Multi-sensing feedback drilling, jacking and pulling combined pipeline laying intelligent construction method and system

Abstract

The invention relates to the technical field of pipeline laying, in particular to a multi-sensing feedback drilling, jacking and pulling combined intelligent construction method and system for pipeline laying, and the method comprises the steps: firstly collecting environment data of a construction region to construct a region model, simulating a construction scheme based on the model to generate an optimization scheme, and carrying out fixed-point sampling according to the optimization scheme; the model and the scheme are adjusted through sampling data, construction is conducted according to the adjusted scheme, monitoring data are collected in construction, evaluation information is obtained through model analysis, intelligent management and control of the whole construction process are achieved, the scheme is simulated and optimized in advance, and construction risks are reduced; and real-time feedback adjustment is achieved, the construction quality and progress are guaranteed, the cost is reduced, the accuracy and efficiency of pipeline laying are improved, and efficient and safe pipeline laying is achieved.

Description

Technical Field

[0001] This invention relates to the field of pipeline laying technology, and more specifically, to an intelligent construction method and system for pipeline laying combining drilling and pulling with multi-sensor feedback. Background Technology

[0002] In traditional pipeline laying projects, the formulation of construction plans often relies on limited geological survey data and experience judgment. Due to the inability to fully and accurately grasp the geological conditions of the construction area, the distribution of underground obstacles and other environmental information, various emergencies are likely to be encountered during the construction process, such as encountering hard rock layers that make drilling difficult, or hitting underground pipelines that cause damage. This not only increases construction costs and time, but may also lead to safety accidents. Summary of the Invention

[0003] In view of this, embodiments of the present invention provide a smart construction method and system for pipeline laying using a combination of drilling and pulling with multi-sensor feedback, so as to achieve efficient and safe pipeline laying.

[0004] To achieve the above objectives, the embodiments of the present invention provide the following technical solutions: According to one aspect of the present invention, a smart construction method for drilling-pull combined pipeline laying with multi-sensor feedback is provided, comprising: Environmental data of the construction area is collected for digital simulation to obtain a regional model of the construction area. The construction plan is simulated based on the aforementioned regional model to generate an optimized plan; Based on the optimization scheme, fixed-point sampling was performed on the construction area to obtain sampling data; The parameters of the region model are adjusted using the sampled data, and the optimization scheme is adjusted simultaneously. According to the adjusted optimization plan, drilling, hole enlargement, and pipe laying were carried out in the construction area. During construction, monitoring data is collected and analyzed using the regional model to obtain construction assessment information.

[0005] According to another aspect of the present invention, a smart construction method system for drilling-pull combined pipeline laying with multi-sensor feedback is provided, comprising: The area simulation module is used to collect environmental data of the construction area for digital simulation to obtain an area model of the construction area. The scheme optimization module is used to simulate the effects of the construction scheme based on the regional model in order to generate an optimized scheme; The fixed-point sampling module is used to perform fixed-point sampling of the construction area according to the optimization scheme to obtain sampling data; The parameter adjustment module is used to adjust the parameters of the region model using the sampled data, and simultaneously adjust the optimization scheme. The construction execution module is used to perform drilling, hole enlargement, and pipe laying in the construction area according to the adjusted optimization plan. The construction monitoring module is used to collect monitoring data during the construction process and analyze it in conjunction with the regional model to obtain construction assessment information.

[0006] As can be seen from the above technical solutions, the intelligent construction method for pipeline laying with multi-sensor feedback and drilling top-pulling combination provided by the present invention has the following beneficial effects: This invention first collects environmental data of the construction area to construct a regional model. Based on this model, it simulates the construction plan and generates an optimized plan. It then samples at fixed points according to the optimized plan, adjusts the model and plan using the sampled data, and constructs according to the adjusted plan. During construction, it collects monitoring data and combines it with the model to obtain evaluation information, thereby achieving intelligent control of the entire construction process. It simulates and optimizes the plan in advance to reduce construction risks; it provides real-time feedback and adjustments to ensure construction quality and progress, reduce costs, and improve the accuracy and efficiency of pipeline laying, so as to achieve efficient and safe pipeline laying. Attached Figure Description

[0007] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are merely embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort: Figure 1 A schematic diagram illustrating the steps of the intelligent construction method for drilling-pull-combined pipeline laying with multi-sensor feedback provided in an embodiment of the present invention; Figure 2 This is a structural schematic diagram of the intelligent construction method system for drilling and pulling combined with multi-sensor feedback pipeline laying provided in an embodiment of the present invention. Detailed Implementation

[0008] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0009] In traditional pipeline laying projects, the formulation of construction plans often relies on limited geological survey data and experience judgment. Due to the inability to fully and accurately grasp the geological conditions of the construction area, the distribution of underground obstacles and other environmental information, various emergencies are likely to be encountered during the construction process, such as encountering hard rock layers that make drilling difficult, or hitting underground pipelines that cause damage. This not only increases construction costs and time, but may also lead to safety accidents.

[0010] In view of this, the present invention provides an intelligent construction method for pipeline laying combining drilling and pulling with multi-sensor feedback, the steps of which are as follows: Figure 1 As shown, it includes: The first step is to collect environmental data of the construction area for digital simulation to obtain a regional model of the construction area; The second step is to simulate the effects of the construction plan based on the aforementioned regional model in order to generate an optimized plan. The third step is to perform fixed-point sampling in the construction area according to the optimization scheme to obtain sampling data; The fourth step is to adjust the parameters of the region model using the sampled data, and simultaneously adjust the optimization scheme. The fifth step is to carry out drilling, hole enlargement, and pipe laying construction in the construction area according to the adjusted optimization plan; The sixth step is to collect monitoring data during construction and analyze it in conjunction with the regional model to obtain construction assessment information.

[0011] Specifically, in the first step of the embodiment provided by this invention, the defined range of pipeline laying is determined, and a pre-constructed digital twin is bounded based on the defined range to obtain a digital twin corresponding to the defined range. This clarifies the specific scope involved in pipeline laying, for example, determining the starting point, ending point, and route of the pipeline according to design drawings, thereby defining a clear area boundary. Then, the pre-constructed digital twin covering a wider area is trimmed and filtered according to this defined range, retaining only the parts related to the pipeline laying area, thus obtaining a digital twin corresponding to the defined range. Based on the digital twin, several detection nodes are selected in the construction area to collect environmental data from each detection node. More specifically, based on the characteristics of the construction area presented by the digital twin, such as topography and geological structure, representative locations are selectively chosen as detection nodes within the construction area. These detection nodes can be distributed across different geological layers and at locations with topographical changes. Using various specialized detection equipment, such as ground-penetrating radar, soil moisture sensors, and groundwater level monitors, environmental data is collected from each detection node, including information on geological type, soil moisture, groundwater level, and topographic elevation. Based on this environmental data, parameters are set for the digital twin, and information extension analysis is performed on specific locations within the construction area to obtain a regional model. More specifically, the environmental data collected from each detection node is accurately input into the corresponding defined range of the digital twin. The relevant parameters of the digital twin are adjusted and set to more accurately reflect the actual environmental conditions of the construction area. Then, using mathematical models and algorithms, based on these known detection node data, the environmental information of other undetected locations in the construction area is inferred and estimated, realizing extended analysis of information, and finally constructing a complete regional model that can comprehensively reflect the environmental characteristics of the construction area.

[0012] More specifically, pipeline laying typically involves only a specific area. Limiting the scope of the digital twin to the limited area of ​​pipeline laying can avoid processing too much irrelevant data, allowing subsequent analysis and simulation to focus more on the actual construction area, improving work efficiency and relevance. Reducing the scope of the digital twin can significantly reduce the amount of data that needs to be processed, lowering computational costs and time consumption, while also helping to improve the accuracy and reliability of simulation results.

[0013] More specifically, the environmental conditions of the construction area are complex and diverse. By selecting detection nodes at different locations and collecting environmental data, the actual environmental information of the construction area can be directly obtained, providing a real and reliable data foundation for subsequent digital simulation. Reasonable selection of detection nodes can ensure that the collected data is representative and can fully reflect the geological, topographical and other environmental characteristics of the construction area, thereby providing strong support for building an accurate regional model.

[0014] More specifically, by inputting the collected environmental data into the digital twin for parameter settings, the digital twin can more accurately simulate the actual situation of the construction area, improving the credibility and effectiveness of the simulation results. Since it is impossible to detect every location in the construction area, information extension analysis can be used to infer and estimate the information of undetected locations using known detection node data, achieving comprehensive coverage of specific locations in the construction area, thereby constructing a complete regional model.

[0015] Specifically, in the second step of the embodiment provided by the present invention, the construction plan is analyzed for each construction stage to obtain construction target information for multiple construction stages. The entire construction plan is divided into multiple different construction stages according to the time sequence or construction process. For example, the pipeline laying construction plan is divided into the preliminary site preparation stage, drilling stage, borehole enlargement stage, pipe laying stage, etc. Specific construction targets are defined for each stage. For example, in the drilling stage, the construction targets may include the drilling depth, diameter, direction, deviation range, etc.; in the pipe laying stage, the construction targets may be the pipeline laying speed, pipeline connection quality, etc., thereby obtaining construction target information for multiple construction stages.

[0016] More specifically, by utilizing a regional model and combining it with construction target information, the effects of each construction stage are simulated. For example, when simulating the drilling stage, based on the geological information, drilling equipment parameters, and set drilling targets in the regional model, the resistance that may be encountered during drilling, whether deviations will occur, etc., are predicted. Through a series of simulation calculations, the construction effect is evaluated to determine whether the expected construction targets can be achieved. If the evaluation results show that some construction targets are difficult to achieve or have room for optimization, the construction target information is decomposed into multiple stages. The stage construction targets of each construction stage are used as adjustment starting points, and the adjustment simulations for the current stage and subsequent stages are performed on each adjustment starting point. For example, if it is found that the deviation from the original plan may be large during the drilling stage, the drilling target of that stage is used as the starting point to simulate the impact of adjusting the drilling speed, changing the drilling angle, etc., on the current drilling stage and subsequent hole enlargement and pipe laying stages. The multi-stage content obtained from the adjustment simulation is combined to obtain a set of adjusted construction targets.

[0017] More specifically, for the several sets of adjusted construction objectives generated, the regional model is used again for simulation and evaluation. Taking into account multiple factors such as construction cost, construction time, and construction quality, the construction effects under different adjusted construction objectives are compared. For example, one set of adjusted construction objectives may shorten the construction time but increase the cost; another set of adjusted construction objectives may have a lower cost but a longer construction time. Through comprehensive evaluation and comparison, the adjusted construction objective with the best overall performance in all aspects is selected and determined as the optimization scheme.

[0018] More specifically, a construction plan is usually a holistic plan. By analyzing the objectives of each construction stage, the abstract construction plan can be refined into specific and actionable construction objectives. This helps to understand the tasks and requirements of each stage more clearly, providing a clear direction for subsequent simulation and optimization. Different construction stages have different characteristics and requirements. Breaking the construction plan into multiple stages for objective analysis allows for separate analysis and processing of the characteristics of each stage, improving the accuracy and effectiveness of simulation and optimization.

[0019] More specifically, by simulating and evaluating the construction effects, potential problems during construction can be identified in advance, such as the impact of geological conditions on construction and the suitability of construction equipment. This allows for corresponding adjustments to be made before actual construction, avoiding serious problems during construction and ensuring smooth progress. Analyzing the adjustment methods of construction target information based on the evaluation results can explore different construction methods and parameter combinations, find possible optimization directions, and take into account the mutual influence between different stages of construction through multi-stage adjustment simulation, generating more comprehensive and reasonable adjustment targets for construction.

[0020] More specifically, by simulating and evaluating multiple adjustment targets and comprehensively considering various factors, the optimal solution can be selected from numerous adjustment options. This helps to optimize the overall construction process, reduce construction costs and shorten construction time as much as possible while ensuring construction quality, thereby improving the economic and social benefits of construction.

[0021] Specifically, in the third step of the embodiment provided by this invention, the various construction parameters and operation steps in the optimization scheme are input into the regional model. Using computer simulation software, the construction process is simulated step by step according to the process of the optimization scheme. For example, in the simulated drilling stage, based on the drilling speed, angle, depth and other parameters set in the optimization scheme, combined with the geological information in the regional model, the movement of the drill bit underground is simulated, and the drilling depth, deviation and other information at different time points are recorded. Through such simulation, the performance information of the regional model in each stage of construction operation according to the optimization scheme is generated, such as the construction progress of different construction stages and possible geological changes.

[0022] More specifically, a careful analysis of the stage performance information obtained from the simulation identifies locations that may have a critical impact on the construction outcome. For example, if the simulation shows a sudden increase in drilling resistance at a certain geological depth, or a potential risk of soil collapse at a certain location, then this location is considered a critical location associated with the construction operation. These locations are marked in the regional model; these marked locations are the potential sampling points, covering areas where important situations such as geological changes and engineering risks may be encountered during construction.

[0023] More specifically, for each potential sampling point, the impact of its geological environment (such as soil type, rock hardness, and groundwater level) on construction operations is comprehensively considered. Through professional geological analysis methods and engineering experience, the importance of the data obtained from sampling at that point for optimizing the construction plan and reducing construction risks is assessed. For example, potential sampling points with complex geological conditions and significant impact on construction are identified as the final sampling points; while potential sampling points with relatively stable geological conditions and less impact on construction may be excluded. After such analysis and screening, several representative and important sampling points are identified on the regional model.

[0024] More specifically, based on the sampling point locations determined on the regional model, corresponding locations are found in the actual construction area. Various specialized geological exploration equipment, such as drilling equipment, ground-penetrating radar, and soil samplers, are used to collect geological environmental data from these sampling points. The collected data includes soil physical properties (such as density and porosity), mechanical properties (such as compressive strength and shear strength), and geological structural information. The collected data is then organized and recorded to form sampling data.

[0025] More specifically, digital simulation can be used to rehearse the execution process of the optimized plan before actual construction, and predict the possible situations at each stage of the construction process. This helps to understand the difficulties and risks in the construction process in advance, and provides a basis for the subsequent determination of potential sampling points. The stage performance information is an important data foundation for subsequent analysis and decision-making. It can reflect the feasibility and effectiveness of the optimized plan under different geological conditions, and provide a reference for further construction adjustments and optimizations.

[0026] More specifically, construction areas are typically large, and comprehensive sampling is not only costly but also inefficient. By marking potential sampling points, attention can be focused on locations that may have a critical impact on construction, improving the targeting and effectiveness of sampling. Potential sampling points cover various important situations that may be encountered during construction, such as geological changes and engineering risks. Sampling these locations can obtain the most valuable geological environmental information, providing strong support for adjusting construction plans.

[0027] More specifically, while the number of potential sampling points may be large, not all points have an equally significant impact on construction. Through construction impact analysis of the geological environment, potential sampling points can be screened and optimized to ensure that the final selected sampling points provide the most critical and useful information. This reduces unnecessary sampling work, lowers costs and time consumption, and ensures that the selected sampling points, having undergone rigorous screening, accurately reflect the geological characteristics and potential risks of the construction area. Sampling these points provides reliable data support for further optimization of the construction plan, thereby guaranteeing construction quality and safety.

[0028] More specifically, while regional models and digital simulations can provide some reference, the actual geological environment may differ. By conducting on-site sampling, we can obtain real geological environment data of the construction area. This data is the most accurate and reliable, providing a solid foundation for the final determination and adjustment of the construction plan. The sampling data can directly reflect the geological conditions of the construction area. Based on this data, the construction team can develop a more reasonable construction plan, select appropriate construction equipment and processes, thereby improving construction efficiency, reducing construction risks, and ensuring the smooth progress of construction.

[0029] Specifically, in the fourth step of the embodiment provided by this invention, the sampled data is matched with the corresponding locations in the regional model. The geological parameters obtained from the sampling (such as soil density, hardness, and water content) are accurately substituted into the corresponding locations in the regional model. Then, using spatial interpolation methods (such as Kriging interpolation and inverse distance weighted interpolation), based on the substituted data, the geological parameters of adjacent unsampled locations are predicted. For example, if the soil hardness of a certain sampling point is known, the soil hardness of adjacent locations is predicted based on the surrounding topography, geological structure, and other information.

[0030] More specifically, the data extension calculation results are compared and analyzed with the original parameters in the regional model. If a large difference is found between the prediction results and the original parameters, it indicates that the original parameters may be inaccurate and the parameters of the regional model need to be adjusted. For example, if the predicted soil moisture content of a certain region differs significantly from the original moisture content parameters of that region in the regional model, the moisture content parameters of that region are corrected based on the prediction results.

[0031] More specifically, the calculation of the changes in geological parameters in each region of the regional model after parameter adjustments is performed, and the impact of these changes on the overall construction area is analyzed. For example, it is assessed whether changes in soil hardness will affect the difficulty and speed of drilling, and whether changes in groundwater level will increase the difficulty of drainage during construction. Based on the analysis results, it is determined whether the optimized scheme needs to be modified, and a judgment criterion for modification is set (e.g., modification is considered necessary when changes in geological parameters exceed a certain proportion).

[0032] More specifically, when the adjustment range of the regional conditions reaches the preset threshold, it indicates that the optimization plan may need to be modified. Using the regional model after parameter adjustment, the effects of possible improvement methods of the optimization plan (such as adjusting the drilling speed, changing the pipeline laying route, etc.) are simulated. The performance of each improvement method in terms of construction cost, construction time, construction quality, etc. is evaluated and compared. The improvement method with the best overall performance in all aspects is selected, and the construction operation parameters of the optimization plan are adjusted.

[0033] More specifically, the sampled data accurately reflects the actual geological conditions of the construction area. Substituting it into the regional model makes the model more closely resemble the actual situation. By extending the calculations to neighboring locations, the limitations of the limited sampling points can be compensated for, enabling the regional model to more comprehensively reflect the geological characteristics of the construction area. A more accurate regional model can provide a more reliable basis for subsequent construction decisions, reducing construction risks and increased costs caused by model inaccuracies.

[0034] More specifically, the difference between the extended calculation results and the original parameters may be due to inaccurate original data or changes in geological conditions. By adjusting the parameters of the regional model, the reliability of the model can be ensured, enabling it to accurately simulate the geological conditions of the construction area. Accurate regional model parameters are the basis for subsequent regional condition analysis and optimization scheme evaluation. Only by ensuring the accuracy of the model parameters can reasonable analysis and evaluation results be obtained.

[0035] More specifically, not all adjustments to the regional model parameters require modification of the optimization scheme. By analyzing the magnitude of the regional condition adjustments, the need for modification of the optimization scheme can be determined, avoiding unnecessary adjustments and saving time and costs. When the adjustment of the regional model parameters has a significant impact on the construction area, timely determination of the need for modification of the optimization scheme can help identify potential problems during construction in advance, allowing for appropriate adjustments to ensure the smooth progress of construction.

[0036] More specifically, when the correction requirement reaches a preset threshold, it indicates that changes in geological conditions may have a significant impact on the implementation of the optimization plan. By simulating, evaluating, and comparing the effects of various improvement methods on the optimization plan, the optimal improvement method can be selected to adjust the parameters of the optimization plan. This allows the optimization plan to better adapt to changes in geological conditions, ensuring the quality and efficiency of construction. Continuously adjusting the optimization plan based on the actual geological conditions enables continuous optimization during construction, reducing construction costs, improving construction quality, and ensuring the smooth achievement of construction goals.

[0037] Specifically, in the fifth step of the embodiment provided by the present invention, the directional drilling rig is precisely set according to the drilling path, drilling depth, drilling angle and other parameters determined in the adjusted optimization scheme. The operator starts the drilling rig through the control system of the drilling rig and drills in the construction area according to the pre-planned path. During the drilling process, the position and direction of the drilling are monitored in real time by the guidance system to ensure that the drilling is carried out strictly according to the specified path and finally forms a guide hole. For example, the drilling direction of the drilling rig is adjusted at any time by using equipment such as underground guidance instruments to ensure the accuracy of the guide hole.

[0038] More specifically, after the pilot hole reaches the outlet end, a receiving pit is excavated at the outlet end according to the requirements of the optimization plan. The size, depth, and shape of the receiving pit need to be determined based on factors such as the diameter and length of the pipeline and the operating space of the construction equipment. After the excavation is completed, the directional drilling rig and guide rail laying device are redeployed to a suitable position near the receiving pit according to the optimization plan. For example, the directional drilling rig is adjusted to a position that can accurately align with the outlet of the pilot hole, the guide rail laying device is installed, and its smooth operation is ensured.

[0039] More specifically, after the equipment is redeployed, the directional drilling rig starts from the exit end of the pilot hole and expands the pilot hole according to the expansion parameters (such as expansion diameter and expansion speed) set in the optimized scheme. During the expansion process, mud is injected into the hole through the mud circulation system to stabilize the hole wall and carry away drill cuttings. At the same time, the guide rail laying device follows the progress of the expansion and gradually drags the prefabricated pipe into the expanded hole for laying. For example, after each section of expansion is completed, the guide rail laying device immediately drags the corresponding length of pipe into the hole until the entire pipe is laid.

[0040] More specifically, the pilot hole is the foundation of the entire pipeline laying construction. It determines the accurate path for subsequent hole enlargement and pipe laying operations. By precisely controlling the drilling path, it can be ensured that the pipeline can accurately cross the construction area according to the design requirements, avoiding damage to the surrounding environment and underground facilities. Real-time monitoring and adjustment of the drilling direction during the drilling process can ensure the accuracy of the pilot hole, providing good preconditions for subsequent hole enlargement and pipe laying operations. High-precision pilot holes can reduce deviations and errors in the construction process and improve construction quality.

[0041] More specifically, the receiving pit provides the necessary working space for the directional drilling rig and guide rail laying device, facilitating equipment operation and maintenance. At the same time, the receiving pit can also serve as the pipeline inlet and the operating platform for construction personnel, ensuring the smooth progress of the construction process. When transitioning from the drilling stage to the reaming and pipe laying stage, it is necessary to readjust the position and direction of the equipment. Excavating the receiving pit at the outlet end of the pilot hole and redeploying the equipment can ensure a smooth connection of the construction process and improve construction efficiency.

[0042] More specifically, the diameter of the guide hole is usually small and cannot meet the requirements of pipeline laying. By enlarging the hole, the diameter of the guide hole can be enlarged to a suitable size, creating conditions for pipeline laying. At the same time, the use of the mud circulation system can ensure the stability of the hole wall and prevent the hole from collapsing. The guide rail laying device follows the progress of hole enlargement to drag and lay the pipeline, realizing the synchronous operation of hole enlargement and pipe laying. This avoids problems such as hole wall collapse that may occur when laying pipe after hole enlargement is completed, improves construction efficiency, and shortens the construction cycle.

[0043] Specifically, in the sixth step of the embodiment provided by the present invention, various sensors, such as pressure sensors, displacement sensors, and speed sensors, are installed at key parts of the directional drilling rig and the guide rail laying device. During the construction process, these sensors collect relevant data in real time, such as the drilling pressure and drilling speed of the directional drilling rig, the displacement of the drill bit, the drag force of the guide rail laying device, and the laying speed of the pipeline. The sensors transmit the collected data to the data acquisition system for storage and preliminary processing.

[0044] More specifically, the collected monitoring data is input into the regional model, and the model's simulation function is used to simulate and reproduce the construction operations and effects in real time. For example, based on the drilling pressure and speed data of the directional drilling rig, the drilling process of the drill bit underground is simulated in the regional model; based on the drag force of the guide rail laying device and the pipeline laying speed, the pipeline laying process is simulated. In this way, the real-time characteristics of the construction process are obtained, such as the actual trajectory of the borehole, the laying position and status of the pipeline, etc.

[0045] More specifically, by utilizing the analysis and prediction functions of the regional model, combined with the actual construction characteristics and the remaining steps of the optimized plan, the construction situation in the future time period can be predicted. For example, based on the current drilling trajectory and geological conditions, the resistance and deviations that may be encountered during the subsequent borehole enlargement process can be predicted; based on the pipeline laying status, potential problems that may arise during the remaining pipeline laying process can be predicted. Through simulation and analysis of various possible scenarios, construction prediction information for the future time period can be obtained, such as construction progress, construction quality, and potential risks.

[0046] More specifically, by comprehensively considering various factors in the construction forecast information, such as construction progress, construction cost, construction quality, and risk level, a value assessment is conducted on the subsequent execution steps of the optimized plan. For example, if it is predicted that continuing construction according to the current plan will lead to a significant increase in costs or a high risk, the subsequent steps need to be reassessed and adjusted. Based on the assessment results, construction assessment information is generated, including the evaluation of the optimized plan, whether the plan needs to be adjusted, and suggestions for adjustment.

[0047] More specifically, by collecting monitoring data through sensor arrays, the working status and construction performance of directional drilling rigs and guide rail laying devices can be obtained in real time. This data can reflect the actual situation during the construction process, helping construction personnel to identify problems in a timely manner, such as equipment failures and abnormal construction parameters, so as to take corresponding measures to deal with them. Monitoring data is the basis for subsequent construction reality reproduction, effect prediction and value assessment. Accurate and comprehensive monitoring data can improve the accuracy and reliability of subsequent analysis and provide strong support for construction decisions.

[0048] More specifically, inputting monitoring data into the regional model for real-time reproduction can intuitively demonstrate construction operations and effects, enabling construction personnel to more clearly understand the actual situation during construction. Through the characteristics of the actual construction situation, deviations from the optimized plan can be identified in a timely manner, providing a basis for subsequent adjustments and optimizations. Comparing the characteristics of the actual construction situation with the simulation results of the regional model can verify the accuracy and reliability of the regional model. If a significant difference is found, it indicates that the regional model may need further adjustment and optimization to better reflect the actual construction situation.

[0049] More specifically, by predicting future construction conditions, construction personnel can understand potential problems and risks in advance and develop targeted countermeasures. For example, if significant resistance is predicted during the subsequent hole enlargement process, more suitable equipment can be prepared in advance or construction parameters can be adjusted to avoid delays or quality issues during construction. Construction forecast information can provide a reference for adjusting the optimization plan. Based on the forecast results, subsequent steps of the optimization plan can be adjusted and optimized to make the construction plan more reasonable and efficient, thereby improving the overall construction benefits.

[0050] More specifically, construction assessment information integrates construction forecast information and value evaluation of optimized solutions, providing a comprehensive and objective basis for construction decisions. Construction personnel can use the assessment information to determine whether adjustments to the optimized solution are necessary and how to make those adjustments, thereby ensuring the smooth progress of the construction process and the achievement of construction goals. Through continuous evaluation and adjustment of the optimized solution, continuous improvement of the construction process can be achieved. After each construction phase, lessons learned from the construction assessment information are summarized to provide a reference for subsequent similar projects, improving construction management and quality.

[0051] As can be seen from the above technical solutions, the intelligent construction method for pipeline laying with multi-sensor feedback and drilling top-pulling combination provided by the present invention has the following beneficial effects: This invention first collects environmental data of the construction area to construct a regional model. Based on this model, it simulates the construction plan and generates an optimized plan. It then samples at fixed points according to the optimized plan, adjusts the model and plan using the sampled data, and constructs according to the adjusted plan. During construction, it collects monitoring data and combines it with the model to obtain evaluation information, thereby achieving intelligent control of the entire construction process. It simulates and optimizes the plan in advance to reduce construction risks; it provides real-time feedback and adjustments to ensure construction quality and progress, reduce costs, and improve the accuracy and efficiency of pipeline laying, so as to achieve efficient and safe pipeline laying.

[0052] Furthermore, the step of collecting environmental data of the construction area for digital simulation to obtain a regional model of the construction area includes: The defined range of pipeline laying is determined, and the boundary of the pre-constructed digital twin is restricted based on the defined range to obtain a digital twin corresponding to the defined range; Based on the digital twin, several detection nodes are selected in the construction area to collect environmental data from each detection node. Based on the environmental data, the parameters of the digital twin are set, and information expansion analysis is performed on the specific locations of the construction area to obtain a regional model.

[0053] Specifically, based on the pipeline laying design plan, the starting point, ending point, and route of the pipeline are clearly defined, thus delineating a specific geographical area as the limiting range for pipeline laying. For a pre-constructed digital twin covering a large area, Geographic Information System (GIS) technology or professional modeling software is used to trim and filter the digital twin according to the defined limiting range, removing the parts outside the limited range, thereby obtaining a digital twin that only corresponds to the defined range. Pipeline laying only involves a specific area. By defining the limiting range and restricting the boundaries of the digital twin, subsequent analysis and simulation work can focus on the actual construction area, avoiding the processing of a large amount of irrelevant data, improving work efficiency and relevance. Narrowing the range of the digital twin can significantly reduce the amount of data that needs to be processed, reduce computing costs and time consumption, and also help improve the accuracy and reliability of simulation results.

[0054] More specifically, the analysis of the corresponding defined digital twin involves selecting representative locations as detection nodes within the construction area based on its topography, geological structure, and hydrological conditions. These locations may include the boundaries of different geological layers, areas with significant topographic changes, and areas where underground obstacles may exist. Various specialized detection equipment, such as geological drilling equipment, ground-penetrating radar, soil moisture sensors, and groundwater level monitors, are used to collect environmental data from each detection node. The collected data includes information on geological type, soil moisture, groundwater level, topographic elevation, and rock hardness. Given the complex and diverse environmental conditions of the construction area, selecting detection nodes at different locations and collecting environmental data allows for the direct acquisition of actual environmental information, providing a reliable data foundation for subsequent digital simulations. Appropriate selection of detection nodes ensures that the collected data is representative and comprehensively reflects the geological, topographical, and other environmental characteristics of the construction area, thus providing strong support for constructing an accurate regional model.

[0055] More specifically, the environmental data collected from each detection node is accurately input into the corresponding defined range of the digital twin. The relevant parameters of the digital twin are then adjusted and set. For example, based on soil type and rock hardness data obtained from geological drilling, the geological parameters at corresponding locations in the digital twin are adjusted; based on groundwater level monitoring data, the water level information in the digital twin is set. Using spatial interpolation algorithms (such as Kriging interpolation, inverse distance weighted interpolation, etc.) and geostatistical methods, environmental information at other undetected locations within the construction area is inferred and estimated based on known detection node data, enabling extended information analysis. In this way, environmental information at specific locations throughout the construction area is obtained, thereby constructing a complete regional model that comprehensively reflects the environmental characteristics of the construction area. Inputting the collected environmental data into the digital twin for parameter setting allows the digital twin to more accurately simulate the actual situation of the construction area, improving the reliability and effectiveness of the simulation results. Since it is impossible to detect every location in the construction area, extended information analysis can utilize known detection node data to infer and estimate information at undetected locations, achieving comprehensive coverage of specific locations throughout the construction area, thus constructing a complete regional model.

[0056] Furthermore, the step of simulating the effects of the construction plan based on the aforementioned regional model to generate an optimized plan includes: The construction plan is analyzed for each construction stage to obtain construction target information for multiple construction stages. Based on the construction target information, the construction effect of the regional model is simulated and evaluated, and the construction target information is analyzed for adjustment based on the evaluation results to generate several adjusted construction targets. The regional model is used to simulate and evaluate the various adjusted construction objectives to determine the optimal adjusted construction objective as the optimization scheme.

[0057] Specifically, based on the construction plan's workflow and timeline, the entire construction process is divided into several clearly defined stages. For example, pipeline laying can be divided into site preparation, pilot hole drilling, borehole reaming, pipeline laying, and final acceptance stages. For each stage, specific and quantifiable construction objectives are determined. In the pilot hole drilling stage, objectives might include drilling depth, directional deviation range, and drilling speed; in the pipeline laying stage, objectives might include pipeline connection quality, laying speed, and accuracy. These objectives are then compiled into detailed construction objective information.

[0058] More specifically, the construction target information is input into the regional model, and simulation software or algorithms are used to simulate the effects of each construction stage. For example, when simulating pilot hole drilling, the geological information in the regional model is combined to predict the drilling situation of the drill bit in different strata, including possible resistance and deviation of the drilling direction. Based on the simulation results, the construction effect is evaluated from multiple dimensions such as construction cost, construction time, and construction quality. For example, the increased cost and time due to encountering hard rocks during drilling, or the quality problems such as weak connections that may occur during pipeline laying, are evaluated. If the evaluation results show that some construction targets are difficult to achieve or have room for optimization, the construction target information is analyzed in depth, and the targets of each construction stage are broken down. Starting with the target of each stage, different adjustment methods are considered. For example, in the pilot hole drilling stage, the drilling speed can be adjusted, and the drill bit type can be changed. Then, the impact of these adjustments on the current stage and subsequent stages is analyzed, and different adjustment methods are combined to generate several adjusted construction targets.

[0059] More specifically, the generated adjusted construction objectives are input into the regional model, and the construction effects are simulated and evaluated again. Taking into account multiple factors such as construction cost, construction time, construction quality, and risk level, the construction effect under each adjusted construction objective is comprehensively analyzed. The simulation evaluation results of different adjusted construction objectives are compared, and the adjusted construction objective with the best overall performance in all aspects is selected. For example, if an adjusted construction objective can guarantee construction quality, complete construction within a reasonable cost and time range, and has low risk, it is determined as the optimal solution.

[0060] More specifically, a construction plan is usually a macro-level plan. Through target analysis, it is broken down into specific target information for multiple construction stages, enabling construction personnel to have a clearer understanding of the tasks and requirements of each stage. This facilitates operation and management during actual construction. Different construction stages have different characteristics and requirements. After clarifying the construction goals of each stage, targeted simulations and evaluations can be conducted for each stage's goals, improving the accuracy and effectiveness of the simulations.

[0061] More specifically, by simulating and evaluating the construction effect through regional models before actual construction, potential problems that may be encountered during construction can be identified in advance, such as the impact of geological conditions on construction and the feasibility of construction techniques. Adjusting construction objectives based on the evaluation results can avoid serious problems during actual construction, reduce losses, and explore more construction scheme possibilities, find better construction strategies, and improve construction efficiency and quality.

[0062] More specifically, by simulating and evaluating the adjusted construction objectives again, and taking into account multiple factors, the optimal solution can be selected from multiple adjustment options, thereby achieving overall optimization of the construction process. This helps to reduce construction costs, shorten construction time, reduce construction risks, and improve the economic and social benefits of construction while ensuring construction quality.

[0063] Furthermore, the steps for adjusting the form of the construction target information based on the evaluation results include: The construction target information is broken down into multiple stages to obtain the stage construction targets for multiple construction stages; The phase construction objectives of each construction phase are used as the starting point for adjustment, and the adjustment simulation of the current phase and subsequent phases is carried out for each of the aforementioned adjustment starting points. The multi-stage content obtained from the adjustment simulation is combined to obtain a set of adjustment construction objectives.

[0064] Specifically, based on the process and logic of the construction plan, different construction stages are identified. For example, pipeline laying construction can be divided into the preliminary preparation stage (including site clearing, equipment arrival, etc.), the pilot hole drilling stage, the hole enlargement stage, the pipeline welding and laying stage, and the post-construction inspection and acceptance stage. The overall construction objectives are broken down according to each construction stage. For example, the overall construction objective might be to complete the laying of a certain length of pipeline with high quality within a specified time. In the preliminary preparation stage, the stage construction objective might be to complete site leveling and equipment debugging before a specific date. The objective of the pilot hole drilling stage might be to accurately drill to the specified depth and position according to the design requirements, with the deviation controlled within a certain range.

[0065] More specifically, for each stage of construction objectives, possible adjustment variables are determined. In the pilot hole drilling stage, adjustment variables could be drilling speed, drill bit type, mud pressure, etc.; in the reaming stage, adjustment variables could be the number of reaming operations, the increasing method of the reaming diameter, etc. Starting from the construction objectives of each stage, the corresponding adjustment variables are changed to simulate the construction process and effects of the current stage. For example, in the pilot hole drilling stage, the drilling accuracy, drilling time and equipment wear under different drilling speeds are simulated. The impact of the current stage's adjustments on subsequent stages is considered, and the construction process and effects of subsequent stages are simulated. If the drilling speed is adjusted in the pilot hole drilling stage, it may affect the timing and difficulty of the reaming stage, and the construction situation of the reaming stage under this influence needs to be simulated.

[0066] More specifically, the results obtained from the simulation adjustments at each stage are integrated, taking into account the interrelationships and influences between the stages. For example, the new drilling time and accuracy obtained after adjustments in the pilot hole drilling stage should be comprehensively considered in conjunction with the reaming time and quality obtained after adjustments in the reaming stage. Based on the integrated results, a new set of construction objectives is determined, including the specific objectives and corresponding construction parameters for each stage. For example, the new adjustment construction objective might be to use a specific drilling speed and drill bit type in the pilot hole drilling stage to achieve higher drilling accuracy, while adjusting the number of reaming operations and the diameter increment method accordingly in the reaming stage to ensure the efficiency and quality of the entire construction process.

[0067] More specifically, the construction process is usually complex, involving multiple interrelated stages. Breaking down the overall construction objectives into multiple stage objectives makes the tasks of each stage clearer and more specific, making it easier for construction personnel to understand and execute. Different construction stages have different characteristics and requirements. After breaking them down, individual analysis and adjustments can be made for each stage, improving the accuracy and effectiveness of the adjustments.

[0068] More specifically, the various stages of construction influence each other, and adjustments in one stage may have a chain reaction on subsequent stages. By simulating adjustments to the current stage and subsequent stages separately, this influence can be fully considered, avoiding the problem of focusing only on the current stage while ignoring the problems of subsequent stages. By changing different adjustment variables in the simulation, the optimization space of each stage can be explored, and better construction parameters and methods can be found to improve construction efficiency and quality.

[0069] More specifically, combining the simulation results of each stage can form a holistic adjustment and construction target plan, ensuring coordination and cooperation between each stage, making the entire construction process smoother and more efficient. By comprehensively considering the simulation results of each stage, a balance and optimization can be achieved among multiple objectives, such as shortening construction time and reducing costs as much as possible while ensuring construction quality.

[0070] Furthermore, the step of performing fixed-point sampling in the construction area according to the optimization scheme to obtain sampling data includes: The optimization scheme is executed using a digital simulation based on the regional model to generate several stages of performance information of the regional model in carrying out construction operations according to the optimization scheme. Based on the stage performance information, each location in the region model associated with the construction operation is marked to obtain several potential sampling points; A construction impact analysis of the geological environment conditions of each potential sampling point is conducted to determine several sampling points on the regional model. Geological environment data were collected at each sampling point in the construction area to obtain sampling data.

[0071] Specifically, the various construction parameters in the optimized plan, such as the operating parameters of construction equipment, construction sequence, and construction schedule, are accurately input into the regional model. The regional model undergoes necessary initialization settings to ensure it accurately reflects the actual conditions of the construction area. A digital simulation program is then initiated to simulate the construction process step-by-step according to the optimized plan. During the simulation, key information for each construction stage is recorded, such as the drill bit stress during drilling, the borehole expansion during reaming, and the pipe stress distribution during pipe laying. This information constitutes several stages of performance data. Digital simulation allows for a preview of the optimized plan's execution process before actual construction, providing advance knowledge of potential issues and risks at each stage. This helps identify potential problems and risks, providing a basis for determining potential sampling points. The stage performance data is a crucial data foundation for subsequent analysis and decision-making, reflecting the feasibility and effectiveness of the optimized plan under different geological conditions, and providing a reference for further construction adjustments and optimizations.

[0072] More specifically, a thorough study of the phase performance information is needed to identify locations that may have a critical impact on the construction outcome. For example, during drilling, locations with significant changes in geological conditions or abnormal drill bit stress; during pipe laying, locations of stress concentration in the pipeline. These critical locations are marked in the regional model and identified as potential sampling points. Different symbols or colors can be used to highlight these potential sampling points in the model for subsequent processing. Construction areas are typically large, and comprehensive sampling is not only costly but also inefficient. By marking potential sampling points, attention can be focused on locations that may have a critical impact on construction, improving the targeting and effectiveness of sampling. Potential sampling points cover various important situations that may be encountered during construction, such as geological changes and engineering risks. Sampling these locations can obtain the most valuable geological environment information, providing strong support for adjusting the construction plan.

[0073] More specifically, geological environmental information of potential sampling points is collected, including geological structure, soil type, rock hardness, and groundwater level. This information can be obtained by consulting geological data and historical data. Based on the collected geological information, the impact of the geological environment of each potential sampling point on construction operations is assessed. A combination of qualitative and quantitative methods can be used for assessment, such as establishing an impact assessment index system, scoring and weighting different geological factors. Based on the impact assessment results, potential sampling points with a greater impact on construction are selected and determined as the final sampling points. At the same time, the rationality of the distribution of sampling points is considered to ensure that they can comprehensively reflect the geological characteristics of the construction area. There may be a large number of potential sampling points, but not all points have an equally important impact on construction. Through the construction impact analysis of geological environmental conditions, potential sampling points can be screened and optimized to ensure that the final sampling points can provide the most critical and useful information, while reducing unnecessary sampling work, reducing costs and time consumption. The determined sampling points have been rigorously screened and can accurately reflect the geological characteristics and potential risks of the construction area. Sampling these points can provide reliable data support for further optimization of the construction plan, thereby ensuring construction quality and safety.

[0074] More specifically, based on the sampling point locations determined on the regional model, positioning equipment (such as GPS locators) is used to accurately locate the corresponding sampling points in the actual construction area. Various specialized geological exploration equipment, such as drilling equipment, ground-penetrating radar, and soil samplers, are used to collect geological environmental data from these sampling points. The collected data includes soil physical properties (such as density and porosity), mechanical properties (such as compressive strength and shear strength), and geological structural information. The collected data is then organized and recorded to ensure its accuracy and completeness. This data can be stored in a database for subsequent analysis and use. While regional models and digital simulations can provide some reference, actual geological conditions may differ. Field sampling provides the most accurate and reliable data on the real geological environment of the construction area, offering a solid foundation for the final determination and adjustment of the construction plan. The sampling data directly reflects the geological conditions of the construction area, allowing the construction team to develop more reasonable construction plans, select appropriate construction equipment and processes, thereby improving construction efficiency, reducing construction risks, and ensuring smooth construction progress.

[0075] Furthermore, the steps of adjusting the parameters of the region model using the sampled data and simultaneously adjusting the optimization scheme include: The sampled data is used to substitute data into the corresponding locations in the region model, and the substituted data is used as the basis for data extension calculation of the adjacent locations. Based on the results of the data extension calculation, the original parameters of the regional model are verified to adjust the parameters of the regional model. The regional condition adjustment range of the adjusted regional model is analyzed to determine the correction requirements of the optimization scheme. When the correction requirement reaches a preset threshold, the optimization scheme is simulated, evaluated and compared with the effects of various improvement methods based on the regional model after parameter adjustment, so as to adjust the parameters of the construction operation of the optimization scheme.

[0076] Specifically, the various indicators in the sampling data (such as soil density, moisture content, rock hardness, etc.) are accurately matched with the corresponding locations in the regional model. For example, if a sampling point corresponds to a specific grid cell in the regional model, the soil density and other data of that sampling point are accurately substituted into the corresponding parameters of that grid cell. Using appropriate spatial interpolation methods (such as Kriging interpolation, inverse distance weighted interpolation, etc.), based on the location of the substituted sampling data, the relevant data of the neighboring unsampled locations are predicted. For example, if the soil moisture content of several sampling points is known, the soil moisture content of the area surrounding these sampling points is predicted through interpolation algorithms.

[0077] More specifically, the calculated results of the extended data are comprehensively compared with the original parameters in the regional model. For example, the predicted soil density of a certain area is compared with the original soil density parameters of that area in the regional model. If a significant difference is found between the predicted results and the original parameters, it indicates that the original parameters may be inaccurate, and the parameters of the regional model need to be corrected. Based on the prediction results, the parameters at the corresponding locations in the regional model are updated to better reflect the actual situation.

[0078] More specifically, the analysis examines the magnitude of changes in geological parameters in each region of the regional model after parameter adjustment. For example, it calculates the difference between the soil moisture content parameter before and after adjustment in a certain region and compares it with the initial value of the parameter to obtain the adjustment magnitude. A judgment criterion (preset threshold) for correction needs is set, and the adjustment magnitude is used to determine whether the optimization scheme needs to be corrected. If the adjustment magnitude exceeds the preset threshold, it indicates that the change in geological conditions may have a significant impact on the implementation of the optimization scheme, and the optimization scheme needs to be corrected.

[0079] More specifically, for the optimization scheme, multiple possible improvement methods are proposed, such as adjusting the construction sequence, replacing construction equipment, and changing construction process parameters. Using the adjusted regional model, the construction effects of each improvement method are simulated. For example, the efficiency and quality changes during drilling are simulated after changing to different types of drilling equipment. The simulation effects of each improvement method are evaluated from multiple dimensions, including construction cost, construction time, construction quality, and risk level. The performance of different improvement methods on various evaluation indicators is compared to identify the improvement method with the best overall performance. Based on the evaluation and comparison results, the optimal improvement method is selected, and the construction operation parameters of the optimization scheme are adjusted accordingly. For example, if the improvement method of replacing drilling equipment performs better in terms of cost, time, and quality, the drilling equipment parameters in the optimization scheme are updated.

[0080] More specifically, the sampled data is a true reflection of the actual geological conditions of the construction area. Substituting it into the regional model can make the model more realistic. Extending the calculation of data to adjacent locations can make up for the limited number of sampling points, allowing the regional model to more comprehensively and accurately reflect the geological characteristics of the construction area. A more accurate regional model provides a more reliable basis for subsequent construction decisions and helps to reduce construction risks and increased costs caused by inaccurate models.

[0081] More specifically, the difference between the data extension calculation results and the original parameters may stem from errors in the original data or actual changes in geological conditions. Adjusting the parameters of the regional model can ensure the reliability of the model and enable it to accurately simulate the geological conditions of the construction area. Accurate regional model parameters are the basis for subsequent regional condition analysis and optimization scheme evaluation. Only by ensuring the accuracy of the model parameters can reasonable analysis and evaluation results be obtained.

[0082] More specifically, not all adjustments to the regional model parameters require modification of the optimization scheme. By analyzing the magnitude of the regional condition adjustments, the need for modification of the optimization scheme can be determined, avoiding unnecessary adjustments and saving time and costs. When the adjustment of the regional model parameters has a significant impact on the construction area, timely determination of the need for modification of the optimization scheme can help identify potential problems during construction in advance, allowing for appropriate adjustments to be made and ensuring smooth construction.

[0083] More specifically, when the correction requirement reaches a preset threshold, it indicates that changes in geological conditions may have a significant impact on the implementation of the optimization plan. By simulating, evaluating, and comparing the effects of various improvement methods on the optimization plan, the optimal improvement method can be selected to adjust the parameters of the optimization plan. This allows the optimization plan to better adapt to changes in geological conditions, ensuring the quality and efficiency of construction. Continuously adjusting the optimization plan based on the actual geological conditions enables continuous optimization during construction, reducing construction costs, improving construction quality, and ensuring the smooth achievement of construction goals.

[0084] Furthermore, the steps for drilling, hole enlargement, and pipe laying in the construction area according to the adjusted and optimized plan include: The directional drilling rig is driven to drill along a specified path in the construction area according to the adjusted optimization scheme to obtain a guide hole; A receiving pit is excavated at the outlet end of the guide hole to redeploy the directional drilling rig and guide rail laying device according to the optimization scheme; According to the optimization scheme, the directional drilling rig starts from the outlet end to expand the guide hole, and the guide rail laying device follows the progress of the hole expansion and digging to lay the pipeline.

[0085] Specifically, before construction, the directional drilling rig undergoes comprehensive debugging and inspection to ensure that all performance indicators (such as the power system, guidance system, and mud circulation system) are operating normally. Based on the adjusted optimization plan, the initial parameters of the drilling rig are set, such as drilling speed, drilling pressure, and guidance angle. Positioning equipment is used to accurately determine the starting position of the borehole in the construction area, and the guidance system is set up according to the path specified in the optimization plan. The guidance system can be a surface guidance instrument or an underground guidance probe, used to monitor and control the drilling direction of the drill bit in real time. The directional drilling rig is then started, and drilling begins according to the set parameters and path. During drilling, the position and direction of the drill bit are monitored in real time through the guidance system. Drilling parameters are adjusted promptly based on geological conditions and guidance information. Simultaneously, the mud circulation system is activated, injecting mud into the borehole to cool the drill bit, carry drill cuttings, and stabilize the borehole wall. Drilling continues until the specified depth and position are reached, forming a pilot hole.

[0086] More specifically, based on the adjusted optimization plan and the outlet position of the guide hole, the size, shape, and depth of the receiving pit are determined. Considering factors such as the pipe diameter, length, laying method, and operating space of the construction equipment, a reasonable excavation plan is formulated. Excavation equipment (such as an excavator) is used to excavate the receiving pit according to the plan. During excavation, the slope and verticality of the pit walls are controlled to ensure that the size and shape of the receiving pit meet the design requirements. Simultaneously, the bottom of the pit is leveled and compacted. After excavation, according to the optimized plan, the directional drilling rig and guide rail laying device are moved to a suitable position near the receiving pit. The directional drilling rig is reinstalled and adjusted to ensure it accurately aligns with the outlet of the guide hole. The guide rail laying device is installed and adjusted and fixed as necessary to ensure it is consistent with the path and direction of the pipeline laying.

[0087] More specifically, before starting the reaming process, check the reaming bit and mud circulation system of the directional drilling rig to ensure they are functioning properly. Determine the number of reaming passes and the diameter increment for each pass based on the optimized plan. Prepare sufficient mud material to ensure its performance meets the reaming requirements. Start the directional drilling rig and begin borehole expansion excavation from the exit end of the pilot hole. Gradually increase the reaming diameter according to the pre-set reaming parameters. During the reaming process, maintain mud circulation and promptly remove drill cuttings to ensure borehole stability. Simultaneously, monitor the direction and position of the reaming through the guiding system to avoid deviations. The guide rail laying device synchronously drags and lays the pipe along with the reaming progress. After reaming a certain distance, slowly drag the prefabricated pipe into the reamed hole using the guide rail laying device. During pipe dragging, carefully control the dragging speed and tension to ensure the connection quality and accurate placement of the pipe. Continue reaming and pipe laying operations until the entire pipe is laid.

[0088] More specifically, the pilot hole provides precise path guidance for subsequent borehole enlargement and pipeline laying, ensuring that the pipeline accurately crosses the construction area according to design requirements. By strictly controlling the drilling path, damage to the surrounding environment and underground facilities can be avoided. Real-time monitoring and adjustment of the drill bit's direction and position during drilling ensures the accuracy of the pilot hole, creating favorable conditions for subsequent borehole enlargement and pipeline laying. High-precision pilot holes can reduce deviations and errors during construction, improving construction quality.

[0089] More specifically, the receiving pit provides the necessary operating space for the directional drilling rig and guide rail laying device, facilitating the installation, commissioning, and construction operations of the equipment. At the same time, the receiving pit can also serve as the pipeline access point and a working platform for construction personnel, ensuring the smooth progress of the construction process. When transitioning from the drilling stage to the reaming and pipeline laying stage, it is necessary to readjust the position and direction of the equipment. Excavating the receiving pit at the exit end of the guide hole and redeploying the equipment can ensure a smooth connection of the construction process and improve construction efficiency.

[0090] More specifically, the diameter of the guide hole is usually small and cannot meet the requirements of pipeline laying. By enlarging the hole, the diameter of the guide hole can be gradually increased to a suitable size, creating enough space for pipeline laying. The guide rail laying device follows the enlarging progress to drag and lay the pipeline, realizing the synchronous operation of enlarging the hole and laying the pipeline. This construction method can avoid problems such as hole wall collapse that may occur when laying the pipeline after enlarging the hole is completed. At the same time, it reduces construction time and cost and improves construction efficiency.

[0091] Furthermore, the steps of collecting monitoring data during construction and analyzing it in conjunction with the aforementioned regional model to obtain construction assessment information include: By deploying sensor arrays on directional drilling rigs and guide rail laying devices, monitoring data on construction performance during the construction process are collected. Based on the monitoring data, the construction operation and construction effect of the area model are reproduced in real time to obtain the construction real-time characteristics; Based on the regional model, the subsequent execution effect of the optimization scheme is predicted based on the actual construction characteristics, so as to obtain construction prediction information for future time periods. The value of subsequent execution steps of the optimized scheme is evaluated based on the construction prediction information to generate construction evaluation information.

[0092] Specifically, various sensors are installed at key locations on the directional drilling rig and guide rail laying device. For example, pressure sensors are installed on the drill rod of the directional drilling rig to monitor drilling pressure; tension sensors are installed on the traction mechanism of the guide rail laying device to measure the tension when the pipeline is being dragged; and speed sensors are installed in the equipment's power system to obtain the equipment's operating speed. During construction, the sensors collect relevant data in real time. This data is transmitted to a data acquisition terminal via wired or wireless transmission. The data acquisition terminal performs preliminary processing on the data, such as filtering and amplification, and then stores the processed data in a database for subsequent analysis. The collected data undergoes quality checks to remove abnormal and erroneous data. The validity of the data can be determined by setting data thresholds and performing data correlation analysis.

[0093] More specifically, the collected monitoring data is mapped to corresponding elements in the regional model. For example, the drilling location data of the directional drilling rig is mapped to the geographical coordinates in the regional model, and the pipeline laying length data is mapped to the pipeline path in the regional model. Based on the mapped data, the relevant parameters and status in the regional model are updated. For example, if the drilling pressure is increased, it means that the drill bit has encountered a harder stratum. The geological parameters at the corresponding location in the regional model are adjusted. Using the updated regional model, the construction operation and construction effect are simulated and reproduced in real time. Various states in the construction process, such as drilling trajectory, pipeline laying position, and equipment operation status, are displayed through a visual interface, thereby obtaining the characteristics of the actual construction situation.

[0094] More specifically, the subsequent execution steps of the optimization plan are analyzed in depth, clarifying the objectives, operation methods, and expected effects of each step. Combined with the characteristics of the actual construction situation, the matching status between the current construction status and the optimization plan is determined. Using a regional model, based on the current construction situation characteristics and the subsequent steps of the optimization plan, the construction situation in the future time period is simulated and predicted. Various possible influencing factors are considered, such as changes in geological conditions and fluctuations in equipment performance. Multi-scenario simulations are conducted, and key information such as construction progress, construction quality (such as pipeline laying accuracy and connection quality), construction cost, and potential risks are extracted from the simulation results to form construction prediction information for the future time period.

[0095] More specifically, an indicator system is established to evaluate the value of subsequent implementation steps of the optimization plan. This system includes construction progress indicators (such as whether the plan can be completed on time), construction quality indicators (such as whether the design requirements are met), construction cost indicators (such as whether the budget is exceeded), and risk indicators (such as the possibility of accidents). Based on construction forecast information, the performance of subsequent implementation steps of the optimization plan on each evaluation indicator is assessed. A combination of quantitative and qualitative analysis methods can be used to assign corresponding weights to each indicator, calculate a comprehensive evaluation score, and generate construction evaluation information based on the evaluation results. The construction evaluation information includes an evaluation of the optimization plan (such as whether it is reasonable and whether adjustments are needed), existing problems and risks, and adjustment suggestions.

[0096] More specifically, by collecting monitoring data through sensor arrays, the operating status and construction performance of directional drilling rigs and guide rail laying devices can be obtained in real time. Construction personnel can promptly understand the changes in various parameters during the construction process, such as drilling pressure, tension, and speed, so as to detect abnormalities in a timely manner and take corresponding measures. Accurate and comprehensive monitoring data is the basis for reproducing the actual construction situation, predicting the effect, and assessing the value. Only based on real and reliable data can accurate analysis results and reasonable decision-making suggestions be obtained.

[0097] More specifically, combining monitoring data with regional models for real-time simulation can intuitively display construction operations and effects. Construction personnel can understand the actual construction situation in real time through a visual interface, making it easier to identify problems and deviations in the construction process in a timely manner, providing a basis for subsequent adjustments and decisions. Comparing the actual construction characteristics with the simulation results of the regional model can verify the accuracy and reliability of the regional model. If a significant difference is found between the two, it indicates that the regional model may need further adjustment and optimization to better reflect the actual construction situation.

[0098] More specifically, by predicting future construction conditions, construction personnel can understand potential problems and risks in advance and develop targeted countermeasures. For example, if significant resistance is predicted during the subsequent hole enlargement process, more suitable equipment can be prepared in advance or construction parameters can be adjusted to avoid delays or quality issues during construction. Construction forecast information can provide a reference for adjusting the optimization plan. Based on the forecast results, subsequent steps of the optimization plan can be adjusted and optimized to make the construction plan more reasonable and efficient, thereby improving the overall construction benefits.

[0099] More specifically, construction assessment information integrates construction forecast information and value assessment of optimized solutions, providing a comprehensive and objective basis for construction decisions. Construction personnel can use the assessment information to determine whether adjustments to the optimized solution are necessary and how to make those adjustments, thereby ensuring the smooth progress of the construction process and the achievement of construction goals. Through continuous evaluation and adjustment of the optimized solution, continuous improvement of the construction process can be achieved. After each construction phase, lessons learned from the construction assessment information can be summarized to provide a reference for subsequent similar projects, improving construction management and quality.

[0100] Based on the technical content of the intelligent construction method for multi-sensor feedback combined drilling and pulling pipeline laying described in the above-disclosed embodiments, the present invention provides an intelligent construction method system for multi-sensor feedback combined drilling and pulling pipeline laying, the structure of which is as follows: Figure 2 The intelligent construction method for drilling-jacking combined with pipeline laying, which implements multi-sensor feedback as described in any one of the first aspects, includes: The area simulation module is used to collect environmental data of the construction area for digital simulation to obtain an area model of the construction area. The scheme optimization module is used to simulate the effects of the construction scheme based on the regional model in order to generate an optimized scheme; The fixed-point sampling module is used to perform fixed-point sampling of the construction area according to the optimization scheme to obtain sampling data; The parameter adjustment module is used to adjust the parameters of the region model using the sampled data, and simultaneously adjust the optimization scheme. The construction execution module is used to perform drilling, hole enlargement, and pipe laying in the construction area according to the adjusted optimization plan. The construction monitoring module is used to collect monitoring data during the construction process and analyze it in conjunction with the regional model to obtain construction assessment information.

[0101] In this embodiment, the specific implementation of each module in the above system embodiment is described in the above method embodiment, and will not be repeated here.

[0102] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0103] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein can be implemented directly by hardware, a software module executed by a processor, or a combination of both. The software module can be located in random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art.

[0104] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A multi-sensor feedback-based intelligent construction method for pipeline laying combining drilling and pulling, characterized in that: include: Environmental data of the construction area is collected for digital simulation to obtain a regional model of the construction area. The construction plan is simulated based on the aforementioned regional model to generate an optimized plan; Based on the optimization scheme, fixed-point sampling was performed on the construction area to obtain sampling data; The parameters of the region model are adjusted using the sampled data, and the optimization scheme is adjusted simultaneously. According to the adjusted optimization plan, drilling, hole enlargement, and pipe laying were carried out in the construction area. During construction, monitoring data is collected and analyzed using the regional model to obtain construction assessment information.

2. The intelligent construction method for drilling-jacking combined with pipeline laying using multi-sensor feedback as described in claim 1, characterized in that, The steps for collecting environmental data of the construction area to perform digital simulation and obtain a regional model of the construction area include: The defined range of pipeline laying is determined, and the boundary of the pre-constructed digital twin is restricted based on the defined range to obtain a digital twin corresponding to the defined range; Based on the digital twin, several detection nodes are selected in the construction area to collect environmental data from each detection node. Based on the environmental data, the parameters of the digital twin are set, and information expansion analysis is performed on the specific locations of the construction area to obtain a regional model.

3. The intelligent construction method for drilling-pull combined pipeline laying with multi-sensor feedback as described in claim 1, characterized in that, The steps for simulating the effects of the construction plan based on the aforementioned regional model to generate an optimized plan include: The construction plan is analyzed for each construction stage to obtain construction target information for multiple construction stages. Based on the construction target information, the construction effect of the regional model is simulated and evaluated, and the construction target information is analyzed for adjustment based on the evaluation results to generate several adjusted construction targets. The regional model is used to simulate and evaluate the various adjusted construction objectives to determine the optimal adjusted construction objective as the optimization scheme.

4. The intelligent construction method for drilling-pull combined pipeline laying with multi-sensor feedback as described in claim 3, characterized in that, The steps for analyzing the adjustment of the construction target information based on the evaluation results include: The construction target information is broken down into multiple stages to obtain the stage construction targets for multiple construction stages; The phase construction objectives of each construction phase are used as the starting point for adjustment, and the adjustment simulation of the current phase and subsequent phases is carried out for each of the aforementioned adjustment starting points. The multi-stage content obtained from the adjustment simulation is combined to obtain a set of adjustment construction objectives.

5. The intelligent construction method for drilling-pull combined pipeline laying with multi-sensor feedback as described in claim 1, characterized in that, The steps for obtaining sampling data by performing fixed-point sampling in the construction area according to the optimization scheme include: The optimization scheme is executed using a digital simulation based on the regional model to generate several stages of performance information of the regional model in carrying out construction operations according to the optimization scheme. Based on the stage performance information, each location in the region model associated with the construction operation is marked to obtain several potential sampling points; A construction impact analysis of the geological environment conditions of each potential sampling point is conducted to determine several sampling points on the regional model. Geological environment data were collected at each sampling point in the construction area to obtain sampling data.

6. The intelligent construction method for drilling-jacking combined with pipeline laying using multi-sensor feedback as described in claim 1, characterized in that, The steps of adjusting the parameters of the region model using the sampled data and simultaneously adjusting the optimization scheme include: The sampled data is used to substitute data into the corresponding locations in the region model, and the substituted data is used as the basis for data extension calculation of the adjacent locations. Based on the results of the data extension calculation, the original parameters of the regional model are verified to adjust the parameters of the regional model. The regional condition adjustment range of the adjusted regional model is analyzed to determine the correction requirements of the optimization scheme. When the correction requirement reaches a preset threshold, the optimization scheme is simulated, evaluated and compared with the effects of various improvement methods based on the regional model after parameter adjustment, so as to adjust the parameters of the construction operation of the optimization scheme.

7. The intelligent construction method for drilling-pull combined pipeline laying with multi-sensor feedback as described in claim 1, characterized in that, The steps for drilling, hole enlargement, and pipe laying in the construction area according to the adjusted optimization plan include: The directional drilling rig is driven to drill along a specified path in the construction area according to the adjusted optimization scheme to obtain a guide hole; A receiving pit is excavated at the outlet end of the guide hole to redeploy the directional drilling rig and guide rail laying device according to the optimization scheme; According to the optimization scheme, the directional drilling rig starts from the outlet end to expand the guide hole, and the guide rail laying device follows the progress of the hole expansion and digging to lay the pipeline.

8. The intelligent construction method for drilling-pull combined pipeline laying with multi-sensor feedback as described in claim 7, characterized in that, The steps for collecting monitoring data during construction and analyzing it in conjunction with the regional model to obtain construction assessment information include: By deploying sensor arrays on directional drilling rigs and guide rail laying devices, monitoring data on construction performance during the construction process are collected. Based on the monitoring data, the construction operation and construction effect of the area model are reproduced in real time to obtain the construction real-time characteristics; Based on the regional model, the subsequent execution effect of the optimization scheme is predicted based on the actual construction characteristics, so as to obtain construction prediction information for future time periods. The value of subsequent execution steps of the optimized scheme is evaluated based on the construction prediction information to generate construction evaluation information.

9. A multi-sensor feedback intelligent construction method system for drilling and pulling combined pipeline laying, characterized in that: include: The area simulation module is used to collect environmental data of the construction area for digital simulation to obtain an area model of the construction area. The scheme optimization module is used to simulate the effects of the construction scheme based on the regional model in order to generate an optimized scheme; The fixed-point sampling module is used to perform fixed-point sampling of the construction area according to the optimization scheme to obtain sampling data; The parameter adjustment module is used to adjust the parameters of the region model using the sampled data, and simultaneously adjust the optimization scheme. The construction execution module is used to perform drilling, hole enlargement, and pipe laying in the construction area according to the adjusted optimization plan. The construction monitoring module is used to collect monitoring data during the construction process and analyze it in conjunction with the regional model to obtain construction assessment information.

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