Exploration drilling parameter control method and system

Abstract

The invention relates to the technical field of drilling parameter control, in particular to an exploration drilling parameter control method and system.The method comprises the following steps that a drilling target and a target priority corresponding to the drilling target are set, and the target priority indicates the importance of the drilling target; acquiring various measurement data in the drilling process, and processing the various measurement data; according to the processed multiple measurement data, the current stratum characteristics and the current drilling tool operation state are recognized; according to geological information in the drilling process, the drilling target and the target priority are adjusted; according to real-time geological information and a drilling state, a drilling target and a parameter control strategy are dynamically adjusted, so that the method has the advantages of better adapting to complex stratum changes, optimizing tradeoff among multiple targets and improving drilling self-adaptability and control precision.

Description

Technical Field

[0001] The present invention relates to the field of drilling parameter control, and in particular to an exploration drilling parameter control method and system. Background Art

[0002] Exploration drilling acquires underground geological information and resources through drilling. Its core goal is to penetrate the formation and obtain cores or data. However, complex and variable formations and harsh downhole environments pose challenges in controlling drilling parameters. Traditional methods struggle to cope with subtle formation variations, measurement data uncertainties, and conflicts between multiple objectives, impacting efficiency and data quality.

[0003] Exploration drilling operations require a high degree of sensitivity to the identification of fine formation features, making it difficult to meet practical needs by simply adjusting macroscopic parameters. For example, when searching for unconventional oil and gas reservoirs, not only is it necessary to drill through the target formation, but it is also necessary to accurately identify tiny oil and gas shows, complex fracture systems, and the locations of different fluid interfaces within the formation. These fine features can be highly sensitive to disturbances during drilling. If drilling parameters are adjusted too roughly and fail to precisely match these microscopic geological features, critical information may be destroyed or omitted. However, the harsh downhole environment often causes sensor data to be subject to random interference or loss, and complex physical correlations exist between different data. Without effective denoising, completion, and disclosure of these correlations, it is difficult to accurately judge the state of the formation and drill tool, leading to decision-making bias.

[0004] Furthermore, the formation's response to drilling parameters during drilling is nonlinear, hysteretic, and uncertain (e.g., stress release, plastic deformation, and microcrack propagation). Furthermore, the behavior of drill tools in complex wellbores (bending, torsion, and vibration) is constantly changing and difficult to predict, influenced by multiple factors. Traditional methods struggle to perceive and predict these complex behaviors in real time. The operational objectives of exploration drilling also complicate parameter control, as these multiple objectives inherently conflict with one another. Unlike development wells, where the primary goal is to quickly reach the target formation, exploration wells often have multiple objectives that must be balanced. For example, obtaining high-quality core samples may require a reduced drilling rate; at the same time, improving drilling efficiency is desirable to control project schedules and costs. Furthermore, there may be trade-offs between ensuring accurate wellbore trajectory, maintaining wellbore stability, efficiently carrying cuttings, and obtaining accurate logging-while-drilling data. Finding an optimal balance between these conflicting operational objectives within complex and changing formation conditions places extremely high demands on drilling parameter control.

[0005] Given the intertwined effects of these complex factors, including high sensitivity to fine formation features, inherent uncertainty in various downhole measurement data, the nonlinear response of the formation to drilling, and the complex and variability of drill tool operating conditions, traditional drilling parameter adjustment methods based on experience, table lookup, or simple feedback have become unable to meet the comprehensive requirements of exploration drilling for accuracy, adaptability, multi-objective optimization, and robust control. This is particularly true in exploration scenarios that require real-time response to subtle formation changes, processing noisy and delayed downhole data, and considering the complex behavior of the formation and drill tools. The challenge of achieving precise, environmentally adaptive, and multi-objective trade-off control of drilling parameters to improve drilling efficiency and avoid downhole accidents while ensuring geological data quality, core integrity, and wellbore safety has become a challenge facing the current field of exploration drilling parameter control.

[0006] In view of the above problems, the existing technology is in urgent need of improvement. Summary of the Invention

[0007] The purpose of the present invention is to solve the shortcomings of the prior art and to propose a method and system for controlling exploration drilling parameters.

[0008] In a first aspect, the present invention provides a method for controlling exploration drilling parameters, the method comprising the following steps: setting a drilling target and a target priority corresponding to the drilling target, wherein the target priority indicates the importance of the drilling target; Acquiring a variety of measurement data during the drilling process and processing the various measurement data; Identify current formation characteristics and current drilling tool operation status based on processed multiple measurement data; Adjusting the drilling target and the target priority according to geological information during the drilling process; Determining a drilling parameter control strategy based on the adjusted target priorities, the identified current formation characteristics, and the identified current drilling tool operating status, wherein the control strategy prioritizes between ensuring the quality of geological information acquisition, wellbore safety, and improving drilling efficiency based on the adjusted target priorities; Calculating the current drilling parameter settings and sending the settings to the drilling equipment; The set value is modified according to the drilling response.

[0009] The core innovation of this application lies in combining the function of dynamically adjusting drilling targets and target priorities according to geological information during the drilling process with the function of determining control strategies focusing on different targets based on real-time identification of formation characteristics and drill tool operating status, thereby achieving adaptive, multi-objective trade-off control of drilling parameters under complex and changeable formation conditions, and improving drilling efficiency while ensuring the quality of geological information acquisition and wellbore safety.

[0010] In a second aspect, an exploration drilling parameter control system is provided, the system comprising: a target setting module, configured to set a drilling target and a target priority corresponding to the drilling target, wherein the target priority indicates the importance of the drilling target; A data processing module, configured to obtain various measurement data during the drilling process and process the various measurement data; A state recognition module is used to identify the current formation characteristics and the current drilling tool operation status based on the processed multiple measurement data; A target adjustment module, configured to adjust the drilling target and the target priority according to geological information during the drilling process; a strategy determination module for determining a control strategy for drilling parameters based on the adjusted target priorities, the identified current formation characteristics, and the identified current drilling tool operating status, wherein the control strategy prioritizes between ensuring the quality of geological information acquisition, wellbore safety, and improving drilling efficiency based on the adjusted target priorities; A parameter calculation module, configured to calculate the set values ​​of the current drilling parameters and send the set values ​​to the drilling equipment; The parameter correction module is used to correct the set value according to the drilling response.

[0011] Compared with the prior art, the present invention has the following beneficial effects: By dynamically adjusting target priorities, identifying formation / drill tool status in real time, determining control strategies focusing on different targets based on this information, and making corrections based on drilling responses, the problem that traditional parameter control is difficult to cope with complex formations, uncertain data, and multi-target conflicts is solved. It has the advantage of being able to dynamically adjust drilling targets and parameter control strategies based on real-time geological information and drilling status, thereby better adapting to complex formation changes, optimizing the trade-offs between multiple targets, and improving drilling adaptability and control accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 is a flow chart of the method of the present invention; Figure 2 Schematic diagram of the system structure of the present invention; In the figure: 201, target setting module; 202, data processing module; 203, state recognition module; 204, target adjustment module; 205, strategy determination module; 206, parameter calculation module; 207, parameter correction module. DETAILED DESCRIPTION

[0013] The embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and are not to be construed as limiting the present invention.

[0014] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of the technical features being referred to. Thus, a feature specified as "first" or "second" may explicitly or implicitly include one or more of the specified features. In the description of the present invention, "plurality" means two or more, unless otherwise specifically defined.

[0015] Traditional exploration drilling parameter control methods struggle to balance the quality of geological information acquisition, wellbore safety, and improved drilling efficiency when dealing with complex and changing formation conditions and downhole environments. The highly sensitive nature of identifying subtle formation features, the inherent uncertainty of various downhole measurement data, the nonlinear response of the formation to drilling forces, and the complex and variable nature of drill tool operation make it difficult for traditional parameter adjustment methods based on experience, table lookups, or simple feedback to achieve precise, adaptive, and multi-objective optimization control. This impacts core integrity, measurement while drilling data accuracy, and wellbore safety, while also limiting overall drilling efficiency improvements.

[0016] For example, when exploring for unconventional oil and gas reservoirs, it's necessary to accurately identify subtle oil and gas shows, complex fracture systems, and the locations of various fluid interfaces within the formation. During drilling, downhole sensors capture various measurement data, including weight on bit (WOB), torque, rotational speed, drilling fluid flow, downhole vibration, temperature, pressure, formation gamma ray patterns, and resistivity, which are subject to random interference and transient loss. The formation's response to drilling parameters exhibits nonlinearity, hysteresis, and uncertainty. In long, nonlinear wellbores, drill tools experience various deformations, including bending, torsion, and axial vibration, such as stick-slip. Simultaneously, there are multiple competing objectives: obtaining high-quality core samples, controlling project schedules, ensuring accurate wellbore trajectory, maintaining wellbore stability, efficiently transporting cuttings, and obtaining accurate logging-while-drilling data. These objectives often conflict. In this scenario, traditional parameter adjustment methods struggle to perceive and predict subtle formation changes and complex drill tool behavior in real time, and they fail to find the optimal balance between these multiple objectives. This can lead to the destruction of critical geological information, downhole accidents, and reduced drilling efficiency.

[0017] If these issues are not addressed, exploration drilling operations will face consequences such as inaccurate or missed geological information, reduced core sample quality, wellbore instability or even collapse, increased risk of drill tool damage, and overall low drilling efficiency. This will directly impact the accuracy of subsurface resource assessments, increase operational costs and cycle time, and even lead to downhole accidents, seriously hindering the success of exploration operations.

[0018] To this end, this application Figure 1 A method for controlling exploration drilling parameters is shown, the method comprising the following steps: S101, setting a drilling target and a target priority corresponding to the drilling target, where the target priority indicates the importance of the drilling target; S102, acquiring a variety of measurement data during the drilling process, and processing the various measurement data; S103, identifying current formation characteristics and current drilling tool operation status based on the processed multiple measurement data; S104, adjusting the drilling target and target priority according to geological information during the drilling process; S105. Determine a control strategy for drilling parameters based on the adjusted target priority, the identified current formation characteristics, and the identified current drilling tool operating status. The control strategy prioritizes ensuring the quality of geological information acquisition, wellbore safety, and improving drilling efficiency based on the adjusted target priority. S106, calculating the setting value of the current drilling parameter and sending the setting value to the drilling equipment; S107: Modify the set value according to the drilling response.

[0019] The drilling objective refers to the specific goal of the drilling operation, such as reaching a specific depth, obtaining a core sample, or traversing a specific formation area. It can be defined using a preset depth range, formation name, or geological event trigger condition, primarily providing directional guidance for the drilling process. Target priority indicates the relative importance of different drilling objectives at the current stage. It can be represented by numerical weights, ranked lists, or Boolean flags, primarily to balance and prioritize multiple conflicting objectives. Multiple measurement data refers to various real-time data acquired by uphole or downhole sensors during the drilling process. This data may include, but is not limited to, weight on bit, torque, rotational speed, drilling fluid flow, downhole vibration, temperature, pressure, gamma rays, resistivity, and other data, primarily for comprehensive perception of the downhole environment and drill tool operating status. Formation properties refer to the physical, chemical, or geological properties of the formation in which the drill bit is currently located. This information may include rock hardness, drillability, porosity, permeability, stress state, and fracture development, primarily for understanding the impact of the formation on the drilling process. Drill tool operating status refers to the dynamic performance of the drill tool during downhole operation. This information may include axial vibration, torsional vibration, bending vibration, stick-slip behavior, bit wear, and drill tool stress conditions, primarily for assessing drill tool efficiency and potential risks. Geological information refers to formation-related knowledge or events extracted or inferred from measurement data. This information may include the identification of formation interfaces, lithologic variations, areas of abnormal pressure, and potential geological risks, primarily for guiding the adjustment of drilling objectives and the formulation of strategies. The control strategy refers to the set of rules or decision logic that determines how to adjust drilling parameters based on the current state and target priorities. This control strategy can be constructed using rule-based expert systems, fuzzy control, model predictive control, or machine learning algorithms, primarily for balancing different objectives and optimizing parameter settings. Drilling response refers to the feedback provided by the drilling equipment or downhole environment to the current drilling parameter settings. It may include changes in drilling rate, torque fluctuations, downhole vibration patterns, changes in wellbore trajectory, cuttings morphology, etc. It is mainly used to evaluate the effect of current parameter settings and make corrections.

[0020] The solution of this application initiates the drilling process by setting initial drilling objectives and target priorities that indicate their importance. During drilling, the system continuously acquires various measurement data from both above and below the wellbore and performs necessary processing on this raw data, such as noise reduction and calibration, to improve data reliability. Based on this processed measurement data, the system can identify in real time the specific characteristics of the formation in which the drill bit is currently located and the current operating status of the drill tool, such as abnormal vibration or wear. Simultaneously, the system continuously analyzes geological information acquired during drilling, which may indicate impending formation changes or the entry into critical areas. Based on this dynamic geological information, the system can timely adjust the previously set drilling objectives and their corresponding target priorities to align control priorities with actual geological conditions. The system then comprehensively considers the adjusted target priorities, the real-time identified formation characteristics, and the operating status of the drill tool to determine the optimal drilling parameter control strategy. The core of this strategy is to dynamically prioritize and balance the interrelated objectives of ensuring the quality of geological information acquisition, wellbore safety, and improving drilling efficiency, based on the current target priorities. Once the control strategy is determined, the system calculates the specific settings for each drilling parameter at the current moment and sends these settings to the drilling equipment for execution. After the parameters are executed, the system monitors the drilling response, such as changes in drilling rate, torque, vibration, and other data. Based on these drilling responses, the system evaluates the actual effectiveness of the current parameter settings and makes necessary corrections to the calculated settings, forming a closed-loop adaptive control process that ensures continuous optimization of drilling parameters to respond to changing downhole conditions.

[0021] As an embodiment of the present invention, the steps of adjusting the drilling target and the target priority according to the geological information during the drilling process include: Continuously analyze the changing trends and correlations of various measurement data to obtain geological information during the drilling process; Based on geological information, it is predicted that the drill bit is about to enter a formation area that requires attention; Before the drill bit is predicted to enter the formation area that requires attention, the drilling target and target priority conversion are started in advance based on the prediction results; According to the converted drilling target and target priority, the command drilling parameters are gradually adjusted in a controlled manner to ensure that when the drill bit enters the formation area requiring attention, the drilling parameters have reached a state suitable for the formation area requiring attention.

[0022] In order to understand this solution more clearly, some of the technical features are explained below.

[0023] The trends and correlations presented by various measurement data refer to analyzing how different types of measurement data (such as weight on bit, torque, rotational speed, downhole vibration, and formation gamma) change over time or depth, and exploring the mutual influence or synchronous change relationships between these data. This can be achieved through techniques such as time series analysis, correlation analysis, and pattern recognition. Geological information during drilling refers to information about the current and adjacent formation attributes, such as lithology, hardness, porosity, permeability, stress state, and fluid properties, obtained through processing and interpretation of downhole measurement data. This can be achieved through techniques such as data fusion, geological interpretation models, and machine learning algorithms. Areas of concern refer to formations during drilling where specific control strategies are required due to their geological characteristics that may have a significant impact on drilling safety, efficiency, or the acquisition of geological information. These areas include high-pressure formations, easily collapsed formations, oil and gas-bearing strata, hard interlayers, and fault zones. These areas can be determined based on pre-set geological models, historical drilling data, or real-time geological information interpretation. Among them, controlled gradual adjustment refers to planning and controlling the adjustment process of drilling parameters (such as bit weight, rotation speed, displacement, etc.) so that they change smoothly according to a predetermined rate, amplitude or curve rather than instantaneous mutations. It can be achieved by using ramp functions, piecewise linear functions, PID control algorithms combined with rate limiting, etc.

[0024] The solution of this application acquires geological information during the drilling process by continuously analyzing the changing trends and correlations presented by various measurement data. This enables the system to gain a more comprehensive and in-depth understanding of the characteristics of the current and adjacent formations. Based on this geological information, the system can predict when the drill bit is about to enter a formation area of ​​concern, thereby obtaining a time window to respond to formation changes. Before predicting that the drill bit is about to enter a formation area of ​​concern, the system preemptively initiates the conversion of drilling targets and target priorities based on the prediction results. This preemptive conversion mechanism ensures sufficient time for subsequent parameter adjustments to transition smoothly. Based on the converted drilling targets and target priorities, the system instructs drilling parameters to adjust gradually in a controlled manner. This controlled, gradual adjustment ensures that parameter changes are not too drastic, avoiding impacts on the formation and drill tools. Ultimately, by the time the drill bit actually enters the formation area of ​​concern, the drilling parameters have already reached a state that is suitable for that area, ensuring a smooth transition during the drilling process, reducing the risk of downhole accidents, and improving the quality of geological information acquisition. Compared with making immediate adjustments based solely on current geological information, this solution introduces a mechanism of prejudgment and gradual adjustment, making the entire drilling parameter control process more forward-looking and robust, and able to more effectively respond to the challenges brought about by complex formation changes.

[0025] As an embodiment of the present invention, the steps of determining a control strategy for drilling parameters, wherein the control strategy focuses on ensuring the quality of geological information acquisition, wellbore safety, and improving drilling efficiency based on the adjusted target priorities, include: Based on the identified current formation characteristics and the identified current drilling tool operating status, evaluate the potential impact of the current drilling environment on geological information acquisition, wellbore safety, and drilling efficiency; Determine the current importance of each drilling objective (including geological information quality, wellbore safety, and improved drilling efficiency) based on the adjusted target priorities and potential impacts; Construct strategic options that reflect the interrelationships between drilling objectives based on current importance; From the strategy options, select a drilling parameter control strategy that best meets the adjusted target priority while minimizing the negative impact on other non-primary targets, thereby balancing the quality of geological information acquisition, wellbore safety, and improved drilling efficiency.

[0026] Assessing the potential impact of the current drilling environment on geological information acquisition, wellbore safety, and drilling efficiency involves predicting the potential positive or negative impacts of the current or upcoming drilling environment on the integrity of geological information acquisition, wellbore stability, and drilling speed and efficiency based on currently identified formation properties (e.g., rock hardness, fracture development, formation pressure) and drill tool operating conditions (e.g., weight on bit, torque, vibration, and drill bit wear). Specifically, this can be accomplished by mapping the current formation and drill tool conditions to the potential impact on various drilling objectives through a pre-defined model or rule base. The goal is to quantify the risks and opportunities associated with achieving each drilling objective. Determining the current importance of each drilling objective involves dynamically adjusting or refining the relative importance of geological information acquisition quality, wellbore safety, and improving drilling efficiency based on the assessed potential impacts, based on the adjusted objective priorities. Specifically, this can be accomplished through weighted calculation, fuzzy logic, or rule-based reasoning, combining static objective priorities with dynamic potential impacts to derive the importance of each objective that reflects the current reality. This allows control decisions to better align with the needs of the real-time drilling environment. Constructing strategic options that reflect the interrelationships among drilling objectives involves generating a series of feasible drilling parameter control schemes, each of which considers the inherent connections and trade-offs among the three objectives of geological information quality, wellbore safety, and drilling efficiency. Specifically, this can be accomplished through predefined strategy templates, optimization algorithm-based generation, or expert experience-based rule sets, resulting in a set of strategies containing different parameter combinations and adjustment logic. The goal is to provide a diverse set of alternatives that consider the interactions between multiple objectives for subsequent strategy selection. Selecting a drilling parameter control strategy from the strategic options involves selecting the control scheme that best suits the current drilling environment and objective requirements from the constructed set of strategic options, based on the current importance of each drilling objective. Specifically, this can be accomplished by evaluating the expected performance of each strategy option at its current importance, for example, using a scoring mechanism, decision tree, or simple rule matching, to select the strategy that maximizes the achievement of the primary objective while minimizing the negative impact on secondary objectives. The goal is to make the optimal parameter control decision.

[0027] The solution of this application evaluates the potential impact of the current drilling environment on geological information acquisition, wellbore safety, and drilling efficiency based on the identified current formation characteristics and the identified current drilling tool operating status, thereby obtaining quantitative information on the risks and opportunities of the current drilling environment for each drilling target. On this basis, the current importance of each drilling target is determined in combination with the adjusted target priority and potential impact. In this way, the static target priority and the dynamic potential impact are combined to obtain the importance of each target that reflects the current actual situation. Furthermore, based on the current importance, strategy options are constructed that reflect the mutual relationship between each drilling target, thereby providing a variety of alternative solutions that consider the interaction of multiple targets for subsequent strategy selection. Finally, a drilling parameter control strategy is selected from the strategy options. This control strategy can maximize the satisfaction of the adjusted target priority while reducing the negative impact on other non-primary targets, thereby making the optimal parameter control decision. The entire process forms a closed-loop decision-making process, organically combining the real-time status of the formation and drill tools, dynamically adjusted target priorities, and the inherent conflicts between various targets. This allows the optimal drilling parameter control strategy to be dynamically determined based on the complex and changing drilling environment, and a flexible and reasonable emphasis to be placed on ensuring the quality of geological information acquisition, wellbore safety, and improving drilling efficiency.

[0028] As an embodiment of the present invention, a drilling parameter control strategy is selected from the strategy options. The control strategy can maximize the satisfaction of the adjusted target priority while reducing the negative impact on other non-primary targets, thereby emphasizing the importance of ensuring the quality of geological information acquisition, wellbore safety, and improving drilling efficiency. The steps include: For each control strategy in the strategy options, a performance simulation is performed based on the current drilling status. The performance simulation considers the evolution trend of the identified current formation characteristics and the identified current drilling tool operation status in a short period of time, and takes into account the fluctuation range of various measurement data to generate the simulation results; Based on the simulation results, a drilling parameter control strategy is selected that can continuously maintain the satisfaction of the adjusted target priority while reducing the negative impact on other non-primary targets, thereby emphasizing the balance between ensuring the quality of geological information acquisition, wellbore safety, and improving drilling efficiency.

[0029] Among them, performance deduction refers to the simulation or prediction of the effect of applying a specific control strategy in a period of time in the future. It can be achieved by means of simulation based on physical models, data-driven prediction models or hybrid modeling, and its purpose is to evaluate the performance of the control strategy under dynamic changes and uncertain environments; the evolution trend of the identified current formation characteristics and the identified current drilling tool operation status in a short period of time refers to the prediction of the change direction and rate of the currently identified formation properties (such as hardness, drillability, stress state) and drilling tool status (such as vibration mode, torque fluctuation, drill bit wear) in a shorter time window in the future, which can be achieved by means of time series analysis, trend extrapolation or pattern recognition based on historical data, and its purpose is to incorporate the dynamic nature of the environment and tool status into the strategy evaluation; the fluctuation range of various measurement data refers to the various types of data obtained by downhole sensors (such as drilling The inherent uncertainty or noise level of the performance simulation process (such as pressure, torque, speed, downhole vibration, etc.) can be quantified, which can be characterized by statistical analysis, error models, or confidence intervals. Its purpose is to evaluate the impact of data uncertainty on the effectiveness of the control strategy. The deduction results refer to the outputs generated by the performance simulation process, which may include predicted drilling parameters (such as predicted drilling speed, torque, vibration level), predicted drilling effects (such as predicted core quality, wellbore stability, and drill bit life), or scores reflecting the degree of target satisfaction. Its purpose is to provide a quantitative evaluation basis for the selection of control strategies. Maintaining the degree of satisfaction of the adjusted target priority means that the selected control strategy can maintain a high level of effectiveness in achieving the main drilling objectives over a period of time in the future, and the negative impact on non-main objectives can be effectively controlled. Its purpose is to ensure the stability and robustness of the drilling process.

[0030] The solution of this application performs a performance simulation for each control strategy in the strategy selection based on the current drilling status. This performance simulation considers the short-term evolution trends of the identified current formation characteristics and the identified current drill tool operating status, and accounts for the fluctuation range of various measurement data to generate simulation results. By incorporating short-term dynamic changes in formation and drill tool conditions and the uncertainty of measurement data into the strategy evaluation process, the simulation results can more accurately reflect the potential performance of the control strategy in a real, dynamic environment, avoiding the limitations of decision-making based solely on instantaneous conditions. Based on this simulation result, a drilling parameter control strategy is selected that can continuously maintain the satisfaction of the adjusted target priority while reducing the negative impact on other non-primary objectives, thereby balancing the quality of geological information acquisition, wellbore safety, and improved drilling efficiency. Because the selection is based on predicted performance simulation results that take into account future trends and uncertainties, the selected control strategy is not only optimal at the current time but also maintains good performance and stability for a period of time in the future, effectively addressing the complexity and dynamic nature of the actual drilling environment.

[0031] As an embodiment of the present invention, the step of correcting the set value according to the drilling response includes: Obtaining a drilling response, the drilling response including a measurement data response indicating formation characteristics and a measurement data response indicating a drilling tool operation status; Analyzing the indicative characteristics of the response of the measurement data indicating the formation characteristics to the formation changes, and the indicative characteristics of the response of the measurement data indicating the operating status of the drilling tool to the drilling tool behavior; Based on the changing trend of the measured data response indicating the formation characteristics, determine the effect of the correction direction and correction amplitude on the set value; Based on the fluctuations in the measured data response indicating the operating status of the drilling tool, combined with the changes in the measured data response indicating the characteristics of the formation, it is determined whether the fluctuations indicate the behavior of the drilling tool itself; Based on the result of the action judgment of the measurement data response indicating the formation characteristics and the result of the fluctuation judgment of the measurement data response indicating the operating status of the drilling tool, the correction direction and correction amplitude of the set value are determined, and the set value is corrected according to the correction direction and correction amplitude.

[0032] Among them, drilling response refers to the feedback data generated by the downhole environment and drill bit status when the drilling equipment executes the set parameters, which can be realized by various sensor measurement values, equipment operating parameters, etc.; measurement data response indicating formation characteristics refers to measurement data that can reflect changes in the physical, chemical or mechanical properties of the formation, which can be realized by logging while drilling data, changes in drilling parameters, etc.; measurement data response indicating the operating status of the drill bit refers to measurement data that can reflect the movement, force or wear status of the drill bit itself, which can be realized by downhole vibration data, torque, bit pressure, rotation speed, downhole temperature and pressure, etc.; the indication characteristics of formation changes refer to the correspondence or sensitivity between the measurement data response and the actual changes in the formation. It can be achieved by using historical data analysis, geological models, machine learning models, etc.; the indicative characteristics of drill tool behavior refer to the correspondence or sensitivity between the measurement data response and the actual operating status of the drill tool, which can be achieved by using mechanical models, vibration analysis, pattern recognition, etc.; the change trend refers to the direction and rate of numerical change of the measurement data response over a period of time, which can be achieved by using time series analysis, filtering, curve fitting, etc.; fluctuation refers to the non-periodic or periodic fluctuations of the measurement data response in the short term, which can be achieved by using statistical analysis, spectrum analysis, anomaly detection, etc.; correction direction refers to the adjustment direction of increasing or decreasing the set value; correction amplitude refers to the specific numerical size of the adjustment to the set value.

[0033] The solution of the present application obtains a drilling response, which includes a measurement data response indicating formation characteristics and a measurement data response indicating the operating status of the drill tool, thereby providing basic data for subsequent analysis and judgment. Based on the acquired response data, the measurement data response indicating formation characteristics is analyzed to determine the indicative characteristics of formation changes, and the measurement data response indicating the operating status of the drill tool is analyzed to determine the indicative characteristics of the drill tool behavior. This helps to understand the current drilling status and accurately grasp the formation changes and drill tool behavior. Furthermore, based on the change trend of the measurement data response indicating formation characteristics, its effect on the correction direction and correction amplitude of the set value is judged, which enables parameter adjustment to adapt to formation changes. At the same time, based on the fluctuations of the measurement data response indicating the operating status of the drill tool, combined with the changes in the measurement data response indicating formation characteristics, it is judged whether the fluctuations indicate the behavior of the drill tool itself, which helps to distinguish interference factors from the actual drill tool status. Ultimately, based on the results of the effect judgment of the response to the measurement data indicating formation characteristics and the fluctuation judgment of the response to the measurement data indicating the operating status of the drill tool, the correction direction and correction amplitude of the set value are determined. The set value is then corrected according to the correction direction and correction amplitude, thereby achieving real-time and dynamic adjustment of the drilling parameter setting value. This real-time feedback correction mechanism is based on the initial parameter setting based on the adjusted target priority, the identified current formation characteristics, and the identified current operating status of the drill tool. It compensates for any deviations in the initial setting, allowing the drilling parameters to more accurately match the rapidly changing formation and drill tool status, thereby better achieving multi-objective trade-offs and improving the overall drilling effect.

[0034] As an embodiment of the present invention, the step of analyzing the characteristics of the response of the measurement data indicating the formation characteristics to the formation changes, and the characteristics of the response of the measurement data indicating the operating status of the drilling tool to the drilling tool behavior includes: By summarizing the response characteristics of measurement data under different formation conditions and drilling tool operation states in drilling data, a response feature library reflecting formation characteristics and drilling tool behavior is constructed; Comparing the real-time acquired measurement data responses indicating formation characteristics and the measurement data responses indicating the operating status of the drilling tool with features in a response feature library to analyze the indicative characteristics of the measurement data responses indicating formation characteristics to formation changes, and the indicative characteristics of the measurement data responses indicating the operating status of the drilling tool to the drilling tool behavior; The response feature library is updated based on the downhole environmental information obtained during the drilling process.

[0035] Among them, the response feature library refers to a collection of measurement data response patterns or laws corresponding to different formation conditions and drilling tool operating states, which can be implemented in the form of databases, lookup tables or machine learning models; summarizing the measurement data response characteristics under different formation conditions and drilling tool operating states in drilling data refers to extracting, summarizing and refining the typical change patterns, numerical ranges or mutual relationships of measurement data exhibited by specific formation types or specific drilling tool behaviors from historical or experimental drilling data, which can be implemented by statistical analysis, pattern recognition or expert systems; the response characteristics reflecting the formation characteristics and the drilling tool behavior refer to data patterns or indicators extracted from the measurement data that can indicate the current formation type, lithology changes, formation stress state and other information, as well as the axial motion state, rotation state, vibration mode, well wall contact state and other information of the current drilling tool, which can include the mean, variance, frequency component, correlation, mutation point, etc. of the measurement data; and Comparing the features in the response feature library refers to comparing and matching the measurement data responses acquired in real time with the known feature patterns stored in the response feature library to determine which known formation condition or drilling tool behavior pattern the current real-time data is closest to. This can be achieved by using methods such as similarity calculation, pattern matching algorithm or classification algorithm; downhole environmental information refers to auxiliary information related to the actual downhole situation obtained through various means during the drilling process, which may include logging while drilling data, rock cuttings analysis results, drilling fluid performance parameters, wellbore trajectory information, drill bit wear state estimation, etc.; updating the response feature library refers to correcting, supplementing or adding existing feature patterns in the response feature library based on the measurement data responses acquired in real time, comparison results and downhole environmental information, so as to improve the accuracy and coverage of the feature library so that it can better adapt to new situations or changes encountered in the actual drilling process. This can be achieved by using strategies such as online learning, incremental update or periodic reconstruction.

[0036] The solution of this application provides a systematic reference standard for analyzing measurement data responses by constructing a response feature library that reflects formation characteristics and drill tool behavior. This feature library, derived from historical drilling data, contains typical measurement data patterns under different formation conditions and drill tool operating conditions, overcoming the lack of an effective reference standard. Subsequently, by comparing the real-time measurement data responses with the features in this feature library, the current formation characteristics and drill tool operating status can be quickly and accurately identified. This comparison-based analysis method makes the judgment of the measurement data indication characteristics more objective and precise, avoiding the uncertainty caused by relying solely on experience or simple threshold judgments. Furthermore, by dynamically updating the response feature library based on downhole environmental information acquired during drilling, it ensures the timeliness and accuracy of the feature library, enabling it to adapt to the ever-changing drilling environment and unknown situations, further improving the reliability of the analysis. This feature library-based analysis method provides more precise input for subsequent correction of set values ​​based on drilling responses, ensuring that the direction and magnitude of the corrections more accurately reflect actual formation changes and drill tool behavior, thereby improving the accuracy and reliability of the entire drilling parameter control method.

[0037] As an embodiment of the present invention, the step of determining whether the fluctuations in the response of the measurement data indicating the operating status of the drilling tool, combined with the changes in the response of the measurement data indicating the formation characteristics, indicate the behavior of the drilling tool itself includes: identifying specific features present in the measurement data response that are indicative of the operational status of the drill tool; identifying variations in the measured data response that are indicative of formation properties; Correlating and comparing the identified specific features of the measurement data response indicating the operating status of the drilling tool with the identified change features of the measurement data response indicating the formation characteristics to obtain a comparison result; Based on the comparison results, determine whether the fluctuations indicate the behavior of the drill tool itself, and clarify whether the fluctuations are caused by changes in the drill tool's own operating status or the evolution of formation conditions.

[0038] Identifying specific features presented in the measurement data response that indicate the operating status of the drill tool refers to patterns that reflect abnormal or changing operating status of the drill tool, such as periodic fluctuations in torque, sudden drops in bit pressure, specific frequencies or amplitudes of drill tool vibration, and abnormal changes in drilling speed. This can be achieved using signal processing techniques, pattern recognition algorithms, or rule-based expert systems. Identifying changing features presented in the measurement data response that indicate formation properties refers to patterns that reflect changes in formation properties or states, such as trend changes, mutations, or outliers in LWD data such as gamma rays, resistivity, and acoustic transit time, changes in cuttings type or content in drilling fluid return, and trend changes in bit pressure or torque under stable drilling conditions. This can be achieved using trend analysis, mutation point detection, data smoothing, filtering, or geological interpretation models. Correlating the identified specific features of the measured data responses indicative of drill tool operation with the identified changing features of the measured data responses indicative of formation properties involves analyzing the temporal, depth, or spatial synchronization, correlation, or causal relationship between these specific features. This can be achieved through time series analysis, cross-correlation analysis, machine learning models, or expert rule bases. Obtaining a correlation result refers to the conclusion or quantitative indicator derived from this correlation comparison, such as the correlation coefficient between the drill tool and formation characteristics, the time difference between synchronization, pattern matching, or preliminary rule-based attribution. Based on the correlation results, determining whether the fluctuations indicate drill tool behavior and determining whether the fluctuations are due to changes in the drill tool's operating status or evolving formation conditions involves conducting a comprehensive analysis based on the comparison results to determine whether the fluctuations are primarily caused by drill tool issues or changing formation conditions. This can be achieved through logical reasoning, probabilistic models, classification algorithms, or expert knowledge-based decision rules.

[0039] The solution of this application first analyzes the measurement data response indicating the operating status of the drill tool to identify specific features reflecting the drill tool's behavior. Simultaneously, the measurement data response indicating formation properties is analyzed to identify variation features reflecting formation changes. These two identified features are then correlated and compared to analyze whether there is any synchronization or correlation between them. For example, if periodic fluctuations in the drill tool torque occur simultaneously with sudden changes in the formation gamma value, this may indicate that the fluctuations are related to formation changes. If the drill tool vibration frequency increases but the formation measurement data does not change significantly, this may indicate that the fluctuations are primarily due to the drill tool's own behavior. Based on the results of this correlation comparison, it is possible to more accurately determine whether the fluctuations in the current measurement data response are primarily caused by changes in the drill tool's own operating status or by evolving formation conditions. This more precise determination allows for more accurate identification of the source of fluctuations when modifying set points based on the drilling response, avoiding misinterpretation of fluctuations caused by the formation as drill tool problems, or vice versa. This allows for more targeted correction direction and magnitude. For example, if fluctuations are caused by formation changes, the drilling pressure or rotational speed may need to be adjusted to accommodate the new formation. If fluctuations are caused by drill stick slip, the drilling pressure, rotational speed, or drilling fluid properties may need to be adjusted to suppress vibration. This accurate attribution of fluctuations improves the reliability of the entire parameter correction process, thereby enhancing the overall performance of exploration drilling parameter control methods and better balancing the quality of geological information acquisition, wellbore safety, and drilling efficiency.

[0040] As an embodiment of the present invention, for each control strategy in the strategy options, a performance deduction is performed based on the current drilling status. The performance deduction considers the evolution trend of the identified current formation characteristics and the identified current drilling tool operation status within a short period of time, and takes into account the fluctuation range of various measurement data. The steps of generating a deduction result include: Monitor drilling data streams, which include various measurements and information reflecting current formation characteristics and current drilling tool operation status; Based on the monitored drilling data stream, the evolution trend of the current formation characteristics and the current drilling tool operation status in a short period of time is identified, and the fluctuation range of various measurement data is identified to obtain evolution trend information and fluctuation range information; For each control strategy in the strategy options, performance deduction is performed based on the current drilling status and according to the evolution trend information and fluctuation range information to generate deduction results.

[0041] Among them, the evolutionary trend refers to the direction or pattern of change of technical characteristics in a short period of time. It can be identified by time series analysis, trend line fitting, machine learning model prediction and other methods, and its purpose is to predict future status; the fluctuation range refers to the numerical change range or degree of uncertainty that may occur in technical characteristics under certain time or conditions. It can be identified by statistical analysis, error analysis, historical data distribution and other methods, and its purpose is to evaluate the uncertainty of the data.

[0042] The solution of this application obtains comprehensive real-time information by continuously monitoring the drilling data stream. On this basis, the data stream is deeply analyzed to identify the changing patterns of the current formation characteristics and drilling tool operating status in a short period of time, and to quantify the uncertainty of the measurement data itself. These dynamic information and uncertainty information are integrated into the performance deduction process. For each candidate control strategy, based on the current drilling status, combined with the predicted evolution trend and data fluctuation range, the potential effect of the strategy in the short term in the future is simulated. This deduction method not only takes into account the current static conditions, but also proactively considers future changes and data uncertainties. In this way, the generated deduction results can more accurately predict the actual performance of different strategies, especially when the formation or drilling tool status changes rapidly and there is interference in the measurement data. Using these more accurate and reliable deduction results for strategy selection enables the system to more effectively select the control strategy that best meets the adjusted target priority and reduces negative effects from the strategy options. This makes decision-making between the quality of geological information acquisition, wellbore safety, and drilling efficiency more informed and robust, thereby improving the overall performance of the exploration drilling parameter control method and solving the problem of inaccurate predictions and insufficient robustness caused by relying solely on instantaneous data for deduction.

[0043] As an embodiment of the present invention, the steps of identifying the evolution trend of the identified current formation characteristics and the identified current drilling tool operation status within a short period of time, and identifying the fluctuation range of multiple measurement data include: Perform segmented analysis on the monitored drilling data stream using an adjustable time window; Adjust the length of the time window based on the data change rate or formation response characteristics reflected in the drilling data stream; Based on the results of segmented analysis using the adjusted time window, the evolution trends of the identified current formation characteristics and the identified current drilling tool operation status in a short period of time are identified, and the fluctuation ranges of various measurement data are identified to obtain evolution trend information and fluctuation range information.

[0044] Among them, the adjustable time window refers to the time period used to analyze the drilling data stream, and its length can be dynamically changed according to specific conditions. It can be implemented by an adjustment mechanism based on data statistical characteristics or preset rules. Its purpose is to enable the granularity of data analysis to adapt to the dynamic changes of the drilling process; among them, the formation response characteristics refer to the specific behavior patterns or data signal characteristics exhibited by the formation when subjected to drilling. It can be implemented by analyzing the change patterns of drilling pressure, torque, drilling speed, downhole vibration, and formation measurement data over time or depth. Its purpose is to reflect the current formation's response characteristics to drilling activities.

[0045] The solution of this application performs segmented analysis on the monitored drilling data stream, and this segmented analysis uses an adjustable time window, eliminating the need for fixed time intervals and enabling flexible adjustments based on actual conditions. By adjusting the length of the time window based on the data change rate or formation response characteristics reflected in the drilling data stream, the system can determine the dynamics of the current drilling process. For example, when drilling into an area with drastic formation changes, the data change rate accelerates; shortening the time window can capture these changes more promptly. Conversely, when drilling into relatively stable formations, the window can be appropriately extended to reduce noise interference. This adaptive adjustment of the time window length allows data analysis to better match the dynamic characteristics of the actual drilling process. By using the adjusted time window for segmented analysis, the evolution trends of the current formation characteristics and the current drill tool operating status over a short period of time are identified, and the fluctuation ranges of various measurement data are identified, generating information on the evolution trend and fluctuation range. By dynamically adjusting the time window, the system can more accurately capture the short-term trends of formation characteristics and drill tool operating status, and quantify the fluctuation range of the measurement data. This information is crucial for subsequent performance simulations because it provides more precise input parameters, enabling simulation results to more realistically reflect potential risks and optimization opportunities during actual drilling. Integrating this more accurate information into the performance simulation process makes the results more reliable, guiding subsequent parameter control decisions and improving control accuracy and robustness.

[0046] like Figure 2 An exploration drilling parameter control system is shown, the system comprising: A target setting module 201 is used to set a drilling target and a target priority corresponding to the drilling target, where the target priority indicates the importance of the drilling target; The data processing module 202 is used to obtain various measurement data during the drilling process and process the various measurement data; A state identification module 203 is used to identify the current formation characteristics and the current drilling tool operation state based on the processed multiple measurement data; A target adjustment module 204 is used to adjust the drilling target and target priority according to geological information during the drilling process; Strategy determination module 205 is used to determine a control strategy for drilling parameters based on the adjusted target priority, the identified current formation characteristics, and the identified current drilling tool operating status. The control strategy focuses on ensuring the quality of geological information acquisition, wellbore safety, and improving drilling efficiency based on the adjusted target priority. Parameter calculation module 206, used to calculate the setting value of the current drilling parameter and send the setting value to the drilling equipment; The parameter correction module 207 is used to correct the set value according to the drilling response.

[0047] The basic principles, main features, and advantages of the present invention are shown and described above. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions only describe the principles of the present invention. Various changes and improvements are possible without departing from the spirit and scope of the present invention, and such changes and improvements fall within the scope of the invention as claimed.

Claims

1. A method for controlling exploration drilling parameters, characterized in that: The method comprises the following steps: setting a drilling target and a target priority corresponding to the drilling target, wherein the target priority indicates the importance of the drilling target; Acquiring a variety of measurement data during the drilling process and processing the various measurement data; Identify current formation characteristics and current drilling tool operation status based on processed multiple measurement data; Adjusting the drilling target and the target priority according to geological information during the drilling process; Determining a drilling parameter control strategy based on the adjusted target priorities, the identified current formation characteristics, and the identified current drilling tool operating status, wherein the control strategy prioritizes between ensuring the quality of geological information acquisition, wellbore safety, and improving drilling efficiency based on the adjusted target priorities; Calculating the current drilling parameter settings and sending the settings to the drilling equipment; The set value is modified according to the drilling response.

2. The method for controlling exploration drilling parameters according to claim 1, wherein: The step of adjusting the drilling target and the target priority according to geological information during the drilling process includes: Continuously analyzing the changing trends and correlations presented by the multiple measurement data to obtain geological information during the drilling process; Based on the geological information, it is predicted that the drill bit is about to enter a formation area requiring attention; Before predicting that the drill bit enters the formation area requiring attention, initiating the conversion of the drilling target and the target priority in advance according to the prediction result; According to the converted drilling target and the target priority, the drilling parameters are instructed to be gradually adjusted in a controlled manner to ensure that when the drill bit enters the formation area requiring attention, the drilling parameters have reached a state suitable for the formation area requiring attention.

3. The method for controlling exploration drilling parameters according to claim 1, wherein: The step of determining a control strategy for drilling parameters, wherein the control strategy prioritizes ensuring the quality of geological information acquisition, wellbore safety, and improving drilling efficiency based on the adjusted target priorities, includes: Assessing the potential impact of the current drilling environment on geological information acquisition, wellbore safety, and drilling efficiency based on the identified current formation characteristics and the identified current drilling tool operating status; Determine the current importance of each drilling target based on the adjusted target priority and the potential impact; Based on the current importance, constructing strategic options reflecting the interrelationships between the drilling objectives; From the strategy options, a drilling parameter control strategy is selected, which can maximize the satisfaction of the adjusted target priority while reducing the negative impact on other non-primary targets, thereby emphasizing the balance between ensuring the quality of geological information acquisition, wellbore safety, and improving drilling efficiency.

4. The method for controlling exploration drilling parameters according to claim 3, wherein: The step of selecting a drilling parameter control strategy from the strategy options, wherein the control strategy can maximize the satisfaction of the adjusted target priority while reducing the negative impact on other non-primary targets, thereby emphasizing the balance between ensuring the quality of geological information acquisition, wellbore safety, and improving drilling efficiency, includes: For each control strategy in the strategy options, based on the current drilling status, a performance deduction is performed, wherein the performance deduction considers the evolution trend of the identified current formation characteristics and the identified current drilling tool operation status within a short period of time, and takes into account the fluctuation range of the multiple measurement data, so as to generate the deduction result; Based on the deduction results, a drilling parameter control strategy is selected, which can continuously maintain the satisfaction of the adjusted target priority while reducing the negative impact on other non-primary targets, thereby emphasizing the quality of geological information acquisition, wellbore safety and improving drilling efficiency.

5. The method for controlling exploration drilling parameters according to claim 1, wherein: The step of correcting the set value according to the drilling response includes: Acquiring the drilling response, the drilling response including a measurement data response indicating formation characteristics and a measurement data response indicating a drilling tool operation status; Analyzing the indicative characteristics of the response of the measurement data indicating the formation characteristics to the formation changes, and the indicative characteristics of the response of the measurement data indicating the operating status of the drilling tool to the drilling tool behavior; Determining the effect of the measurement data response indicating the formation characteristics on the correction direction and correction amplitude of the set value according to the change trend thereof; determining, based on fluctuations in the response of the measurement data indicating the operating status of the drilling tool and changes in the response of the measurement data indicating formation characteristics, whether the fluctuations indicate behavior of the drilling tool itself; Based on the results of the action judgment of the measurement data response indicating the formation characteristics and the results of the fluctuation judgment of the measurement data response indicating the operating status of the drilling tool, the correction direction and correction amplitude of the set value are determined, and the set value is corrected according to the correction direction and correction amplitude.

6. The method for controlling exploration drilling parameters according to claim 5, characterized in that: The step of analyzing the characteristics of the measurement data indicating the formation characteristics in response to the formation changes, and the characteristics of the measurement data indicating the operating status of the drilling tool in response to the drilling tool behavior includes: By summarizing the response characteristics of measurement data under different formation conditions and drilling tool operation states in drilling data, a response feature library reflecting formation characteristics and drilling tool behavior is constructed; Comparing the real-time acquired measurement data responses indicating formation characteristics and the measurement data responses indicating the operating status of the drilling tool with features in the response feature library to analyze the indicative characteristics of the measurement data responses indicating formation characteristics with respect to formation changes, and the indicative characteristics of the measurement data responses indicating the operating status of the drilling tool with respect to drilling tool behavior; The response feature library is updated in combination with downhole environmental information acquired during the drilling process.

7. The method for controlling exploration drilling parameters according to claim 5, characterized in that: The step of determining whether the fluctuations indicated by the response of the measurement data indicating the operating status of the drilling tool, combined with the changes in the response of the measurement data indicating the formation characteristics, indicate the behavior of the drilling tool itself includes: identifying a specific feature present in the measurement data response indicative of the operational status of the drilling tool; identifying a characteristic of variation present in the measurement data response indicative of a formation property; Correlating and comparing the identified specific features of the measurement data response indicating the operating status of the drilling tool with the identified change features of the measurement data response indicating the formation characteristics to obtain a comparison result; Based on the comparison results, it is determined whether the fluctuations indicate the behavior of the drill tool itself, and it is clarified whether the fluctuations are caused by changes in the operating state of the drill tool itself or the evolution of formation conditions.

8. The method for controlling exploration drilling parameters according to claim 4, wherein: The step of performing performance deduction for each control strategy in the strategy options based on the current drilling state, wherein the performance deduction considers the evolution trend of the identified current formation characteristics and the identified current drilling tool operation state within a short period of time, and takes into account the fluctuation range of the multiple measurement data, to generate the deduction result includes: monitoring a drilling data stream, the drilling data stream including the plurality of measurement data and information reflecting current formation characteristics and current drilling tool operation status; Identifying, based on the monitored drilling data stream, the evolution trends of the identified current formation characteristics and the identified current drilling tool operating status within a short period of time, and identifying the fluctuation ranges of the multiple measurement data, to obtain the evolution trend information and the fluctuation range information; For each control strategy in the strategy options, performance deduction is performed based on the current drilling state and in accordance with the evolution trend information and the fluctuation range information to generate the deduction result.

9. The method for controlling exploration drilling parameters according to claim 8, characterized in that: The steps of identifying the evolution trend of the identified current formation characteristics and the identified current drilling tool operation status within a short period of time, and identifying the fluctuation range of the multiple measurement data include: Performing segmented analysis on the monitored drilling data stream, wherein the segmented analysis uses an adjustable time window; adjusting the length of the time window according to a data change rate or formation response characteristics reflected in the drilling data stream; Based on the results of the segmented analysis using the adjusted time window, the evolution trend of the identified current formation characteristics and the identified current drilling tool operation status in a short period of time is identified, and the fluctuation range of the multiple measurement data is identified to obtain the evolution trend information and the fluctuation range information.

10. An exploration drilling parameter control system, characterized in that: The system includes: a target setting module, configured to set a drilling target and a target priority corresponding to the drilling target, wherein the target priority indicates the importance of the drilling target; A data processing module, configured to obtain various measurement data during the drilling process and process the various measurement data; A state recognition module is used to identify the current formation characteristics and the current drilling tool operation status based on the processed multiple measurement data; A target adjustment module, configured to adjust the drilling target and the target priority according to geological information during the drilling process; a strategy determination module for determining a control strategy for drilling parameters based on the adjusted target priorities, the identified current formation characteristics, and the identified current drilling tool operating status, wherein the control strategy prioritizes between ensuring the quality of geological information acquisition, wellbore safety, and improving drilling efficiency based on the adjusted target priorities; A parameter calculation module, configured to calculate the set values ​​of the current drilling parameters and send the set values ​​to the drilling equipment; The parameter correction module is used to correct the set value according to the drilling response.

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