Multi-drilling-machine-group collaborative operation scheduling system for offshore investigation

Abstract

The invention relates to the technical field of cluster control, in particular to an offshore investigation multi-drilling-machine-group collaborative operation scheduling system which comprises an environment monitoring module, an adaptability analysis module, a scheduling decision module and a dynamic regulation and control module. By acquiring water depth, flow velocity, sediment, tide and other multi-source marine environment data in real time, the adaptive analysis module calculates equipment adaptation tendency parameters, and intelligently discriminates drilling equipment types applicable to each sea area; the scheduling decision module dynamically selects and adjusts in-place equipment parameters or starts cross-platform collaborative operation according to an analysis result; and the dynamic regulation and control module finally executes an equipment switching or parameter optimization instruction. The problems that multi-drilling-machine cooperation efficiency is low and response is slow in a complex marine environment are solved, the overall adaptability and stability of exploration operation are remarkably improved, and operation risks and construction period delay caused by sudden sea condition change are reduced.

Description

Technical Field

[0001] This invention relates to the field of cluster control technology, and in particular to a collaborative operation scheduling system for multiple drilling rigs in offshore exploration. Background Technology

[0002] Current offshore exploration multi-rig operation technology systems utilize a variety of equipment, including lightweight portable drilling rigs, amphibious drilling platforms, and large shipborne drilling rigs, tailored to different operating environments such as tidal flats, intertidal zones, shallow water, and deep water areas. Through coordinated scheduling, large-area simultaneous exploration is achieved. This technology heavily relies on in-situ testing and specialized sampling equipment to ensure the quality of samples from complex strata such as soft soil and sand. Advanced instruments, such as laser particle size analyzers, are introduced to enable rapid acquisition and analysis of geotechnical parameters. Coupled with an information system for data integration and operational coordination, this significantly improves the efficiency and data accuracy of offshore exploration.

[0003] However, this technology still faces several challenges: First, the scheduling and coordination of multiple drilling rigs and platforms is extremely complex, requiring high levels of project management and communication, making optimal coordination difficult to achieve in practice; second, the high cost of leasing and operating large ships, amphibious platforms, and other equipment results in poor overall project economics; third, operational efficiency is severely constrained by sea conditions such as wind, waves, and currents, with short effective working windows in adverse weather conditions and a high risk of project delays; furthermore, differences exist in geotechnical parameters from different equipment and in-situ testing methods, data fusion and consistency assessment lack unified standards, and the positioning accuracy of equipment in complex marine environments, sampling depth, and sampling techniques in extreme formations still need further improvement. Summary of the Invention

[0004] To address this issue, the present invention provides a collaborative operation scheduling system for multiple drilling rigs in offshore exploration, which overcomes the problem in the prior art where insufficient equipment positioning accuracy in complex marine environments leads to inadequate matching between cluster scheduling based on sampling results and the actual environment.

[0005] To achieve the above objectives, the present invention provides a multi-drilling rig collaborative operation scheduling system for offshore exploration, comprising: The multi-drilling rig group for offshore exploration includes horizontal leveling and vertical positioning equipment for fixed drilling platforms in different sea areas such as shallow waters, intertidal zones, and deep seas, as well as mobile operating equipment for controlling the position and attitude of each platform. The operating parameters of the mobile operating equipment include: positioning accuracy, wave resistance level, and operating time window. A multi-drilling rig collaborative operation scheduling system for offshore exploration includes: The environmental monitoring module is used to continuously acquire current marine environmental parameters, including water depth, current velocity, seabed type, and tidal data. An adaptive analysis module, which is connected to the environmental monitoring module, is used to analyze the environmental parameters to obtain marine characteristics, and determine the equipment adaptation tendency parameters based on the marine characteristics to determine the recommended drilling equipment category for the marine area. A scheduling decision module, connected to both the environmental monitoring module and the adaptive analysis module, is used to determine whether the operational strategy needs to be adjusted based on the recommended drilling equipment type for the sea area, including: Adjust the working parameters of the mobile operating equipment to adapt to tidal and wave changes, obtain real-time stability indicators, and calculate the operational feasibility tendency parameters to determine whether it is necessary to switch drilling equipment. Alternatively, select sea areas whose environmental characteristics do not meet the current equipment operating conditions, match the type of backup drilling platform, and determine the scheduling intervention parameters based on the platform performance parameters to determine whether cross-platform collaborative operation needs to be initiated; The dynamic control module, which is connected to the scheduling decision module, is used to issue scheduling instructions and perform equipment switching or parameter optimization when it is determined that the operation strategy needs to be adjusted.

[0006] Furthermore, the environmental monitoring module includes: The hydrological monitoring unit consists of tidal sensors deployed on the legs of the drilling platform and depth sensors installed at the bottom of the platform, used to measure the water depth and tidal data at the work site in real time. The hydrodynamic monitoring unit consists of an acoustic Doppler current profiler installed on the bottom or bottom support of the drilling platform, used to measure the flow velocity at different water depths below the platform in real time. The bottom sediment characteristic identification unit consists of a shallow seismic profiler or side-scan sonar installed at the bottom of the drilling platform, used to detect and identify the type of bottom sediment before and after the platform is in place.

[0007] Furthermore, the adaptability analysis module determines the actual operating efficiency of drilling equipment corresponding to different sea area locations, as well as the standard operating efficiency of drilling equipment at different sea area locations under the current environmental conditions, based on the marine environmental parameters. The adaptability analysis module determines the equipment performance characterization factor based on the ratio of the actual operating efficiency of the drilling equipment to the standard operating efficiency at the same location under the same environmental conditions, and determines the equipment adaptation tendency parameter based on the ratio of the average deviation of the equipment performance characterization factor to its mean.

[0008] Furthermore, the adaptability analysis module determines the recommended drilling equipment category for the sea area based on the equipment adaptation tendency parameter, including: If the equipment adaptation tendency parameter is greater than or equal to the standard equipment adaptation tendency parameter, then the recommended drilling equipment category for the sea area is the current equipment's operational category. If the equipment adaptation tendency parameter is less than the standard equipment adaptation tendency parameter, then the recommended drilling equipment category for the sea area is one that needs to be switched.

[0009] Furthermore, the scheduling decision module determines whether the operational strategy needs to be adjusted based on the recommended drilling equipment category for the sea area, including: If the recommended drilling equipment category for the sea area is the category that the current equipment can operate in, then it is determined whether the operation strategy needs to be adjusted by adjusting the working parameters of the mobile operation equipment, adapting to tidal and wave changes, obtaining real-time stability indicators, and recalculating the operation feasibility tendency parameters to determine whether the drilling equipment needs to be switched. If the recommended drilling equipment category for the sea area is one that needs to be switched, then determine whether the operation strategy needs to be adjusted by screening out sea areas whose environmental characteristics do not meet the current equipment operation conditions, matching the backup drilling platform type, and determining the scheduling intervention parameters based on the platform performance parameters to determine whether cross-platform collaborative operation needs to be initiated.

[0010] Furthermore, the scheduling decision module determines whether to switch drilling equipment based on the operation feasibility tendency parameter, including: If the operational feasibility tendency parameter is greater than the preset operational feasibility tendency parameter, it is determined that there is no need to switch drilling equipment. If the operational feasibility tendency parameter is less than or equal to the preset operational feasibility tendency parameter, it is determined that the drilling equipment needs to be switched.

[0011] Furthermore, the scheduling decision module obtains the real-time stability indicators, including: The scheduling decision module selects drilling platforms with a wave resistance level greater than the current wave level; Select the drilling platform with the best real-time stability index for parameter matching to obtain its operating parameters.

[0012] Furthermore, the scheduling intervention parameters are determined according to the following formula: Ks=Σ(Pc-Pe) / N In the formula, Ks is the scheduling intervention parameter, Pc is the actual measured value of the platform performance parameter, Pe is the expected required value of the platform performance parameter, and N is the total number of performance parameters participating in the evaluation.

[0013] Furthermore, the scheduling decision module determines whether to initiate cross-platform collaborative work based on the scheduling intervention parameters, including: If the scheduling intervention parameter is greater than or equal to the standard scheduling intervention parameter, it is determined that cross-platform collaborative operation needs to be initiated. If the scheduling intervention parameter is less than the standard scheduling intervention parameter, it is determined that there is no need to start cross-platform collaborative operation.

[0014] Compared with existing technologies, the advantages of this invention are as follows: the system collects multi-dimensional marine environmental parameters such as water depth, current velocity, seabed sediment, and tides in real time through an environmental monitoring module; the adaptability analysis module calculates equipment performance characterization factors and equipment compatibility parameters based on these parameters, intelligently determining the type of drilling equipment to be used in the current sea area; the scheduling decision module dynamically decides whether to adjust existing platform operating parameters or initiate cross-platform collaborative operations based on the adaptation results; and finally, the dynamic control module executes equipment switching or parameter optimization. This solution achieves multi-level closed-loop matching of environment, equipment, and task, significantly improving operational adaptability, positioning accuracy, and platform stability under harsh sea conditions, and reducing project delays and equipment risks caused by sudden environmental changes; at the same time, it optimizes resource allocation through a cross-platform collaborative mechanism, reducing redundant investment in high-cost large equipment, and improving the overall economy and operational efficiency of marine exploration.

[0015] Furthermore, in this invention, the entire environmental monitoring module, through the aforementioned multi-unit collaborative sensing and threshold discrimination mechanism, achieves multi-level, multi-parameter acquisition and preliminary interpretation of hydrological, fluid, and geological environments. Its core principle lies in transforming continuous environmental parameters into recognizable state categories for the operational system through the combination of physical sensors and characteristic threshold criteria, thereby providing structured input for subsequent adaptive analysis and scheduling decisions. This implementation method enhances the system's perception accuracy and decision-making reliability in complex marine environments without relying on specific numerical effects.

[0016] Furthermore, in this invention, a two-stage screening mechanism is used to first eliminate platforms with insufficient wave resistance, and then select those with the best real-time operational status. This achieves efficient optimization and precise matching of drilling equipment, avoiding operational risks caused by insufficient wave resistance and maximizing the stability of drilling operations and the quality of data acquisition. Its core principle lies in combining environmental conditions, platform structural performance, and real-time dynamic response to form a hierarchical decision-making logic, thereby enhancing the system's scheduling rationality and operational adaptability under complex sea conditions.

[0017] Furthermore, through macro-level performance deviation assessment, a collaborative mechanism can be introduced when necessary to optimize resource allocation and operational efficiency while ensuring operational safety and reliability. This data-driven threshold discrimination mechanism enables the system to more intelligently adapt to complex and ever-changing marine operating environments, enhancing the robustness and adaptability of the overall operating system. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of the structure of the multi-drilling rig collaborative operation scheduling system for offshore exploration according to an embodiment of the present invention; Figure 2 This is a logic diagram illustrating how the recommended drilling equipment category for a sea area is determined according to an embodiment of the present invention. Figure 3This is a logic diagram for determining whether to switch drilling equipment according to an embodiment of the present invention. Detailed Implementation

[0019] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0020] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0021] It should be noted that in the description of this invention, the terms "upper", "lower", "left", "right", "inner", "outer", etc., which indicate directions or positional relationships, are based on the directions or positional relationships shown in the accompanying drawings. This is only for the convenience of description and is not intended to indicate or imply that the device or element must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation of this invention.

[0022] Furthermore, it should be noted that, in the description of this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0023] Please see Figure 1 As shown, this is a structural schematic diagram of a multi-drilling rig collaborative operation scheduling system for offshore exploration according to an embodiment of the present invention. The present invention provides a multi-drilling rig collaborative operation scheduling system for offshore exploration, comprising: The multi-drilling rig group for offshore exploration includes horizontal leveling and vertical positioning equipment for fixed drilling platforms in different sea areas such as shallow waters, intertidal zones, and deep seas, as well as mobile operating equipment for controlling the position and attitude of each platform. The operating parameters of the mobile operating equipment include: positioning accuracy, wave resistance level, and operating time window. A multi-drilling rig collaborative operation scheduling system for offshore exploration includes: The environmental monitoring module is used to continuously acquire current marine environmental parameters, including water depth, current velocity, seabed type, and tidal data. An adaptive analysis module, which is connected to the environmental monitoring module, is used to analyze the environmental parameters to obtain marine characteristics, and determine the equipment adaptation tendency parameters based on the marine characteristics to determine the recommended drilling equipment category for the marine area. A scheduling decision module, connected to both the environmental monitoring module and the adaptive analysis module, is used to determine whether the operational strategy needs to be adjusted based on the recommended drilling equipment type for the sea area, including: Adjust the working parameters of the mobile operating equipment to adapt to tidal and wave changes, obtain real-time stability indicators, and calculate the operational feasibility tendency parameters to determine whether it is necessary to switch drilling equipment. Alternatively, select sea areas whose environmental characteristics do not meet the current equipment operating conditions, match the type of backup drilling platform, and determine the scheduling intervention parameters based on the platform performance parameters to determine whether cross-platform collaborative operation needs to be initiated; The dynamic control module, which is connected to the scheduling decision module, is used to issue scheduling instructions and perform equipment switching or parameter optimization when it is determined that the operation strategy needs to be adjusted.

[0024] In this invention, the system collects multi-dimensional marine environmental parameters such as water depth, current velocity, seabed sediment, and tides in real time through an environmental monitoring module. Based on these parameters, an adaptability analysis module calculates equipment performance characterization factors and equipment compatibility parameters, intelligently determining the type of drilling equipment appropriate for the current sea area. A scheduling decision module dynamically decides whether to adjust existing platform operating parameters or initiate cross-platform collaborative operations based on the compatibility results. Finally, a dynamic control module executes equipment switching or parameter optimization. This solution achieves multi-level closed-loop matching of environment, equipment, and task, significantly improving operational adaptability, positioning accuracy, and platform stability under harsh sea conditions, and reducing project delays and equipment risks caused by sudden environmental changes. Simultaneously, the cross-platform collaborative mechanism optimizes resource allocation, reduces redundant investment in high-cost large equipment, and overall improves the economy and operational efficiency of marine exploration.

[0025] Specifically, the environmental monitoring module includes: The hydrological monitoring unit consists of tidal sensors deployed on the legs of the drilling platform and depth sensors installed at the bottom of the platform, used to measure the water depth and tidal data at the work site in real time. The hydrodynamic monitoring unit consists of an acoustic Doppler current profiler installed on the bottom or bottom support of the drilling platform, used to measure the flow velocity at different water depths below the platform in real time. The bottom sediment characteristic identification unit consists of a shallow seismic profiler or side-scan sonar installed at the bottom of the drilling platform, used to detect and identify the type of bottom sediment before and after the platform is in place.

[0026] The hydrological monitoring unit collects tidal level cycle changes and real-time water depth data through tidal sensors deployed on the drilling platform's legs and depth sensors on the platform's bottom. The determination of water depth safety thresholds and tidal range alarm thresholds within this unit is typically based on a limited number of tests calibrated using historical operational safety data and the platform's draft characteristics. For example, by statistically analyzing the platform's stability performance under different water depths and tidal ranges, and combining platform structural parameters with typical marine conditions, empirical weighting or linear regression methods are used to comprehensively determine the threshold range. The aim is to identify the risks of shallow water operations and the critical points where the platform transitions between bottoming and floating states due to tides.

[0027] The hydrodynamic monitoring unit employs an acoustic Doppler current profiler (ADCP) mounted on the platform's hull or bottom support to measure water velocity and direction in stratification, assessing the impact of water flow on platform stability and drilling operations. The velocity grading thresholds set for this unit, such as the critical values ​​distinguishing between low-velocity operating areas and high-velocity risk areas, are typically calibrated based on the platform's current-resistant design parameters and the statistical characteristics of the marine current field, through a combination of flume tests and actual sea area tests. For example, thresholds can be determined using statistical distribution analysis or critical state discrimination methods based on platform offset monitoring data at different flow velocities and the maximum permissible flow velocity for maintaining positioning accuracy.

[0028] The seabed characteristic identification unit uses a shallow seismic profiler or side-scan sonar to detect and identify the seabed type and stratigraphic structure before and after platform placement. The classification thresholds for seabed types in this unit (such as parameters distinguishing between mud, sand, and gravel) are largely based on matching analysis between acoustic signal feature databases and historical geological data. Typically, thresholds are determined by collecting acoustic reflection characteristics of typical seabed samples and combining them with machine learning classification algorithms or discriminant analysis methods. For example, clustering results using parameters such as acoustic wave reflection intensity and spectral characteristics can be used to determine classification boundaries. This setup effectively identifies seabed types that are unfavorable for platform habitation or pose a risk of puncture, thereby mitigating operational risks arising from geological conditions.

[0029] The above-mentioned equipment selection can be replaced by other equipment that can meet the testing requirements. This is existing technology and no specific limitation is made.

[0030] In this invention, the entire environmental monitoring module, through the aforementioned multi-unit collaborative sensing and threshold discrimination mechanism, achieves multi-level, multi-parameter acquisition and preliminary interpretation of hydrological, fluid, and geological environments. Its core principle lies in combining physical sensors with characteristic threshold criteria to transform continuous environmental parameters into identifiable state categories for the operational system, thereby providing structured input for subsequent adaptive analysis and scheduling decisions. This implementation method enhances the system's perception accuracy and decision-making reliability in complex marine environments without relying on specific numerical results.

[0031] Please see Figure 2As shown, it is a logic diagram for determining the recommended drilling equipment category for a sea area according to an embodiment of the present invention. The adaptive analysis module determines the actual operating efficiency of drilling equipment corresponding to different sea area locations and the standard operating efficiency of drilling equipment for different sea area locations under the current environmental conditions based on the sea area environmental parameters. The adaptability analysis module determines the equipment performance characterization factor based on the ratio of the actual operating efficiency of the drilling equipment to the standard operating efficiency at the same location under the same environmental conditions, and determines the equipment adaptation tendency parameter based on the ratio of the average deviation of the equipment performance characterization factor to its mean.

[0032] In practice, equipment performance characterization factors are quantified by the ratio of actual operating efficiency to standard operating efficiency. The threshold of this factor is usually calibrated based on statistical analysis of multiple sea trials and historical operating data. Specifically, multiple sets of actual efficiency and standard efficiency data can be collected in different typical sea areas, such as shoals, intertidal zones, and deep water areas, and statistical distribution methods or regression analysis can be used to determine the critical level of performance deviation. The purpose is to identify whether the equipment is in the expected operating state.

[0033] Specifically, the equipment adaptability parameter is obtained by calculating the ratio of the average deviation of the performance characterization factors obtained by the same type of equipment at multiple operating locations to its mean. The threshold for this parameter is generally determined by combining a limited number of real-ship tests and simulations, based on the consistency requirements of equipment performance in cluster collaborative operations.

[0034] For example, based on efficiency fluctuation data of multiple devices operating collaboratively in different marine environments, variance analysis or clustering methods can be used to define the classification boundaries of the suitability status. The principle of this method is to determine whether the current environment is suitable for the continued operation of this type of equipment, or whether equipment scheduling decisions need to be triggered, by quantifying the dispersion of the performance of the equipment group.

[0035] Understandably, quantitatively evaluating the performance of drilling equipment in different marine environments provides objective and calculable adaptability indicators for scheduling decisions. Based on water depth, current velocity, seabed type, and tidal data collected by the environmental monitoring module, combined with equipment operating status data, the actual operational efficiency of drilling equipment at different marine locations under current environmental conditions is calculated. Simultaneously, based on historical operational databases or performance curves calibrated under standard environmental conditions during the equipment's design phase, the standard operating efficiency corresponding to the same location under current environmental conditions is determined.

[0036] Specifically, the adaptability analysis module determines the recommended drilling equipment category for the sea area based on the equipment adaptation tendency parameter, including: If the equipment adaptation tendency parameter is greater than or equal to the standard equipment adaptation tendency parameter, then the recommended drilling equipment category for the sea area is the current equipment's operational category. If the equipment adaptation tendency parameter is less than the standard equipment adaptation tendency parameter, then the recommended drilling equipment category for the sea area is one that needs to be switched.

[0037] Specifically, the scheduling decision module determines whether the operation strategy needs to be adjusted based on the recommended drilling equipment type for the sea area, including: If the recommended drilling equipment category for the sea area is the category that the current equipment can operate in, then it is determined whether the operation strategy needs to be adjusted by adjusting the working parameters of the mobile operation equipment, adapting to tidal and wave changes, obtaining real-time stability indicators, and recalculating the operation feasibility tendency parameters to determine whether the drilling equipment needs to be switched. If the recommended drilling equipment category for the sea area is one that needs to be switched, then determine whether the operation strategy needs to be adjusted by screening out sea areas whose environmental characteristics do not meet the current equipment operation conditions, matching the backup drilling platform type, and determining the scheduling intervention parameters based on the platform performance parameters to determine whether cross-platform collaborative operation needs to be initiated.

[0038] Understandably, if the equipment adaptation tendency parameter is greater than or equal to the standard equipment adaptation tendency parameter, it indicates that the equipment group still maintains good coordination and efficiency in the current environment; conversely, if the equipment adaptation tendency parameter is less than the standard equipment adaptation tendency parameter, it indicates that environmental conditions have led to inconsistent or significantly degraded equipment performance. By identifying system-level adaptation risks through the dispersion of group performance, the reliability of decision-making and adaptability to marine operations can be improved.

[0039] The scheduling decision module triggers different operational strategy adjustment processes based on the recommended equipment categories. If the recommended category indicates that the current equipment is operational, the decision module prioritizes adjusting the working parameters of the mobile equipment, such as positioning accuracy, wave resistance level, and operational time window, to adapt to real-time tidal and wave dynamics. At the same time, it re-collects stability indicators and recalculates operational feasibility parameters to determine whether the current equipment can maintain operation through parameter optimization.

[0040] If the recommended category requires equipment switching, the decision-making module initiates a cross-equipment scheduling strategy: first, it filters out sea areas where environmental characteristics exceed the operational capabilities of the current equipment; then, it matches suitable equipment from the backup drilling platform types and calculates scheduling intervention parameters based on their performance parameters; finally, it determines whether multi-platform collaborative operations need to be initiated. This improves resource utilization efficiency and system flexibility while ensuring operational safety. The overall implementation significantly enhances the system's decision-making capabilities and operational robustness in complex marine environments through a multi-layered judgment and response mechanism.

[0041] Please see Figure 3 The diagram shown is a logic diagram for determining whether to switch drilling equipment according to an embodiment of the present invention. The scheduling decision module determines whether to switch drilling equipment based on the operation feasibility tendency parameter, including: If the operational feasibility tendency parameter is greater than the preset operational feasibility tendency parameter, it is determined that there is no need to switch drilling equipment. If the operational feasibility tendency parameter is less than or equal to the preset operational feasibility tendency parameter, it is determined that the drilling equipment needs to be switched.

[0042] The operational feasibility tendency parameter is a comprehensive evaluation index obtained by weighted fusion or numerical calculation based on a physical model, taking into account multiple dimensions such as real-time stability indicators, positioning accuracy deviation, and operational time window adaptability. It is used to characterize the feasibility of continued safe operation of existing equipment under current environmental conditions. The preset threshold of this parameter is usually determined by a limited number of experimental calibrations and regression analysis methods based on historical operational data, equipment design performance limits, and actual sea area test results.

[0043] For example, based on stability data, positioning error data, and task completion rate of multiple drilling rigs operating under different sea conditions, critical conditions that cause a sharp decline in equipment performance or a significant increase in operational risk can be identified through statistical distribution analysis or machine learning classification algorithms, thereby setting the threshold.

[0044] If the calculated operational feasibility tendency parameter is greater than the preset threshold, it indicates that the current equipment is still within an acceptable range in terms of environmental adaptability, positioning capability, and operational stability, and the system determines that there is no need to switch drilling equipment. Conversely, if the parameter is equal to or lower than the preset value, it indicates that the environmental dynamics have exceeded the equipment tolerance, and there is a high risk of continuing to operate, so it is necessary to switch to a more suitable type of drilling equipment.

[0045] Understandably, through the aforementioned data-driven parameter setting and threshold discrimination mechanism, the system can standardize and automate equipment switching decisions without affecting operational continuity, significantly enhancing the safety and resource allocation rationality of drilling operations in complex marine environments.

[0046] Specifically, the scheduling decision module obtains the real-time stability indicators, including: The scheduling decision module selects drilling platforms with a wave resistance level greater than the current wave level; Select the drilling platform with the best real-time stability index for parameter matching to obtain its operating parameters.

[0047] During implementation, the real-time stability index acquisition mechanism in the scheduling decision module quickly identifies the operational equipment best suited to the current marine environment from among available drilling platforms, ensuring the stability and safety of the drilling process. Based on real-time wave level data provided by the environmental monitoring module, a set of candidate drilling platforms with wave resistance levels higher than the current actual wave level is selected. The determination of the wave resistance level threshold typically relies on structural strength analysis, tank model tests, and dynamic response records at different wave levels from historical operational data of various drilling platforms during the design phase. Through a limited number of full-scale ship tests and regression analysis, the correspondence between the platform's wave resistance capability and wave level is established, and a certain safety margin is introduced to determine the appropriate value.

[0048] Based on the initial screening, the scheduling decision module further selects the platform with the best real-time stability index from among the platforms that meet the wave resistance requirements as the preferred equipment. This stability index is a composite parameter, which is usually calculated by fusing data from multiple sources such as platform attitude sensors, positioning offset, and structural vibration monitoring. It is used to comprehensively characterize the dynamic stability of the platform under dynamic loads such as waves and ocean currents.

[0049] In this invention, a two-stage screening mechanism is used to first eliminate platforms with insufficient wave resistance, and then select those with the best real-time operational status. This achieves efficient optimization and precise matching of drilling equipment, avoiding operational risks caused by insufficient wave resistance and maximizing the stability of drilling operations and the quality of data acquisition. Its core principle lies in combining environmental conditions, platform structural performance, and real-time dynamic response to form a hierarchical decision-making logic, thereby enhancing the system's scheduling rationality and operational adaptability under complex sea conditions.

[0050] Specifically, the scheduling intervention parameters are determined according to formula (1). Ks=Σ(Pc-Pe) / N In the formula, Ks is the scheduling intervention parameter, Pc is the actual measured value of the platform performance parameter, Pe is the expected required value of the platform performance parameter, and N is the total number of performance parameters participating in the evaluation.

[0051] Specifically, the scheduling decision module determines whether to initiate cross-platform collaborative work based on the scheduling intervention parameters, including: If the scheduling intervention parameter is greater than or equal to the standard scheduling intervention parameter, it is determined that cross-platform collaborative operation needs to be initiated. If the scheduling intervention parameter is less than the standard scheduling intervention parameter, it is determined that there is no need to start cross-platform collaborative operation.

[0052] The scheduling intervention parameter quantifies the overall deviation between the actual performance of the drilling platform and the expected requirements, providing an objective basis for decision-making on whether to initiate cross-platform collaborative operations.

[0053] The expected requirement value Pe involved in the formula is usually determined based on the design performance of the drilling platform, the operational requirements of a specific sea area, or historical best operational data. The values ​​of standard scheduling intervention parameters are usually determined based on historical data and simulation analysis of multi-platform collaborative operations, and are calibrated through a limited number of field tests combined with regression analysis methods.

[0054] Specifically, by collecting a large amount of data on platform performance deviations and operational effectiveness under different sea states, the correlation between the Ks value and operational success rate, equipment failure rate, etc., is analyzed to determine the critical value that can significantly distinguish between independent operations and those requiring coordinated supplementation. The purpose of this design is to integrate the performance deviations of multiple parameters into a comprehensive evaluation index, enabling the system to quickly identify whether the overall performance of the current equipment group is insufficient, thereby triggering a higher-level scheduling strategy.

[0055] Understandably, if Ks is greater than or equal to the standard scheduling intervention parameter, it indicates that the overall performance deviation of the existing platform group has exceeded the acceptable range, and independent operation is either too risky or too inefficient. The system determines that cross-platform collaborative operation needs to be initiated to improve overall operational capabilities through functional complementarity or resource integration between devices. If Ks is less than the standard scheduling intervention parameter, it indicates that the current platform performance is basically in line with the expected requirements, and there is no need to initiate a complex multi-platform collaborative process. Through macro-level performance deviation assessment, a collaborative mechanism is introduced when necessary, thereby optimizing resource allocation and operational efficiency while ensuring operational safety and reliability. Through this data-driven threshold discrimination mechanism, the system can more intelligently adapt to complex and ever-changing marine operating environments, enhancing the robustness and adaptability of the overall operating system.

[0056] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

[0057] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A collaborative operation scheduling system for multiple drilling rigs in offshore exploration, comprising horizontal leveling equipment and vertical positioning equipment for fixed drilling platforms in different sea areas such as shallow waters, intertidal zones, and deep seas, as well as mobile operation equipment for controlling the position and attitude of each platform, wherein the operating parameters of the mobile operation equipment include: Positioning accuracy, wave resistance level, and operating time window. A multi-drilling rig collaborative operation scheduling system for offshore exploration, characterized by comprising: The environmental monitoring module is used to continuously acquire current marine environmental parameters, including water depth, current velocity, seabed type, and tidal data. An adaptive analysis module, which is connected to the environmental monitoring module, is used to analyze the environmental parameters to obtain marine characteristics, and determine the equipment adaptation tendency parameters based on the marine characteristics to determine the recommended drilling equipment category for the marine area. A scheduling decision module, connected to both the environmental monitoring module and the adaptive analysis module, is used to determine whether the operational strategy needs to be adjusted based on the recommended drilling equipment type for the sea area, including: Adjust the working parameters of the mobile operating equipment to adapt to tidal and wave changes, obtain real-time stability indicators, and calculate the operational feasibility tendency parameters to determine whether it is necessary to switch drilling equipment. Alternatively, select sea areas whose environmental characteristics do not meet the current equipment operating conditions, match the type of backup drilling platform, and determine the scheduling intervention parameters based on the platform performance parameters to determine whether cross-platform collaborative operation needs to be initiated; The dynamic control module, which is connected to the scheduling decision module, is used to issue scheduling instructions and perform equipment switching or parameter optimization when it is determined that the operation strategy needs to be adjusted.

2. The multi-drilling rig collaborative operation scheduling system for offshore exploration according to claim 1, characterized in that, The environmental monitoring module includes: The hydrological monitoring unit consists of tidal sensors deployed on the legs of the drilling platform and depth sensors installed at the bottom of the platform, used to measure the water depth and tidal data at the work site in real time. The hydrodynamic monitoring unit consists of an acoustic Doppler current profiler installed on the bottom or bottom support of the drilling platform, used to measure the flow velocity at different water depths below the platform in real time. The bottom sediment characteristic identification unit consists of a shallow seismic profiler or side-scan sonar installed at the bottom of the drilling platform, used to detect and identify the type of bottom sediment before and after the platform is in place.

3. The multi-drilling rig collaborative operation scheduling system for offshore exploration according to claim 2, characterized in that, The adaptive analysis module determines the actual operating efficiency of drilling equipment at different sea locations and the standard operating efficiency of drilling equipment at different sea locations under the current environmental conditions based on the marine environmental parameters. The adaptability analysis module determines the equipment performance characterization factor based on the ratio of the actual operating efficiency of the drilling equipment to the standard operating efficiency at the same location under the same environmental conditions, and determines the equipment adaptation tendency parameter based on the ratio of the average deviation of the equipment performance characterization factor to its mean.

4. A multi-drilling rig collaborative operation scheduling system for offshore exploration according to claim 3, characterized in that, The adaptive analysis module determines the recommended drilling equipment category for the sea area based on the equipment adaptation tendency parameter, including: If the equipment adaptation tendency parameter is greater than or equal to the standard equipment adaptation tendency parameter, then the recommended drilling equipment category for the sea area is the current equipment's operational category. If the equipment adaptation tendency parameter is less than the standard equipment adaptation tendency parameter, then the recommended drilling equipment category for the sea area is one that needs to be switched.

5. A multi-drilling rig collaborative operation scheduling system for offshore exploration according to claim 4, characterized in that, The scheduling decision module determines whether the operation strategy needs to be adjusted based on the recommended drilling equipment type for the sea area. If the recommended drilling equipment category for the sea area is the category that the current equipment can operate in, then it is determined whether the operation strategy needs to be adjusted by adjusting the working parameters of the mobile operation equipment, adapting to tidal and wave changes, obtaining real-time stability indicators, and recalculating the operation feasibility tendency parameters to determine whether the drilling equipment needs to be switched. If the recommended drilling equipment category for the sea area is one that needs to be switched, then determine whether the operation strategy needs to be adjusted by screening out sea areas whose environmental characteristics do not meet the current equipment operation conditions, matching the backup drilling platform type, and determining the scheduling intervention parameters based on the platform performance parameters to determine whether cross-platform collaborative operation needs to be initiated.

6. A multi-drilling rig collaborative operation scheduling system for offshore exploration according to claim 5, characterized in that, The scheduling decision module determines whether to switch drilling equipment based on the operation feasibility tendency parameter. include, If the operational feasibility tendency parameter is greater than the preset operational feasibility tendency parameter, it is determined that there is no need to switch drilling equipment. If the operational feasibility tendency parameter is less than or equal to the preset operational feasibility tendency parameter, it is determined that the drilling equipment needs to be switched.

7. A multi-drilling rig collaborative operation scheduling system for offshore exploration according to claim 1, characterized in that, The scheduling decision module obtains the real-time stability indicators, including: The scheduling decision module selects drilling platforms with a wave resistance level greater than the current wave level; Select the drilling platform with the best real-time stability index for parameter matching to obtain its operating parameters.

8. A multi-drilling rig collaborative operation scheduling system for offshore exploration according to claim 1, characterized in that, The scheduling intervention parameters are determined according to the following formula. Ks=Σ(Pc-Pe) / N In the formula, Ks is the scheduling intervention parameter, Pc is the actual measured value of the platform performance parameter, Pe is the expected required value of the platform performance parameter, and N is the total number of performance parameters participating in the evaluation.

9. A multi-drilling rig collaborative operation scheduling system for offshore exploration according to claim 1, characterized in that, The scheduling decision module determines whether to initiate cross-platform collaborative operations based on the scheduling intervention parameters. If the scheduling intervention parameter is greater than or equal to the standard scheduling intervention parameter, it is determined that cross-platform collaborative operation needs to be initiated. If the scheduling intervention parameter is less than the standard scheduling intervention parameter, it is determined that there is no need to start cross-platform collaborative operation.

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