1395 results about "Oil production" patented technology

The invention provides an oil extraction equipment fault monitoring system and method, and belongs to the technical field of oil extraction equipment fault monitoring. The method comprises the following steps: acquiring operation data of oil extraction equipment, and performing feature extraction on the acquired operation data to obtain a target feature vector; fusing the obtained target feature vector with a historical fault case library and an oil extraction equipment physical constraint equation, and constructing a dynamically updated knowledge graph; based on the space-time causal adversarial network, analyzing the distribution offset of the target feature vector in the space-time dimension, detecting an abnormal event and outputting an abnormal type label; and according to the output abnormity type label, combining with a knowledge graph, tracing a propagation path of an abnormal event, and calculating a fault probability of a root cause component through a Bayesian network so as to carry out monitoring and early warning on the oil extraction equipment. According to the method, accurate fault detection and root cause positioning are realized through multi-modal data fusion and the dynamic causal knowledge graph, and the equipment shutdown risk and the operation and maintenance cost are remarkably reduced.

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

The invention relates to the technical field of data control, in particular to a digital visual control method and system for a grease production line. The method comprises the following steps: acquiring full-process physical data; performing noise filtering on the whole-process physical data to obtain whole-process noise filtering data; abnormal data detection is carried out on the whole-process noise filtering data, and abnormal data are removed to obtain a whole-process data set of the grease production line; therefore, by constructing a feature driving mechanism of physical-data fusion of the grease production line, the problems of low data utilization rate, insufficient prediction precision and control optimization lag in a traditional grease production line are solved, and the operation efficiency and decision intelligent level of the grease production line under complex working conditions are improved.

The invention provides an automatic history fitting method for gas drive numerical reservoir simulation, which comprises the following steps of: 1, establishing a gas drive numerical simulation mathematical model, and correcting the gas drive numerical simulation mathematical model by using a gas drive PVT phase state fitting experiment; 2, solving the corrected gas drive numerical simulation mathematical model obtained in the step 1, performing parameter analysis, and screening main control factors influencing accumulated oil production; 3, generating a numerical simulation training sample set based on an orthogonal experiment, and obtaining the main control factor parameter initial value constraint screened out in the step 2 through a machine learning algorithm; step 4, establishing a multi-parameter fitting objective function for realizing historical fitting; and step 5, using the main control factor parameter initial value constraint obtained in the step 3, performing iterative calculation through a projection gradient method, fitting the target function established in the step 4, and terminating when a convergence condition is satisfied. According to the method provided by the invention, the constraint parameter values can be adaptively calculated, automatic historical fitting is completed, and the definition of the fitting parameter range does not depend on empirical and experimental determination any more.

The invention provides an oil-water separation real-time monitoring system in a petroleum extraction process, and belongs to the field of image processing, and the method comprises the following steps: obtaining an oil-water separation image of each frame and an emulsion layer area in the oil-water separation image of each frame; obtaining the separation degree of the oil-water separation image of each frame according to the gray level distribution of the pixel points in the emulsion layer area of each frame and the distribution difference of the gradient values of the pixel points in the emulsion layer areas of each frame and the first frame; and setting the length of the time interval, and comparing the separation degrees of the oil-water separation images of different frames in the same time interval to obtain the oil-water separation effect in each time interval. The invention aims to solve the problem that the oil-water separation effect in each time interval cannot be accurately judged directly through an oil-water separation image due to low image discrimination in the oil-water separation process in the oil extraction process.

The invention discloses an oil reservoir injection-production optimization method based on an improved multi-objective particle swarm algorithm, and belongs to the technical field of oil and gas field development. According to the method, an attention mechanism, a Transform and a long-short-term memory network are introduced based on a relational graph convolutional network, geological features and production system information are combined, inter-well water content prediction is taken as a target, an HSTMF model is constructed, an injection-production well production system does not need to be adjusted, the calculated amount is greatly reduced, and the prediction precision is remarkably superior to that of a traditional method; in the aspect of optimization algorithms, a Cauchy disturbance variation mechanism is introduced into a genetic algorithm and combined with a particle swarm optimization algorithm to form a new optimization strategy, a real-time closed-loop collaborative oil reservoir management framework is constructed in combination with the moisture content prediction capability of an HSTMF model, the net present value and the total oil production are effectively increased, the total moisture content is reduced, and good practical application value is shown.

The invention provides a WaveNet-BiLSTM-ATA oil well yield prediction method based on PSO optimization, and the method is characterized in that the method comprises the following steps: 1) collecting oil well time sequence characteristic data; 2) data cleaning and preprocessing; 3) executing data formatting and standardization operation to adapt to model test requirements; 4) dividing a training set and a test set according to oil well models; 5) screening important features of the oil well by adopting an isolated forest and a Pearson's correlation coefficient method, and constructing a daily oil production data set; 6) sequentially inputting the oil well characteristics in the step 5) into a WaveNet module and a BiLSTM module, introducing an ATA mechanism at the same time, and building a prediction model; 7) optimizing model hyper-parameters by using a PSO algorithm; and 8) carrying out grouping performance verification by adopting an independent test, completing model evaluation by calculating MAE, RMSE and MAPE indexes, and outputting a prediction result at the same time. According to the method, the WaveNet local feature extraction capability, the BiISTM bidirectional time sequence modeling advantage and the PSO efficient parameter optimization characteristic are fused, so that a relatively good prediction effect is obtained in a specific oil well test.

The invention relates to the technical field of oil extraction and water reduction, in particular to an oil extraction and water reduction combined multi-source heating system which comprises an oil storage and water reduction separator, a liquid inlet is formed in one side of the top of the oil storage and water reduction separator, an exhaust port is formed in the middle of the top of the oil storage and water reduction separator, and a water outlet and an oil outlet are formed in one side of the bottom of the oil storage and water reduction separator. The oil storage and water reduction separator is used for receiving produced liquid with high water content in an oil well, removing a water phase and a gas phase through physical separation, outputting an intermediate oil phase with low water content to the heating furnace, and conveying the separated high-temperature water phase to the multi-source heat pump unit for heat recovery. Compared with the prior art, the oil storage and water reduction separator is arranged to be matched with the waste heat recovery multi-source heat exchange unit, most of water phases in produced liquid are rapidly removed, the follow-up treatment burden is relieved, the conveying efficiency is improved, multi-source cooperative energy supply is achieved, dependence on traditional fossil energy is reduced, and the energy utilization efficiency is improved; the environment-friendly property and the sustainability are good.

The invention provides a lubricating oil production multi-source data fusion analysis method which comprises the following steps: acquiring a stirrer rotating speed signal, acquiring pressure distribution data of a corresponding pipeline, and if the stirrer rotating speed fluctuation range exceeds a preset threshold range, marking that the stirring rotating speed is abnormal; analyzing the pressure distribution change of the pipeline when the stirring rotating speed is abnormal, combining the monitored viscosity change of the oil fluid and the difference of the oil circulating flow speed, and performing fusion calculation to obtain a shear stress distribution index in the pipeline; if the shear stress distribution index is abnormal, the suspension state of oil particles and the deposition rate of pollution particles are detected, and if the suspension state and the deposition rate exceed corresponding preset threshold values, the oil pollution diffusion degree is determined through the suspension state and the deposition rate; and identifying abnormal equipment according to the abnormal signal time sequence correlation, acquiring operation parameters of the abnormal equipment, synchronously analyzing to obtain equipment operation state coupling, analyzing equipment fault chain reaction characteristics, and generating an equipment chain abnormality distribution diagram according to the chain reaction characteristics.

The system comprises a plurality of oil pipes and a plurality of pipe penetrating packers, the oil pipes are arranged on the inner side of a casing pipe, every two adjacent oil pipes are connected through an intelligent control switch, and each intelligent control switch is used for opening and closing a channel, communicating with the inner side of the oil pipe, of the outer side of the oil pipe. The intelligent control switch is provided with an in-pipe pressure gauge for detecting the pressure inside the oil pipe and an out-pipe pressure gauge for detecting the pressure outside the oil pipe; the pipe penetrating packers are used for dividing the outer side of an oil pipe and the inner side of a sleeve into a plurality of independent cavities, and each intelligent control switch is located between the two corresponding pipe penetrating packers. The separate mining method is implemented based on the underground intelligent separate mining system. The intelligent control switch has the beneficial effects that each intelligent control switch is provided with the in-pipe pressure gauge for detecting the pressure on the inner side of the oil pipe and the out-pipe pressure gauge for detecting the pressure on the outer side of the oil pipe, so that the corresponding real-time oil layer pressure is obtained, reasonable working parameters can be formulated, and the optimal oil yield is obtained.

The invention relates to the technical field of oil production engineering, in particular to a fracturing and plugging method for a chemical flooding injection low-efficiency well of a middle-shallow sandstone thin and poor oil layer. The method comprises the steps that a target fractured well is determined, historical fracturing data and dynamic profile test data of the target fractured well are collected, and a fracturing plugging target layer is determined; according to historical fracturing data analysis and an ASP flooding core blockage rule experiment, the fracture radius of a target layer, the ASP flooding reservoir blockage radius, the reservoir physical property and fracturing scheme of the target layer, the lower limit of the quality-divided injection permeability of the target layer and the damage degree caused by fracturing residues of the target layer are obtained; the method comprises the following steps: sequentially acquiring the dosage of a blocking remover for chemical blocking removal of a target layer, slug combination parameters, fracture parameters of a fractured position, a post-fracturing quality-divided injection process and post-fracturing injection mode combination, performing fracturing blocking removal on the target layer according to the acquired data, and collecting fracturing blocking removal effect data in real time. According to the method, the operation efficiency is improved, and meanwhile the construction cost is reduced.

The invention discloses an oil extraction machine ground rotating machine fault diagnosis method based on a parallel diagnosis model, and the method constructs a double-branch fusion diagnosis model based on deformable convolution DCN and Transformer in order to solve the problems that fault features of an oil extraction machine rotating machine are difficult to extract under a strong noise condition and the anti-interference capability of a diagnosis model is insufficient. The model combines the local feature adaptive extraction capability of deformable convolution and the global time sequence modeling advantage of Transform, the diagnosis robustness in the noise environment is effectively improved through a multi-dimensional feature fusion mechanism, and the experimental result shows that the method has high average diagnosis accuracy under the condition of low signal-to-noise ratio. And the fault diagnosis precision of the rotating machine on the oil extraction machine well is obviously improved.

The invention discloses a water injection regulation and control method based on deep reinforcement learning under data and model fusion driving, and the method comprises the following steps: collecting operation parameter data under an oil field injection-production working condition, and carrying out the data preprocessing; a model-free water injection regulation strategy is designed, a traditional oil yield prediction model is removed, and a water injection action is directly generated based on an environment state by constructing a state-action space containing the parameters; a soft actor-commentator (SAC) algorithm and a long short-term memory network (LSTM) collaborative decision framework are adopted, an oil reservoir parameter time sequence rule is captured by using LSTM to provide state prediction for SAC, and water injection and oil extraction joint debugging of a well group is optimized in combination with a state-driven dynamic reward function; a priority experience playback mechanism is introduced to optimize SAC training, and the action generation efficiency is improved. According to the model constructed by the method, the calculation complexity is remarkably reduced, the oil production is improved, the water content is reduced, and the method has relatively high practical value and economic benefits and is particularly suitable for water injection regulation and control scenes under complex oil reservoir conditions.

The invention relates to the technical field of oil exploitation equipment, in particular to an oil reservoir pressurizing device which comprises a plurality of setting devices arranged on the outer wall of a sleeve shell in the axial direction of the sleeve shell, the outer walls of the setting devices are attached to the well wall of a water injection well, the space between the sleeve shell and the well wall is divided into a first gap and a second gap, and the first gap corresponds to an oil reservoir low-permeability layer; the second gap corresponds to an oil reservoir high-permeability layer; the shunting mechanism comprises a first nozzle communicated with the first gap and a second nozzle communicated with the second gap; and the hydraulic flow conversion part communicates with the reversing valve, the first nozzle and the second nozzle, and the hydraulic flow conversion part has a first state of introducing gel into the second nozzle, a second state of introducing gel into the first nozzle and a third state of introducing high-pressure water into the first nozzle and the second nozzle. The problem that a high-permeability layer is not blocked thoroughly or a low-permeability layer is excessively polluted is effectively solved.

The invention relates to the technical field of oil exploitation equipment, and discloses an underground filling tool for oil exploitation, which comprises a sealing element for sealing a section to be filled, an activating element for activating the sealing element is arranged on the sealing element, and a removing element for removing residual materials on the well wall is arranged at the bottom end of the sealing element; through the gravity driving design of the counterweight ring of the activating piece, expansion activation of the sealing gasket can be achieved without an additional hydraulic or electric device, the underground structure is simplified, the fault probability in the high-temperature and high-pressure environment is reduced, the four sets of evenly-distributed top plates are matched with the downward moving groove, the guiding effect of the limiting block and the limiting groove is combined, and the sealing gasket is more stable. The balance weight ring is ensured to be balanced in stress when rotating and aligning, deflection and jamming are avoided, the synchronous plate and the lower pressing plate are symmetrically distributed to ensure that the sealing gasket is uniformly stressed, the synchronous plate and the lower pressing plate are synchronously expanded and attached to the well wall, the stability and efficiency of sealing activation are improved, and manual operation errors are reduced.

The system comprises a plurality of oil pipes and a plurality of pipe penetrating packers, the oil pipes are arranged on the inner side of a casing pipe, every two adjacent oil pipes are connected through an intelligent control switch, and the size of an opening of each intelligent control switch can be adjusted so as to adjust the flow entering the inner side of the corresponding oil pipe from the outer side of the corresponding oil pipe; the pipe penetrating packers are used for dividing the space between the outer side of the oil pipe and the inner side of the sleeve into a plurality of independent cavities, and each intelligent control switch is located between the two corresponding pipe penetrating packers. The method is implemented based on the underground cable intelligent separate mining system. The device has the beneficial effects that the flow entering the inner side of the oil pipe from the outer side of the oil pipe of the corresponding oil layer is controlled through each intelligent control switch, so that the liquid inlet ratio of each oil production layer is optimized, the pressure of each oil layer is in a proper range, interlayer interference during mixed production is reduced, and the crude oil yield is improved.

The invention discloses a macromolecular demulsifier as well as a preparation method and application thereof, and belongs to the technical field of oil exploitation. The polymer demulsifier has a structure as shown in a formula (I): # imgabs0 # formula (I); wherein R is selected from any one of NH2-(CH2CH2NH) m-CH2CH2, and m represents an integer from 1 to 4; n represents an integer from 25 to 600; a represents an integer from 60 to 200; and b represents an integer of 40-150. The macromolecular demulsifier has a good demulsification effect, improves the water phase cleanliness of demulsified dehydrated water, is suitable for various working conditions and environments, and solves the problem of difficulty in treatment of crude oil produced in oil fields in the prior art.

The utility model relates to the field of oil extraction equipment, in particular to a sucker rod centralizer which aims at solving the technical problem that an existing centralizer cannot adapt to oil pipes of different specifications. The sucker rod centralizer comprises a fixing ring, the movable ring and the fixed ring are coaxially arranged; the plurality of groups of righting mechanisms are distributed around the axis of the movable ring at intervals; the righting mechanism comprises two supporting rods and a sliding assembly, one ends of the two supporting rods are hinged to the sliding assembly, and the other ends of the two supporting rods are hinged to the side wall of the fixed ring and the side wall of the movable ring respectively. The driving mechanism is arranged on the fixed ring and is in transmission connection with the movable ring so as to drive the movable ring to move in the axial direction of the movable ring. According to the sucker rod centralizer, the movable ring can be separated from or get close to the fixed ring in the length direction of the sucker rod through the driving mechanism, so that the angle between the upper supporting rod and the lower supporting rod is adjusted, the position of the sliding assembly is adjusted, the sliding assembly can adapt to oil pipes with different inner diameters, and the adaptability is improved.

The invention relates to a variable-scale fracturing filling parameter design method considering longitudinal reservoir difference, which comprises the following steps of: (1) correcting a three-dimensional geologic model of a target reservoir based on numerical simulation parameters of a fracturing filling well to obtain a stratified geologic model of stratified physical property data reflecting the longitudinal physical property difference of the target reservoir; step (2), based on layered physical property data of the layered geologic model and historical stage cumulative oil production data, considering an inter-layered parameter interaction effect at the same time, and performing layered master control parameter screening; (3) training a deep learning model by taking the screened hierarchical master control parameters as input and the stage cumulative oil production as output to obtain a trained hierarchical stage cumulative oil production prediction model; and step (4), taking layered physical property data as constraints, taking the layered stage cumulative oil production prediction model and the construction cost model as objective functions, sampling a multi-objective genetic algorithm to carry out variable-scale self-kernel design on fracturing parameters of each layer, and outputting a final fracturing parameter combination of each layer.

A method and apparatus for forecasting oil production from an oil well in a geological formation includes receiving a plurality of sets of predicted geological data, for each of the plurality of sets of predicted geological data, determining a probability for the predicted geological data of the formation, iteratively selecting one of the plurality of sets of predicted geological data using Monte Carlo sampling based on the determined probabilities, assigning the selected set of predicted geological data to a cluster of historical data, and for each set of historical data of the cluster generating a predicted oil production rate as a function of time utilizing a machine learning based oil model, generating, based on the predicted oil production rates, a forecasted oil production rate, determining, based on the forecasted oil production rate, a preferred operating parameter for the well, and operating based on the preferred operating parameter.

The invention discloses an oil well production multi-step prediction method based on multi-feature fusion, which relates to the field of electrical digital data processing, and comprises the following steps: carrying out double standardization processing of numerical standardization and spatial dimension normalization based on statistical distribution on an original daily oil production data set; generating a structured derived feature set comprising a first-order difference feature, a sliding sum feature and an accumulation sum feature by using the time sequence data; performing feature space mapping on the input feature set through a linear transformation module in combination with a nonlinear activation function; performing missing information injection on the observation data by adopting a context information mask mechanism, and constructing a time subsequence containing a controllable missing mode; performing hierarchical feature coding on the time subsequences by using a multi-scale expansion convolution encoder, and extracting a time sequence dependency relationship under different time scales; and based on the generated context embedding representation, realizing future multi-time-step daily oil production sequence prediction of the target oil well through a deep learning prediction model. The prediction precision is improved.

The plunger pump for oil pumping comprises a cylinder body, a plunger, a threaded driving rod, a liquid inlet one-way valve port, a liquid outlet one-way valve port and a rotary power output device, the plunger is arranged in the cylinder body in a sliding mode and can do reciprocating motion, and a sealed working containing cavity is formed by one end of the plunger and the top of the cylinder body; the other end of the plunger is connected with the rotating power output end of a threaded driving rod, and the rotating power input end of the threaded driving rod extends out of the cylinder body to be connected with the rotating power output end of a rotating power output device. The liquid inlet one-way valve port is circumferentially arranged on the upper portion of the cylinder body, an inlet of the liquid inlet one-way valve port is communicated with an oil layer, an outlet of the liquid inlet one-way valve port is communicated with the sealed working cavity, the liquid outlet one-way valve port is arranged on the top of the cylinder body, and an inlet of the liquid outlet one-way valve port is communicated with the sealed working cavity and an outlet of the liquid outlet one-way valve port is communicated with an overground oil outlet pipeline. The plunger pump for oil pumping is convenient to install and convenient to pump oil, and meanwhile the defect that an oil pumping unit does work on an oil pumping rod in the working process is overcome.

The invention relates to the technical field of productivity evaluation, in particular to a thickened oil polymer flooding reservoir horizontal well productivity evaluation method and system.The method comprises the following steps that injection volume and daily fluid production data are collected to construct a sequence, rate transition and fluid volume inflection point judgment response starting are recognized, the fluid volume rising trend is analyzed to recognize a growth section, and the productivity of a horizontal well is evaluated. Dividing sub-intervals, evaluating fluctuation to determine an oil production stable section, and determining response association by combining concentration and a ratio to obtain a productivity section distribution interval. According to the method, the time sequence is constructed by collecting the daily injection volume, the rate transition is recognized, the production liquid increasing inflection point is extracted, the response starting moment is measured, the state of the horizontal well is recognized more accurately, based on the daily production liquid change comparison before and after starting, the daily oil production fluctuation in the lagging stage is evaluated, the stable oil production stage is screened, and the effective time of evaluation focusing is ensured. And a continuous descending starting point is delimited by comparing periodic oil production change, and the injection state is analyzed by combining the injection concentration and the liquid production ratio, so that productivity response staged identification is realized, and a basis is provided for adjustment.

The invention discloses kinematic viscosity detection equipment for lubricating oil production and processing, and relates to the technical field of lubricating oil kinematic viscosity detection.The kinematic viscosity detection equipment comprises a base and a second supporting frame, the top end of the base is fixedly connected with a second fixing plate and the second supporting frame, and one end of the second supporting frame is fixedly connected with an operation screen; a positioning mechanism is fixedly connected to one end of a second fixing plate, a moving mechanism is fixedly connected to one end of a second supporting frame, a detection mechanism is arranged at the top end of a carrying plate, and through the synergistic effect of a first coil, a second coil and a magnet block, an inner shaft is made to suspend on the inner side of an outer cylinder; therefore, mechanical friction interference of a traditional bearing is thoroughly eliminated, and rotation blocking of the inner shaft is avoided. Compared with a measurement mode depending on a torque spring, the design not only saves the tedious step of spring calibration, but also solves the measurement error caused by spring lag, and remarkably improves the overall detection precision.

The present application relates to the technical fields of oil extraction water injection, and more particularly to an oil extraction wellhead water injection device, comprising a mixing tank, a water inlet pipe and a first auxiliary pipeline are connected to a water inlet of the mixing tank, a mixing cavity and a reduced diameter cavity are arranged in the mixing tank from top to bottom, a conical hopper is fixedly connected in the mixing cavity, a plurality of first through grooves are formed in an inner wall of the reduced diameter cavity, the water inlet pipe is connected to a water inlet of a filter through a second auxiliary pipeline, the other end of the first auxiliary pipeline is connected to a water outlet of the filter, a water outlet pipe is connected to the water outlet of the filter, the water outlet pipe is connected to the water inlet of the filter through a third auxiliary pipeline, a dosing mechanism and a self-mixing mechanism are arranged on the mixing tank; the water and the medicine are automatically mixed when flowing, the spiral vortex is driven completely by the kinetic energy of the fluid itself, the three modes are flexibly switched, the addition of different medicines is adapted, and the pertinence and efficiency of the oil extraction water injection are improved.

The invention belongs to the technical field of oil exploitation equipment, and particularly provides a screw pump rotor structure optimization method and system based on wear trajectory quantization, and the method comprises the steps: obtaining the contact conditions of the motion trajectory of feature points on the surface of a rotor and the inner wall of a stator in different angle intervals according to the motion trajectory of the surface of the rotor; calculating the geometric wear strength of each feature point according to the contact condition; and optimizing the rotor structure according to the geometric wear strength so as to homogenize the wear. From the perspective of structure optimization, the problem of uneven wear can be more effectively solved by quantifying the wear track and optimizing the rotor line type in a segmented manner.

The invention discloses a well spacing method for heating a stratum by adopting an electric heating well. The method comprises the following steps: determining a well pattern type of the electric heating well adopted by a target stratum; according to the well pattern type of the electric heating well, boundary electric heating wells are arranged in combination with a preset rule; and obtaining a final electric heating well pattern according to the boundary electric heating well and the electric heating well in the electric heating well pattern type.

The invention relates to a method for improving the huff-puff effect of carbon dioxide, which comprises the following steps of: when liquid carbon dioxide is injected, monitoring horizon data by using an oil well profile logging instrument, judging whether the liquid carbon dioxide is a target horizon or not by sucking the horizon data, and smoothly injecting the liquid carbon dioxide into the target horizon by adopting a process adjustment or layered injection method, so as to improve the huff-puff effect of the liquid carbon dioxide. The carbon dioxide utilization rate, the measure effect and the effective rate are improved, and the remaining oil potential tapping effect and the oil well recovery rate are improved; when the oil increasing amount of well opening oil production does not reach the standard, whether the output layer is the target layer or not continues to be monitored, if the output layer is not the target layer, the measure target layer can be replaced in time, the layered pipe column structure can be adjusted when liquid carbon dioxide is injected, the purpose that the output layer is the target layer is achieved, and the measure effective rate and effect are improved.

The invention provides a cluster spacing design method based on a three-dimensional geologic model, and relates to the technical field of oil and gas exploitation, and the method mainly comprises the steps: building a three-dimensional geologic model through integrating multivariate data such as geology, rock mechanics and ground stress, and precisely simulating an underground structure and physical attributes. The numerical simulation technology is used for contrastively analyzing the fracture three-dimensional equilibrium expansion and pore pressure influence range when the cluster spacing is reduced and increased, the fracture equilibrium index and the pore pressure difference are calculated, and the optimal cluster spacing interval capable of ensuring fracture equilibrium expansion and efficiently utilizing matrix resources is determined. And by combining yield prediction and economic benefit analysis, the accumulated oil production and fracturing cost under different cluster spacing schemes are compared and selected, and the cluster spacing with the best economic benefit is selected. The method successfully solves the problem that the optimal cluster spacing cannot be accurately obtained in a traditional mode, guarantees balanced expansion of cracks, maximizes matrix utilization, gives consideration to engineering safety and economic efficiency, remarkably improves the fracturing effect, reduces the cost and improves the long-term stable yield of an oil and gas well.

The invention provides a pressure control casing head for a gas production wellhead device, and relates to the field of petroleum production, the pressure control casing head comprises a casing head body, a flange plate arranged on the casing head body, a gas outlet formed in the casing head body, and a boss arranged in the casing head body, the protective plug is in threaded connection with the casing head body, and the cleaning mechanism is arranged in the casing head body. The cleaning mechanism comprises a sliding cavity formed in the casing head body, in order to solve the problems that in the prior art, a casing head is tedious in operation and low in working efficiency, through the arranged cleaning mechanism, automatic cleaning of the boss is achieved, and the working efficiency is improved; the cleaning mechanism is arranged, so that the problem that the hanger is loosened or falls off due to external force in the prior art is solved; and through the arranged cleaning mechanism, the problem that in the prior art, the air tightness between the hanger and the casing head body is affected by the air lock phenomenon is solved.