4117results about "Automatic control for drilling" patented technology

The invention discloses a drilling key parameter automatic regulation and control method based on an improved DDPG algorithm. The method comprises the following steps: collecting and preprocessing drilling data, and constructing a complete data set for training; a drilling speed (ROP) time sequence prediction model is constructed and trained on the basis of a self-attention mechanism (self-attention); building a simulation environment by using the trained ROP prediction model, and defining a state space, an action space and a multi-target reward function of a reinforcement learning DDPG algorithm model; a deep deterministic strategy gradient algorithm (DDPG) is adopted to train a reinforcement learning model, through an Actor-Critic network structure, an intelligent agent learns an optimal bit pressure (WOB) and rotating speed (RPM) regulation strategy in a simulation environment, and dynamic optimization of the drilling speed (ROP) is achieved. According to the method, through automatic and intelligent parameter regulation and control, the efficiency and stability of the drilling process are improved, the drill bit wear rate and the operation cost are reduced, and the method has good adaptability and multi-target optimization capacity and is suitable for drilling operation under the complex stratum condition.

A method can include, receiving by a computational device at a wellsite, real-time, time series data from pump equipment at the wellsite, where the wellsite includes a wellbore in contact with a fluid reservoir; using the computational device, processing the time series data as input to a trained machine learning model to detect a performance issue of the pump equipment; and issuing a signal responsive to detection of the performance issue.

The present invention relates to pile foundations and provides an intelligent construction control method and system for jet grouting piles based on stratum information inversion. This method integrates multi-source sensing components and local transmission to perceive real-time drilling information to a data integration terminal. Using engineering soil layer data as training samples, a machine learning algorithm correlates perception information with geological conditions, judging and outputting stratum conditions in real time. An XGBoost model quickly and accurately identifies soil layers at the site. Based on big data matching of a cloud platform, an optimal construction parameter database is established, and the optimal combination of parameters is acquired through algorithm matching. A variable-frequency and variable-speed pressure adjusting device links a piling machine intelligent control system with other subsystems to achieve intelligent control, reducing material consumption and improving pile quality and efficiency.

The invention provides a measuring device suitable for wire saw rock cutting drilling positioning and a control method, and relates to the field of rock cutting construction. The plane position of a drilling machine and three-dimensional space attitude data of a drilling rod are obtained in real time through a GNSS receiver module arranged on drilling machine equipment, and the angle and the position of the drilling rod are accurately controlled through real-time monitoring of a multi-sensor module; the data processing module verifies and analyzes the received data, transmits an analysis result to the deviation judgment module and calculates the deviation value of the data, meanwhile, the HMI control module facilitates an operator to monitor the equipment state in real time, and when the deviation judgment module confirms that the deviation of all the data is within a preset threshold value, the HMI control module sends the data to the data processing module. The HMI module indicates the drilling machine to start drilling operation; the method is suitable for various rock cutting and drilling tasks, particularly in the environment needing high-precision positioning and drilling control, the accuracy and reliability of data are improved, and therefore the drilling precision and stability are improved.

The present invention belongs to the technical field of coal mine drilling rigs, and relates to an intelligent directional coal mine drilling rig and a drilling method thereof. The intelligent directional coal mine drilling rig comprises a moving platform, a frame, a clamping device, a main manipulator, a power head, a drill pipe storage system, a control system and a hydraulic system. The present invention improves the structure of a power head by providing an angle adjuster having accurate angle adjusting and anti-rotation locking functions on the side of a transmission away from a main motor, a driving shaft in the transmission connecting the main motor and the angle adjuster; in addition, the control system comprises a tool face angle measurement and initialization system. Therefore, by means of cooperation between the tool face angle measurement and initialization system and the angle adjuster, the present invention solves the problems that drilling rigs in the prior art lack special tool face angle adjusting devices and thus have low precision and efficiency in trajectory adjustment and have difficulty in achieving automatic directional drilling.

Processes and systems for automating a conveyance operation using an elongated conveyance member. In some embodiments, the process can include modeling one or more system state profiles of a downhole tool string during the conveyance operation within a wellbore to define one or more profile models; calibrating the one or more profile models; using the one or more calibrated profile models to calculate at least one of a tension profile and a force profile along the elongated conveyance member based, at least in part, on one or more detectable system states and / or one or more undetectable system states; and using one of: (i) a surface tension uncertainty quantification model to calculate a surface tension and uncertainty bounds around the calculated surface tension; or (ii) a surface weight uncertainty quantification model to calculate a surface weight and uncertainty bounds around the calculated surface weight.

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 provides an intelligent drilling guide method and system for a petroleum drilling tool face, and relates to the technical field of intelligent control, and the method comprises the steps: determining a first target point, a second target point and a third target point in the process of tracking a target azimuth angle according to a dynamic adjustment instruction; constructing a dynamic triangle through the first target point, the second target point and the third target point, and taking the barycentric coordinate of the dynamic triangle as an azimuth angle correction value; correcting forward and reverse rotation angles and periodic parameters of the drill string according to the azimuth angle correction value so as to obtain a corrected dynamic adjustment instruction; and controlling a drill string to act based on the corrected dynamic adjustment instruction, so that the underground tool surface continuously approaches the target azimuth angle through closed-loop iteration adjustment. The control efficiency and stability of the tool face under the complex working condition can be improved.

The invention relates to a shale oil borehole wall collapse pressure prediction method. The method comprises the following steps: acquiring components, structures and physicochemical properties of a shale oil reservoir; carrying out soaking-nuclear magnetism-sound wave-triaxial stress combined measurement experiments of different drilling fluid systems; constructing a shale oil reservoir rock heterogeneous water absorption and strength degradation equation; establishing ground stress and pore pressure profiles; converting the far-field crustal stress into a borehole and bedding coordinate system; calculating a well periphery stress field generated by water absorption of the surrounding rock; simulating and calculating the temperature field distribution of the rock and calculating a thermal stress value; the well periphery stress value under the force-chemical-thermal-bedding coupling effect is calculated in a superposition mode; constructing a well surrounding rock matrix and weak plane shear failure discrimination function and condition; constructing a shale oil reservoir collapse pressure numerical simulation iterative trial algorithm; determining a formation collapse pressure density control factor and a control mechanism; and the shale oil borehole wall collapse risk is reduced through optimization. According to the method, the shale oil borehole wall collapse pressure under the force-chemical-thermal-bedding coupling effect can be predicted more accurately.

The invention discloses a gas generator and energy storage battery hybrid energy supply scheduling strategy, belongs to the technical field of storage and charging, and mainly solves the problems that in an energy supply mode of a gas generator in existing oil and gas drilling operation, the power generation efficiency of the gas generator is low, and the gas generator is prone to flameout when coping with an impact load. Measuring and acquiring data of voltage and current of oil and gas drilling operation energy consumption equipment, the starting number of gas generators and the residual electric quantity of an energy storage battery; 2, calculating the real-time total power, the power abrupt change rate and the load rate of the gas generator according to the measured data; 3, the number of gas generators needing to be started and the charging and discharging state of energy storage electricity are determined according to the calculation and analysis result; and 4, repeating the steps 1-3 until the drilling operation is finished. The scheduling strategy depends on an existing energy management system, the starting number of the gas generators and the charging and discharging states of the energy storage batteries are reasonably controlled by combining the total power fluctuation characteristics of oil and gas drilling operation, comprehensive management of hybrid energy supply of the gas generators and the energy storage batteries in the oil and gas drilling operation is achieved, the power generation efficiency of the gas generators is improved, and the energy consumption is reduced. Meanwhile, flameout of the gas generator is avoided, and operation safety is guaranteed.

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.

According to the drilling, sealing and injecting integrated anchor rod drilling intelligent monitoring system and method, a rod body is sequentially provided with a head-section wave-shaped threaded section, a middle-section large threaded section and a tail-section wave-shaped threaded section from the head end to the tail end, and a grouting channel is formed in the axis of the rod body; the drill bit and the round nut are respectively mounted at the head and tail ends of the rod body; the anti-shearing tray, the constant-torque pressing sheet and the hexagon nut are arranged on the outer side of the tail-section wave-shaped thread section in a sleeving manner; the built-in mixer is inserted into the grouting channel; the drilling machine is connected with the drilling, sealing and injecting anchor rod through a monitoring sensor arranged outside the hexagon nut in a sleeving mode. A strain type force sensor, a rotating speed sensor, a high-frequency vibration sensor, a well deviation instrument and a load sensor are arranged in the monitoring sensor. The method comprises the steps that a drilling machine rotates forwards to drive a drill bit to conduct drilling operation, deslagging operation is conducted synchronously, and in the drilling process, various sensors are used for collecting various parameters in real time; pre-tightening is conducted through reverse rotation of the drilling machine; a built-in mixer is used for grouting operation; and blocking treatment. According to the system and the method, the operation process can be intelligently monitored.

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.

In some implementations, a computing device may include one or more processors, a memory for storing instructions that when executed by the one or more processors perform operations may include: accessing a drill plan for a drilling operation; receiving a plurality of drilling parameters for the drilling operation; generating a report including: a graphical depiction of the drilling operation based on the plurality of drilling parameters for the drilling operation, the graphic depiction including an animated or video illustration of the drilling operation within a past predetermined time period; a plurality of metrics associated with the drilling operation as provided by the drill plan; and a summary of a planned activity for a drilling operation for a future predetermined time period. Also, the device may include saving the report on a sever connected to a network. Further, the device may include providing the report to at least one user. Similar systems and methods may be used to automatically generate and distribute or provide access to video reports of completion and / or production activities during a first time interval and planned completion and / or production activities during a future, second time interval.

A system and method for accessing drilling records. A semantic web for drilling records is built, wherein building includes converting drilling records retrieved from a database into a Resource Description Framework (RDF) format and storing the RDF formatted drilling records in the semantic web. Transfer learning is applied to drilling domain knowledge to obtain a large language model (LLM) with drilling domain knowledge. A schema is applied to unstructured records to extract information from unstructured records and the extracted information is then stored in RDF format to the semantic web. The LLM is configured to query the semantic web and to manipulate RDF formatted data within the semantic web.

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.

The invention relates to the technical field of engineering early warning, in particular to a drilling engineering early warning method and system, and the method comprises the following steps: collecting a plurality of operation parameters of drilling equipment in real time based on a drilling engineering environment, screening the data, carrying out the comparative analysis of the parameters, evaluating the deviation between the current operation parameter and the conventional operation data, and carrying out the early warning of the drilling engineering. And obtaining equipment operation deviation information. According to the method, the operation parameters of the drilling equipment are collected and processed, key parameters such as the drill bit speed and torque are monitored in real time, deviation with conventional data is found in time, the abnormal condition of the equipment can be quantitatively evaluated by analyzing the frequency and duration of the operation deviation of the equipment, and the stratum data aggregation and trend analysis are combined. The safety of drilling operation is enhanced, the stability of a drilling site can be evaluated by extracting key features such as stratum density and rock hardness, risk classification is performed accordingly, risk early warning is achieved, and potential accidents are effectively avoided.

The invention relates to the technical field of horizontal directional drilling monitoring, and particularly discloses a horizontal directional drilling track real-time dynamic monitoring system which comprises a drilling data acquisition module, a self-adaptive data transmission module, a geological layer analysis module, a three-dimensional track monitoring module and an automatic control module. According to the invention, the geological layer analysis module applies an advanced intelligent analysis technology to carry out deep excavation and accurate identification on dynamic data, and the converted drilling data is further converted into a three-dimensional trajectory diagram, so that an operator of a ground control center can master the full view of the drilling operation in real time, the visual monitoring of the operation process is realized, and the working efficiency is improved. The automatic control module fuses a deep learning algorithm, can intelligently identify route deviation or abnormal conditions in the three-dimensional trajectory diagram, quickly generates a visual adjustment instruction, can find and correct potential problems in the first time, and effectively avoids operation delay or resource waste caused by factors such as trajectory deviation.

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.

Systems and methods are for autonomous real-time 3D interactive planning and execution of well paths in a reservoir and controlling drilling of wells within the reservoir. A data processing system determines in-situ well placement based on mapping of the subsurface. The data processing system can optimize well placement based on two-dimensional (2D) or three-dimensional (3D) subsurface mapping based on proactive planning and interactive data acquisition and analysis.

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.

The invention relates to the technical field of drill rod loading and unloading, and discloses a drill rod loading and unloading method for a drilling machine, which comprises a rotary speed reducer, a rotary arm, a turnover device, a clamping device and a drill rod box which are connected in sequence, and further comprises a swing mechanism and a transportation device, the transportation device is arranged at the upper end of the drill rod box, and the swing mechanism is arranged between the turnover device and the clamping device; the rack is provided with a first proximity switch, the rotary arm is provided with a first arc-shaped block and a second arc-shaped block, the support is provided with a second proximity switch and a third proximity switch, the turnover device is provided with a signaling block, and the rotary arm is provided with a receiver. The transporting device is arranged at the upper end of the drill rod box, so that the overall width of the drilling machine is reduced, meanwhile, the swinging device is matched to enable the drill rod clamped by the clamping device to swing into the clamping device above the rack, the moving distance of the drill rod in the axis direction of the rack is reduced, and then the length of the rack is reduced; the drilling machine can work in the environment of a narrow roadway of an underground coal mine, and the applicability of the drilling machine in different environments is improved.

The invention discloses a hard rock stratum continuous excavation automatic cutting depth control method based on deep learning. The control method comprises the steps of establishment and training of a deep neural network model, pre-drilling fracturing operation and rock stratum strength parameter prediction, determination of a reasonable cutting depth control value and monitoring and control of continuous excavation operation. The cutting performance of the hard rock stratum is improved through pre-drilling fracturing operation, meanwhile, the strength parameter of the fractured rock stratum is predicted according to a deep learning algorithm, then a reasonable cutting depth value is determined, the excavation efficiency of continuous excavation equipment in the hard rock stratum environment can be improved, and the consumption of cutting tools is reduced; and then, according to real-time monitoring data and the trained deep neural network model, a current continuous mining equipment operation strategy is calculated in real time, so that real-time monitoring and control of the cutting depth, the cutting mechanism power and the mining working face flatness are realized, and improvement of the control precision, safety and automation of the continuous mining equipment is facilitated.

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 relates to the field of intelligent remote control, in particular to a digitization-based intelligent remote control method and a digitization-based intelligent remote control system for a drilling machine. The system monitors and collects drilling parameter data in real time through a sensor network, and transmits the drilling parameter data to a remote control server through a wireless communication network. In a remote control server, a data processing and analysis algorithm based on artificial intelligence and deep learning is used to carry out time sequence analysis and collaborative association feature description on the drilling parameter data, so as to capture context semantics among time sequence features of each drilling parameter. The bit pressure time sequence semantics are used as query features to query and match the optimal bit pressure recommendation decoding value from the other drilling parameter time sequence collaborative association features, and the bit pressure recommendation decoding value is compared with the bit pressure value at the current time point to generate a bit pressure remote regulation and control instruction, so that the bit pressure remote regulation and control instruction is quickly adapted to the change of geological conditions in the drilling process; and remote intelligent control of the drilling machine is realized.