.05-0.1 (consistent with conventional parameter settings for marine engineering optimization): A single-point crossover operation is used to exchange parameter fragments of different chromosomes (e.g., exchanging the code for the support beam cross-section and equipment spacing) to generate offspring chromosomes; a mutation operation is used to randomly flip 1-2 bits of the code in the chromosome (e.g., mutating "tooling layer number 2 layers" to "3 layers") to expand the search range; after each iteration, the objective function values ​​(η and γ) of all offspring chromosomes are calculated, and combined with SACS structural strength verification and CFD heat dissipation effect verification, valid offspring that meet all constraints are selected. In this specific embodiment, the number of iterations is set to 40 generations, the crossover probability is 0.75, and the mutation probability is 0.08. Offspring chromosomes are generated through crossover and mutation operations. After each generation iteration, the structural strength is verified by SACS and the heat dissipation effect is verified by CFD to select effective offspring. S3324, Global Optimal Filtering: After the iteration terminates, the objective function values ​​of all valid offspring are collected. A weighted scoring method (η weight 60%, γ weight 40%) is used to calculate the comprehensive score, and the parameter combination with the highest comprehensive score is selected as the global optimal solution. If there are two or more parameter combinations with a comprehensive score difference ≤ 0.3%, structural weight and construction difficulty (such as hoisting accessibility and sliding traction requirements) are further compared to determine the unique optimal parameter combination. This approach balances local optimization accuracy and global optimality, fully adhering to the technical logic of multi-objective optimization in marine engineering. The optimal parameter combination is the integrated tooling with the optimal configuration.

[0033] In this specific embodiment, after the iteration terminates, the comprehensive score of 58 effective offspring groups is calculated (η weight 60%, γ weight 40%). Among them, one scheme has the highest comprehensive score (η=117.7%, γ=104%, comprehensive score 112.22 points), and the support beam UC value of 0.82, node displacement of 0.437cm, and maximum equipment temperature of 75℃ all meet the constraint requirements, and are determined to be the globally optimal scheme.

[0034] The optimal parameter combination in the output results includes core parameters such as the tooling layout, modular structure dimensions, slide rail arrangement, equipment installation sequence, and sliding mechanism model. The output results can be directly connected to marine engineering construction drawing design standards to guide actual tooling manufacturing and equipment installation, reducing the difficulty of on-site implementation.

[0035] Figure 2 The optimal configuration integrated tooling three-dimensional structure result obtained after the solution stage of step S33 is presented intuitively, showing the final optimized tooling three-dimensional layout, module composition and equipment installation position, providing an intuitive reference for tooling manufacturing and installation. Figure 3 This is a detailed structural diagram of the hinge point in the optimal configuration obtained through steps S32 (modeling stage) + S33 (solution stage). It is determined by the SACS structural mechanics model simulation analysis, which helps to ensure the machining accuracy of the hinge point, the installation quality and the stability of the tooling structure. Figure 4 The optimal configuration integrated tooling structure decomposition result obtained after the solution stage in step S33 is obtained by decomposing based on the final optimal parameter combination, clarifying the function and connection relationship of each component, which facilitates the tooling block manufacturing, transportation and assembly. Figure 5 The optimal configuration equipment layout result obtained after the solution stage of step S33 is a specific deployment scheme for fracturing equipment on a mobile offshore platform. Combined with the actual space of the platform, it intuitively reflects the space optimization and utilization effect, and provides an example reference for the equipment layout of similar platforms. Figure 6The final overall layout result obtained after the solution stage of step S33 is the overall coordinated layout of the integrated tooling and stacked tooling of the optimal configuration on the platform deck. It reflects the coordination relationship between the tooling and other facilities on the platform and is one of the core final outputs of the entire design method.

[0036] The parameter comparison between the optimized technical solution of this embodiment and the traditional planar layout and single sliding technology is shown in Table 1 below: Table 1: Comparison Table of Optimization Parameters for Integrated Tooling of Fracturing Equipment Example 2 An integrated tooling design device for fracturing equipment based on a mobile offshore platform for implementing the aforementioned method includes: The parameter selection module is configured to select an optimization parameter system and supports data import; The function building module is configured to build objective functions and constraint functions; The optimization execution module is configured to solve for the optimal configuration through modeling, simulation, and algorithms. The verification module is configured to perform strength, hoisting, and compatibility verifications.

[0037] The parameter selection module uses a touch-screen interface with an ergonomic design that is easy to use and allows even non-professionals to quickly get started. The built-in equipment parameter database covers national and industry standards for 12 types of fracturing-related equipment, ensuring the standardization and accuracy of the parameters. The platform adaptation parameter library stores data for more than 10 typical offshore platforms, covering various common platform types to meet the adaptation needs of different platforms. It supports one-click import of laser scanning point cloud data, ensuring fast and efficient data import with a parameter entry error of ≤0.5%, guaranteeing the accuracy of input parameters and providing a reliable data foundation for subsequent optimization. Meanwhile, the parameter selection module has parameter query and modification functions. Users can query the entered parameter information at any time. If a parameter error is found or needs to be adjusted, it can be easily modified. At the same time, the system will automatically record the parameter modification history, which is convenient for traceability and management, and improves the flexibility and reliability of parameter management.

[0038] The function construction module provides a "wizard-style" function configuration function. After the user selects the platform type and operation target, the system guides the user through steps to complete the function configuration, reducing the difficulty of operation. It automatically generates the target function expression and constraint parameter range, and the generated function conforms to mathematical logic and engineering practice requirements. It supports the addition of constraint items for special working conditions (such as typhoon zone operations). Users can flexibly add constraints according to actual special needs, and the constraint matching accuracy rate reaches 98%, ensuring that the function can accurately reflect the operation requirements and constraints. At the same time, the function construction module has function preview and editing functions. After generating the function, users can preview it to view the function expression, parameter range, etc. If there are any unreasonable parts, they can be edited directly on the interface. The system will verify the rationality of the modified function in real time to ensure that the final generated function is accurate.

[0039] The optimization execution module integrates the SACS modeling plugin and the ANSYS Fluent CFD simulation module. The SACS modeling plugin can quickly build accurate mechanical models of the tooling structure, while the ANSYS Fluent CFD simulation module can efficiently analyze the heat dissipation characteristics of the equipment. The two work together to provide comprehensive model support for optimization. It automatically generates a 3D model of the tooling, a heat dissipation analysis report, and parameter sensitivity analysis curves. The 3D model can be rotated 360° for easy viewing and comprehensive understanding of the tooling structure. The heat dissipation analysis report records detailed heat dissipation simulation data and conclusions. The parameter sensitivity analysis curves clearly show the degree of influence of each parameter on the optimization results, providing a basis for parameter adjustment. The hybrid optimization algorithm (steepest descent method with multiple starting points in parallel + genetic algorithm for secondary search) on the optimized execution module can solve 100 sets of parameter combinations in 28 minutes, which is faster than the expected 30 minutes and significantly shortens the optimization cycle. The parameter optimization accuracy reaches 99.2%, which is higher than the set accuracy requirement of 99%, ensuring that the obtained optimal configuration parameters are accurate and reliable, and can effectively guide the actual tooling design and manufacturing. The optimization execution module has an optimization result comparison function, which can compare the optimization results of different rounds, display the differences in objective function values, key parameters, etc., to help users select the optimal optimization solution; it also supports the export of optimization results, which can be exported to Excel, PDF and other formats, so that users can save, analyze and report them.

[0040] The verification module can output a PDF strength verification report, an MP4 hoisting simulation animation, and a TIF heat dissipation simulation cloud map. The PDF strength verification report includes detailed structural strength calculations, UC values, displacement data, etc., and is formatted in a standardized way for easy archiving and approval. The MP4 hoisting simulation animation vividly demonstrates the entire hoisting process, clearly showing the hoisting path, equipment posture changes, and load distribution, facilitating the early detection and adjustment of potential problems during hoisting. The TIF heat dissipation simulation cloud map has high resolution, clearly showing the temperature distribution in different areas of the equipment and intuitively reflecting the heat dissipation effect. The verification module supports integration with platform equipment management systems (such as the SAP PM module). The integration process is simple and convenient, enabling compatibility verification of optimized solutions with existing facilities' pipelines and circuits through data interaction. The verification process is highly automated, requiring minimal manual intervention. Compatibility verification takes ≤10 minutes, efficiently completing the verification work and avoiding on-site construction delays or rework due to compatibility issues. If incompatibility issues are found during verification, the system will automatically indicate the location and cause of the incompatibility, providing clear guidance for users to adjust and optimize their solutions.

[0041] The applicant declares that the above description is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Those skilled in the art should understand that any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention fall within the protection and disclosure scope of the present invention.

Claims

1. A method for designing integrated tooling for fracturing equipment based on a mobile offshore platform, characterized in that: Includes the following steps: S1. Construct an optimized parameter system; S2. Construct the objective function and constraint functions; S3. Solve the optimization parameter system constructed in step S1 based on the objective function and constraint function established in step S2 to obtain the integrated tooling with the optimal configuration.

2. The integrated tooling design method for fracturing equipment based on a mobile offshore platform according to claim 1, characterized in that: The optimized parameter system includes fracturing equipment parameters, tooling structure parameters, platform adaptation parameters, and operational constraint parameters.

3. The integrated tooling design method for fracturing equipment based on a mobile offshore platform according to claim 2, characterized in that: The fracturing equipment parameters include the number of core equipment units and the external dimensions, weight, center of gravity coordinates, and working load of each core equipment unit; the tooling structure parameters include the number of modular tooling layers, the net height between modular tooling layers, the cross-sectional dimensions of the support beams, the type of connection nodes, the length of the slide rails, and the traction force parameters of the sliding mechanism; the platform adaptation parameters include the available deck area, the bearing threshold for different areas, the operating radius of the cantilever beam, the maximum lifting capacity of the crane, and the capacity of the mud pit; the operational constraint parameters include the target fracturing displacement, the equipment operation and maintenance space threshold, the minimum curvature radius of the pipeline, and the upper limit of the safe load.

4. The integrated tooling design method for fracturing equipment based on a mobile offshore platform according to claim 1, characterized in that: The objective function has two objectives: maximizing space utilization and maximizing the fracturing discharge rate. The mathematical expression for the objective function is: ； in: ； 。 5. The integrated tooling design method for fracturing equipment based on a mobile offshore platform according to claim 1, characterized in that: The constraint function is a triple constraint system consisting of structural safety constraints, operational function constraints, and platform adaptation constraints. The structural safety constraints include the support beam stress utilization factor UC≤1, the maximum Z-direction displacement of the node ≤ beam span / 240, the equipment hoisting load ≤ the crane rated load, and the total tooling load ≤ the deck area safety load. The operational constraints include equipment spacing ≥ 0.65m, air velocity in the fracturing pump heat dissipation channel ≥ 3m / s, and traction force of the sliding mechanism ≤ rated pulling force of the winch; The platform adaptation constraints include that the tooling dimensions do not exceed the deck boundary, the equipment center of gravity projection falls within the range of the platform's main load-bearing beam, and the pipeline layout does not conflict with the platform's existing facilities.

6. The integrated tooling design method for fracturing equipment based on a mobile offshore platform according to claim 1, characterized in that: Step S3 specifically includes the following steps: S31. Based on the engineering practice rules for the layout of offshore oil engineering equipment, and combined with the constraint boundary of the optimization parameter system constructed in step S1, multiple sets of feasible initial layout schemes are automatically generated through integrated tools. S32. Establish a mechanical model of the tooling structure to simulate the stress of the tooling under working load and hoisting load, and output the core structural data; analyze the heat dissipation characteristics of the equipment and output the key heat dissipation data; use the Kriging proxy model to perform dimensionality reduction modeling on the high-dimensional combination of the core structural data, key heat dissipation data and optimization parameter system. S33. The optimal integrated tooling configuration is obtained by using a hybrid optimization strategy of steepest descent method and genetic algorithm.

7. The integrated tooling design method for fracturing equipment based on a mobile offshore platform according to claim 6, characterized in that: The production quantity of the initial layout scheme conforms to the conventional quantity for multi-scheme comparison in marine engineering, and the production quantity of the initial layout scheme is 30 to 100 sets.

8. The integrated tooling design method for fracturing equipment based on a mobile offshore platform according to claim 6, characterized in that: The mechanical model of the tooling structure was established using SACS software, a mature application in the field of marine engineering. The core structural data includes the stress utilization factor of the support beam, the Z-direction displacement of the nodes, the overall weight of the tooling, and the adaptability parameters of the support beam cross-sectional dimensions. The analysis of the equipment's heat dissipation characteristics was performed using the integrated ANSYS Fluent CFD simulation module; the key heat dissipation data included the average temperature of the densely populated equipment area, the wind speed distribution in the heat dissipation channels, the location and temperature of hot spots, and the power requirements for the fans.

9. An integrated tooling design device for fracturing equipment based on a offshore mobile platform for implementing the method described in any one of claims 1 to 8, characterized in that: include: The parameter selection module is configured to select an optimization parameter system and supports data import; The function building module is configured to build objective functions and constraint functions; The optimization execution module is configured to solve for the optimal configuration through modeling, simulation, and algorithms. The verification module is configured to perform strength, hoisting, and compatibility verifications.

10. The integrated tooling design device for fracturing equipment based on a mobile offshore platform according to claim 9, characterized in that: The optimization execution module integrates the SACS structural modeling plugin, CFD simulation module, and a hybrid optimization strategy of steepest descent method + genetic algorithm, with a solution time of ≤30 minutes and parameter optimization accuracy of ≥99%.

Images