2957results about "Automatic control for drilling" patented technology

The present invention relates to a coal mine intelligent directional drill and its drilling method, belonging to the technical field of coal mine drills. It comprises a moving platform, machine frame, clamper, main manipulator, power head, drill pipe storage system, control system, and hydraulic system. The power head structure is improved by adding an angle adjuster with accurate angle adjustment, locking, and anti-rotation functions. The angle adjuster is positioned on the gearbox side opposite the main motor, connected via a driving shaft. The control system includes a toolface azimuth detection and initialization system that works with the angle adjuster. This solves prior issues such as the absence of specialized toolface azimuth adjustment devices, low precision, low track adjustment efficiency, and challenges in achieving automatic directional drilling in the prior art. The invention enhances precision and efficiency, enabling automated, intelligent directional drilling.

The invention relates to the technical field of directional drilling track control, and discloses a coal mining underground directional drilling track control method and system, and the method comprises the steps: carrying out the fusion track analysis of a drilling machine based on sensor data, drilling parameters and pre-obtained geological hardness parameters, and obtaining a reference track of the drilling machine, a sensor, an azimuth angle sensor and a bit pressure sensor are used for synchronously collecting drill bit attitude data of a drilling machine to generate a real-time track of the drilling machine, then track offset calculation is carried out to obtain inclination angle deviation and azimuth angle deviation, and dynamic gain adjustment analysis is carried out on the drilling machine to obtain adjustment parameters of the drilling machine. And finally, the drill bit posture of the drilling machine is adjusted based on the adjusting parameters. According to the method, the directional control accuracy of the underground drilling track can be improved.

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.

The invention provides a multi-sensor dynamic calibration method in rotary geosteering drilling, and relates to the technical field of petroleum engineering and drilling, and the method comprises the following steps: collecting original sensing data in real time through a multi-source sensor array deployed on a rotary geosteering drilling tool, wavelet packet decomposition is combined with an improved sliding window algorithm to carry out online denoising processing on original data, and a three-dimensional feature matrix containing environmental interference factors is established; and based on the three-dimensional feature matrix, constructing a dynamic calibration model based on depth time sequence association, respectively processing sensor body feature flow and environment interference feature flow by using a dual-channel LSTM network, performing dynamic weight distribution and fusion on dual-channel features by means of a gating attention mechanism, and outputting a dynamic deviation compensation coefficient of each sensor. The parameter set is generated and reconstructed through the three-dimensional feature matrix, the two-channel network and cooperative calibration, the drilling efficiency and precision are improved, errors are reduced, and intelligent development is promoted.

The invention relates to the technical field of unconventional oil-gas exploration, and discloses a well-seismic integrated horizontal well geosteering risk evaluation method, which comprises the following steps: S1, acquiring three-dimensional seismic data, measurement while drilling data and geological logging data through a well-seismic integrated data acquisition platform; s2, constructing a horizontal well geosteering dynamic model based on multi-source heterogeneous data, and integrating a seismic inversion result and real-time drilling parameters; by establishing a well-seismic data dynamic fusion mechanism and a multi-source risk quantification model, the problem of space-time dislocation of seismic inversion and measurement-while-drilling data is solved, the recognition precision of a fault boundary, a lithologic interface and a pressure abnormal zone is ensured to be matched with drilling position changes in real time, risk misjudgment caused by model updating lag in a traditional method is eliminated, and the accuracy of the method is improved. The accuracy and timeliness of geosteering decision making of the complex structure area are improved; by monitoring well track deviation and geological model prediction deviation in real time, the risks of well wall instability and target deviation are avoided, and the operation safety of the horizontal well in the full life cycle is guaranteed.

A system and method may include receiving data acquired by a downhole tool of a tool string disposed at least in part in a borehole in a subsurface region. The system and method may also include inverting the data using a trained machine learning model to generate a structural feature of the subsurface region. The system and method may further include controlling operation of the tool string based at least in part on the structural feature of the subsurface region.

The present invention provides an intelligent construction control method, apparatus, and system for splitting jet grouting mixing piles, relating to geotechnical engineering. The method includes receiving real-time perception information from a construction information self-perception system, which includes drilling depth, drilling rig output power, drill bit torque, drill rod axial force, and pore water pressure of the drill bit. This information is input into a trained machine-learning model for stratum information, establishing a nonlinear implicit correspondence relationship between the perception information and construction stratum conditions, and outputting real-time stratum state information. The real-time stratum state information is then input into a trained self-matching machine-learning model for optimal construction parameters, establishing a nonlinear implicit correspondence relationship between the stratum state information and optimal construction parameters, and outputting current optimal construction parameters. This invention enables real-time intelligent inversion of stratum information and dynamic self-optimization control of construction parameters.

The present invention belongs to the technical field of anchor protection apparatuses. Provided is an automatic anchor protection platform having combined support of anchor rods and anchor cables. The automatic anchor protection platform comprises a movable chassis, a multi-cycle anchor rod drilling rig, an anchor rod drilling rig posture positioning control device, an anchor cable support device, a temporary support device, an electrical system and a hydraulic system. Said automatic anchor protection platform integrates the multi-circle anchor rod drilling rig, the anchor cable support device and the temporary support device, and therefore meets the anchoring and support requirements of roadways under different geological conditions, allows anchor rod and anchor cable parallel support operations to be conducted at the same time, and achieves efficient coordinating matching linkage integrated design, thus further promoting efficient operation processes in limited spaces such as coal mines and tunnels.

The invention provides a cobblestone stratum bored pile construction and drilling parameter intelligent control method, and relates to the technical field of artificial intelligence and bored pile construction, and the method comprises the following steps: arranging a sound wave emission array at the end part of a drill bit to collect cobblestone distribution information, identifying a weak connecting band as a passable area, calculating an optimal obstacle avoidance track, and setting a posture control point; and drill bit displacement, slurry injection and drill rod deformation parameters are adjusted, so that the drilling tool can intelligently pass along the obstacle avoidance track. Large cobblestones can be effectively avoided, the drilling resistance is reduced, the drilling efficiency is improved, and equipment abrasion is reduced.

The invention provides a well drilling automatic control system which comprises an input establishing module used for inputting well track design parameters and establishing a well drilling system dynamic model; the target trajectory planning module is used for verifying stratum parameters according to the actual drilling data and planning the target trajectory of the current drilling section based on the verification result by using the drilling system dynamics model to obtain the target trajectory; the control quantity feed-forward calculation module is used for calculating the control quantity of the drilling machine by adopting a feed-forward algorithm based on the target track parameters, controlling the drilling real-time calibration module of the drilling machine, and correcting the control quantity in real time based on real-time evaluation of drilling errors in the drilling process; and the data output module is used for outputting logging data in the drilling process of the column after the preset drilling distance of the column is reached. Full-intelligent operation in the drilling process is achieved, and the precision, safety and oil and gas recovery efficiency of drilling operation are effectively improved.

The invention discloses a while-drilling intelligent rock drill and method for self-calibrating a tunnel blast hole drilling track, and the while-drilling intelligent rock drill comprises a rock drill main body, a drill rod, a drill bit, an air leg, a monitoring module, an execution module and a control module, the monitoring module is used for receiving and collecting real-time data such as the drilling depth, the drill bit posture, the linear speed, the angular speed and the contact pressure of a drill bit and a rock stratum in real time and transmitting the data to the control module. The control module is used for receiving data of the monitoring module in real time, drawing an actual drilling track of a drill hole, calculating a drill hole deviation with a preset track, predicting lithology change in combination with an LSTM deep learning model, and outputting a correction instruction to the execution module; and the execution module dynamically adjusts the drilling deviation according to the received correction instruction. The method is realized based on the intelligent rock drill while drilling. The system has the advantages that the system has good real-time deviation monitoring and automatic calibration capabilities, the drilling precision can be effectively improved, and the problem of drilling deviation caused by lithology changes and personal errors is avoided.

Systems and methods for characterizing a subterranean formation that include a drill bit for drilling a deviated wellbore through the formation and that repeatedly changes direction. Also included is a directional drilling system and measurement equipment to detect a property of the formation. A trajectory control system is operable to: receive a well log; determine a property of the wellbore; segment the well log based on the property; and correlate one of the segments with the well log previous to the segment to determine a matching score for the segment. If the matching score is equal to or greater than a minimum threshold, the segment was taken in the formation and at the same stratigraphical true vertical depth (“STVD”). If the matching score is less than the minimum threshold, the segment was not taken in the formation and not at the same STVD and the STVD is estimated.

The invention provides a drilling formation identification and adaptive parameter adjustment method and system, and the method comprises the steps: converting multi-source sensing data into structured formation feature representation through constructing a formation response mode library, and achieving the precise identification of formation interface distribution; a parameter response area distribution analysis and missing information reconstruction technology is adopted, recessive stratum characteristics are deeply excavated, and the internal law of stratum changes is revealed; an adjusting point optimization selection and enhanced drilling path planning mechanism is introduced, and an efficient drilling control network is constructed; potential field distribution is constructed through parameter change features, and coupling correlation between the parameter features and spatial positions is established; intelligent configuration and self-adaptive adjustment of drilling parameters are realized by combining harmonic force analysis and execution scheme generation; and finally, a complete drilling stratum identification and parameter control system is formed, an accurate and efficient technical solution can be provided for drilling operation in a complex stratum environment, and the drilling efficiency and the operation quality are improved.

The invention belongs to the technical field of construction control, and particularly discloses a dry-method precise positioning construction control system and method based on machine learning. Multi-dimensional data such as drilling resistance, vibration frequency, shovel head angle deviation, position and soil layer hardness are acquired in real time through a multi-source data acquisition module; the deviation calculation module carries out dynamic comparison analysis based on data corresponding to a preset sampling area, the dynamic adjustment module dynamically optimizes the drilling speed and angle through a multi-condition triggering mechanism and a transfer adjustment rule, and finally the control execution module generates a precise control instruction to drive the Luoyang shovel to execute deviation correction action. Through multi-dimensional data fusion analysis and a real-time dynamic adjustment strategy, the path precision and the stratum adaptability of the drilling operation are remarkably improved, meanwhile, the adaptability of equipment to stratum sudden change is improved, the construction risk under the complex geological condition is reduced, and collaborative optimization of the drilling efficiency and the operation safety is achieved.

The invention discloses a drilling trajectory real-time dynamic tracking control method and system based on deep learning, and relates to the technical field of petroleum drilling, and the method comprises the steps: generating well trajectory control parameters according to the basic information of a well and preset well trajectory data; setting an optimal drilling fluid performance parameter corresponding to the current working condition according to the stratum environment where the drilling tool is located; deep learning is conducted on the well track control parameters and the optimal drilling fluid performance parameters through the correlation model, a drilling parameter setting scheme is generated, and an underground drilling tool is controlled to conduct drilling; comparing the drilling data with data in the drilling parameter setting scheme, and determining deviation in the drilling data; and determining a corresponding fault mode, and determining a corresponding solution from the solution library to correct the drilling parameter setting scheme. According to the method, deep learning is carried out on geological conditions and historical data, the well trajectory control model and other models are constructed, the model can be continuously updated and optimized along with data accumulation, and the drilling trajectory tracking and control precision is continuously improved.

Certain embodiments of the present disclosure include a method that includes receiving data relating to a coiled tubing operation in substantially real time during the coiled tubing operation. The method also includes iteratively generating an estimated friction coefficient between coiled tubing and a wellbore within which the coiled tubing is disposed during the coiled tubing operation based at least in part on the data relating to the coiled tubing operation. The method further includes estimating one or more parameters of the coiled tubing operation during the coiled tubing operation based at least in part on the estimated friction coefficient.

The invention discloses a multi-well linkage drilling parameter multi-level optimization decision-making method and system, and the method comprises the steps: obtaining real-time drilling data in a drilling operation process, so as to determine a first rock breaking parameter; under the condition that the first rock breaking parameter is out of the preset range, the mechanical drilling speed corresponding to the real-time drilling data is predicted according to a preset model; generating a plurality of candidate parameter groups according to the mechanical drilling speed and the drilling constraint condition, and determining a function value corresponding to each candidate parameter group based on a multi-objective optimized objective function; determining a target parameter group in the plurality of candidate parameter groups according to the function value of each candidate parameter group; and target drilling working parameters are determined according to the target parameter set, and the target drilling working parameters serve as current drilling working parameters for drilling operation. According to the scheme, the drilling working parameters are intelligently optimized by using the multi-objective optimization algorithm while complex working conditions are avoided, and the drilling efficiency is comprehensively improved.

The invention relates to the technical field of downhole operation control, in particular to a downhole operation platform control system and a crane, and the system comprises a task identification module, a demand index module, a power sequencing module, a rhythm switching module and a command reconstruction module. According to the method, through accurate recognition of the structure state and parameter linkage, accurate judgment of the initial operation stage is achieved, false starting and false action of the platform are avoided, coupling analysis between operation data can dynamically set the scheduling priority, it is guaranteed that key tasks are executed in advance, coordination is improved, energy supply conditions are judged through power parameter fusion, and paths are distributed according to needs; the energy utilization efficiency is enhanced, stage rhythm conversion achieves stable switching based on action states and logic mapping, action disjunction is prevented, finally, control instructions are rearranged through feedback time delay and an execution sequence, an efficient and ordered response mechanism is formed, the overall operation efficiency, stability and the intelligent level are improved, and the risk of manual intervention and operation imbalance is reduced.

A system and method for modifying operation of a drilling platform controller. A prompt generator receives drilling operations data relevant to drilling platform controller operation, wherein the drilling operations data includes current drilling parameters of a selected drilling platform controller. The prompt generator generates a prompt for recommended changes in operation of the selected drilling platform controller and applies the prompt to a large language model (LLM) trained with drilling operations domain knowledge. The LLM generates a recommendation for one or more changes in operation of the selected drilling platform controller. Feedback on efficacy of the recommendation is received from the selected drilling platform controller and is used to modify operation of the prompt generator.

The invention provides a drilling risk processing method and device based on a large language model. On the basis of the method, firstly, current drilling state parameters of a target well are obtained, and state sensing data matched with the current drilling state of the target well are determined according to the current drilling state parameters; textualization processing is carried out according to the state sensing data, and a current drilling state text of the target well is obtained; determining target knowledge data matched with the current drilling state of the target well by utilizing the current drilling state text of the target well and combining a preset external knowledge base; generating a target prompt word for the current drilling state of the target well according to the target knowledge data and the current drilling state text of the target well; according to the method, whether the target well has the drilling risk currently or not is efficiently and accurately determined by processing the target cue word through a preset large language model, and corresponding risk reason explanation and / or risk processing measures are determined under the condition that it is determined that the target well has the drilling risk currently.

A system and method of monitoring a downhole tool implemented in a wellbore that include identifying, from surface parameters, a surface downlink sent from a surface of the wellbore to the downhole tool. The surface downlink indicates a downlink command for the downhole tool to implement. The system and method further include confirming that the downhole tool received the surface downlink based on comparing downhole telemetry data received from the downhole tool to the surface downlink. The system and method additionally include, determining a status of the downhole tool indicated by the surface downlink based on confirming that the downhole tool received the surface downlink.

The invention discloses a self-adaptive rock drilling control method and a drill jumbo. The self-adaptive rock drilling control method comprises the steps that S1, initialization is conducted, specifically, parameters including the quality of a drilling component, a drilling included angle, a calculation coefficient, target propulsion pressure, target impact pressure and control parameters are initialized based on a control system before operation; s2, drilling is conducted according to the initialized parameters, the number of drill rods is recorded by a drill rod number counter, and impact pressure compensation and propelling pressure compensation are conducted according to the increased number of the drill rods; s3, adjusting the output propulsion pressure based on the difference between the target rotation pressure and the actual rotation pressure to enable the actual rotation pressure to tend to the target rotation pressure, adjusting the impact pressure based on the relation between the effective impact pressure and the effective propulsion pressure to enable the effective impact pressure to tend to the target impact pressure, and ensuring that the effective rock drilling parameters at the drill bit are matched with the rock. It is guaranteed that the effective propelling pressure and impact pressure at the drill bit meet the requirements, and therefore the drilling precision and quality are guaranteed.

The invention provides an operation control method, system and equipment of a coring drilling machine and a program product. The method comprises the steps that geological information of a construction area is obtained, and geological features are analyzed; constructing rock stratum partitions and predicting the rock stratum depth; configuring partition features and predicting a drilling scheme; constructing a prediction data transmission scheme; controlling the preset coring drilling machine to drill the construction area and obtain actual drilling data, and analyzing rock stratum data from the actual drilling data; and selecting a reference rock stratum partition, and performing operation and data transmission based on the prediction drilling scheme and the prediction data transmission scheme of the reference rock stratum partition. According to the method, accurate prediction of geological information is matched with dynamic adjustment of data transmission, the rock stratum condition is mastered dynamically and accurately, the stability and timeliness of data transmission in the operation process are improved while accurate and efficient operation of the coring drilling machine is guaranteed, most of data analysis and decision-making processes are completed intelligently, and the working efficiency of the coring drilling machine is improved. And the automation level of operation is improved.

The invention belongs to the technical field of drilling, and provides an active vibration reduction method and system based on self-adaptive adjustment of a drill rod load in order to effectively reduce vibration of a drill rod. A real-time feeding oil pressure signal is converted into real-time feeding thrust, and a real-time rotating oil pressure signal is converted into real-time rotating torque; filtering the original vibration signal by adopting a singular value subspace decomposition method to obtain a real vibration signal; according to the preset initial value of the feeding thrust and the preset initial value of the rotating torque, a neural network self-adaptive PID control algorithm is used for conducting self-adaptive comparison calculation, the vibration adjustment amount is obtained, and active vibration reduction is conducted according to the vibration adjustment amount; the system comprises six closed-loop control modules including a preset parameter input module, a signal acquisition module, a signal filtering module, a control algorithm module, a control output module and an execution module, accurate vibration reduction control is achieved, the bounce phenomenon of a drill bit is eliminated, the deviation error of a drill hole is reduced, meanwhile, stick-slip vibration is restrained, and the clamping stagnation failure rate of a drill rod is greatly reduced.

A system and method of real-time optimization of drilling performance metrics during a well drilling operation, for oil and gas as well as geothermal wells, or wells drilled for any other purpose. In a preferred form, the system receives information about allowable drilling metrics and real-time information of performance indicators. The drilling performance metrics and performance indicators are used to build a model to predict drilling parameters likely to optimize one or more drilling performance metrics.

The embodiment of the invention provides an underground tool face dynamic control method and system based on reinforcement learning, and belongs to the technical field of directional drilling. The method comprises the steps of collecting drilling state data of a target well, performing data preprocessing on the drilling state data, and constructing a corresponding state vector based on the preprocessed drilling state data; calling an action decision model obtained by training based on a DDPG algorithm based on the state vector to obtain an action instruction; wherein the network strategy parameter of the action decision model is obtained by correcting the previous network strategy parameter based on the deviation between the current drilling state data and a pre-constructed reward function; analyzing the action instruction to determine a target physical action; and executing top drive torsional pendulum based on the target physical action, and recycling an execution result until the execution result indicates that the tool face angle meets the expectation. According to the scheme, the stability and the real-time control effect under the working conditions of complex well sections and severe disturbance are improved.

Some implementations include a system configured for real-time well path optimization of a wellbore being drilled into a subsurface formation, the system comprising: a downhole tool including a resistivity sensor; a drilling assembly coupled to a drill bit, the drilling assembly including the downhole tool; and a learning machine configured to, compare an input image of a resistivity inversion against an archive of historical data; generate, based on the comparison, a real-time well path suggestion; and output the real-time well path suggestion to a user interface.

The invention provides a cast-in-place pile construction system and method in a soft foundation area. The system comprises a drilling system, a grouting system, a monitoring system and a control system, wherein the drilling system is used for drilling and monitoring and optimizing the drilling condition; the grouting system is used for grouting into the drill hole and optimizing grouting parameters; the monitoring system is used for monitoring conditions in the drill hole and slurry parameters of grouting; the control system is electrically connected with the drilling system, the grouting system and the monitoring system and used for controlling the drilling system to drill holes and the grouting system to grout and adjusting construction parameters of the drilling system and the grouting system according to information monitored by the monitoring system. According to the invention, the drilling system and the grouting system can perform monitoring and optimization, and meanwhile, the monitoring system performs real-time monitoring, so that the control device can conveniently adjust the drilling system and the grouting system, the construction quality of the cast-in-place pile is improved, the construction efficiency can be improved, and even if a problem encounters in the construction process, the problem can be timely monitored and optimized.

A method can include rendering a graphical user interface to a display; receiving data; responsive to determining boundary locations for formations in the subsurface environment using the data, automatically rendering the boundary locations in the graphical user interface; responsive to determining extended boundary locations in the subsurface environment for a region beyond an end of the borehole using the boundary locations, automatically rendering the extended boundary locations in the graphical user interface; responsive to determining a target location in the region using the extended boundary locations, automatically rendering the target location in the graphical user interface; and, responsive to generation of a trajectory from an end of the borehole location to the target location, automatically rendering the trajectory in the graphical user interface.

The invention relates to the technical field of coal mine safety mining, and discloses a coal mine roadway high-stress area unloading-to-suction danger relieving method which comprises the following steps: step 1, a pressure relief stage: drilling holes in a roadway high-stress area to form a pressure relief channel; 2, a transfer stage, wherein stress is transferred to the deep part of the coal rock mass through the layout of the drill holes; and (3) an energy absorption stage: an energy absorption device is installed in the drill hole, the device comprises an outer steel pipe, an internal high polymer material and a monitoring element, the diameter of the drill hole in the step (1) is 50-150mm, the depth of the drill hole is 5-20m, a one-time hole forming process is adopted for construction, and the drill hole is formed in a high stress concentration area which is 6-20m away from the surface of the roadway and is arranged at intervals in the axial direction of the roadway. By constructing a pressure relief-transfer-energy absorption three-stage synergistic effect system, the whole-process dynamic regulation and control of the surrounding rock stress of the roadway is realized, and the problem that the pressure relief effect is uncontrollable due to the fact that a stress transfer path is not clear in the prior art is effectively solved.