An automatic control system for underground drilling operations in coal mines

Abstract

The present invention relates to the field of drilling control technology, and discloses an automatic control system for underground drilling operations in coal mines. The system comprises: a data acquisition module for acquiring the gas concentration distribution of the drilling operation, as well as the drill bit pressure value and the drill bit position offset of the drilling rig; a trajectory generation module for simulating the predicted trajectory of the drilling rig based on the drill bit pressure value and the drill bit position offset; a correction module for correcting the predicted trajectory based on the gas concentration distribution to obtain a corrected drilling trajectory; an optimization module for inputting the parameters in the corrected drilling trajectory into a penalty optimization algorithm to obtain optimized trajectory parameters; and an adjustment module for dynamically adjusting the drilling trajectory of the drilling rig based on the optimized trajectory parameters. The present invention can solve the problem that the drilling operation system is difficult to adapt to the complex operating environment underground in coal mines.

Description

Technical Field

[0001] The present invention relates to the technical field of drilling control, in particular to an automatic control system for drilling operations in underground coal mines. Background Art

[0002] Traditional drilling systems struggle to accurately capture key data such as gas concentration distribution, drill bit pressure, and drill bit offset during actual operation. This makes it difficult to accurately simulate the drill's predicted trajectory, resulting in unreliable drilling trajectory planning and prone to deviations, impacting the efficiency and safety of drilling operations. Furthermore, they are unable to effectively correct the predicted trajectory based on gas concentration distribution, making it difficult to dynamically adjust the drill's trajectory and failing to adapt effectively to the complex operating environment of underground coal mines.

[0003] In addition, traditional systems are unable to accurately obtain the delay and conflict characteristics of the drilling rig in data processing and analysis, which in turn affects the acquisition of formation characteristic parameters and the compensation correction of the drilling trajectory. It is difficult to generate the optimal trajectory parameters, resulting in low control accuracy of the drilling rig's drilling trajectory, which cannot meet the needs of efficient and safe drilling operations in modern coal mines. Summary of the Invention

[0004] The present invention provides an automatic control system for drilling operations in underground coal mines, the main purpose of which is to solve the problem that the drilling operation system is difficult to adapt to the complex operating environment in underground coal mines.

[0005] To achieve the above-mentioned purpose, the present invention provides an automatic control system for underground drilling operations in coal mines, the system comprising:

[0006] Data acquisition module: used to obtain the gas concentration distribution of the drilling operation, as well as the drill bit pressure value and drill bit position offset of the drilling rig;

[0007] A trajectory generation module is configured to simulate a predicted trajectory of the drilling rig based on the drill bit pressure value and the drill bit position offset;

[0008] Correction module: used for correcting the predicted trajectory based on gas concentration distribution to obtain a corrected drilling trajectory;

[0009] Optimization module: used for inputting the parameters in the modified drilling trajectory into a preset penalty optimization algorithm to obtain optimized trajectory parameters;

[0010] Adjustment module: used for dynamically adjusting the drilling trajectory of the drilling rig based on the optimized trajectory parameters.

[0011] Preferably, the steps for obtaining the gas concentration distribution are as follows:

[0012] Gas data is collected based on the preset gas extraction monitoring device to obtain the gas concentration distribution.

[0013] Preferably, simulating the predicted trajectory of the drilling rig based on the drill bit pressure value and the drill bit position offset includes:

[0014] Performing a time-dependent misalignment analysis on the drill bit pressure value and the drill bit position offset to obtain a delayed conflict characteristic of the drilling rig;

[0015] Performing a fluctuation backtracking analysis on the geological energy state in the delayed conflict feature to obtain formation characteristic parameters;

[0016] Compensating and correcting the drilling trajectory of the drilling rig based on the oscillation frequency parameter in the formation characteristic parameter to obtain a drilling correction trajectory that resists formation rebound;

[0017] Comparing the real-time offset value of the drilling rig based on the historical offset mean of the drilling rig to obtain a cross-period trajectory correction value;

[0018] A historical interference analysis is performed on the drilling correction trajectory based on the cross-time period trajectory correction value to obtain a predicted trajectory.

[0019] Preferably, the correcting the predicted trajectory based on the gas concentration distribution to obtain a corrected drilling trajectory includes:

[0020] Performing spatial gradient vector alignment on the gas concentration distribution and the predicted trajectory to obtain a trajectory conflict area;

[0021] Scan the high-risk area of ​​gas leakage in the trajectory conflict area to obtain the concentration peak area,

[0022] Dividing the predicted trajectory into a gas adsorption gradient based on the concentration peak area to obtain a gas adsorption-free state conversion boundary;

[0023] performing curvature correction on the predicted trajectory based on the conversion boundary to obtain a trajectory unit for preventing gas focusing;

[0024] The wellbore annulus pressure parameter of the predicted trajectory is integrated to perform dynamic inertia verification on the revised trajectory to obtain a revised drilling trajectory in which gas and rock formations are mutually exclusive and balanced.

[0025] Preferably, inputting the parameters in the modified drilling trajectory into a penalty optimization algorithm to obtain optimized trajectory parameters comprises:

[0026] Extracting parameters of the modified drilling trajectory and adjusting the parameters based on mechanical constraints of the drilling rig to obtain optimized parameters;

[0027] Inputting the optimization parameters into a penalty optimization algorithm;

[0028] A penalty optimization process is performed to generate adjusted candidate parameters, from which the final optimized trajectory parameters are screened.

[0029] Preferably, the dynamically adjusting the drilling trajectory of the drilling rig based on the optimized trajectory parameters includes:

[0030] Extracting key control quantities of the optimized trajectory parameters to obtain trajectory adjustment reference data of the optimized trajectory parameters;

[0031] Performing execution signal synthesis on the trajectory adjustment reference data to obtain a driving instruction;

[0032] A safety margin check is performed on the corrected drilling trajectory based on the driving instruction and the drill bit pressure value to obtain a drilling trajectory.

[0033] Preferably, the calculation formula of the penalty optimization algorithm is:

[0034]

[0035] in: is the kth parameter vector to be optimized, To correct the parameters of the trajectory at point k, is the gas concentration gradient value at point k, is the parameter change vector of adjacent points, is the curvature upper threshold, k is the index of the trajectory point in the modified drilling trajectory, is the gradient sensitivity factor, is the adaptive load factor, is the dynamic risk weight, is the objective function, is the gas risk index penalty item.

[0036] Preferably, the optimization formula of the parameter vector to be optimized is:

[0037]

[0038] Where: t is the number of iterations, is the parameter to be optimized for the tth iteration and , is the objective function gradient, is the adaptive step size of the tth iteration.

[0039] Preferably, performing spatial gradient vector alignment on the gas concentration distribution and the predicted trajectory to obtain a trajectory conflict area includes:

[0040] Performing depth segment sampling on the predicted trajectory to obtain a discrete path point set of the predicted trajectory;

[0041] Perform gradient field calculation on the gas concentration distribution to obtain the gradient vector field of the gas concentration distribution:

[0042] performing drilling direction calculation on the discrete path point set to obtain a drilling course vector of the predicted trajectory;

[0043] Risk conflict detection is performed based on the gradient vector field and the drilling course vector to obtain a trajectory conflict area.

[0044] Preferably, performing a time-dependent misalignment analysis on the drill bit pressure value and the drill bit position offset to obtain a delayed conflict characteristic of the drilling rig includes:

[0045] Detecting a sudden change event of the drill bit pressure value at a first moment to obtain a pressure surge event with a time mark;

[0046] At a second moment, performing time series slicing on the drill bit position offset to obtain an offset variation curve associated with a pressure event;

[0047] detecting an abnormal descending section of the offset variation curve to obtain an abnormal pressure-offset response point;

[0048] A dynamic ratio calculation is performed on the pressure surge event and the abnormal response point to obtain a delay conflict feature.

[0049] Compared with the prior art, the present invention has the following beneficial effects:

[0050] 1. Acquire key data such as gas concentration distribution, drill bit pressure value, and position offset. By performing time-dependent dislocation analysis on the drill bit pressure value and position offset, combined with the fluctuation backtracking of the geological energy state, the formation characteristic parameters are obtained and the drilling trajectory is compensated and corrected. This effectively improves the accuracy of trajectory simulation, resists formation rebound, and provides a reliable trajectory foundation for subsequent drilling operations.

[0051] 2. In terms of trajectory optimization and safety control, the predicted trajectory is spatially aligned with gradient vectors and curvature corrected based on gas concentration distribution, which can divide the gas adsorption-free state conversion boundary and form a trajectory unit to prevent gas focusing. At the same time, the trajectory parameters are dynamically adjusted through the penalty optimization algorithm, and the wellbore annulus pressure parameters are integrated for dynamic inertia verification, realizing a corrected drilling trajectory with a mutual exclusion balance between gas and rock formations. This not only reduces the risk of gas leakage, but also improves the control accuracy of the drilling trajectory, ensuring the safety and reliability of the drilling rig's drilling trajectory, and can better adapt to the complex operating environment underground in coal mines, significantly improving the efficiency and safety of drilling operations. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1This is a functional module diagram of an automatic control system for underground drilling operations in a coal mine provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0053] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments belong to some embodiments of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0054] The terms used in the embodiments of the present invention are for the purpose of describing specific embodiments only and are not intended to limit the present invention. The singular forms "said" and "the" used in the embodiments of the present invention and the appended claims are also intended to include plural forms, unless the context clearly indicates otherwise, and "a plurality" generally includes at least two.

[0055] As used herein, the words “if” or “when” may be interpreted as “at the time of” or “when” or “in response to determining” or “in response to detecting,” depending on the context. Similarly, the phrases “if it is determined” or “if (stated condition or event) is detected” may be interpreted as “when it is determined” or “in response to the determination” or “when detecting (stated condition or event)” or “in response to detecting (stated condition or event),” depending on the context.

[0056] The embodiment of the present application provides an automatic control system for underground drilling operations in coal mines. The execution subject of the automatic control system for underground drilling operations in coal mines includes but is not limited to at least one of the electronic devices such as a server and a terminal that can be configured to execute the method provided by the embodiment of the present application. In other words, the automatic control system for underground drilling operations in coal mines can be executed by software or hardware installed on a terminal device or a server device. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, etc. The server can be an independent server, or it can be a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (CDNs), and big data and artificial intelligence platforms.

[0057] like Figure 1 FIG. 1 is a functional module diagram of an automatic control system for underground drilling operations in a coal mine according to the present invention.

[0058] The automatic control system 100 for underground coal mine drilling operations described in the present invention can be installed in an electronic device. Depending on the functionality implemented, the automatic control system 100 can include a data acquisition module 101, a trajectory generation module 102, a correction module 103, an optimization module 104, and an adjustment module 105. A module, also referred to as a unit, is a series of computer program segments that can be executed by an electronic device processor and perform a fixed function. These modules are stored in the electronic device's memory.

[0059] In this embodiment, the functions of each module / unit are as follows:

[0060] Data acquisition module: obtains the gas concentration distribution of the drilling operation, as well as the drill bit pressure value and drill bit position offset of the drilling rig.

[0061] In this embodiment, the steps for obtaining the gas concentration distribution are as follows:

[0062] Gas data is collected based on the preset gas extraction monitoring device to obtain the gas concentration distribution.

[0063] Specifically, the preset gas extraction monitoring device is used to collect gas data of the underground drilling operation area of ​​the coal mine in real time, and the pressure value and position offset of the drilling rig drill bit are obtained respectively using the pressure sensor and the position sensor.

[0064] Specifically, gas concentrations at different locations around a borehole in a coal mine reflect the distribution of gas within the coal seam. In the complex physical environment underground, gas can be unevenly distributed due to factors such as coal seam permeability and geological structure. For example, gas concentrations may be higher near faults or in areas with developed coal seam fractures.

[0065] Specifically, the drill bit is subjected to resistance pressure from coal seams, rock formations, etc. during the drilling process. This pressure is affected by physical factors such as rock hardness and rock formation inclination. For example, the pressure will increase significantly when drilling into hard rock formations.

[0066] Specifically, the deviation between the actual drilling position of the drill bit and the preset trajectory position. The undulation of the underground geological structure and the hardness and softness of the coal seam can cause the drill bit to deviate during drilling. For example, when encountering a soft coal seam, the drill bit may deviate to the direction of less resistance.

[0067] Furthermore, to obtain the gas concentration distribution, we rely on the preset gas extraction monitoring device to continuously collect gas data, such as sensing the concentration of gas molecules through gas sensors, and then through data transmission and processing, sort out the gas concentrations at different locations and construct a distribution situation.

[0068] To obtain the drill bit pressure value, a pressure sensor installed on the drill bit or related parts of the drill pipe is used to detect the pressure signal during drilling in real time, convert the mechanical signal into an electrical signal or other identifiable signal, and transmit it to the control system.

[0069] Trajectory generation module: simulates the predicted trajectory of the drilling rig based on the drill bit pressure value and the drill bit position offset.

[0070] In this embodiment, simulating the predicted trajectory of the drilling rig based on the drill bit pressure value and the drill bit position offset includes:

[0071] Performing a time-dependent misalignment analysis on the drill bit pressure value and the drill bit position offset to obtain a delayed conflict characteristic of the drilling rig;

[0072] Performing a fluctuation backtracking analysis on the geological energy state in the delayed conflict feature to obtain formation characteristic parameters;

[0073] Compensating and correcting the drilling trajectory of the drilling rig based on the oscillation frequency parameter in the formation characteristic parameter to obtain a drilling correction trajectory that resists formation rebound;

[0074] Comparing the real-time offset value of the drilling rig based on the historical offset mean of the drilling rig to obtain a cross-period trajectory correction value;

[0075] A historical interference analysis is performed on the drilling correction trajectory based on the cross-time period trajectory correction value to obtain a predicted trajectory.

[0076] Specifically, the delay conflict feature is a feature generated by the mismatch in time between the pressure signal change and the position offset, and their mutual influence.

[0077] For example, when the drill bit encounters a hard rock layer, the pressure signal suddenly changes first, but the position offset is delayed due to the elastic deformation of the drill pipe. The time difference and change amplitude difference between the two constitute the delay conflict characteristics, reflecting the complex relationship between geological action and drilling rig response.

[0078] Furthermore, the drill bit's real-time pressure signals and position offsets are collected and organized into time series. Signal processing algorithms are then used to compare the moments of pressure signal changes with the moments of position offsets, analyzing their temporal misalignment. The correlation between the magnitude of the pressure change and the offset is calculated, allowing for the identification of delay conflict characteristics. For example, this analysis identifies patterns such as how long after a sudden pressure change, position offsets occur, and at what offsets does the pressure reverse course.

[0079] Specifically, the geological energy state refers to the energy contained in the underground strata due to rock stress and gas pressure. Rock strata, squeezed by geological structures, possess elastic strain energy, while gas-bearing areas possess internal gas energy. This energy is released when drilling disrupts equilibrium, manifesting itself in delayed conflict characteristics. For example, the high energy in hard rock formations can lead to a more pronounced conflict between pressure signals and position offsets.

[0080] Specifically, formation characteristic parameters describe the physical and mechanical properties of the formation, such as its elastic modulus, gas content, and inclination. By backtracking energy fluctuations, these inherent properties of the formation can be inferred, providing a basis for subsequent trajectory corrections.

[0081] Furthermore, based on the delayed conflict characteristics, data related to energy changes are extracted, geological energy is analyzed, and the energy generation, accumulation, and release processes are traced back. Combined with the coal mine underground geological database (including rock formation mechanical parameters and gas storage data during regional geological exploration), the formation characteristic parameters are inverted and calculated.

[0082] For example, the elastic modulus of the rock formation can be calculated based on the frequency and amplitude of the pressure signal fluctuations, and the effect of gas content on drilling can be analyzed based on the law of the influence of position offset, thereby determining the characteristic parameters of the formation.

[0083] Specifically, the oscillation frequency parameter is the vibration frequency generated by the energy fluctuations of the formation and the drilling rig. Different formations (such as sandstone, coal seams, and mudstone) have different elasticity and stiffness, resulting in different oscillation frequencies during drilling. Hard rock formations have a high oscillation frequency, while soft coal seams have a relatively low oscillation frequency. This parameter reflects the formation's reaction rhythm to drilling.

[0084] Specifically, the drilling correction trajectory that resists formation rebound takes into account the rebound force generated by the formation due to energy release (such as rock formation elastic recovery force and gas pressure recoil force). After correcting the original trajectory, it can resist the rebound effect and ensure a stable drilling trajectory.

[0085] Furthermore, the oscillation frequency parameters in the formation characteristic parameters are extracted by combining the natural frequency of the drilling system of the drilling rig to analyze the impact of the oscillation frequency on the drilling trajectory. For example, high-frequency oscillation can easily cause the drill bit to deviate, and the direction and amplitude that need to be compensated are calculated.

[0086] The control system sends instructions to the drilling rig's actuators, such as the drill rod adjustment hydraulic device and the drill rig's guide mechanism, to adjust drilling parameters such as drilling speed, feed pressure, and drill rod posture, and correct the drilling trajectory so that it can resist the formation rebound force and maintain stable drilling.

[0087] Specifically, the historical mean offset is the average amount of drill bit position offset in similar geological conditions and drilling operations. It reflects the average offset pattern caused by factors such as the formation and rig performance in the area over a long period of operation and is based on historical experience.

[0088] The real-time offset value is the offset value of the actual position of the drill bit relative to the preset trajectory at the current drilling moment, reflecting the deviation of the current drilling.

[0089] The cross-period trajectory correction value is calculated by comparing historical and real-time offset data, taking into account changes in the formation in different periods, differences in the drilling rig status, etc., and the value used to correct the trajectory can take into account both historical laws and current actual conditions.

[0090] Furthermore, historical drilling data of the drilling rig in the same or similar operating area in the coal mine is retrieved from the system database, and the historical mean of the drill position offset is statistically calculated.

[0091] The current drill bit position offset value is collected in real time, compared with the two, and the differences are analyzed. For example, if the current offset value is larger than the historical average, it is explored whether it is a local change in the formation, such as a small fault, or a temporary failure of the drilling rig, such as a loose actuator.

[0092] Based on the cause and extent of the difference, calculate the trajectory correction value across time periods. If it is due to gradual changes in the strata, adjust the correction amplitude according to the trend; if it is due to temporary interference, make targeted compensation corrections.

[0093] Specifically, the cross-period trajectory correction value is a calculated value used to correct the trajectory across time periods, which contains comprehensive adjustment information for historical patterns and current deviations.

[0094] Specifically, historical interference analysis is to analyze the impact patterns and laws of various interference factors on the trajectory in past drilling operations, such as sudden changes in the formation and wear of drilling rig components, to determine whether these interferences exist in the current operation and the extent of their impact.

[0095] Specifically, the predicted trajectory is a simulated trajectory of the drilling rig's subsequent drilling, taking into account the current drilling status, formation characteristics, historical interference patterns, etc., and is used to guide drilling operation control in advance.

[0096] Furthermore, combined with the cross-time trajectory correction value, the interference events and corresponding trajectory change data encountered in historical drilling operations are retrieved, such as the record of a significant trajectory deviation due to abnormal gas outburst. The geological environment parameters of the current operation are compared with the parameters when the historical interference occurred to determine whether there is a similar interference risk.

[0097] Based on the analysis results, the drilling correction trajectory is adjusted. If there is a possibility of historical interference recurring, the trajectory direction and drilling parameters are corrected in advance, such as increasing trajectory curvature compensation and adjusting drilling pressure. Finally, a predicted trajectory is simulated for the automatic control system to control the drilling rig based on it.

[0098] In this embodiment, the time-dependent misalignment analysis of the drill bit pressure value and the drill bit position offset is performed to obtain the delayed conflict characteristics of the drilling rig, including:

[0099] Detecting a sudden change event of the drill bit pressure value at a first moment to obtain a pressure surge event with a time mark;

[0100] At a second moment, performing time series slicing on the drill bit position offset to obtain an offset variation curve associated with a pressure event;

[0101] detecting an abnormal descending section of the offset variation curve to obtain an abnormal pressure-offset response point;

[0102] A dynamic ratio calculation is performed on the pressure surge event and the abnormal response point to obtain a delay conflict feature.

[0103] Specifically, a sudden change is a situation where the pressure signal changes significantly in a short period of time, such as an instantaneous increase of several times. Underground geology is complex, such as when the drill bit enters a hard rock layer from a soft coal seam, the pressure may suddenly increase.

[0104] The time stamp records the precise moment when the pressure surge event occurs and is used for subsequent temporal correlation with position offsets. Underground coal mine operations require precise time stamps to ensure data correspondence. Because the drilling process is dynamic and the environment is complex, time deviations can affect analysis accuracy.

[0105] A pressure surge event is a rapid increase in pressure that marks the time of occurrence. It is the basic data for subsequent analysis of the interaction between the drilling rig and the formation, reflecting the change in the instantaneous strong resistance of the formation to the drill bit.

[0106] Furthermore, underground in coal mines, pressure sensors continuously collect drill bit pressure data and transmit it to the control system in real time. The system continuously monitors pressure signals. When the pressure value is detected to exceed the normal fluctuation range within a very short period of time (e.g., milliseconds), the system detects that the pressure value exceeds the normal fluctuation range (pre-set based on historical operation data and coal seam characteristics). For example, when drilling in a soft coal seam, the pressure fluctuation is ±2 MPa. If it exceeds this range, it is considered a sudden change. A pressure sudden change event is detected and the precise time is recorded. Using a high-precision underground clock to ensure accurate time in complex electromagnetic environments and other interference, the system generates time-stamped pressure surge event data and stores it in the system for subsequent analysis.

[0107] Specifically, the second moment is the time interval associated with the pressure surge event, encompassing the period before and after the pressure surge. This moment is used to capture position offset data for that time period. Downhole drilling is a continuous process, so it's important to select an appropriate time period around the pressure surge to comprehensively analyze the position change response. For example, selecting from one second before to three seconds after the pressure surge covers both the formation impact before the surge and the drilling rig adjustments afterward.

[0108] Specifically, time series slicing is to extract segments from the continuous position offset time series data according to specific time intervals, focusing on the data during the period related to the pressure surge event, so as to facilitate the analysis of the impact of pressure changes on position.

[0109] Specifically, the offset curve associated with a pressure event plots the position offset over time before and after a pressure surge event, with time on the horizontal axis and position offset on the vertical axis. This provides a visual representation of how a sudden pressure surge affects the drill bit's position. For example, after a pressure surge, does the offset increase rapidly or fluctuate? This indicates how the formation interferes with the drill bit's trajectory.

[0110] Furthermore, the system determines the time interval of the second moment based on the time mark of the pressure surge event. For example, if the pressure surge moment is T0, the second moment is set to T0-Δt to T0+Δt. Δt is set according to the downhole drilling speed and data analysis requirements. If the drilling speed is 1 meter / minute, Δt can be set to 1 second to analyze the short-term response, or set to 10 seconds to cover a longer adjustment process.

[0111] From the continuous time series data of position offset, the data in this interval is intercepted, sorted and interpolated, and a curve with time as the horizontal axis and position offset as the vertical axis is drawn, that is, the offset change curve associated with the pressure event, which is used to observe the dynamic process of position offset after the pressure mutation.

[0112] Specifically, the abnormal decline section is the part of the curve where the offset decreases unexpectedly quickly. During normal drilling, the position offset changes regularly with the geological and drilling parameters. The abnormal decline section may be caused by special effects of the formation, such as sudden breakage of coal rock and instantaneous rebound of the drilling rig. In the complex underground environment, formation stress release and elastic deformation of the drill pipe may also cause it.

[0113] Specifically, the abnormal response point of pressure-offset is the correlation point of pressure and position offset corresponding to the abnormal decline section. It marks the key moment and value of the abnormal change of position offset after the pressure mutation, reflects the abnormal state of interaction between the formation and the drilling rig, and is an important basis for identifying drilling risks.

[0114] Furthermore, the offset change curve is scanned segment by segment. A threshold range for normal offset change is set based on historical normal drilling data and combined with downhole geological conditions. For example, during normal drilling, the offset change rate should not exceed 0.5 mm / ms; exceeding this is considered abnormal.

[0115] Specifically, when it is detected that the offset change rate of a certain section in the curve is less than the normal range and lasts for a certain period of time, such as 5 consecutive data points, it is determined to be an abnormal decline section because the downhole data is noisy and accidental fluctuations need to be excluded.

[0116] Specifically, determine the start and end times of the abnormal drop segment, extract the pressure values ​​at the corresponding times, associate the pressure surge event data and the position offset value, mark it as the abnormal response point of pressure-offset, and record its time, pressure, offset and other parameters for subsequent analysis.

[0117] Specifically, the abnormal response point is an abnormal correlation point marked with pressure, position offset and time, including the pressure value, offset and corresponding time at the time of the abnormality.

[0118] Dynamic ratio calculation takes into account dynamic changes over time and calculates the ratio of parameters related to pressure surge to parameters of abnormal response points. Parameters at different times are involved in the calculation, reflecting the dynamic relationship between the interaction between pressure and position offset. Because the downhole drilling process is dynamic, formation feedback and drilling rig response change over time. Dynamic calculation can accurately capture this relationship.

[0119] Specifically, the delayed conflict feature is obtained through dynamic ratio calculation, which reflects the conflict relationship between the pressure surge event and the position offset abnormal response in time and value, and reflects the delay and complexity of the effect of the formation on the drill bit. For example, after the pressure surge, the delay time of the position offset abnormal response and the degree of mismatch between the change amplitudes of the two can be used to judge the stability of the formation, the adaptability of the drilling rig and the formation, etc., and provide a basis for subsequent trajectory correction and drilling parameter adjustment.

[0120] Furthermore, the system extracts parameters of the pressure surge event, such as the pressure surge moment T1, the pressure before the surge P1, and the pressure after the surge P2, and calculates the pressure change ΔP=P2-P1 and the pressure change rate Vp=ΔP / (T2-T1).

[0121] The steps for extracting the parameters of the abnormal response point are: the time of the abnormality T3, the offset before the abnormality S1, the offset after the abnormality S2, and the calculation of the offset change ΔS = S2-S1 and the offset change rate Vs = ΔS / (T4-T3), where T4 is the time when the offset stabilizes. Dynamic ratio calculations are then performed, such as the ratio of ΔP to ΔS and the ratio of Vp to Vs at different times. Over time, a series of dynamic ratio data is obtained.

[0122] Specifically, feature extraction is performed on these data, such as the maximum value, minimum value, and fluctuation amplitude of the statistical ratio, to sort out the features that can reflect the conflict and delay relationship between pressure and position offset, namely the delay conflict features, which serve as the basic basis for subsequent simulation of drilling rig trajectory prediction and adjustment of drilling control.

[0123] Correction module: corrects the predicted trajectory based on the gas concentration distribution to obtain a corrected drilling trajectory.

[0124] In this embodiment, the predicted trajectory is corrected based on the gas concentration distribution to obtain a corrected drilling trajectory, including:

[0125] Performing spatial gradient vector alignment on the gas concentration distribution and the predicted trajectory to obtain a trajectory conflict area;

[0126] Scan the high-risk area of ​​gas leakage in the trajectory conflict area to obtain the concentration peak area,

[0127] Dividing the predicted trajectory into a gas adsorption gradient based on the concentration peak area to obtain a gas adsorption-free state conversion boundary;

[0128] performing curvature correction on the predicted trajectory based on the conversion boundary to obtain a trajectory unit for preventing gas focusing;

[0129] The wellbore annulus pressure parameter of the predicted trajectory is integrated to perform dynamic inertia verification on the revised trajectory to obtain a revised drilling trajectory in which gas and rock formations are mutually exclusive and balanced.

[0130] Specifically, gas concentration distribution refers to the distribution of gas concentration values ​​at different spatial locations, three-dimensional coordinates: x, y, z, corresponding to the direction of the underground tunnel, the direction perpendicular to the tunnel, and the depth direction within the underground drilling operation area of ​​a coal mine.

[0131] Affected by the permeability of coal seams, geological structure, and gas storage conditions, gas concentration is unevenly distributed in space. For example, the gas concentration may be higher near faults.

[0132] The predicted trajectory is the path of the drill bit drilling in the coal seam / rock layer, which is pre-simulated and calculated based on the drilling parameters of the drill rig, geological exploration data, etc. It is presented in the form of a spatial coordinate sequence, such as recording a three-dimensional coordinate point at a certain distance, reflecting the extension direction of the drill hole under ideal conditions.

[0133] The spatial gradient vector is a vector representation of the rate of change and direction of change of gas concentration in space, reflecting the trend and rate of gas concentration diffusion from high-value areas to low-value areas.

[0134] Trajectory conflict areas are areas where the spatial gradient vector of the gas concentration distribution interferes with the spatial direction vector of the predicted trajectory, potentially posing a gas safety risk. Trajectory conflict areas are identified when a predicted trajectory passes through an area with a sharp change in gas concentration gradient and a small angle between the gradient vector and the trajectory direction, indicating that gas is likely to flow and accumulate along the trajectory.

[0135] Furthermore, within the physical environment of a coal mine, a network of gas sensors deployed underground first collects gas concentration data at different spatial locations to construct a three-dimensional data field of the gas concentration distribution. Then, based on the drilling parameters of the drill rig and the initial geological model, a spatial coordinate sequence of the predicted trajectory is calculated. The spatial gradient vector of the gas concentration distribution and the strike vector of the predicted trajectory are aligned, calculating the direction and magnitude of the gas concentration gradient vector for each trajectory point. By determining the angle between the gradient vector and the trajectory strike vector, and the relationship between the gradient amplitude and the trajectory safety threshold, conflicting trajectory areas are identified and their extent within the underground space is marked.

[0136] Specifically, high-risk areas for gas leakage are those within trajectory conflict zones where gas concentration gradients are high and coal / rock seam fissures exist, making gas susceptible to leakage into the drilling area. These areas have a high rate of gas concentration change and a high degree of fissure development, making them potential triggers for gas accidents.

[0137] Specifically, a concentration peak area is a localized high-value region in the gas concentration distribution. This refers to a point where the gas concentration is significantly higher than that of the surrounding area, and a certain range around it. This region is typically a spherical or cylindrical area with a certain radius, centered on the peak point. The radius is determined by the gas diffusion range and the downhole spatial scale. These areas are typically located at the intersection of fractures and in gas-rich zones, and are the source of gas leakage.

[0138] Furthermore, the control system uses gas concentration distribution data and geological structure data for the trajectory conflict area. In the underground physical environment, grid-based regional scanning divides the trajectory conflict area into small grid cells, adapting to the complex spatial structure of the underground well. The gas concentration gradient and fracture development within each grid cell are indirectly judged through pressure fluctuations during drilling and the morphology of returned slag particles. When the gas concentration gradient within a grid cell exceeds the set high-risk threshold and suspected fracture channel characteristics are detected, it is determined to be a high-risk area for gas leakage.

[0139] In high-risk areas, find the local maximum point of gas concentration, that is, the concentration peak point. With the peak point as the center, expand outward to a certain range. According to the diffusion radius of gas in the coal seam, combined with the gas pressure, temperature and other conditions underground, calculate and determine the concentration peak point area, and mark its spatial coordinate range.

[0140] Specifically, the gas adsorption gradient is the concentration gradient of gas in coal / rock formations as it transitions from an adsorbed state to a free state. This gradient reflects the spatial variation of gas from adsorption to release, and is related to the pore structure, specific surface area, and gas pressure of the coal.

[0141] The gas adsorption-free transition boundary is the spatial interface where gas transitions from being primarily adsorbed to being primarily free. The gas's presence and migration characteristics change significantly on both sides of the boundary, making it a key interface for controlling gas flow and accumulation.

[0142] Furthermore, first, based on the gas concentration data in the concentration peak area, combined with the physical parameters of the coal rock, such as the porosity and specific surface area of ​​the coal, through preliminary laboratory analysis or rapid measurement by portable underground detectors, a gas adsorption-desorption theoretical model, such as the Langmuir adsorption model, is used to adapt to the gas adsorption characteristics of underground coal seams and calculate the spatial distribution gradient of the gas adsorption degree.

[0143] In underground coal mine environments, starting from the concentration peak area, the change in gas adsorption is calculated segment by segment along the extension direction of the predicted trajectory. When the rate of change in gas adsorption reaches a certain threshold, the location is marked as a transition boundary point.

[0144] Specifically, all conversion boundary points are connected to form the conversion boundary of gas adsorption-free state, and its three-dimensional shape in the downhole space is determined to provide boundary conditions for trajectory correction.

[0145] Specifically, curvature correction adjusts the curvature of the predicted trajectory, directing it around or avoiding high-risk areas near the gas adsorption-free transition boundary. Curvature is a parameter that describes the curvature of the trajectory. It is mathematically calculated using the second-order derivative of the trajectory coordinates. The greater the curvature, the more pronounced the trajectory curvature.

[0146] The anti-gas focus trajectory unit, with curvature correction, prevents gas from focusing and accumulating around the borehole. For example, it prevents free gas from accumulating at bends in the trajectory due to flow obstruction. The unit's trajectory design fully considers the migration characteristics of gas, ensuring that gas does not accumulate during drilling operations due to improper trajectory, potentially posing a risk.

[0147] Furthermore, the control system acquires the spatial coordinate data of the transition boundary between the adsorbed and free gas states and analyzes the spatial relationship between the transition boundary and the predicted trajectory. Under the physical constraints of downhole drilling operations, such as the drill rig's minimum turning radius and the drill pipe's flexibility, the drill rig cannot bend indefinitely when adjusting its trajectory in the downhole space due to its mechanical structure and drill pipe strength. Therefore, a trajectory optimization algorithm is used to calculate the trajectory curvature that needs to be corrected.

[0148] Specifically, if the predicted trajectory passes through a high-risk area near the conversion boundary, such as an area where free gas is prone to accumulate, the curvature of the trajectory is increased so that the trajectory bypasses the area; if the trajectory is close to the conversion boundary but does not enter the high-risk area, the curvature is fine-tuned to maintain a safe distance from the conversion boundary. The safe distance is determined based on the gas explosion limit, gas pressure, etc. to ensure that even if there is a gas leak, it will not reach a dangerous concentration around the borehole.

[0149] The curvature of the predicted trajectory is corrected section by section, and the corrected trajectory is divided into multiple trajectory units. The curvature of each unit meets the requirements for preventing gas focusing. The spatial coordinates and curvature parameters of each trajectory unit are marked to form a trajectory unit sequence for preventing gas focusing.

[0150] Specifically, the annular pressure parameter refers to the fluid pressure within the annular space between the drill pipe and the borehole wall within the wellbore. It includes the combined pressure values ​​of mud pressure, gas pressure, and formation pore pressure. Influenced by factors such as mud circulation, gas leakage, and formation stress release during drilling, it is a key parameter reflecting the interaction between the borehole, the surrounding rock formation, and gas.

[0151] Specifically, dynamic inertia verification considers the dynamics of the drilling process, such as changes in drilling speed and gas pressure fluctuations, to verify the mechanical stability of the corrected trajectory. By simulating the inertial motion of the trajectory under dynamic pressure, such as the vibration and deviation of the drill pipe caused by pressure fluctuations, the system determines whether the trajectory will deviate from the design due to pressure fluctuations, thereby ensuring trajectory stability.

[0152] Specifically, the corrected drilling trajectory of the mutually exclusive balance between gas and rock formations is the final drilling trajectory, which not only meets the gas safety requirements, such as avoiding gas focusing and leakage, but also adapts to the mechanical properties of the rock formation, such as avoiding the trajectory passing through the rock fracture zone and causing collapse, achieving a balance between gas and rock formations in spatial distribution and mechanical action, and ensuring safe and efficient drilling operations.

[0153] Furthermore, firstly, the wellbore annulus pressure parameters, including pressure value, pressure fluctuation frequency, pressure change rate, etc., are collected in real time through the pressure sensor installed between the drill pipe and the hole wall.

[0154] The modified trajectory is then subjected to dynamic inertia verification, combining its spatial morphological parameters, such as curvature, strike, and depth. The drill pipe and trajectory are simulated under varying wellbore annular pressure fluctuations. When annular pressure suddenly increases, the trajectory is calculated to determine whether the pressure pushes on the drill pipe and deflects. When pressure fluctuations redistribute formation stress, the trajectory is determined to determine whether it will enter the rock fracture zone.

[0155] Based on the verification results, the parameters of the corrected trajectory are fine-tuned again to ensure that the trajectory can not only allow the gas to be discharged smoothly but also ensure the stability of the rock formation under a dynamic pressure environment. Ultimately, a corrected drilling trajectory with a mutually exclusive balance between gas and rock formation is obtained, which serves as the basis for the drilling rig to automatically control drilling.

[0156] In this embodiment, the spatial gradient vector alignment of the gas concentration distribution and the predicted trajectory to obtain the trajectory conflict area includes:

[0157] Performing depth segment sampling on the predicted trajectory to obtain a discrete path point set of the predicted trajectory;

[0158] Perform gradient field calculation on the gas concentration distribution to obtain the gradient vector field of the gas concentration distribution:

[0159] performing drilling direction calculation on the discrete path point set to obtain a drilling course vector of the predicted trajectory;

[0160] Risk conflict detection is performed based on the gradient vector field and the drilling course vector to obtain a trajectory conflict area.

[0161] Specifically, depth segment sampling is the process of selecting discrete points from the predicted trajectory at fixed or adaptive intervals along the borehole depth. Due to the large borehole depth, continuous trajectories are difficult to directly calculate and analyze, requiring discretization.

[0162] The discrete path point set is a series of discrete spatial point coordinate sets obtained after depth segment sampling. Each point contains the three-dimensional coordinates of the well, representing the key nodes of the predicted trajectory at different depths, and is the basic data for subsequent calculations and analysis.

[0163] Furthermore, within the physical environment of a coal mine, the control system initiates a segmented depth sampling process based on the preset predicted trajectory data. The sampling interval is set, taking into account the depth-dependent characteristics of the borehole. Starting from the predicted trajectory's starting point, the coordinates of points along the trajectory are extracted at set intervals along the depth direction. The 3D coordinate values ​​of each point are recorded to form a discrete path point set.

[0164] For example, the predicted trajectory is a curve extending from the tunnel floor (Z=0) to the deep coal seam with an inclination of 30°. The sampling interval is set to 1m. The coordinates of the trajectory points at Z=1m, Z=2m... are extracted in sequence to form a discrete path point set, which is suitable for the underground drilling and segmented control operation mode.

[0165] Specifically, gradient field calculation is the process of using mathematical gradient operations, such as taking partial derivatives of the gas concentration distribution function, to calculate the rate of change and direction of change of gas concentration at each point in space.

[0166] Gradient is a vector that contains magnitude and direction. The gradient field is the collection of gradient vectors at all points, reflecting the spatial variation trend of gas concentration. Underground gas is affected by the permeability of the coal seam and geological structure, and the gradient field presents a complex distribution. For example, the gradient is large near the fault zone.

[0167] Specifically, the gradient vector field is a field composed of the gas concentration gradient vectors at each point in space. It describes the change pattern of gas concentration in three-dimensional space and is an important basis for subsequent analysis of gas flow and judgment of drilling risks. Each vector in the vector field corresponds to the gas concentration change characteristics of a spatial point.

[0168] Furthermore, the underground gas concentration distribution data is obtained by real-time transmission of the gas sensor or calling historical stored data. The data needs to be preprocessed, such as filtering to remove noise. Due to the high interference of the underground environment and the fluctuation of the sensor data, the gradient field calculation module is started.

[0169] Based on the spatially discretized gas concentration data, the underground space is divided into grids. Each grid node corresponds to a gas concentration value. Numerical differentiation methods, such as the finite difference method, are used to calculate the ratio of the concentration difference and distance between adjacent grid nodes, and the gas concentration gradient vector of each grid node is calculated.

[0170] Specifically, for the complex spatial morphology of underground coal mines, it is necessary to perform spatial interpolation and correction on the gradient calculation results to ensure that the gradient vector field is continuous and accurate.

[0171] For example, in areas with sparse gas sensors, the concentration data is supplemented by the Kriging interpolation method and then the gradient is calculated to obtain a gas concentration gradient vector field covering the entire drilling operation area, clearly showing the changing trend of gas concentration in the underground space and providing a basis for subsequent risk analysis.

[0172] Specifically, drilling direction solution is the process of calculating the borehole extension direction between adjacent points based on a discrete path point set. By solving the difference vector between the coordinates of two points, the borehole's strike and inclination in space are determined, reflecting the desired change in drilling direction of the drill bit. Downhole drilling requires strict direction control to accurately hit the target layer.

[0173] Specifically, the drilling process vector is a vector that describes the drilling direction and distance between adjacent discrete points on the predicted trajectory. It contains direction information and length information and is a key parameter to characterize the extension characteristics of the drilling trajectory. It is used for subsequent interactive analysis with the gas gradient field.

[0174] Furthermore, the control system accesses the discrete pathpoint set data, selects two adjacent points in depth order, and calculates their coordinate difference. This coordinate difference is then converted into a drilling travel vector. The direction of the vector, represented by a unit vector, reflects the drilling direction of the borehole in that section; the length of the vector represents the drilling distance. This operation is repeated for each pair of adjacent points in the discrete pathpoint set, resulting in a series of drilling travel vectors that fully describe the predicted trajectory extension direction and travel changes. This allows the downhole driller to control the drilling direction by section, such as by adjusting the drill pipe angle to achieve vector-directed drilling.

[0175] Specifically, risk conflict detection analyzes the interaction between the drilling trajectory vector and the gas concentration gradient vector to determine whether there are gas safety risks. For example, if the drilling trajectory passes through an area with a large gas concentration gradient, it could cause gas outbursts and leaks, making the drilling operation dangerous. Risk areas are identified by calculating the angle between the vectors, the gradient amplitude, and the relationship between the stroke.

[0176] Specifically, the trajectory conflict area is the area on the predicted trajectory where the drilling process vector and the gas concentration gradient vector interact with each other, posing a gas safety risk. For example, if the angle between the gas concentration gradient direction and the drilling direction is too small, gas is likely to accumulate along the borehole; if the gradient amplitude is too large and exceeds the safety threshold, the trajectory of these areas needs to be corrected to ensure the safety of underground drilling operations.

[0177] Furthermore, the control system imports the gradient vector field and drilling process vector data into the risk conflict detection module. For each discrete path point on the predicted trajectory corresponding to the drilling process vector, the gas concentration gradient vector at the spatial location of the vector is extracted.

[0178] Then, calculate the angle between the two vectors, such as using the dot product formula: cosθ=(V・G) / (|V||G|), where V is the drilling process vector and G is the gradient vector. Determine whether the angle is too small. For example, if it is less than 30°, gas tends to flow and accumulate along the drilling direction.

[0179] Specifically, the gradient vector amplitude is checked to see if it exceeds a safety threshold, such as greater than 0.3% CH4 / m, which could trigger a potential outburst risk. If the drilling process vector and the gradient vector meet the conditions of too small an angle and the gradient amplitude exceeding the limit, the trajectory segment corresponding to the drilling process is marked as a risk conflict area.

[0180] Specifically, after detecting all drilling process vectors, continuous risk sections are integrated to obtain a complete trajectory conflict area, providing a clear spatial range for subsequent trajectory corrections and ensuring that underground drilling operations avoid high-risk gas environments.

[0181] Optimization module: inputs the parameters in the modified drilling trajectory into the penalty optimization algorithm to obtain the optimized trajectory parameters.

[0182] In this embodiment, the inputting of the parameters in the modified drilling trajectory into the penalty optimization algorithm to obtain the optimized trajectory parameters includes:

[0183] Extracting parameters of the modified drilling trajectory and adjusting the parameters based on mechanical constraints of the drilling rig to obtain optimized parameters;

[0184] Inputting the optimization parameters into a penalty optimization algorithm;

[0185] A penalty optimization process is performed to generate adjusted candidate parameters, from which final optimized trajectory parameters are screened.

[0186] Specifically, the parameters for correcting the drilling trajectory are the relevant parameters of the drilling trajectory after steps such as gas concentration distribution correction, including the spatial coordinate sequence of the trajectory, the curvature of the trajectory, the drilling inclination, the drilling azimuth, etc. These parameters reflect the spatial form of the drilling trajectory and are the basic data for subsequent optimization.

[0187] Specifically, the mechanical constraints of the drilling rig are the physical performance limitations of the underground coal mine drilling rig itself, such as the maximum drilling torque, maximum feed pressure, minimum turning radius, etc. These constraints determine the range of drilling trajectories that the drilling rig can actually achieve and must be followed during optimization.

[0188] Specifically, the optimization parameters are obtained by adjusting the modified drilling trajectory parameters under the premise of satisfying the mechanical constraints of the drilling rig, so that the drilling trajectory not only meets the geological and gas safety requirements, but can also be actually executed by the drilling rig. It is a bridge connecting the theoretical trajectory and actual drilling, ensuring that the trajectory can be constructed underground.

[0189] Furthermore, in the physical environment of an underground coal mine, the control system first extracts trajectory parameters such as coordinates, curvature, inclination, and azimuth from the corrected drilling trajectory data file. It then retrieves the drilling rig's mechanical constraint parameters, such as maximum torque, maximum feed pressure, and minimum turning radius.

[0190] Furthermore, if the trajectory curvature exceeds the drill rig's minimum turning radius, the curvature is reduced to within the constraints. If the feed pressure corresponding to the drilling inclination exceeds the drill rig's maximum feed pressure, the inclination is adjusted to meet the pressure requirement. Trajectory parameters are individually verified and optimized to obtain optimized parameters that meet the drill rig's mechanical constraints. This sets the optimized parameters and provides input for the subsequent penalty optimization algorithm. This ensures that the optimized trajectory can be executed by the drill rig during actual drilling, avoiding equipment damage or drilling failure due to exceeding mechanical performance.

[0191] Specifically, the optimized trajectory parameters are calculated using a penalty optimization algorithm to obtain the optimal comprehensive drilling trajectory parameters, which not only meet the mechanical constraints of the drilling rig, but also achieve the optimal balance in terms of gas extraction effect, construction efficiency, and safety risks. These are the final trajectory parameters that guide the automatic drilling of the downhole drilling rig.

[0192] Furthermore, the optimization parameters are used as input to initialize the objective function and constraints of the penalty optimization algorithm. The objective function comprehensively considers multiple objectives of downhole drilling operations, such as minimizing the distance between the borehole and gas-rich areas, minimizing drilling time, and maximizing the overlap of the trajectory with the stable rock formation. Constraints include not only mechanical constraints of the drilling rig, but also gas safety constraints and geological constraints. The algorithm iteratively calculates the objective function value for each candidate parameter set, applying penalties to parameter sets that fail to meet the constraints or deviate from the optimal objective.

[0193] Furthermore, in the complex environment of underground multi-objective optimization, the algorithm continuously searches and iterates until it finds the parameter set with the minimum objective function value, which is output as the optimized trajectory parameter to ensure that the drilling trajectory achieves the optimal balance in terms of safety, efficiency, and accuracy, and adapts to the complex operational needs of underground coal mines.

[0194] In this embodiment, the calculation formula of the penalty optimization algorithm is:

[0195]

[0196] in: is the kth parameter vector to be optimized, To correct the parameters of the trajectory at point k, is the gas concentration gradient value at point k, is the parameter change vector of adjacent points, is the curvature upper threshold, k is the index of the trajectory point in the modified drilling trajectory, is the gradient sensitivity factor, is the adaptive load factor, is the dynamic risk weight, is the objective function, is the gas risk index penalty item.

[0197] Specifically, is the kth parameter vector to be optimized, representing the parameter set of the kth point on the drilling trajectory, including the trajectory's spatial coordinates, drilling direction, curvature, and so on. In underground coal mines, these parameters determine the actual direction of the borehole and must be adapted to the geology and mechanical properties of the drilling rig.

[0198] Specifically, To correct the trajectory parameters at point k, the ideal parameters of the trajectory at point k are the “reference targets” for optimization after preliminary corrections such as gas concentration distribution, ensuring that the basic direction of the trajectory meets safety and geological requirements.

[0199] Specifically, The parameter change vector of the adjacent points is the parameter difference between the kth point and its adjacent points, reflecting the degree of trajectory curvature. Downhole drilling rigs are subject to mechanical constraints when adjusting their trajectory. Excessive changes can easily cause the drill to become stuck and damage the equipment.

[0200] Specifically, The gas concentration gradient at point k is the spatial rate and direction of change of the gas concentration at point k. Underground gas distribution is uneven, with large gradients at faults and fractures. This reflects the gas flow trend and is a key safety constraint indicator.

[0201] Specifically, The curvature upper threshold is the maximum trajectory curvature that a drilling rig can safely operate. Downhole drill pipes are rigid, and curvature exceeding this threshold can cause stress concentration in the pipe, leading to fracture and hole collapse, requiring strict control.

[0202] Specifically, The gradient sensitivity factor is the degree to which the control algorithm pays attention to the gas concentration gradient. , making the algorithm more sensitive and avoidant; reducing low-risk areas, balancing safety and construction efficiency.

[0203] Specifically, The adaptive load coefficient is the penalty for exceeding the threshold value of trajectory curvature. The downhole drilling rig load increases with the increase of curvature. Dynamic adjustment (such as increase when the load is high) enforces curvature constraints to protect equipment.

[0204] Specifically, The dynamic risk weight is a weight coefficient that combines gas risk and geological risk. It increases when encountering faults and high gas areas. , giving priority to ensuring safety; reducing stable strata and focusing on construction efficiency.

[0205] Further, initial drive: to preliminarily correct the trajectory As a starting point, let Stick to the basic safety path first.

[0206] Risk avoidance: in high gas gradient areas ( big), Rapid increase, the algorithm automatically adjusts , so that the trajectory will bypass it (such as drilling from the side of a high-gas area).

[0207] Mechanical constraints: If overtake is the upper curvature threshold, When a penalty is triggered, the algorithm adjusts parameters in the opposite direction to reduce the trajectory curvature (e.g., changing a sharp turn to a gentle one) and adapt to the drilling rig performance.

[0208] Dynamic balance: As the underground environment changes dynamically, it balances safety requirements and construction feasibility, ultimately outputting an optimized trajectory that avoids risks while ensuring construction is possible.

[0209] In this embodiment, the optimization formula of the parameter vector to be optimized is:

[0210]

[0211] Where: t is the number of iterations, is the parameter to be optimized for the tth iteration and , is the objective function gradient, is the adaptive step size of the tth iteration.

[0212] Specifically, t is the number of iterations, which is the number of steps in the algorithm optimization. The underground environment is complex, and multiple iterations are required to approach the optimal solution, such as gradually adjusting from the initial trajectory until all constraints are met.

[0213] Specifically, The parameter to be optimized for the tth iteration is the tth iteration. Point trajectory parameters (such as coordinates, direction), initial value .

[0214] Specifically, The objective function gradient is the objective function exist The rate of change and direction at Better. Downhole optimization requires gradient guidance to effectively avoid risks and meet constraints.

[0215] Specifically, The adaptive step size of the tth iteration is the amplitude of parameter adjustment in each iteration, dynamically adapting to the downhole environment:

[0216] Initial Iteration ( Small): Move away from the danger zone quickly, such as adjusting the trajectory over a large span to avoid high-gas areas.

[0217] Later iterations ( big): Small, fine-tuning of parameters, such as optimizing trajectory curvature and adapting to drilling rig constraints.

[0218] Furthermore, the initial assignment is: iteration 0 (t=0), Directly take the preliminary correction trajectory , as the starting point for optimization.

[0219] Gradient calculation: Each iteration calculates the current parameters The corresponding objective function gradient , determine the optimization direction.

[0220] Parameter adjustment: along the negative direction of the gradient, with a step size Adjust the parameters to get .

[0221] Specifically, for example: if the gradient shows that the current trajectory is close to a high gas area If it is large, the coordinates will be adjusted significantly along the negative direction of the gradient. Big, let the track quickly away from danger.

[0222] Iterative convergence: Repeatedly calculate gradient → adjust parameters until Small enough, at this time Converge to the optimized trajectory parameters to guide the downhole drilling rig to drill automatically.

[0223] Adjustment module: dynamically adjusts the drilling trajectory of the drilling rig based on the optimized trajectory parameters.

[0224] In this embodiment, dynamically adjusting the drilling trajectory of the drilling rig based on the optimized trajectory parameters includes:

[0225] Extracting key control quantities of the optimized trajectory parameters to obtain trajectory adjustment reference data of the optimized trajectory parameters;

[0226] performing signal synthesis on the trajectory adjustment reference data to obtain a driving instruction;

[0227] A safety margin check is performed on the corrected drilling trajectory based on the driving instruction and the drill bit pressure value to obtain a drilling trajectory.

[0228] Specifically, the optimized trajectory parameters include trajectory spatial coordinates, curvature, drilling inclination, azimuth, etc. These parameters are generated by the modified drilling trajectory through a penalty optimization algorithm, which comprehensively considers the gas concentration gradient, mechanical constraints of the drilling rig and geological risks. For example, the curvature parameter must be ≤ the maximum curvature threshold allowed by the drilling rig to avoid stress concentration and fracture of the drill pipe.

[0229] The key control quantities are the parameters that directly affect the execution of the drilling rig from the optimized trajectory parameters. For example, the three-dimensional coordinates (X, Y, Z) in the trajectory coordinate sequence determine the drilling depth and direction, the curvature parameter determines the degree of bending of the drill pipe, and the inclination parameter affects the feed pressure of the drilling rig.

[0230] Furthermore, in the physical environment of an underground coal mine, the control system retrieves the optimized trajectory parameters from the optimization module database via industrial Ethernet, and converts the parameters into electrical signals using the analog input module of the PLC.

[0231] The parameters are filtered based on the mechanical characteristics of the drilling rig to eliminate outliers caused by electromagnetic interference downhole. The historical drilling data is fused through the Kalman filter algorithm to generate trajectory adjustment benchmark data.

[0232] Specifically, the trajectory adjustment benchmark data is a set of key control quantities that have been screened and filtered, including timestamps, coordinate points, curvature, inclination, etc. The timestamp is used to ensure that the drilling rig action timing is synchronized with the trajectory planning.

[0233] The execution signal is the conversion of the reference data into a physical signal that can be recognized by each actuator of the drilling rig, such as the pressure signal of the hydraulic system and the pulse signal of the servo motor.

[0234] Furthermore, in the underground explosion-proof control cabinet, the signal synthesis module decomposes the benchmark data according to the drilling rig actuator: the coordinate and inclination parameters correspond to the extension and contraction of the feed cylinder, and the curvature parameters correspond to the deflection angle of the guide mechanism.

[0235] The Modbus protocol is used to encode the decomposed parameters into digital signals, which are transmitted to the drivers of each actuator through explosion-proof cables. The drivers convert the digital signals into analog drive signals.

[0236] In the several embodiments provided by the present invention, it should be understood that the disclosed methods and systems can be implemented in other ways. For example, the system embodiments described above are merely illustrative. For example, the module division is merely a logical function division, and other division methods may be used in actual implementation.

[0237] The modules described as separate components may or may not be physically separate, and the components shown as modules may or may not be physical units, that is, they may be located in one place or distributed across multiple network elements. Some or all of the modules may be selected to achieve the purpose of the solution of this embodiment according to actual needs.

[0238] In addition, the functional modules in various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or hardware plus software functional modules.

[0239] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0240] The embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. Artificial intelligence refers to the theories, methods, technologies, and application systems that use digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use knowledge to achieve optimal results.

[0241] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not limiting. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. An automatic control system for underground drilling operations in coal mines, characterized in that: The system comprises: Data acquisition module: used to obtain the gas concentration distribution of the drilling operation, as well as the drill bit pressure value and drill bit position offset of the drilling rig; A trajectory generation module is configured to simulate a predicted trajectory of the drilling rig based on the drill bit pressure value and the drill bit position offset; Correction module: used to correct the predicted trajectory based on the gas concentration distribution to obtain a corrected drilling trajectory, including: Performing spatial gradient vector alignment on the gas concentration distribution and the predicted trajectory to obtain a trajectory conflict area; Scan the high-risk area of ​​gas leakage in the trajectory conflict area to obtain the concentration peak area, Dividing the predicted trajectory into a gas adsorption gradient based on the concentration peak area to obtain a gas adsorption-free state conversion boundary; performing curvature correction on the predicted trajectory based on the conversion boundary to obtain a trajectory unit for preventing gas focusing; Integrating the wellbore annulus pressure parameter of the predicted trajectory to perform dynamic inertia verification on the revised trajectory to obtain a revised drilling trajectory in which gas and rock formations are mutually exclusive and balanced; Optimization module: used to input the parameters in the modified drilling trajectory into the penalty optimization algorithm to obtain optimized trajectory parameters, including: Extracting parameters of the modified drilling trajectory and adjusting the parameters based on mechanical constraints of the drilling rig to obtain optimized parameters; Inputting the optimization parameters into a penalty optimization algorithm; performing a penalty optimization process to generate adjusted candidate parameters, and selecting final optimized trajectory parameters from the candidate parameters; The calculation formula of the penalty optimization algorithm is: ； in: is the kth parameter vector to be optimized, To correct the parameters of the trajectory at point k, is the gas concentration gradient value at point k, is the parameter change vector of adjacent points, is the curvature upper threshold, k is the index of the trajectory point in the modified drilling trajectory, is the gradient sensitivity factor, is the adaptive load factor, is the dynamic risk weight, is the objective function, is the gas risk index penalty item; Adjustment module: used for dynamically adjusting the drilling trajectory of the drilling rig based on the optimized trajectory parameters.

2. The automatic control system for underground drilling operations in coal mines according to claim 1, characterized in that: The steps for obtaining the gas concentration distribution are as follows: Gas data is collected based on the preset gas extraction monitoring device to obtain the gas concentration distribution.

3. The automatic control system for underground drilling operations in coal mines according to claim 1, characterized in that: The simulating a predicted trajectory of the drilling rig based on the drill bit pressure value and the drill bit position offset includes: Performing a time-dependent misalignment analysis on the drill bit pressure value and the drill bit position offset to obtain a delayed conflict characteristic of the drilling rig; Performing a fluctuation backtracking analysis on the geological energy state in the delayed conflict feature to obtain formation characteristic parameters; Compensating and correcting the drilling trajectory of the drilling rig based on the oscillation frequency parameter in the formation characteristic parameter to obtain a drilling correction trajectory that resists formation rebound; Comparing the real-time offset value of the drilling rig based on the historical offset mean of the drilling rig to obtain a cross-period trajectory correction value; A historical interference analysis is performed on the drilling correction trajectory based on the cross-time period trajectory correction value to obtain a predicted trajectory.

4. The automatic control system for underground drilling operations in coal mines according to claim 1, characterized in that: The dynamically adjusting the drilling trajectory of the drilling rig based on the optimized trajectory parameters includes: Extracting key control quantities of the optimized trajectory parameters to obtain trajectory adjustment reference data of the optimized trajectory parameters; performing signal synthesis on the trajectory adjustment reference data to obtain a driving instruction; A safety margin check is performed on the corrected drilling trajectory based on the driving instruction and the drill bit pressure value to obtain a drilling trajectory.

5. The automatic control system for underground drilling operations in coal mines according to claim 1, characterized in that: The optimization formula of the parameter vector to be optimized is: ； Where: t is the number of iterations, is the parameter to be optimized for the tth iteration and , is the objective function gradient, is the adaptive step size of the tth iteration.

6. The automatic control system for underground drilling operations in coal mines according to claim 1, characterized in that: The gas concentration distribution and the predicted trajectory are spatially aligned with each other to obtain a trajectory conflict area, including: Performing depth segment sampling on the predicted trajectory to obtain a discrete path point set of the predicted trajectory; Perform gradient field calculation on the gas concentration distribution to obtain the gradient vector field of the gas concentration distribution: performing drilling direction calculation on the discrete path point set to obtain a drilling course vector of the predicted trajectory; Risk conflict detection is performed based on the gradient vector field and the drilling course vector to obtain a trajectory conflict area.

7. The automatic control system for underground drilling operation in a coal mine according to claim 3, characterized in that: The performing time-dependent misalignment analysis on the drill bit pressure value and the drill bit position offset to obtain a delay conflict characteristic of the drilling rig includes: Detecting a sudden change event of the drill bit pressure value at a first moment to obtain a pressure surge event with a time mark; At a second moment, performing time series slicing on the drill bit position offset to obtain an offset variation curve associated with a pressure event; detecting an abnormal descending section of the offset variation curve to obtain an abnormal pressure-offset response point; A dynamic ratio calculation is performed on the pressure surge event and the abnormal response point to obtain a delay conflict feature.

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