2613 results about "Wellbore" patented technology

The invention discloses a radioactive measurement data processing method for improving uranium exploration efficiency. The method comprises the following steps: standardized data acquisition: integrating a multi-parameter module, carrying out time-space synchronous acquisition of geological geophysical environment parameters, standardizing protocol alignment data, and supporting three-dimensional modeling; a three-dimensional coupling model is used for processing interference in a sub-module mode, LiDAR-DEM is used for correcting gamma attenuation in the terrain, an optical fiber thermopermeability instrument is used for correcting daughter errors in the hydrology, signal attenuation of a borehole is compensated through a drilling fluid chart, and a space-time continuous interference field is formed; performing dynamic equilibrium coefficient inversion: constructing equilibrium coefficient isoparametric mapping, and inputting rock core, logging and geochemical data into a random forest model; the transfer learning is trained by using historical data, and dynamic inversion and updating of a new area are carried out; intelligent data processing three-dimensional visualization: self-adaptive denoising and spectral shape matching reinforcement abnormity are carried out; constructing a three-dimensional model, and carrying out transfer learning to optimize the precision; the WebGL platform integrates multi-parameter display, virtual drilling functions and high-dimensional data intuitive interpretation.

The invention relates to the technical field of oil and gas field development, and discloses an ultra-large type true triaxial hydraulic fracturing fracture evolution path prediction method and system.The prediction method comprises the steps that a coupling geomechanical model integrating microscopic, macroscopic and wellbore flow scales is constructed; initializing the model and performing crack initial expansion simulation; collecting construction data in real time, and dynamically optimizing model parameters through a data assimilation algorithm; performing fracture evolution advanced prediction by using the updated model; and generating an optimization decision based on the prediction result and feeding back to the construction site. According to the method, fusion of a multi-scale physical mechanism and real-time dynamic prediction is realized, and accurate prediction and active control can be performed on crack expansion under the ultra-large true triaxial condition.

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.

The invention relates to a wellbore multiphase flow model numerical solution and gas-liquid distribution state inversion method and system, and belongs to the technical field of petroleum engineering, and the method comprises the steps: 1, constructing and training a physical information neural network for drilling wellbore multiphase flow dynamic simulation and overflow gas distribution state inversion; determining input and output of the physical information neural network; determining a loss function of the physical information neural network; training a physical information neural network; 2, designing an adaptive optimization algorithm, optimizing the final solution precision and convergence speed of the physical information neural network, and obtaining an adaptive physical information neural network; designing an adaptive activation function; designing a self-adaptive sampling mechanism based on residual errors; 3, based on the self-adaptive physical information neural network, numerical solution and gas-liquid distribution state inversion of the shaft multiphase flow model are achieved. According to the method, the problem that a traditional numerical method usually needs high-precision grid division and a large number of computing resources is effectively solved.

The invention relates to the technical field of petroleum and natural gas engineering, and discloses an oil and gas reservoir optimized mining method based on multi-modal data, which comprises the following steps: constructing an oil and gas reservoir multi-modal data acquisition system, seismic wave field data, logging interpretation data, production dynamic data, micro-seismic monitoring data, underground temperature and pressure time sequence data and shaft structure parameter data are obtained through the acquisition system; and performing space-time alignment processing on the acquired multi-modal data, establishing a unified geological coordinate system and a time reference, and eliminating data isomerism caused by different acquisition frequencies and spatial resolutions. A six-dimensional heterogeneous data acquisition system covering a seismic wave field, well logging interpretation, production dynamics, micro-seismic monitoring, an underground temperature and pressure time sequence and shaft structure parameters is constructed, so that the depiction precision of a reservoir porosity field, a permeability field, a saturation field and a pressure field is essentially improved.

Systems and methods of the present disclosure includes a mixer configured to mix air and hydrocarbons and a burner configured to receive the mixed air and hydrocarbons and to generate syngas. The system also includes a cooling system configured to receive the syngas and to cool the syngas to form cooled syngas. The system further includes a collector configured to collect carbon from the cooled syngas as soot. Moreover, the system includes a flare stack configured to receive the cooled syngas and to burn off at least part of the cooled syngas.

Methods and systems are disclosed that use a temperature sensor integral to a drill bit during drilling. The temperature sensor is configured to measure temperature associated with a cutting element of the drill bit over time during drilling. The temperature sensor is used to generate temperature data representing temperature of the cutting element of the drill bit over time during drilling. The temperature data is processed to determine and monitor at least one condition of the wellbore and / or the drill bit during drilling, such as i) detection of faults or openings or cracks or other geological rock features of the wellbore being drilled, ii) estimation of one or more drilling parameters of the drill bit (such as rate of penetration (ROP), iii) detection of lost cutting element(s), iv) detection of bit balling, and v) detection of drilling efficiency.

The invention belongs to the technical field of shale oil and gas development, and particularly discloses a multi-source information fused horizontal well casing deformation risk section prediction method, which comprises the following steps: representing shaft crack zone information; establishing a work area construction model and an attribute model; with shaft crack zone information as a constraint, disturbance is performed on crack information predicted based on seismic data, and a three-dimensional crack network model is established; a work area geomechanical model is established, and crustal stress distribution characteristics in the shaft direction of the horizontal well are obtained; a work area casing deformation comprehensive database is established by combining casing mechanical attribute data and work area fracturing construction parameters, and fault zone activity factors are obtained based on the Mohr-Coulomb criterion; and establishing a stratum-fracture-wellbore model, obtaining a mathematical model of fracture zone activity factors and casing deformation degrees, and dividing casing deformation risk grades. According to the method, accurate recognition of the well periphery crack network and advanced pre-judgment of the well periphery crack activation risk and the wellbore casing deformation can be achieved, and guidance is provided for formulating targeted casing deformation prevention and control measures.

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 provides an ultra-deep high-pressure gas well variable-flow-state sand-carrying capacity evaluation method, and relates to the technical field of oil-gas exploration, and the method comprises the steps: collecting well logging data of a target gas well, constructing a gas-liquid two-phase flow parameter expression, and carrying out the quantitative analysis of key flow characteristics such as the gas content and the speed; a mathematical model is established by applying an H-K flow state judgment criterion, and numerical simulation is performed in combination with fluid dynamics simulation software, so that the flow state in the shaft is accurately identified and distinguished; then, according to high-temperature and high-pressure characteristics under actual working conditions and sand shape information monitored in a mine field, carrying out secondary correction on the resistance coefficient CD so as to improve a sand-carrying capacity prediction model; and finally, the critical sand-carrying flow velocity and yield are calculated based on the corrected model, and a scientific basis is provided for setting the sand-carrying capacity and reasonable production parameters of the gas well in different flow states. Safe and efficient development of a gas reservoir is guided, production parameter setting is optimized, and long-term stable and efficient operation of a gas well is ensured.

The invention discloses a shaft operation state intelligent prediction method based on a hybrid deep learning framework, and belongs to the field of petroleum engineering oil-gas field development engineering, and the method comprises the following steps: building a geological sequestration shaft transient temperature-pressure coupling mathematical model, and carrying out the numerical solution; constructing a double sequence feature database covering CO2 injection and leakage working conditions; adopting a parallel architecture to process the double sequence features to construct an improved double attention network; the method comprises the following steps: establishing a hybrid deep learning framework DT-DANet by coupling an improved double attention network and a time fusion Transform; and carrying out collaborative optimization training on the hybrid deep learning framework by adopting a composite loss function, wherein the output of the framework is a wellbore pressure profile, a temperature profile and phase state distribution under different time steps. According to the method, high-precision prediction of shaft multi-parameter dynamic evolution in the CO2 geological storage process is realized.

The invention relates to the technical field of petroleum drilling engineering, and particularly discloses an analysis and prediction system based on petroleum drilling and production data, which realizes virtual reconstruction of a physical drilling system by constructing a digital mapping body, and adopts a multi-source sensor network to collect drill string vortex frequency and wellbore temperature field gradient data. Forming a time sequence feature set through time sequence alignment and fusion processing; performing differential transformation and modal decomposition on the feature set to extract transient response feature vectors and generate a risk distribution diagram; establishing a parameter-risk correlation model, and decoupling mechanical vibration and thermal stress interference by solving a physical equation to obtain a dynamic risk index; the risk indexes and the process parameters are mapped to a three-dimensional grid to construct a multi-dimensional feature space, a feature fusion grid is adopted to achieve information aggregation and reconstruction, and comprehensive risk assessment indexes are generated; a dynamic early warning threshold value is established according to the evaluation indexes, and drilling parameters are optimized in real time through closed-loop control.

The invention discloses a geothermal development oil shale and CO2 geological storage integrated method, which relates to the field of complex oil and gas reservoir development, and comprises the following steps: designing U-shaped well process parameters, enabling CO2 fluid to flow to a high-temperature geothermal reservoir through a descending section of a U-shaped well, injecting the CO2 fluid into the oil shale reservoir along an ascending section of a shaft after sufficient heat exchange, preheating the oil shale, and storing the CO2 fluid into a high-temperature geothermal reservoir through the descending section of the U-shaped well. Terrestrial heat extraction and utilization are realized; after the temperature of the oil shale layer rises to the target temperature, the oil shale layer is further heated through manual heating, and in-situ conversion development of the oil shale is achieved; after completion, produced CO2 is injected into the oil shale layer again through the U-shaped well, and collaborative development of CO2 geological storage, geothermal extraction and oil shale in-situ conversion is achieved. Geothermal energy is efficiently extracted through CO2 and used for oil shale in-situ pyrolysis, the extra manual heating cost needed by oil shale in-situ conversion is remarkably reduced, and the economic feasibility of a pure storage project and oil shale in-situ conversion development is improved.

The invention relates to the technical field of parameter optimization, in particular to a data-driven hydraulic parameter real-time optimization method and system, and the method comprises the steps: obtaining drilling multi-source heterogeneous data, and carrying out the cleaning and multi-modal space-time alignment fusion, and generating a standardized multiphase flow parameter; inputting a pre-trained multiphase flow transient model through a data-model combined driving mechanism, dynamically correcting fluid density distribution and phase change parameters, and outputting a transient simulation result matched with a drilling working condition in real time; and determining hydraulic parameters to be optimized based on a simulation result, and generating a real-time optimization scheme of optimal displacement, throttling pressure and well killing parameters by combining wellbore pressure constraint and a multi-objective optimization function and adopting an adaptive particle swarm optimization algorithm for iterative calculation. According to the method, multi-source data space-time alignment and model dynamic correction are achieved, transient simulation precision is improved through a combined driving mechanism, and an optimal hydraulic parameter scheme meeting wellbore safety constraints can be generated by combining an adaptive optimization algorithm.

This disclosure relates to a predictive lookahead system that generates simulated or predicted wellbore trajectory plans in a drilling environment and determines when a simulated wellbore trajectory plan is at risk based on various lookahead metrics, such as torque and drag (T&D) metrics and hydraulic pressure metrics. For instance, the predictive lookahead system uses a predictive framework with various steps to determine if drilling metrics for a predictive wellbore trajectory plan, such as T&D metrics and / or hydraulic pressure metrics corresponding to subsurface formations, may exceed one or more risk threshold limits and cause damage to the drill bit, drill string, casing, and / or surface rig. The predictive lookahead system determines whether a predictive wellbore trajectory, which aims to converge with a previously planned wellbore trajectory, can proceed safely along the projected trajectory without exceeding T&D, pressure window, or other lookahead metric limits in the wellbore.

The invention relates to a deep stratum well hole and cave mining system and method, the system comprises a traffic well hole system, the traffic well hole system is provided with at least one well hole smaller than 1 m, an internal channel formed by the well hole is communicated with a cave formed by excavation, and the internal channel formed by the well hole is configured to be a flow-back channel and / or an injection channel; the well hole and cave mining device is provided with a crushing assembly and / or a cleaning and transporting assembly, the crushing assembly is used for carrying out form-controllable mining on the ore on the cave rock wall surface, and the cleaning and transporting assembly is used for cleaning ore particles in the cave or transporting the ore particles to the flowback channel; and the particle flow lifting system is used for lifting the extracted ore particles out of the well through the flow-back channel. The technical problems that when caves of deep stratums are mined, the supporting effect is poor, and the ore particle clearing and transporting efficiency is low are solved, and large-scale and high-efficiency mining operation can be conducted on the deep stratums or non-hard stratums.

A method may include performing, by a drilling system, a drilling operation to produce a wellbore in a geological region of interest. The method may further include determining time elapse data describing an amount of time between the drilling operation and a hydraulic stimulation operation. The method may further include determining borehole stress data based on the wellbore, reservoir data, and geological data. The method may further include determining thermal diffusivity data regarding a temperature front in the geological region of interest based on the time elapse data, the reservoir data, and the geological data. The method may further include determining a wellbore breakdown pressure of the geological region of interest based on the thermal diffusivity data, the geological data, the borehole stress data, and the reservoir data. The method may further include transmitting a command to a stimulation control system based on the wellbore breakdown pressure.

The invention discloses a parameter-controlled intelligent oil field shaft digital twinning modeling method, which belongs to the field of petroleum engineering and comprises the following steps of: generating well track data by adopting a multi-source data fusion mode, and optimizing a multi-source data fusion weight coefficient by adopting a genetic algorithm when a measurement depth is generated; well track curvature optimization is conducted based on the minimum curvature principle, a minimum curvature second derivative serves as a target function, and geological factors are introduced to dynamically adjust the smooth weight; a second-order Taylor expansion compensation item is provided for curvature factor dynamic correction, and three-dimensional coordinate data of the well track are generated; and based on the three-dimensional coordinate data of the wellbore track, parameterized-driven wellbore geometric modeling is carried out, and parameterized programmable control over the wellbore radius, the wellbore wall thickness and the section inclination angle is achieved. The invention provides an efficient and accurate wellbore three-dimensional modeling solution, and the wellbore modeling efficiency is greatly improved.

The invention discloses an ultra-deep well drilling wellbore pressure inversion correction method, and aims to improve pressure prediction precision and well control safety in an ultra-deep well drilling process. The method mainly comprises the following two parts: firstly, establishing a wellbore pressure calculation model, fully considering the change of drilling fluid density along with temperature and pressure based on a mass and momentum conservation equation in a drill rod and an annulus, performing discrete solution on the established control equation by adopting a finite difference method, and performing iterative calculation from a well bottom to a well mouth and from the well mouth to the well bottom, so as to obtain a well pressure calculation model; and acquiring pressure and physical property parameters of each node. Secondly, on the basis of model output, a friction correction factor is introduced, a nonlinear state space model is constructed, an unscented Kalman filter (UKF) algorithm is used for conducting dynamic estimation on the friction correction factor, and online self-adaptive correction on the wellbore pressure model is achieved; according to the method, the accuracy of wellbore pressure calculation is effectively improved, and reliable technical support is provided for ultra-deep well operation.

A drift bar is lowered into a well. The drift bar has a density that is less than a density of a wellbore fluid residing in the well. A tubular is lowered into the well below a surface level of the wellbore fluid residing in the well. The tubular defines an inner bore having an inner diameter that is greater than an outer diameter of the drift bar. The drift bar is positioned to pass through the inner bore of the tubular as the tubular is lowered into the well. After the tubular is positioned below the surface level, an absence or presence of the drift bar floating at the surface level is detected. An absence or presence of a restriction in the inner bore of the tubular is determined in response to detecting the presence or absence, respectively, of the drift bar floating at the surface level.

A ratcheting setting tool can use wellbore fluid to inflate expandable seals positioned downhole in a wellbore. For example, the ratcheting setting tool can include a piston within a first chamber. The piston can move from a first position to a second position in the first chamber when a pressure is applied to the piston. The ratcheting setting tool can include a first check valve in a second chamber. The first check valve can transmit wellbore fluid from the wellbore into the second chamber. The ratcheting setting tool can include a second check valve. The second check valve can transmit the wellbore fluid in the second chamber into an inflatable valve when the piston moves from the first position to the second position. In some examples, the ratcheting setting tool may be a hydraulic ratchet.

The present application relates to the technical field of shale oil and gas field development, and is a test system for simulating fault activation and induced earthquake under the action of horizontal well hydraulic fracturing, which comprises a horizontal well geological model, a distributed optical fiber monitoring system, a perforating system, a fracturing system, a formation temperature simulation system and a stress applying system. The present application has a reasonable and compact structure and is convenient to use. It can realize the application of true triaxial formation pressure, simulate the real formation temperature of the formation where the horizontal well is located, and continuously and real-timely monitor the multi-physical field of the fault-containing geological reservoir under the conditions of formation pressure, temperature, the whole process of horizontal well hydraulic fracturing and multi-step conditions. Therefore, the mechanism of hydraulic fracturing activating faults, the feature difference of multi-stage fracturing fracture network, the deformation of casing and the risk of induced earthquake can be quantitatively characterized and regularly analyzed, so as to study the formation and expansion of rock mass fracturing fracture network, the activation of faults and the deformation and damage process of wellbore casing during the whole process of fracturing at different stages of horizontal well.

The invention discloses a horizontal well fracturing perforation parameter optimization method and device considering non-uniform crustal stress and a medium, and relates to the field of unconventional oil and gas reservoir yield increase renovation. The method comprises the steps that a three-dimensional non-uniform crustal stress field of reservoir fracturing is constructed; the method comprises the following steps of: performing grid division on a hydraulic fracture by using a fracture unit, acting a three-dimensional non-uniform ground stress field on a divided grid, and establishing a constitutive model of reservoir rock deformation and stress in a hydraulic fracturing process; according to the constitutive model, establishing a flow model of the fracturing fluid in the horizontal shaft, the perforation hole and the hydraulic fracture; establishing an expansion criterion of the hydraulic fracture in the fracture length and fracture height directions; according to the expansion criterion and the flow model, the expansion results of the horizontal well fracturing cracks under different perforation parameters are simulated; and the horizontal well fracturing perforation parameters are optimized according to the expansion result. According to the method, the defects of a uniform crustal stress field assumption and a plane crack propagation assumption in the prior art are overcome, and the optimization of the horizontal well fracturing perforation parameters in the non-uniform crustal stress field is realized.

The invention belongs to the technical field of petroleum and natural gas engineering, and particularly relates to a logging data intelligent inversion method fusing an attention mechanism and a convolutional neural network, and the method comprises the steps: S100, selecting a borehole which is subjected to well drilling and logging as a research well, and obtaining the drilling, logging and logging data of the research well; s200, constructing a unified depth reference of well drilling, well logging and well logging data, and improving the resolution of the well drilling and well logging data by adopting an interpolation method; s300, constructing an attention mechanism module based on a multi-scale adaptive compression excitation network, and improving the modeling capability through triple mechanisms of multi-scale feature perception, adaptive compression proportion adjustment and residual enhancement attention weight; s400, constructing a feature extraction and regression prediction network based on a one-dimensional convolutional neural network; s500, supervised learning training is carried out on the inversion model until comprehensive evaluation index requirements are met; and S600, intelligent prediction and inversion of the logging curve are carried out by using the trained model. According to the invention, intelligent and efficient inversion of the logging data by using the low-cost drilling and logging data is realized.

The invention discloses an intelligent diagnosis system for health and collapse risks of a vertical shaft structure, and relates to the technical field of mine safety monitoring. The acute lesion diagnosis module is used for diagnosing acute physical damage of a sensing optical fiber so as to generate a spatial data confidence index map; the chronic lesion compensation module is used for compensating chronic signal drift caused by internal residual stress relaxation of the sensing optical fiber so as to establish a dynamic zero correction vector; the signal fusion processing module purifies the original apparent strain information through a nonlinear weighting algorithm according to the output of the first two modules, and reconstructs a net structure strain field calibrated by the space-time drift of the instrument; and the collapse risk prediction module is used for intelligently diagnosing and predicting the structural health state and the collapse risk of the vertical shaft. According to the method, the authenticity of monitoring data can be improved from the source, the false alarm rate is greatly reduced, and long-term and weak structural evolution omen are effectively captured.

The application belongs to the technical field of oil well production management, and discloses a submersible electric pump well group management system and method based on digital twinning. The method collects the operation data of the submersible electric pump unit and the environmental data in the wellbore in real time, constructs a multi-scale digital twinning model for the received data, obtains the mechanical structure and electrical characteristics of the submersible electric pump unit, the multiphase flow dynamics in the wellbore, and the geological pressure field data, performs trend prediction on the multi-scale digital twinning model operation parameters, energy efficiency indicators and health status of each well, correlates the trend prediction data with the historical health database through a machine learning algorithm and an expert knowledge base, completes early warning and intelligent diagnosis of equipment failure, and generates a maintenance strategy. The application can assist managers in decision-making based on the historical health database. The application can realize unified management and intelligent well inspection of multiple well sites, and greatly improves the efficiency of oil well production management.

Methods and related systems for drilling a subterranean wellbore includes rotating a bottomhole assembly (BHA) to drill the wellbore. The BHA includes a cutting tool and at least one sensor. The at least one sensor is configured to make measurements while drilling. These measurements are processed to compute a magnetic field profile, which is further processed to identify and characterize a signature or pattern in the magnetic field profile that is representative of a target well proximate to the wellbore being drilled. At least one of a distance or a direction to the target well can be computed based on characteristics of the signature or pattern in the magnetic field profile. The computed distance or direction to the target well can be used to control the direction of drilling of the wellbore.

The invention belongs to the technical field of oil and gas exploitation, and particularly relates to a low-yield well distributed optical fiber sound wave wellbore flow interpretation system and method based on thermal excitation. Downhole fluid is heated through a downhole heating device, and a thermal fluid slug with the temperature higher than that of unheated fluid is formed; the moving distance of the thermal fluid slug in the shaft in unit time is tracked by drawing an optical fiber strain response diagram, and the downhole fluid flow speed can be obtained. The shaft flow interpretation method is small in underground flow interference and obvious in optical fiber signal response, the technology is simple and easy to implement, and the problem that signals of the DAS in a low-yield well are not obvious can be effectively solved.

The invention provides a tight gas and deep coal bed gas collaborative exploitation simulation experiment device. The tight gas and deep coal bed gas collaborative exploitation simulation experiment device is composed of a shaft simulation device, a reservoir simulation device, a gas-liquid two-phase flow supply device and a control system. The casing pipe is provided with a plurality of transparent converging sections, and the oil pipe can be downwards inserted to different layers. And the gas-liquid two-phase flow supply device is provided with a plurality of groups of independent gas-liquid conveying manifolds which are respectively connected with each convergence section of the sleeve through the reservoir simulation device, so that the independent regulation and control of seepage parameters and production pressure difference of each layer are realized. The control system integrates pressure and flow acquisition and image recording functions, monitors and analyzes data in real time, is used for simulating an interlayer coupling relationship, a mutual interference mechanism and dynamic productivity response during multi-layer commingling production, and provides an experimental basis for collaborative production layer strategy optimization.

The invention discloses a rigid casing stabilizer and relates to the technical field of oil field low-carbon exploitation. An annular counter bore is upwards formed in the lower end face of the centralizing sleeve, a lifting sleeve is arranged in the annular counter bore and connected with the annular counter bore through threads, the upper portion of the lifting sleeve is connected with a compression spring A through a plane bearing, the upper portion of the compression spring A abuts against the bottom of the annular counter bore, and a balance cutting mechanism is arranged on the lower portion of the lifting sleeve. The drilling tool has the beneficial effects that the balance cutting mechanism is arranged on the lower portion of the centralizing sleeve, when the well diameter is irregular during casing running and the main cutting block and the auxiliary cutting block encounter the inner protrusion of the well wall, the lifting sleeve starts to rotate and ascend, the main cutting block and the auxiliary cutting block cut the well wall, the casing can be smoothly put into a shaft, and the drilling tool is convenient to use. And during cutting, large bending force cannot be formed on the casing pipe, so that the casing pipe is protected.