635 results about "Drilling engineering" patented technology

The invention relates to a preparation method and application of a composite leakage-proof agent while drilling, and belongs to the technical field of petroleum drilling engineering. The composite leakage-proof agent while drilling is prepared from the following components in percentage by mass: 20-45% of nano composite particles, 15-35% of a multi-stage fiber reinforced network material, 10-20% of an intelligent response blocking agent, 5-10% of a high-temperature-resistant additive, 1-5% of a dispersing agent and the balance of deionized water, wherein the sum of the contents of all the components is 100%. According to the composite leak-proof agent while drilling provided by the invention, the temperature-sensitive resin with a core-shell structure is introduced, so that a three-dimensional synergistic mechanism of nano-composite particle filling-multistage fiber network bridging-intelligent response curing is realized, and efficient and environment-friendly plugging of an ultrahigh-temperature and high-pressure stratum is realized. The success rate of one-time plugging is increased from 45% to 92%, the average operation time is shortened by 60%, and an efficient solution is provided for deep and ultra-deep drilling.

The invention is suitable for the technical field of petroleum drilling engineering, and provides a drilling overflow early recognition method based on self-supervised learning, which comprises the following steps: constructing drilling multidimensional parameters into a time sequence sample by using a sliding time window, and inputting the time sequence sample into a multi-branch consistency constraint twinning network (MCSiam); the MCSiam firstly performs data enhancement on a sample, then extracts a local spatial-temporal feature and a long-term dependency relationship through an encoder composed of CNN-LSTM, and performs multi-branch comparative learning, consistency constraint optimization and predictor prediction and model optimization, and the finally trained model is used for early recognition of drilling overflow. The MCSiam is superior to a traditional method and other deep learning models in performance indexes such as accuracy, the calculation complexity is low, the applicability is wide, overflow early recognition is achieved, efficient and reliable technical support is provided for petroleum drilling safety and well control safety, and the method has good practicability and innovativeness in the field of drilling overflow early recognition.

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 is applicable to the technical field of petroleum drilling engineering, and provides a drilling overflow early recognition method based on deep reinforcement learning, which comprises the following steps of: firstly, collecting and preprocessing data, and then constructing and optimizing a drilling overflow early recognition model based on a near-end strategy optimization (PPO) algorithm, and finally, collecting data in real time in drilling operation, preprocessing the data, inputting the data into the model, analyzing the change of the characteristic quantity according to a PPO algorithm, judging whether an overflow sign exists according to an overflow drilling process flow, and if so, early warning according to a Reward function strategy. According to the method, a traditional threshold value method and machine learning are combined, a deep reinforcement learning algorithm is used for optimizing drilling parameter threshold values, characteristic quantity is monitored in real time to capture changes before overflow, historical data are self-learned to recognize an overflow mode, and dependence on field operators is reduced; meanwhile, model decision logic is displayed, understanding and trust of engineers are enhanced, more reliable overflow monitoring guarantee is provided for drilling operation, accident risks are reduced, and wellbore safety is guaranteed.

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 belongs to the field of petroleum and natural gas drilling engineering, and particularly relates to an ocean fine pressure control drilling inspection device and method. A wellhead monitoring device is used for monitoring locking information of a hoop of an annular blowout preventer; the drill floor monitoring device is used for monitoring the coupling information of the drilling tool; the gas cut monitoring device is used for monitoring gas cut information in the well pipe; the pressure monitoring and automatic control system state monitoring device is used for monitoring valve information of the wellhead device; and the remote control center is used for receiving information sent by the wellhead monitoring device, the drill floor monitoring device, the gas cut monitoring device and the pressure monitoring and automatic control system state monitoring device. According to the invention, state monitoring of different processes such as a drill floor surface, a well mouth, a gas cut state, pressure monitoring and an automatic control system is realized, information interaction with a fine pressure control well drilling control center can be realized, whole-process monitoring of an equipment operation process is guaranteed, safety of a fine pressure control well drilling operation process is guaranteed, and labor force is saved.

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 self-adaptive downhole rock annular cutting groove stress unloading percussion bit and a drilling method, and belongs to the technical field of petroleum drilling engineering. The self-adaptive downhole rock annular cutting groove stress unloading percussion bit comprises a bit connector, a cutting groove unloading barrel body and a percussion bit body; the upper end of the percussion bit matrix is fixedly connected with the lower end of the bit joint; the upper end of the grooving unloading barrel matrix is in axial sliding fit with the lower end of the bit joint; a bit pressure transmission disc spring is arranged in an annular space between the bottom end face of the drill bit connector and the top end face of the annular step. A plurality of annular grooving unloading stress teeth are arranged at the lower end of the grooving unloading barrel matrix; impact crushing teeth are arranged at the lower end of the impact drill bit matrix; when the drill bit reaches the well bottom, the annular cutting groove unloading stress teeth make contact with the well bottom earlier than the impact crushing teeth. Through the structural arrangement of the drill bit, annular grooving of shaft bottom rock is achieved, shaft bottom stress is unloaded, the efficiency of impact rock breaking is improved by reducing the strength of the rock, and the drilling speed is increased.

The invention relates to a plugging agent suitable for a malignant leakage formation and a preparation method and application thereof, and belongs to the technical field of petroleum and natural gas drilling engineering. According to the invention, through compounding of the skeleton particles, the intelligent response adhesive and the impact-resistant reinforcing component and cooperation of the skeleton particles and the intelligent response adhesive, a mechanical barrier can be rapidly formed at a crack inlet and a crack is dynamically filled, so that the plugging efficiency and the anti-scouring capability are improved, the compressive strength of a plugging layer is greater than or equal to 20MPa, and the anti-scouring time is prolonged to more than 48 hours; the intelligent response adhesive enables the plugging agent to have good intelligent response characteristics and reservoir protectiveness, self-adaptive adjustment in the plugging process is ensured through a temperature and pH dual mechanism, the biodegradation rate is larger than or equal to 70%, the reservoir pollution risk is remarkably reduced, the compressive strength of a plugging layer formed at high temperature and high pressure is larger than or equal to 20 MPa and is improved by 100% or above compared with that of a traditional plugging agent, and the plugging agent has good application prospects. The biodegradation rate is greater than or equal to 70%, and the plugging problem of the ultra-deep malignant leakage stratum is effectively solved.

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 belongs to the technical field of petroleum and natural gas drilling engineering, and particularly relates to a borehole friction coefficient segmented inversion method based on a genetic algorithm and string mechanics, which comprises the following steps of: acquiring specified data of a construction well, dividing a borehole of the construction well to be predicted into well sections with fixed lengths, defining depth ranges of the well sections, and setting a global search range of a friction coefficient; initializing the population size, the maximum number of iterations, the selection probability, the crossover probability and the mutation probability of the genetic algorithm, and performing downward inversion section by section from a wellhead section: initializing a candidate friction coefficient population of a current well section, setting a sectional friction coefficient, calculating a hook load at the tail of the current section, and calculating the maximum number of iterations; iterative optimization is carried out until a termination condition is met, and then the optimal friction coefficient of the section is output and fixed; and iteratively executing until inversion of all well sections is completed, outputting a full-borehole segmented friction coefficient profile, and realizing intelligent segmented inversion of the borehole friction coefficient by combining a tubular column mechanical model and a genetic algorithm, so that the prediction precision of the friction coefficient is improved, and the well drilling design and construction are optimized.

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 belongs to the technical field of drilling engineering monitoring, and particularly relates to a real-time monitoring method and system for carbon emission in a fracturing operation scene. The method comprises the following steps: acquiring working parameter data of each device in a fracturing operation scene; determining the current carbon emission of the equipment according to the working parameter data of each piece of equipment; and determining abnormal equipment according to the historical carbon emission and the current carbon emission of the equipment, and performing diagnosis optimization on the operation condition of the abnormal equipment. Based on hardware interface recognition and scene recognition, the fracturing operation scene can be intelligently recognized, the carbon emission of the fracturing operation scene can be monitored in real time, follow-up accurate calculation of the carbon emission is facilitated, and therefore data support is provided for accurate carbon reduction.

Provided in the present invention are a high-temperature-resistant filtrate reducer, a water-based drilling fluid and the use of the high-temperature-resistant filtrate reducer in drilling engineering in high-temperature subsurface environments. The filtrate reducer comprises carboxymethyl cellulose and a water-soluble polymer containing epoxy, and an open-loop coupling reaction of carboxyl and epoxy groups in high-temperature environments is utilized to induce in-situ self-crosslinking of carboxymethyl cellulose in high-temperature deep downhole environments, so that the filtrate loss reduction performance of the filtrate reducer at high temperatures is remarkably improved.

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 discloses a preparation method of a lignite resin drilling fluid filtrate reducer, and relates to the technical field of petroleum and natural gas drilling engineering. The method comprises the following steps: carrying out superfine grinding on lignite, carrying out alkaline hydrolysis pretreatment on waste nylon PA66, alkalizing lignite powder, carrying out sulfonation reaction on the alkalized lignite powder and phosphorous acid to introduce phosphonic acid groups, carrying out cross-linking with tetrabutyl titanate to form a three-dimensional network structure, and adding a nano-montmorillonite suspension to realize physical enhancement. A reaction product is subjected to freeze-drying, a porous structure is reserved, and then the product and polyethylene glycol 400 are mixed and granulated. By utilizing humic acid functional group grafting, inorganic-organic composite cross-linking and waste raw material recycling technologies, the product still keeps excellent filtration loss control capability at the high temperature of 200 DEG C and in a saturated salt solution, the high-temperature and high-pressure filtration loss is less than or equal to 6.50 mL, the viscosity retention rate is greater than or equal to 92.8%, the lubricating coefficient reduction rate is greater than or equal to 48.5%, and the product has the advantages of temperature resistance, salt resistance, environmental protection and low cost, and is suitable for industrial production. And the method is suitable for deep oil-gas drilling engineering.

The invention is suitable for the field of extra-deep and ultra-deep geotechnical engineering and petroleum engineering, and particularly relates to an extra-deep stratum parameter inversion and fracture prediction method based on Bayesian. By constructing a Bayesian inversion method combining a gradient lifting regression (GBR) machine learning model and a Markov chain Monte Carlo (MCMC) algorithm, deep rock mass mechanical parameter field distribution considering cross correlation among parameters is efficiently obtained, and accurate prediction of a well wall surrounding rock fracture area is achieved. Compared with the prior art, the method has the advantages of being high in prediction precision, wide in application range, high in calculation efficiency and the like, and reliable technical guarantee is provided for safe and efficient construction of ultra-deep drilling engineering.

The invention provides a while-drilling optical fiber communication system and method, and relates to the technical field of drilling engineering, and the while-drilling optical fiber communication system comprises a wellhead mechanism, a connection mechanism and a pay-off mechanism; the wellhead mechanism comprises a wellhead drill floor and a wellhead drill rod section; the connecting mechanism is located above the well mouth mechanism, can move up and down and comprises a fixing frame, a driving rod, a connecting drill rod section, a cable coiling device, a photoelectric sliding ring and a rigid connecting rod. And the upper end of the continuous drill rod section is detachably connected with the driving rod and the lower end is detachably connected with the wellhead drill rod section. A first optical fiber is arranged in the rigid connecting rod, and the rigid connecting rod is connected with a second optical fiber of the pay-off mechanism through a wet joint; the pay-off mechanism comprises a wire bin and an anchoring device, the top of the wire bin is provided with a wet connector connected with the second optical fiber, and the anchoring device fixes the wire bin and the continuous drill rod section. Through a three-stage optical fiber transmission path of'photoelectric composite cable-rigid connecting rod-wire cabin ', optical fiber communication maintenance during drill rod connection is realized, continuity and reliability of optical fiber communication during rotary drilling are ensured, and the problem of communication interruption is solved.

The invention relates to an underground HPHT area identification method and device, and belongs to the technical field of petroleum drilling engineering.The method comprises the steps that an initial temperature predicted value is calculated based on a temperature physical model, and an initial pressure predicted value is calculated based on a pressure physical model; extracting time sequence characteristic data and static characteristic data from the initial temperature prediction value, the initial pressure prediction value and the drilling data; respectively inputting the time sequence characteristic data and the static characteristic data into two base models of a completely trained integrated learning model to obtain a temperature compensation value and a pressure compensation value; and obtaining a final temperature prediction value based on the initial temperature prediction value and the temperature compensation value, obtaining a final pressure prediction value based on the initial pressure prediction value and the pressure compensation value, and identifying the HPHT region based on the final temperature prediction value and the final pressure prediction value. According to the method, the prior knowledge of the physical model and the learning ability of the integrated learning model are combined, and the prediction precision of the temperature and the pressure under the complex geological condition is effectively 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.

The invention discloses a vibration short section and an underground electric control rotary percussion rope sampler, and relates to the technical field of drilling engineering coring tools, and the vibration short section comprises a vibration short section body; the vibration nipple body comprises a lower cylinder, a control cylinder, a vibration cylinder and a guide cylinder which are sequentially connected through threads. The end surface of the lower cylinder is a hammering surface; a battery pack and a control module are mounted in the control cylinder; two electromagnets are fixed in the vibrating cylinder and are controlled by a battery pack and a control module, a retainer slidably connected in the vibrating cylinder is arranged between the two electromagnets, a permanent magnet is mounted on the retainer, two ends of the retainer slidably penetrate out of the two electromagnets respectively, and one end, penetrating into the control cylinder, of the retainer is in threaded connection with a vibrating hammer; and the vibration hammer is used for striking the hammering surface. The underground electric control rotary percussion rope sampler is provided with a vibration short section, and further comprises a spearhead, a hanging short section, a connecting short section, a sampling pipe and a drill bit. Through the interaction of the electromagnet and the permanent magnet, stable impact force can be generated, and the drilling efficiency is effectively improved.

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 invention relates to the technical field of drilling fluid cooling, and discloses a drilling fluid cooling composite shell layer phase change microcapsule and a preparation method thereof.The drilling fluid cooling composite shell layer phase change microcapsule comprises a core material and a shell material, the core material comprises a phase change material, a heat conduction material, a stabilizer, a dispersing agent, a coupling agent and a thickening agent, and the shell material comprises an inner shell layer and an outer shell layer; the drilling fluid cooling composite shell phase-change microcapsule has excellent cooling effect and environmental protection performance, when the temperature of the drilling fluid rises, the phase-change material in the microcapsule can absorb heat and generate phase change, so that the temperature of the drilling fluid is reduced, the shell material of the microcapsule can prevent the phase-change material from leaking, the stability and safety of the drilling fluid are ensured, and the drilling fluid cooling composite shell phase-change microcapsule has good application prospects. The microcapsule has the advantages of simple preparation method, low cost, wide application prospect, good cooling effect, excellent environmental protection performance, high stability, good dispersibility and the like, can be widely applied to drilling engineering, improves the drilling efficiency, protects drilling equipment, and has wide application prospect and market potential.

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.