479 results about "Drilling engineering" patented technology

The invention discloses a directional drilling track accurate control technology based on machine learning, and relates to the technical field of drilling engineering. The directional drilling track accurate control technology comprises the following steps that underground parameters of a drilling tool during underground operation are obtained; establishing a dynamic model based on the drilling tool structure and the motion state; based on the dynamic model, introducing a long-short-term memory neural network, and constructing a hybrid prediction model; drilling parameters are input into the hybrid prediction model, and trend information of multiple tracks is output; based on current geological conditions, drilling tool configuration and operation safety constraints, performing simulation evaluation on the trend information of the plurality of candidate tracks, and screening out an optimal track meeting track precision and underground safety requirements from the candidate tracks; based on the optimal track, control strategy input is constructed, and a state space containing a tool face angle, target azimuth deviation and a drilling tool state is set; and through a deep reinforcement learning method, an advanced adjustment instruction for the guiding tool is generated, and drilling operation is executed according to the optimal track and the advanced adjustment instruction.

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 provides a petroleum drilling geomechanical characteristic estimation method based on deep learning, and aims to solve the problems of high measurement cost and poor real-time performance of shear wave velocity Vs in traditional geomechanical analysis by fusing logging while drilling LWD data and real-time drilling engineering parameters. According to the method, a Transformer model is adopted to carry out depth correction on logging-while-drilling data, depth offset of a drill bit and a logging sensor is eliminated, and real-time drilling parameters such as torque T, bit pressure WOB and drilling speed ROP are combined and input into a multi-layer perceptron MLP network to predict the shear wave speed Vs. And further calculating key geomechanical parameters based on the predicted shear wave velocity Vs. In practical application, the method improves the shear wave velocity prediction accuracy to 97.2%, the mean absolute error MAE of the shear modulus is reduced from 0.186 to 0.059, and the bulk modulus is reduced from 0.189 to 0.040. The method can be used for outputting stratum elastic parameters, optimizing bit pressure, pre-warning well wall instability and adjusting a well track, well drilling safety and efficiency are improved, and meanwhile dependence on an expensive well logging technology is reduced.

The invention provides a tunnel three-dimensional geologic body modeling method and system based on in-hole camera shooting and while-drilling lithology perception, and relates to the technical field of tunnel and underground engineering and intelligent geological information processing.The method comprises the steps that firstly, a drill hole wall optical image sequence and while-drilling engineering parameters are synchronously collected and preprocessed respectively; then establishing a depth-time mapping relation to realize accurate alignment of the multi-source data in a depth domain; then fracture intelligent identification and parameter extraction are realized through an improved U-Net network, and lithology classification is completed by using an XGBoost model; feature level and decision level fusion is carried out on the fracture features and the lithologic features, and rock mass quality grades are generated; and finally, constructing an integrated geologic model fusing lithologic distribution and a three-dimensional fracture network by adopting an implicit modeling and discrete fracture network technology. According to the method, the problem of splitting of in-hole visual information and while-drilling physical information is solved, automation and precision of geological recognition are improved, and reliable geological information support is provided for tunnel construction safety and support design.

The invention discloses a lithofacies intelligent identification method, device and equipment, a medium and a program product, and the method comprises the steps: building a sample data set through logging parameters, drilling parameters and historical drilling data corresponding to lithofacies labels, screening out a feature subset for modeling based on correlation analysis, and building a lithofacies identification model based on a Transform neural network; and training the constructed lithofacies identification model by using the sample data set to obtain an optimized lithofacies identification model, inputting the feature subset of the well to be identified into the optimized lithofacies identification model, and outputting a lithofacies prediction result of a corresponding depth. The intelligent lithofacies identification method relies on the Transform model, has high identification precision, high automation degree and strong generalization ability, can effectively integrate two types of information of logging data and drilling engineering data, provides a more comprehensive basis for lithofacies judgment, and can meet the requirement of real-time lithofacies identification while drilling.

The invention discloses a reamer electromechanical driving mechanism and method capable of detecting the position state of a blade, and relates to the technical field of tools of petroleum drilling engineering, the reamer electromechanical driving mechanism comprises a power assembly, a lead screw assembly, an ejector rod, a locking assembly, a rotation detector and a displacement detector which are mounted in a drill collar; the power assembly is connected with the lead screw assembly, the lead screw assembly is connected with the ejector rod, the ejector rod is connected with the reamer blade, the power assembly rotates and drives the ejector rod to move up and down through the lead screw assembly, and the ejector rod moves up and down to drive the reamer blade to be unfolded or folded. The locking assembly is assembled on the ejector rod, and after the reamer blade is unfolded in place, mechanical self-locking is conducted on the ejector rod. The rotation detector is assembled beside the lead screw assembly to detect rotation of the lead screw assembly, and the displacement detector is assembled beside the ejector rod to detect up-and-down movement of the ejector rod. The opening and closing state of the cutter wing is measured and uploaded through the rotating detector and the displacement detector, the cutter wing is expanded in place, the underground condition can be judged easily, and controllable multiple reaming is achieved.

The invention discloses a high-temperature-resistant and high-pressure-resistant autonomous deep well pressure maintaining sampler, and belongs to the technical field of drilling engineering sampling. The sampler comprises an upper joint, a control outer pipe, an end cover, a valve body and a liquid storage chamber which are connected in sequence, an electromagnet is arranged on the outer side of the end cover; an electric control module is arranged in the control outer pipe; a valve element with a permanent magnet is arranged in the valve body in a sliding mode, the valve element is driven to move axially through non-contact electromagnetic force between the electromagnet and the permanent magnet, and opening and closing of the sampling flow channel are achieved. The bottom of the valve core is provided with a valve core inner channel communicated with the sampling flow channel and the liquid storage chamber and a one-way valve; a sampling inlet channel is formed in the joint of the end cover and the valve body. According to the invention, a pure mechanical sealing-based structure is adopted, so that the sealing reliability and the operation stability in a high-temperature and high-pressure environment of a deep well are remarkably improved, drilling fluid is not needed, and efficient and pressure-maintaining sampling of in-situ formation fluid is realized.

The invention relates to the technical field of drilling engineering, and discloses an impact-assisted rock breaking inwards-concave PDC drill bit which comprises a drill bit body and an impact structure, and the drill bit body is provided with an inner cavity and a first transmission protrusion arranged at the head of the drill bit body; the impact structure comprises a turbine, a transmission shaft and an impact blade, the turbine is arranged in the inner cavity of the drill bit body, the impact blade is arranged outside the drill bit body, the transmission shaft is connected between the impact blade and the turbine and provided with a second transmission protrusion, and the turbine is used for driving the transmission shaft to rotate; the second transmission protrusion and the first transmission protrusion abut against each other or are staggered in the rotating process. The impact cutter wings are used for stretching out relative to the drill bit body when the second transmission protrusions abut against the first transmission protrusions; a reset spring is further arranged between the transmission shaft and the drill bit body and used for driving the impact blades to reset when the second transmission protrusions and the first transmission protrusions are staggered. The high-frequency axial reciprocating motion of the impact blades directly crushes the center area of the drill bit, and the rock breaking efficiency of the center area of the drill bit is improved.

The invention belongs to the technical field of petroleum and natural gas drilling engineering, and relates to a rotary steering test method and system for simulating underground drilling fluid circulation in a workshop. The method comprises the following steps: firstly, determining a dynamic fingerprint and a tolerance band of a circulation channel of a target well section, wherein the dynamic fingerprint comprises a time domain step and a frequency domain phase index; constructing a test loop of a series-connected adjustable hydraulic dynamic equivalent module, wherein the module comprises a containing cavity, a throttling unit and an inertia pipe unit to regulate and control flexibility, damping and inertia; applying flow disturbance and collecting flow pressure data to obtain a current dynamic fingerprint; comparing the tolerance band to iteratively adjust module parameters until the fingerprint reaches the standard; and after locking the parameters, carrying out function testing. The problem that traditional testing is disjointed with underground working conditions can be solved, testing accuracy and reliability are improved, testing cost is reduced, and testing requirements of different well sections are met.

The invention discloses a disassembly-free top drive drilling device pulley and guide rail system, relates to the field of petroleum drilling engineering, and solves the problems that a top drive drilling device is too long in assembly and disassembly time and too high in safety risk when applied to a telescopic derrick drilling machine. The derrick is divided into an upper derrick section and a lower derrick section; the slide rail comprises an upper slide rail section and a lower slide rail section; the upper-section sliding rail and the lower-section sliding rail are hooked through a hook; an upper-section sliding rail and a lower-section sliding rail are respectively arranged on two sides of the inner sides of the derrick upper section and the derrick lower section; two ends of the pulley are in contact with the upper-section slide rail and the lower-section slide rail; the working surfaces of the upper-section sliding rail and the lower-section sliding rail in contact with the tackle are on the same plane to form a tackle guide channel; the middle of the pulley is connected with a top drive; the top drive is hung below the traveling block and moves up and down along with the traveling block. According to the disassembly-free top drive well drilling device pulley and guide rail system, the assembly and disassembly time is saved, the danger in the assembly and disassembly process is reduced, and the well drilling efficiency and the construction quality are improved.

The invention relates to the technical field of petroleum drilling engineering, and particularly discloses a drilling plugging agent as well as a preparation method and application thereof. According to the plugging agent, nano silicon dioxide and graphene oxide serve as a composite matrix, and the well drilling plugging agent with excellent dispersion stability, compact plugging performance, temperature resistance, salt resistance and reservoir friendliness is obtained through silane coupling agent graft modification and polymer copolymerization composite modification. The technical defects that an existing nano plugging agent is prone to agglomeration, poor in compatibility with drilling fluid, insufficient in extreme working condition resistance and the like are overcome, the preparation process is simple and controllable, the cost is relatively low, the plugging agent can be added into water-based or oil-based drilling fluid according to the mass ratio of 0.5-5%, the plugging agent is suitable for shale, deep high-temperature high-pressure high-salt complex stratums and the like, a compact plugging layer can be formed, and the plugging effect is good. Shale micro-cracks and deep stratum large cracks are effectively blocked, and the problems that a traditional blocking agent is prone to agglomeration, poor in extreme working condition resistance and the like are solved.

According to the logging-while-drilling data lag compensation method based on deep learning provided by the invention, the prediction precision of the lag logging-while-drilling data is improved by combining the drilling engineering data and the historical logging-while-drilling data. According to the method, an encoder-decoder neural network model based on a self-attention mechanism is utilized, lag logging-while-drilling data is predicted in combination with drilling engineering features, and prediction precision is improved through a convolutional layer. Results show that when the method is used for predicting the gamma curve in the logging-while-drilling data, the root mean square error within the prediction range of 30 meters is lower than 0.589, and the average absolute percentage error is lower than 1.587. The problem of lag of the logging while drilling data is effectively solved, the operation risk under the complex stratum condition is reduced, the drilling strategy can be optimized in real time, and the safety and efficiency of the drilling process are improved.

The invention provides a well bottom ECD accurate determination method based on a field multi-point cycle test, and belongs to the technical field of petroleum and natural gas drilling engineering. Comprising the following steps: selecting at least three different-depth test points on a casing section, and synchronously obtaining pump pressure, drilling fluid rheological parameters and borehole-drill rod geometric data; preprocessing the data; calculating annulus pressure loss, drill rod pressure loss and drill bit pressure loss of each test point based on an API standard formula; establishing a pumping pressure-pressure consumption associated linear equation set and solving annulus and drill rod pressure consumption correction coefficients; and outputting a shaft bottom ECD for eliminating naked eye interference in combination with the real-time drilling parameters and the inversion coefficient. According to the method, the multi-point cycle test and the dynamic inversion model are combined, the deviation between the theoretical model and the actual working condition is quantified through the correction coefficient, the weighted least square and the matrix condition number pre-judgment technology are combined, the problem of ECD calculation misalignment of a traditional method is solved, and the pressure control precision and safety in a complex drilling scene are remarkably improved.

The present application relates to the field of logging while drilling and intelligent steering control technology in oil and gas drilling engineering, in particular to a rotary steering drilling adaptive trajectory control method for image processing. It comprises: receiving original logging while drilling image data frames of downhole transmission channels; generating a high-resolution predicted geological texture map; synchronously generating a feature uncertainty distribution map representing the pixel probability distribution characteristics in the high-resolution predicted geological texture map; calculating the matching degree of the high-resolution predicted geological texture map and a preset stress-induced artifact feature library; generating a sensor contamination marker signal; calling a safety baseline geological model constructed before drilling; calculating the geological texture structure difference value relative to the safety baseline geological model; generating a geological illusion entropy; receiving the geological illusion entropy and the sensor contamination marker signal; and driving a downhole steering tool according to the activated mode. The present application ensures that the steering instruction is always based on the real existing geological information, and avoids the deviation of the drilling trajectory caused by the fictitious texture.

The invention relates to the technical field of drilling engineering, and particularly discloses an intelligent torque control method suitable for a high-torque drilling screw rod, and the method comprises the steps: collecting drill string vibration frequency data and bit pressure adjustment frequency data in real time in a drilling process, extracting a zero-sequence vibration frequency characteristic value in combination with sparse Fourier transform, and evaluating the vibration stability of a drill string; meanwhile, differential adjustment frequency is analyzed through empirical mode decomposition and Hilbert transform, differential adjustment frequency characteristic values are constructed to measure bit pressure adjustment stability, the two characteristic values are fused into a comprehensive characteristic vector, the comprehensive characteristic vector is input into a risk prediction model trained based on a random forest algorithm, and the bit pressure adjustment stability is improved. Intelligent identification of whether the drill column is in a high-frequency resonance critical state or not is achieved, and when it is judged that resonance risks exist, the system automatically triggers a torque compensation mechanism, and bit pressure and torque output are dynamically adjusted.

The invention belongs to the technical field of petroleum drilling engineering, and discloses a chitosan-quaternary ammonium salt modified composite shale inhibitor and a preparation method thereof. According to the inhibitor, natural chitosan is used as a main chain, dimethyl diallyl ammonium chloride (DMDAAC) is adopted for free radical grafting modification, glycine is combined as a synergistic auxiliary agent, and a composite structure with high cation density is constructed. The preparation method comprises the following steps: dissolving 15-25 parts of chitosan in 1000 parts of 1% glacial acetic acid, and stirring at room temperature; dropwise adding 2 to 4 parts of DMDAAC, reacting at 65 to 75 DEG C, and then adding 0.1 to 1 part of ammonium persulfate for grafting for 3.5 to 4.5 hours; and cooling, filtering and drying to obtain powder. And dissolving 10-20 parts of the solution in deionized water, adding 1.5-2.5 parts of glycine, and uniformly mixing to obtain the composite inhibition liquid. The inhibitor has good water solubility and thermal stability, can significantly inhibit shale hydration expansion and particle dispersion, and experiments show that the inhibitor can be suitable for well wall stability control of complex stratums such as high-temperature deep wells and the like, and has good field adaptability and industrial popularization value.

The invention discloses a geothermal resource assessment method and system based on big data analysis, and is applied to the technical field of digital analysis. The method comprises the following steps of obtaining multi-source heterogeneous data of historical drilling engineering, performing data preprocessing and feature engineering, and establishing a drilling success probability intelligent prediction-risk quantification model; in combination with geospatial information and environmental multi-source data, identifying an earth surface thermal anomaly region as a target region to perform geothermal potential assessment, and completing preliminary grading assessment of the target region; integrating seismic active band high-frequency monitoring data, inverting deep structure features by using a seismic wave velocity tomography technology, and performing multi-mode correlation matching with a target region; the coupling model realizes accurate evaluation and grading screening of a target region; and constructing a geothermal target area digital twinborn model fused with geologic and geophysical constraints, and realizing dynamic evaluation and productivity prediction of geothermal resources. Automatic geothermal resource evaluation is achieved, and efficient development and reasonable utilization of geothermal resources are promoted.

An old well corrosion oil casing safety evaluation and life dynamic prediction method is characterized in that based on old well basic parameters and a well bore structure, pipe mechanics, thermodynamics and electrochemical experiments are carried out, and a corrosion rate model is established; then, on the basis of the pipe corrosion morphology / contour, utilizing SOLIDWORKS to establish a three-dimensional geometric model of the casing containing corrosion damage, importing ABAQUS finite element simulation software, simulating the corrosion depth, the time-varying strength and the residual life of the casing under different service conditions, and establishing a prediction model of the corrosion depth of the casing, the time-varying strength of the corroded casing and the residual life of the corroded casing; in combination with on-site underground service conditions and casing damage detection data, an isolation forest method and a data cleaning technology are adopted to preprocess original data, then required parameters are input into a prediction model for dynamic prediction, and the method provides a basis for petroleum engineers to predict the residual life of the casing with corrosion defects according to the on-site service conditions. The method is suitable for the technical field of petroleum and natural gas drilling engineering.

This specification relates to the field of drilling technology, and more particularly to a wellbore trajectory control method, apparatus, and electronic equipment. The method includes: acquiring drilling engineering data during the drilling process, the drilling engineering data including inclination measurement data; calculating initial build-up rate data based on the acquired inclination measurement data; querying historical build-up rate data under the same drilling conditions as the initial build-up rate data; determining the actual build-up rate data based on the historical build-up rate data and the initial build-up rate data; determining the drilling deviation level based on the actual build-up rate data and the designed build-up rate data; and executing a corresponding wellbore trajectory control strategy based on the drilling deviation level. The embodiments of this specification can improve the wellbore trajectory control effect, reduce manual workload, and lower drilling risks.

The invention provides an ultra-deep well large annulus flexible righting transverse vibration reduction method, which belongs to the technical field of well drilling and drilling, and comprises the following steps of: inputting pre-drilling well drilling engineering information, and calculating a whole well section drill string vibration distribution form based on an established drill string finite element dynamic model; the tripping-in positions and the number of the flexible stabilizers and the layer number and the compression space of plate springs in the flexible stabilizers are designed, and an initial vibration reduction scheme is generated; comparing the real-time vibration data with the predicted vibration distribution pattern, carrying out real-time risk assessment, carrying out dynamic optimization on the initial vibration reduction scheme according to the real-time risk assessment, adjusting the tripping-in position and number of flexible stabilizers, the number of plate spring layers and the compression space, and generating an optimized real-time vibration reduction scheme; a flexible stabilizer is put in the designated position of the drill column; when the drill column transversely vibrates and collides with the well wall, the buffer block of the flexible stabilizer is pressed, the plate spring is driven to generate radial elastic deformation, part of radial impact kinetic energy is converted into elastic potential energy of the plate spring to be stored, and radial vibration reduction is achieved.

The invention discloses an electricity-to-oil intelligent digital driving method and system adaptive to a petroleum drilling working condition, and belongs to the field of petroleum drilling engineering.The method comprises the steps that petroleum drilling data are collected through a multi-source sensor group, and the collected data are sent to an edge gateway controller to be preprocessed; a multi-source data stream obtained through preprocessing is sent to a cloud end, and a multi-source database is constructed; the intelligent torque prediction model is deployed at the cloud end, real-time estimation of the current drill bit load torque is achieved according to data in the multi-source database, and a drill bit prediction torque value is obtained; the cloud end issues the predicted torque value obtained through calculation to the edge gateway controller, and the edge gateway controller generates an actual control instruction according to the received predicted torque value. Safe and stable operation of drilling operation can be effectively guaranteed.

The invention discloses a real-time guiding control system and method for a borehole track of a wireless measurement-while-drilling instrument, and belongs to the technical field of drilling engineering.The real-time guiding control method comprises the steps that the wireless measurement-while-drilling instrument collects borehole attitude data and environmental factor data, and fusion data is generated; based on the fusion data and the historical guiding effect data, generating adaptive control parameters through an adaptive learning mechanism; performing channel adaptation processing and dynamic compensation on the adaptive control parameter to generate a compensation control signal; the compensation control signal is used for controlling the operation posture of the guiding tool, the deviation between the actual well track data and preset target well track data is calculated, and track deviation data is generated; and learning parameters of the adaptive learning mechanism are updated based on the trajectory deviation data. Multi-source data fusion perception, intelligent decision based on a self-adaptive learning mechanism, dynamic compensation communication of channel adaptation and closed-loop feedback updating based on trajectory deviation are adopted, and real-time guiding control over the well trajectory can be achieved.

The invention relates to the technical field of petroleum and natural gas drilling engineering, and discloses a deep well geological exploration tunneling parameter control system and method, and the system comprises a signal collection and synchronization module which collects drilling parameters and aligns timestamps; the initialization and modeling module is used for calculating fluid transmission time lag and blade skim-over frequency; the active disturbance generation module generates a target bit pressure instruction superposed with sine disturbance to drive load application; the two-channel feature extraction and verification module aligns the historical torque and the current pressure according to time delay and calculates the confidence coefficient in combination with the frequency; the adaptive decision and closed-loop control module uses the confidence coefficient to correct the gain and update the reference bit pressure to form a closed loop. A dual-channel verification framework based on fluid-structure interaction transmission time lag and blade characteristic frequency is constructed, the covering effect of long-distance drill column friction torque on real cutting torque in deep well operation is effectively stripped, and it is ensured that a control system only responds to effective rock breaking action.

The invention discloses a new-type barite deposit mineralization mode construction method based on a same sedimentary fault. The method belongs to the field of geological exploration and mineral resource prediction, and comprises the following steps: analyzing the earth crust cracking activity history of an earthquake-Hangjian broken basin, and recovering a basin'checkerboard 'structure prototype; by means of field geological survey and research, drilling engineering, geophysics, remote sensing geological big data and the like, north-east-east-direction and north-west-direction co-sedimentary fault networks are identified and modeled, and a deep metallogenic fluid rising and jet flow channel is determined; the metallogenic process is concluded into a hydrothermal jet flow stage and an underwater gravity flow deposition stage, deep fluid is revealed to rise, jet flow and precipitate along a fault, and an ore-rich zone of a composite seabed fan body group is formed; and a geochemical prospecting prediction model combining trace element and sulfur isotope characteristics is established. The method systematically clarifies a coupling mechanism of ore control of the same sedimentary fault, ore-forming fluid migration and gravity flow deposition, and provides a theoretical basis and a technical means for prospecting prediction of the barite deposit in the Hendan-Hangjian fault basin.

The invention discloses a real-time well drilling lithology identification method fusing double attention and wavelet transform. The method comprises the steps that firstly, drilling parameters are collected and preprocessed, and a depth domain analysis matrix is formed through a sliding window; then carrying out wavelet transform, and extracting and filtering amplitude and phase characteristics; secondly, constructing a double-attention model, capturing time domain dependence by using self-attention, and fusing time-frequency features by using cross attention; after the fusion features are subjected to linear projection and layer normalization, a lithology classification result is output through a multi-layer perceptron; according to the method, through fusion of double attention and wavelet transformation, collaborative modeling of time domain and frequency domain features is achieved, the problems that long-range dependence modeling is weak, cross-domain fusion is difficult and the like in a traditional method are solved, lithology can be accurately recognized in real time, and the method is suitable for being used for a large-scale popularization and application. The method does not need to depend on expensive logging-while-drilling equipment, and has high practical value in petroleum drilling engineering.

The invention discloses a casing centralizer with a pipe diameter adjusting function, and relates to the technical field of petroleum and natural gas drilling engineering equipment, the casing centralizer comprises two fixing rings which are symmetrically distributed left and right, the outer surface of each fixing ring is provided with a plurality of fixing seats at equal intervals in the circumferential direction, and each fixing seat is rotatably connected with a connecting plate; an elastic plate is arranged between the left connecting plate and the right connecting plate in the horizontal direction, and the two ends of each elastic plate are rotationally connected with the two adjacent connecting plates respectively. By rotating the adjusting bolt, the driving screw rod and the fixing pipe are in threaded transmission, and the distance between the two fixing rings is accurately controlled, so that the annular supporting frame formed by the connecting plate and the elastic plate generates controllable radial deformation; stepless adjustment of the supporting outer diameter is achieved, different borehole sizes are accurately matched, the problem that a centralizer with a fixed size is insufficient in supporting or difficult to descend is solved, it is ensured that a casing pipe is efficiently centered, and a foundation is laid for forming a uniform cement sheath.

The invention relates to the technical field of petroleum and natural gas drilling engineering, and particularly discloses a multi-field coupled complex fractured formation fracture width distribution inversion method, which is characterized in that a drilling fluid leakage model considering a fluid-solid coupling effect is constructed based on a porous elastic mechanics theory, and a roughness correction factor is introduced to correct a traditional cubic law; the application of the Darcy law in the matrix is perfected, a matrix and crack coupled drilling fluid leakage mathematical model is established, the influence rule of key parameters such as fluid viscosity, pressure difference and crack width on the drilling fluid leakage amount is obtained through numerical simulation, and on the basis, the drilling fluid leakage amount is calculated. According to the method, the crack width multiple linear regression inversion equation with the fluid viscosity, the pressure difference and the accumulated leakage as independent variables is established, the inversion equation has high prediction precision and practicability and can be used for rapidly and accurately inversing the crack width on site, and theoretical and technical supports are provided for multi-scale fractured formation leakage mechanism understanding and leakage prevention and control optimization.

The invention relates to the technical field of underground resource drilling and production engineering, and discloses a rescue well underground detection method based on ultrasonic probes and a related device.A plurality of ultrasonic probes are arranged in a rescue well applying the detection method in the circumferential direction of the rescue well, and the ultrasonic probes are used for emitting detection sound wave signals to the surrounding stratum of the rescue well; receiving a reflected sound wave signal from the target well; the detection method comprises the following steps: acquiring a reflected sound wave signal received by each ultrasonic probe; the position of the target well relative to the rescue well and the distance between the target well and the rescue well are determined according to the reflected sound wave signals. The problem that the detection performance of an existing active magnetic distance measurement scheme based on a current injection mode is limited in a high-resistance stratum environment can be solved, and measurement response errors caused by divergent current of a stratum loop can be avoided.

The invention provides a construction method and application of a well site real-time data pre-training model, and belongs to the crossing field of petroleum engineering and artificial intelligence. Carrying out discrete marking; the method comprises the following steps: constructing a self-supervised time sequence model based on a Transform architecture, and fusing position coding and an embedding mechanism; designing a self-supervised task, and setting multiple task targets such as mask prediction, comparative learning, sequence judgment and future state prediction; performing end-to-end training on the model through a joint loss function, and extracting deep time sequence features; deploying the pre-training model in an actual well site environment, and executing tasks such as anomaly detection, working condition recognition and trend prediction; and carrying out model optimization and iteration. The invention further provides application of the method in the field of intelligent monitoring of oil and gas drilling engineering. According to the method, the problems of high dependence on manual labeling, weak model generalization ability, insufficient real-time adaptability and the like of a traditional method are solved, and the method has good engineering deployment and cross-well-site popularization value.

The invention relates to the technical field of drilling engineering and geological safety monitoring, in particular to a water drilling hole wall stability early warning method based on slurry parameters and drilling tool postures, which comprises the following steps of: 1, sensing and acquiring multi-source heterogeneous parameters in real time; 2, constructing a hole wall stability evaluation index system; step 3, constructing a virtual drilling digital twinborn model and performing stress simulation; according to the method, synchronous acquisition and fusion analysis are carried out by integrating the mud performance parameters, the drilling tool attitude parameters and the stratum response parameters, a multi-source heterogeneous hole wall stability evaluation index system is constructed, multi-source information fusion algorithms such as a D-S evidence theory and Kalman filtering are adopted, the limitation of dependence on a single parameter in the prior art is overcome, and the method is suitable for large-scale popularization and application. According to the method, the hole wall state can be comprehensively judged from multiple dimensions of mechanical balance, slurry wall protection efficiency and drilling tool disturbance, the comprehensiveness of risk identification and the accuracy of early warning signals are remarkably improved, and misjudgment or missed judgment caused by information islands is avoided.