11739results about "Survey" patented technology

In one aspect of the present invention, a drill string has a drill bit with a body intermediate a shank and a working face. The working face has a plurality of blades converging at a center of the working surface and diverging towards a gauge of the working face. At least one blade has a cutting element with a carbide substrate bonded to a diamond working end with a pointed geometry. The diamond working end also has a central axis which intersects an apex of the pointed geometry. The axis is oriented between a 25 and 85 degree positive rake angle.

The invention relates to an array electric imaging logging based reservoir oil-water identification method and system. Aiming at the resistivity distribution characteristics of mud-invaded formations, a 'five-parameter formation model' is established, which is adapted to the requirement for simulating the resistivity distribution characteristics of different mud types and different invaded formations, and is pioneering in the aspects of forward-inversion models and processing methods of array electric imaging logging; and based on a 'five-parameter inversion' method for array electric imaging logging, an operation of carrying out resistivity distribution profile reconstruction on mud-invaded formations is performed, which reflects the actual differences between different resistivity distribution characteristics or change rules of mud-invaded oil formations or water formations. The method has stronger practicability, and is pioneering in the actual application aspects of qualitative identification and quantitative calculation on reservoir fluid properties.

Provided is a two-part drilling and running tool, a well system, and a method for forming a well system. The two-part drilling and running tool, in one aspect, includes a conveyance, a smaller assembly coupled to an end of the conveyance, and a larger bit assembly slidably coupled to the conveyance, the smaller assembly and larger bit assembly configured to slidingly engage one another downhole to form a combined bit assembly. The two-part drilling and running tool, according to this aspect, further includes a one way mechanism coupled between the smaller assembly and the larger bit assembly, the one way mechanism configured to allow the smaller assembly and larger bit assembly to axially slide in one direction relative to one another and prevent the smaller assembly and larger bit assembly from axially sliding in an opposite direction relative to one another.

The present invention relates to the technical field of oil and natural gas exploitation, and discloses a real-time monitoring and intelligent control system for hydraulic fracturing cracks in oil reservoirs, including: a real-time monitoring module, which is used to collect crack geometric morphology parameters and construction operation parameters in real time during crack expansion; a nonlinear modeling module, which is connected to the real-time monitoring module, and is used to construct a nonlinear dynamic model of crack expansion according to the collected crack expansion parameters and construction operation parameters, and output a predicted value of crack morphology; an optimization control module, which is connected to the nonlinear modeling module, and is used to calculate the optimized construction parameters according to the nonlinear dynamic model, including injection pressure, injection flow rate and viscosity of fracturing fluid. The present invention realizes precise control of crack expansion, intelligent optimization of construction parameters and efficiency improvement through the closed-loop linkage of real-time monitoring, nonlinear modeling, optimization control and feedback execution.

The disclosure relates to a technical field of oil monitoring, and in particular to real-time monitoring system for an internal environment of an oil well platform. The system includes: a group of Internet of Things sensors used for collecting data of the internal environment of the oil well platform in real time; a satellite transmission unit communicated with a plurality of Internet of Things sensors and used for receiving data collected by the Internet of Things sensors; the satellite receiving terminal used for receiving data from the satellite transmission unit and transmitting data to a central server; the central server with a data processing function used for receiving data from the satellite receiving terminal and carrying out data integration and analysis; and a control center used for displaying monitoring results and data trends from the central server, and issuing early warning or alarm based on a preset environmental parameter standard.

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 invention relates to the technical field of oil and gas field development, and discloses an oil and gas reservoir intelligent dynamic monitoring and optimized mining method based on big data. According to the method, through multi-source data real-time sensing and dynamic coupling modeling, the limitation of traditional static analysis is broken through, and minute-level accurate description of the state of the oil and gas reservoir is achieved; a machine learning prediction model based on physical constraints effectively fuses a data rule and a geomechanics principle, and the early warning reliability of water-driven dynamics and equipment faults is remarkably improved; a multi-objective optimization strategy of digital twin driving comprehensively plans the recovery ratio, the economy and the safety, and supports intelligent decision making under complex working conditions; the edge control and the block chain technology are combined to form a'sensing-optimizing-executing-auditing 'closed loop, so that the high efficiency, the self-adaptability and the data credibility of the mining process are ensured. According to the overall scheme, oil and gas exploitation is promoted to be transformed to intelligentization, refinement and transparency, and technical support is provided for cost reduction, efficiency improvement and sustainable development of an oil field.

The invention discloses a multi-source collaborative advanced geological exploration method based on TBM construction, and belongs to the technical field of tunnel engineering geological exploration. A three-dimensional geological model is constructed through multi-scale collaborative operation of directional long exploration drilling, branch short exploration drilling and in-hole transient electromagnetic detection; the directional long exploration adopts a secondary drilling structure and a screw motor directional drilling technology to realize accurate control of a deep stratum, the branch short exploration realizes dynamic and rapid verification through a TBM integrated drilling machine, meanwhile, in-hole transient electromagnetic exploration adopts three-component measurement and an intelligent inversion algorithm to fill the blank of geological information between drill holes, and by means of mutual data correction of the three methods, the detection accuracy is improved. A three-in-one detection system of drilling, geophysical prospecting and intelligent analysis is formed, and then accurate advanced prediction is achieved, so that the problems that a traditional single detection technology is low in precision and insufficient in coverage range are effectively solved, the water inrush risk is remarkably reduced, construction safety is guaranteed, and the method is effectively suitable for deep tunnel TBM safety construction.

A well location and well trajectory determination method, comprising: on the basis of a stratum pressure test, and a flow phase constraint of each stratum, establishing a full-stratum-series three-dimensional rock mechanical parameter field model, so as to obtain full-stratum-series rock mechanical parameters; on the basis of a geological structure, and a stratum pressure field of each stratum, establishing a three-dimensional full-stratum-series stress field prediction model, so as to acquire full-stratum-series three-dimensional stress field parameters; on the basis of the full-stratum-series rock mechanical parameters, the full-stratum-series three-dimensional stress field parameters and a three-dimensional natural fracture model, establishing a natural fracture activity prediction model, so as to evaluate fracture activity; and determining a well location and a well trajectory on the basis of a three-dimensional original field geostress model, a three-dimensional fracturability prediction model, the fracture activity and a three-dimensional collapse pressure prediction model. By means of the method, the effects of drilling speed increases and modification and production increases can be achieved in complex oil and gas field blocks. Further provided are a drilling speed increase method, a modification and production increase method, a well location and well trajectory determination apparatus, an electronic device, and a computer-readable storage medium.

The invention provides a while-drilling formation pressure early warning method and device based on model prediction, equipment and a medium, and relates to the technical field of low-carbon mining, and the method comprises the steps: in a pre-drilling stage, based on seismic data, adjacent well historical data and design data, analyzing and generating prediction risk data of a target monitoring well; in the drilling process, actual formation pressure data are calculated in real time by using drilling data collected for a target monitoring well in real time, and the actual formation pressure data are compared with the predicted risk data; in the drilling stage, a pressure safety window is depicted based on the predicted risk data, the cycle equivalent density of the target monitoring well calculated in real time is compared with the safety window, and the drilling safety risk is recognized and analyzed; and after drilling is finished, summarizing the predicted risk data, the actual formation pressure data and the drilling safety risk, and updating and iterating the model algorithm through the summarized data. The method has the effect of improving the accuracy of formation pressure early warning while drilling in the petroleum drilling process.

The invention relates to the technical field of well drilling monitoring, in particular to a well drilling well track monitoring and control method based on multi-sensor fusion, which comprises the following steps of: arranging an inertial sensor and a geomagnetic sensor on a drill bit, and acquiring multi-source data reflecting a well track in the operation process of the drill bit in real time; reconstructing a real-time moving track of the drill bit, wherein the moving track of the drill bit is a real-time borehole track; correcting the attitude drift of the gyroscope in the attitude solution; on the basis of zero-speed updating, the speed is corrected to be zero, and meanwhile position drift is corrected; generating track deviation data; and according to the track deviation data, generating a drill bit attitude adjustment instruction by adopting a fuzzy logic control algorithm. According to the invention, the precision of attitude and position calculation is improved, so that the high-precision monitoring of the drill bit well track is realized.

A bottom hole assembly can include a cable head configured to connect the bottom hole assembly to a cable in a coiled tubing, an electrical orienter to rotate multiple sensor packages downhole, and multiple conductors extending between the cable head and the sensor packages via the electrical orienter. A method can include connecting a bottom hole assembly to a coiled tubing, the bottom hole assembly comprising an electrical orienter, a sensor package including ranging equipment, a fluid motor and a drill bit, deploying the coiled tubing and the bottom hole assembly into the well, activating the electrical orienter to rotate the ranging equipment, and then drilling an offset wellbore toward a target wellbore located using the ranging equipment. An electrical orienter can include an electric motor, a flow path extending completely longitudinally through the electrical orienter, and multiple conductors extending completely longitudinally through the electrical orienter.

The invention relates to the technical field of geothermal drilling monitoring management, in particular to a construction monitoring system and method for geothermal drilling. The method comprises the following steps: constructing a state variable set, quantifying structural disturbance intensity by adopting a disturbance derivative method, normalizing the structural disturbance intensity, and defining a state transition tensor mapping behavior influence coefficient; in combination with the high-order derivative of the disturbance trend function and the behavior collaborative change matrix, an offset risk factor is generated through fusion for early warning; dividing a well drilling area into three-dimensional grids, calculating local stress potential energy, adjusting weight through a dynamic sensitive belt, and generating a risk distribution diagram through smooth filtering; performing closed-loop dynamic regulation and control by using risk potential energy centroid coordinates and gradient field inversion intervention vectors for medium and high risk areas; and through multi-period risk potential energy tensor analysis, calculating the matching degree of a self-healing index and a stable cone region, evaluating the self-healing capability of the system and feeding back a regulation and control strategy. According to the invention, a closed-loop monitoring and active control system for nonlinear risks of geothermal drilling is formed.

The present invention relates to the field of geothermal resource development technology, specifically a geothermal well monitoring and maintenance management system and method based on the Internet of Things; the method steps are: through a denoising method combining adaptive fuzzy clustering and deep convolutional neural network, the real signal of sensor data is restored; by generating a check mark, the integrity of the collected geothermal well monitoring data is checked; combined with LSTM time series modeling and deep reinforcement learning for fault prediction and optimization, support vector machine is used for fault type identification, and maintenance strategies are formulated according to the prediction results, the appropriate maintenance type and timing are selected, and resource scheduling optimization is performed to generate a detailed maintenance plan; data and maintenance information are visualized and pushed to on-site staff in real time, and the staff performs operations according to the maintenance plan, and automatically records and updates the health status of the equipment. The present invention improves the monitoring and maintenance efficiency of geothermal wells through intelligent data processing and decision support.

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 the technical field of pressure detection, in particular to an oil well pressure anomaly detection method and system based on deep learning, and the method comprises the following steps: collecting a control signal and pressure data, calculating a slope difference and fluctuation to mark a sudden change point, extracting a multi-dimensional feature group to generate a training sample, and constructing a deep learning model to recognize pressure difference anomaly. The oil well pressure abnormal time period is predicted in real time. According to the method, accurate attribution of abnormal fluctuations in the oil well operation process is achieved by constructing the time sequence corresponding relation between control signals and pressure difference sudden change, the target pertinence of pressure change recognition is improved, a sliding structure extracts multi-dimensional dynamic characteristics, the capacity of capturing wellhead or underground pressure micro-amplitude abnormity is enhanced, and the training sample is combined with a control behavior label, so that the accuracy of the abnormal fluctuations in the oil well operation process is improved. The distinguishing capability of the model to different abnormal forms is optimized, the adaptability under complex working conditions is improved, a real-time prediction mechanism ensures that oil well pressure state recognition has continuity, rapidness and high confidence, and risk early warning and operation guarantee in the oil extraction process are effectively supported.

The invention provides a high-negative-pressure gas extraction drill hole full-life-cycle efficiency evaluation method, and belongs to the technical field of mineral exploitation. A ground stress distribution model is established through microseism monitoring to determine drill hole arrangement parameters; a distributed optical fiber sensing system and a multi-parameter gas flow meter are used for monitoring the stress change around a drill hole and gas extraction data in real time, the coal fracture development degree is obtained in combination with sound wave testing, and all the data are input into a physical numerical value coupling model to calculate a permeability dynamic evolution curve. Establishing a permeability influence coefficient matrix and determining a key parameter weight, constructing an evaluation index system including the extraction amount, the permeability change rate, the drilling life and the coverage range, and performing multi-objective optimization configuration by applying a Pareto optimal solution theory. The technical problem that full-life-cycle dynamic monitoring and comprehensive efficiency evaluation of the high-negative-pressure gas extraction drill hole are lacked at present is solved.

A well system comprising: a sediment separator to be positioned downhole in a well, wherein the sediment separator is configured to receive a formation fluid from a subsurface formation surrounding the well, the sediment separator configured to separate out sediment from the formation fluid, wherein the sediment is disposed or stored at surface of the well or a different downhole location in the well; and a fluid separator to be positioned downhole in the well, the fluid separator configured to receive the formation fluid from the sediment separator, wherein the fluid separator is configured to separate the formation fluid into production fluid and nonproduction fluid.

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.

The invention relates to the technical field of petroleum engineering intelligent drilling data processing, in particular to a multi-source data fusion while-drilling formation pressure monitoring system and method, and the system comprises a data collection verification module, a data transmission alignment module, a pressure prediction engine module, a closed-loop optimization module and an intelligent regulation and control module. The data acquisition and verification module acquires pore pressure, annulus equivalent circulation density and vibration spectrum data through the circumferential sensor array, the closed-loop optimization module updates model parameters based on measured data after drilling and triggers periodic reconstruction, and the geological rule constraint unit verifies a gradient change threshold. The intelligent regulation and control module generates a slurry density adjustment instruction and rechecks and issues the slurry density adjustment instruction through the accident case knowledge base; and the three-dimensional dynamic rendering unit realizes pressure gradient visualization. The problems of prediction hysteresis, model mismatch and frequent manual intervention in formation pressure monitoring while drilling are solved through multi-source data real-time fusion, model dynamic optimization and autonomous decision closed loop.

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 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.

The invention relates to the technical field of underground casing monitoring, and discloses an injection well immovable string casing damage rapid detection device based on efficient testing and adjusting, the injection well immovable string casing damage rapid detection device comprises a testing vehicle, a top sheave and a casing, one side in the testing vehicle is provided with a ground control system, and the other side in the testing vehicle is provided with a double-roller winch; a cable is wound on the outer side of the double-roller winch, an electromagnetic flaw detection testing instrument is installed at one end of the cable, an oil pipe is arranged in the casing pipe in a sleeved mode, a plurality of packers are sequentially installed between the outer side of the oil pipe and the inner wall of the casing pipe from top to bottom, and a plurality of water distributors are sequentially distributed in the oil pipe from top to bottom. A water injection well efficient testing and adjusting technology and an electromagnetic flaw detection technology are combined, an electromagnetic flaw detection testing instrument is tripped in through a testing vehicle, cable power supply and communication are tested, a ground control system carries out signal acquisition and processing on the electromagnetic flaw detection instrument, and rapid detection of casing damage of a water injection well immovable string is achieved.

This invention relates a drill head (4) for use with a microtunneling apparatus (1) having a cutter bar (12) that is rotatable to produce swarf in a working zone. The drill head (4) includes a movable imaging device (46) that is adapted to capture images in the working zone (13). The imaging device (46) is adapted to move from a position within an annular shell (11) to a position external from the annular shell (11).

The invention relates to an intelligent inversion method and system for well drilling overflow shaft gas distribution based on a self-encoder, and belongs to the technical field of oil gas and geothermal development drilling and completion engineering. Comprising the following steps: step 1, accurately solving multiphase flow parameters of a shaft; 2, in combination with the drilling working condition and the geological condition of a specific overflow high-risk well section, based on a Monte Carlo sampling method, eight parameters are changed, uniform sampling is carried out, and a high-precision simulation data set is formed; step 3, constructing a neural network model for gas cut state inversion based on an auto-encoder neural network; 4, training is carried out; 5, standardizing one-dimensional time sequence parameters in the monitoring data; and inputting into a trained neural network model for gas cut state inversion based on an auto-encoder neural network to obtain distribution data of the overflow gas in the shaft in a time period in which the time sequence parameter at the current moment is located. According to the invention, the real-time rapid inversion of the gas distribution in the parallel cylinder during the drilling overflow parallel control period is realized.

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 invention relates to the field of measurement while drilling in drilling operation, in particular to a small-diameter resistivity while drilling measuring device which comprises a drill bit installed at the bottom of a drill rod, a main shaft rotationally arranged in the drill rod, hinged plates symmetrically arranged at the upper end of the drill rod, and an annular cavity formed in the drill rod. Annular frames with U-shaped sections are symmetrically arranged in the annular cavity in a sliding manner, a receiving end and a transmitting end are respectively mounted in the annular frames which correspond to each other up and down, and mounting units for limiting the transmitting end and the receiving end are arranged in the annular frames. The high-efficiency detection of measured objects with different depths and angles in a complex geological environment is realized, the vibration generated in the drilling process of the drill bit is effectively absorbed, the transmitting end and the receiving end are ensured to work in a stable environment, the measurement error caused by the vibration is avoided, and the detection precision and reliability are greatly improved.

The invention discloses a shale oil reservoir geology-engineering double-dessert compressibility comprehensive evaluation method, and relates to the technical field of petroleum and natural gas yield increase transformation and geotechnical engineering, in particular to a shale oil reservoir geology-engineering double-dessert compressibility comprehensive evaluation method, which comprises the following steps of performing normalization processing on a logging basic parameter standard deviation; geological dessert parameters are established by calculating the weight of each factor; influence factors influencing the longitudinal expansion capacity of the hydraulic fracture of the target reservoir are obtained; constructing a geological-engineering double-dessert compressibility comprehensive evaluation model of three types of lithofacies'reservoir performance-transformation potential 'synergistic mechanisms; and establishing a geological-engineering double-dessert compressibility kernel density estimation map, and dividing the reservoir compressibility on the premise of adaptive bandwidth. According to the method, the operability and prediction precision of an evaluation result are remarkably improved, and an innovative decision support tool is provided for horizon optimization and scheme design of shale oil reservoir fracturing transformation.