4199 results about "Natural gas" patented technology

The invention relates to the technical field of pipeline stress fatigue detection, and discloses a natural gas station elbow tee joint stress fatigue digital intelligent analysis method and system and a product. The method comprises the following steps: establishing a multi-physics field coupling digital twinborn model of the elbow tee joint, integrating a geometric structure, material attributes and a fluid-solid coupling mechanism, and simulating flow-induced vibration stress and corrosion fatigue interaction; collecting real-time multi-source data of the elbow tee joint; real-time multi-source data is utilized to update boundary conditions and parameters of the digital twin model, and material constants are dynamically corrected through machine learning, so that self-calibration of the model is realized; performing stress distribution analysis based on the updated model to obtain stress field data, and performing fatigue crack propagation prediction in combination with real-time multi-source data to generate a prediction result; and based on the prediction result, evaluating fatigue failure risks, including crack growth rate, residual life evaluation and failure probability, and outputting alarm information or optimization decision information.

The invention provides an online calibration method and system for a flowmeter of a natural gas well, and belongs to the technical field of natural gas exploitation and transportation, firstly, a multiphase flow state sensing signal in a transportation pipeline of the natural gas well and a structural deformation monitoring signal of the flowmeter to be calibrated are obtained, and then interactive interference characteristic analysis is conducted on the two kinds of signals; the method comprises the following steps: obtaining a flow state-deformation interaction interference characteristic set, generating a multiphase flow adaptive calibration factor based on the flow state-deformation interaction interference characteristic set, inputting the multiphase flow adaptive calibration factor into a metering signal processing unit to dynamically correct an original metering signal, and obtaining a corrected metering output signal; and finally, collecting matching degree data of the correction signal and the real-time multiphase flow state sensing signal to form a calibration adaptive feedback signal, thereby comprehensively considering the influence of the multiphase flow state and structural deformation, and improving the metering precision and reliability of the flowmeter.

The invention relates to the technical field of pipeline safety monitoring, and discloses an online lossless real-time monitoring system for micro-strain of an in-service natural gas pipeline. A micro-strain data acquisition unit of the system acquires a micro-strain data set on the surface of the in-service natural gas pipeline in real time. And the three-dimensional strain field reconstruction unit receives the data set and executes three-dimensional strain field reconstruction processing to generate strain distribution characteristics of the pipeline. And the life prediction model analysis unit calls a pre-trained life prediction model to carry out nonlinear analysis processing on the strain distribution characteristics, and outputs a residual life prediction value and a key risk area identifier of the pipeline. The environmental factor compensation unit performs environmental factor compensation correction processing on the residual life prediction value to generate a corrected residual life prediction value. And the maintenance strategy generation unit generates a pipeline maintenance strategy set according to the key risk area identifier. According to the invention, real-time and accurate evaluation and intelligent maintenance decision support of the health condition of the pipeline are realized.

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

An improved method and apparatus for removing acid gases and other impurities from raw biogas streams, such as biogas from landfills or biogas from controlled anaerobic digestion, is disclosed. The method provides efficient generation of high-purity renewable natural gas from raw biogas. The biogas is treated in a multi-stage membrane system integrated with compression equipment. The membrane separation units are arranged into interconnected high-pressure and low-pressure gas recycling loops powered by high-pressure and low-pressure compressors. The multi-stage membrane system can be integrated with deoxygenation and auxiliary nitrogen removal systems. The combined system provides for the generation of efficient contaminant removal from raw biogas to generate high-purity methane products with reduced compression energy consumption.

The invention provides a static mixer with a bionic starfish type inlet structure and a mixing method thereof. The static mixer comprises a shell, a cavity is formed in the shell, one end of the shell is provided with an air inlet communicating with one end of the cavity, and the other end of the shell is provided with an air outlet communicating with the other end of the cavity; an air inlet pipe set is arranged at the end, close to the air inlet, of the shell and comprises a center air inlet pipe extending in the axial direction and five peripheral air inlet pipes evenly distributed in the circumferential direction of the center air inlet pipe. The central air inlet pipe and the peripheral air inlet pipe form a bionic starfish type inlet structure for simulating a central disc and a radiation wrist structure of starfish; a plurality of spiral pieces arranged in the axial direction of the cavity are arranged in the cavity, and the arrangement angles of the adjacent spiral pieces are different. By means of the bionic starfish type inlet structure design, hydrogen is evenly dispersed to the whole mixing area, the mixing uniformity of natural gas and hydrogen is effectively improved, and meanwhile the risk of hydrogen embrittlement is delayed.

A natural gas filling device reliable in sealing is disclosed. The device is characterized in that the device comprises a liquid filling gun, a liquid receiving component matched with the liquid filling gun and used for filling a gas cylinder with liquid, and a gas returning component communicated with the gas outlet of the gas cylinder; the liquid filling gun is provided with a first outer shell, a first rotating fastener disposed in the first outer shell and connected to the first outer shell and the inner wall of which is provided with a symmetrical spiral groove, a first valve body between the first rotating fastener and the first shell, and a first valve core disposed in the first valve body and containing a liquid inlet and a liquid outlet; and the liquid receiving component is provided with a first shell, wherein the head of the first shell extends into the first rotating fastener and is in sealing match with the tail part of the first valve body, and the periphery of the first shell is provided with a first pivot pin engaged with the spiral groove in the first rotating fastener. The device is convenient in maintenance, replacement and operation of quick-wear parts and convenient to use. The device can be used for other low-temperature liquid media besides LNG and is simple in structure, low in cost, convenient in operation and reliable in sealing.

The present invention relates to the field of pipeline leakage monitoring. Disclosed is an oil and gas pipeline leakage wave identification and monitoring system. In the present invention, an mCNN is combined with LFLBs for performing feature extraction on an acoustic wave signal collected by a DFB, and the collected data improves information completeness; a three-way parallel one-dimensional CNN used in the present invention exhibits good temporal resolution and sensitivity to high-frequency feature transformations in signals; and the present invention integrates advantages of different scales, enabling the algorithm to learn more features, and incorporating the LFLBs to further extract high-level local features. An mCNN-LFLBs network model of the present invention exhibits significant innovation and advancement on the technical level, and also demonstrates extremely high value in actual application. The network model not only provides a novel and efficient technical means for critical fields such as natural gas pipeline inspection, but also introduces new ideas and methods to research fields related to deep learning and signal processing.

The invention relates to the field of gas concentration detection, and particularly discloses a real-time feedback and adaptive learning method for natural gas infrared spectrum measurement, which comprises the following steps: S1, acquiring infrared spectrum information of a natural gas body by using an infrared spectrometer, and constructing a historical sample set; s2, preprocessing the spectral data of the historical sample set; s3, selecting an optimal algorithm and a hyper-parameter by adopting XGBoost and Bayesian optimization; s4, constructing a qualitative model to identify gas types and match data; s5, calculating the similarity between a field sample and a historical sample through a Siamese network, and setting a threshold value to screen local data; s6, improving the KNN to construct a local dynamic quantitative model to predict the concentration; s7, processing low-similarity abnormal data by the global dynamic model, and improving the reliability by combining moving average and abnormal calibration; and S8, introducing reinforcement learning and online gradient descent to adjust parameters in real time to optimize the precision. According to the technical scheme, high-accuracy natural gas detection can be carried out in a complex environment.

The invention discloses a multielement multiphase fluid displacement coalbed methane 4D visual simulation experiment system and a multielement multiphase fluid displacement coalbed methane 4D visual simulation experiment method. The system comprises a gas-liquid mixed injection system, a Kr adsorption system, a visual triaxial core holder system, a CT scanning system and a tail gas analysis and treatment system. According to the experimental method, Kr similar to CH4 in dynamic diameter and other parameters is selected as a CT tracer to replace CH4, and 4D visualization of coal body internal pore and fracture structure evolution and Kr concentration field displacement migration process can be realized through three-dimensional reconstruction of CT images at different displacement moments and registration, gray correction and normalized concentration calculation of the images. The problem that the gas migration rule in the coal body in the displacement experiment is not clear is solved; the dynamic diffusion process inversion of the coal bed gas in the coal bed difficult to extract is realized by utilizing the distribution characteristic evolution of the Kr gas in the coal body, so that the in-situ coal body fissure structure in the coal sample and the dynamic migration law of methane in the displacement process are obtained, and the method has great significance for revealing the displacement development mechanism of unconventional natural gas such as the coal bed gas.

The invention belongs to the technical field of petroleum and natural gas development engineering, discloses a shale reservoir three-dimensional dessert prediction method based on physical-data dual drive, and solves the defects of an existing shale reservoir dessert evaluation method in the aspect of space continuity. The prediction method comprises the following steps: (1) constructing a three-dimensional attribute field, and forming a multi-channel standardized three-dimensional data volume through voxelization processing; (2) fusing multi-parameter attributes of the shale reservoir and constructing a multi-channel three-dimensional feature body; (3) constructing a dessert prediction model based on the physically constrained space-attribute joint attention three-dimensional convolutional network; and (4) calculating a comprehensive dessert index, performing dessert grading and cause analysis, analyzing and quantifying the contribution degree of each attribute to dessert grading, and analyzing the dessert connectivity and the advantage extension direction. The predicted productivity potential and fracturing potential dessert field keeps reasonable gradient change and continuous distribution in the inter-well area, and the inter-well prediction error is small.

The invention provides a deep natural gas formation cause identification and quantitative evaluation method combined with methane cluster isotope composition, and belongs to the technical field of oil-gas exploration. Based on a method of combining methane cluster isotope values (delta13CH3D and delta12CH2D2) with stable hydrocarbon isotope values (delta13CCH4 and deltaDCH4), the relative contribution of each end member of an inorganic cause and a thermal cause to deep natural gas accumulation is quantitatively analyzed according to the cluster isotope values of two methane sources, namely Fischer-Tropsch inorganic synthesis and organic matter thermal cracking. According to the method, the multi-solution limitation caused by the fact that a traditional method only depends on the methane monomer isotope is overcome, the accuracy of deep natural gas cause type judgment is remarkably improved through the methane cluster isotope, and accurate quantitative evaluation of the proportion of different cause components in the mixed-source natural gas is achieved; and a more reliable basis is provided for exploration and development of deep natural gas resources.

The invention belongs to the technical field of petroleum and natural gas engineering, and particularly relates to a priori knowledge embedded unsupervised learning geology-engineering dessert comprehensive evaluation method, which comprises the following steps: S1, obtaining an evaluation data set of a research area, and preprocessing and standardizing the evaluation data set; s2, dividing the evaluation data set into a positive index and a negative index according to the prior knowledge, constructing positive and negative ideal points through the prior knowledge, and fusing to generate an unsupervised evaluation data set; s3, clustering is carried out on the unsupervised evaluation data set by adopting principal component analysis and an incremental online k-means algorithm; and S4, according to category labels obtained by clustering, determining geological-engineering dessert grades by adopting a standardized variable distance grading evaluation method, and carrying out segmented clustering optimization and perforation position optimization on the geological-engineering dessert grades. According to the method, a supervised evaluation effect is achieved through an unsupervised algorithm, comprehensive evaluation of the dessert of the fractured horizontal well section is achieved, and the problem of unlabeled data evaluation is effectively solved.

The embodiment of the invention relates to the technical field of petroleum and natural gas development, and provides an oil pipe make-up quality evaluation model construction and evaluation method and an intelligent make-up torquemeter, and the method comprises the steps: obtaining an original oil pipe make-up torque curve data set; carrying out expansion processing on the data set by utilizing a pre-trained data expansion model to obtain an expanded oil pipe make-up torque curve data set; constructing a make-up torque curve classification model based on a convolutional neural network; and training the make-up torque curve classification model by using the expanded oil pipe make-up torque curve data set to obtain a trained make-up torque curve classification model. According to the embodiment of the invention, the accuracy and efficiency of oil pipe screwing-on quality evaluation can be improved.

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

The invention relates to the technical field of geological informatization, in particular to an artificial intelligence modeling analysis method for a hydrate pilot production data set, which comprises the following steps of: acquiring logging data, lithology data, stratum physical property parameters and natural gas hydrate production dynamic data; screening, cleaning, complementing, de-noising and standardizing are carried out in sequence to obtain an artificial intelligence modeling data set; and establishing a stratum lithology machine learning recognition model, a stratum physical property machine learning recognition model and a natural gas hydrate artificial intelligence historical fitting model through a support vector machine SVM, a random forest RF and a neural network DNN. According to the method, a serial modeling architecture of lithology identification, physical property prediction and production history fitting is created, and the prediction output of the upstream model is used as the optimization input of the downstream model, so that the downstream production prediction model can learn physical property parameters which are recalculated based on machine learning and have higher precision; and the accuracy of final production prediction is improved from the data source.

The invention belongs to the technical field of welding process optimization, provides a pipeline welding parameter optimization method and system for natural gas conveying system construction, and is used for solving the technical problems of high hydrogen-induced cracking risk, parameter dependence on artificial experience and optimization process isolation lag in shallow hydrogen natural gas conveying pipeline welding. According to the method, a visual image of a molten pool, a joint thermal field, electric arc electrical parameters and environmental data are synchronously collected through a multi-source sensor, a hydrogen diffusion-thermal coupling model is constructed to calculate hydrogen concentration and stress, after reference parameters of a knowledge base are called, current, voltage and speed adjustment amounts are generated through a GBDT algorithm, and then real-time correction is conducted through a closed-loop module. According to the method, hydrogen-induced cracking can be quantitatively prevented and controlled, the weld joint failure probability in the shallow hydrogen environment is reduced, the process robustness and quality consistency are improved, the safe service life of the pipeline is effectively prolonged, and the high-safety energy conveying requirement is met.

The utility model relates to desulfurization equipment, belongs to the technical field of natural gas desulfurization, and particularly relates to desulfurization equipment for natural gas, which comprises a shell, a rotating pipe is rotatably connected to the top of the shell, and an external pipe is rotatably connected to the top end of the rotating pipe; through the arrangement of the desulfurization mechanism, natural gas is guided into liquid medicine through a gas inlet pipe and a movable pipe, so that the natural gas is in contact with the liquid medicine and is desulfurized, a motor drives a rotating pipe, a liquid spraying pipe and a liquid spraying head to rotate through two gears, so that the liquid spraying head uniformly sprays liquid, and the rotating pipe rotates to drive a fixed rod and a stirring rod to rotate; the stirring rod rotates to scatter natural gas bubbles, the stirring rod rotates to drive a vertical rod to rotate, the vertical rod rotates to drive a movable pipe and a jet head to stretch out and draw back through a strip-shaped ring, natural gas can make uniform contact with liquid medicine, the natural gas can make full contact with the liquid medicine, and the problem that the sprayed liquid medicine cannot make full contact with the natural gas is solved. The desulfurization effect on the natural gas is not ideal.

The invention provides an intelligent control method for natural gas continuous heat treatment equipment based on digital twinning, and relates to the technical field of heat treatment equipment control. The method comprises the steps that a digital twinning model of the natural gas continuous heat treatment equipment is established, and production monitoring data collected on line are utilized; the method comprises the following steps: predicting combustion process characteristics and unmeasurable states through a digital twin model, performing multi-layer strategy search by adopting a hierarchical control strategy according to a state prediction result, performing safety constraint simulation verification on the multi-layer strategy in the digital twin model, and predicting unmeasurable state parameters through a soft sensor. And introducing the quality index as a soft constraint condition into optimization control, and generating a control execution parameter meeting the constraint condition. The technical problems that in the prior art, natural gas continuous thermal treatment equipment is poor in control effect and unstable in workpiece quality are solved. The technical effects that the natural gas continuous heat treatment equipment is intelligently, accurately and reliably controlled, and the product quality is improved are achieved.

The invention discloses an electrical integrated energy system toughness planning method considering an extreme event tail risk, and relates to the technical field of integrated energy system optimization, and the method comprises the steps: firstly, considering the massive load shedding risk caused by a small-probability extreme event, and constructing a pre-disaster defense-post-disaster emergency response electrical integrated energy system toughness planning frame; secondly, comprehensively considering toughness planning cost, emergency scheduling cost and tail risk loss in a small-probability extreme scene, and establishing an objective function of a planning model; then, for a disaster stage, establishing disaster prevention resource deployment related constraints of the toughness planning model; then, considering operation constraints of the post-disaster power distribution system and the natural gas system, and establishing post-disaster emergency response related constraints; and finally, performing linearization processing on the established planning model, and calling a commercial solver for solving.

An improved method and apparatus for removing acid gases and other impurities from raw biogas streams, such as biogas from landfills or biogas from controlled anaerobic digestion, is disclosed. The method provides efficient generation of high-purity renewable natural gas from raw biogas. The biogas is treated in a multi-stage membrane system integrated with compression equipment. The membrane separation units are arranged into interconnected high-pressure and low-pressure gas recycling loops powered by high-pressure and low-pressure compressors. The multi-stage membrane system can be integrated with deoxygenation and auxiliary nitrogen removal systems. The combined system provides for the generation of efficient contaminant removal from raw biogas to generate high-purity methane products with reduced compression energy consumption.

The invention relates to a method and a device for determining the flow characteristic of CO2 in a porous medium and the distribution rule of CH4 in a pore space. The method comprises the following steps: (1) pretreating a sample; (2) system connection and air tightness inspection; (3) vacuumizing the system; (4) temperature control; (5) CH4 saturation and pressure stabilization; (6) displacement experiment and data acquisition; (7) monitoring outlet gas; and (8) data processing. The problem that in existing CO2 geological sequestration and enhanced gas production research, due to the fact that in-situ visualization of the pore size cannot be achieved, a microscopic displacement mechanism is unclear is solved, and the method aims at providing scientific basis and technical support for efficient exploitation of natural gas and effective geological sequestration of CO2.

The invention relates to a method for predicting the corrosion rate of a natural gas pipeline, in particular to the field of natural gas pipeline corrosion prediction.The high-precision dynamic early warning is achieved through the four-step cooperative technology, firstly, visible light and radar data are fused to generate a three-dimensional corrosion base film fully covering the pipeline, and blind areas caused by the complex environment are effectively eliminated; secondly, speculating corrosion probability distribution of a shielding area based on a physical constraint generative adversarial network, and solving a hidden area prediction problem; then, in combination with the stress field and historical data, deducing a space-time diffusion path of corrosion through a graph neural network, and outputting a future corrosion thermodynamic diagram; and finally, dynamically adjusting model parameters according to actually measured data to form a corrosion risk decision matrix of closed-loop optimization, thereby realizing the transformation of pipeline corrosion from passive protection to intelligent prevention in a breakthrough manner.

The invention belongs to the technical field of natural gas pipelines, and particularly relates to a self-compensation device for a metal sealing ring of a high-pressure natural gas pipeline. An outer connecting sleeve is fixedly connected to the exterior of a first pipeline, and a wear-resistant mechanism is mounted between a first inner connecting sleeve and a second inner connecting sleeve; the space between the first sealing ring and the packing sealing plate and the space between the second sealing ring and the packing sealing plate are filled with rigid packing, and the space between the first sealing ring and the second sealing ring is filled with flexible packing; a first toothed plate is fixedly connected to the exterior of the inserting plate, a sliding rod is slidably connected to the inner side of the translation groove, a clamping mechanism is installed at one end of the sliding rod, and a positioning mechanism is installed at the other end of the sliding rod; according to the device, rolling friction of balls is adopted to replace sliding contact, high-pressure vibration abrasion is greatly reduced, rigid-flexible double-filler combination elastically responds to deformation, continuous pressing of a sealing face is maintained, internal pressure impact is resisted through the right-angle toothed plate meshing self-locking design, and zero-leakage stable connection under the extreme working condition is achieved in combination with three-stage insertion rod positioning and bolt fastening.

The invention relates to the technical field of gas reservoir geology evaluation and exploration through earthquake three-dimensional data, in particular to a model and method for predicting rock stratum natural gas development potential based on earthquake three-dimensional data. The method comprises the following steps of: obtaining fault displacement and fault zone width, normalizing data to obtain strike-slip fracture deformation strength S, and predicting rock stratum natural gas development potential according to the strike-slip fracture deformation strength S, so that quantitative correlation between strike-slip fracture structure characteristics and natural gas yield is realized. The fracture reservoir control effect can be converted into a quantifiable evaluation standard from experience judgment, and meanwhile reference is provided for complex structure zone fracture reservoir control research.

The invention discloses a fuel gas metering variable component influence detection system and method, the system comprises a gas distribution regulation and control module, a standard metering module, a signal acquisition module, a closed-loop control module, a medium replacement module and a data processing module, and all the modules are connected through pipelines, circuits and data transmission lines to form a mechatronics detection system. According to the method, multiple times of vacuumizing and nitrogen filling operation are executed through the medium replacement module to isolate oxygen, and a detection medium is filled through the natural gas standard gas cylinder; the gas distribution regulation and control module regulates gas components, the standard metering module controls flow and metering volume, the signal acquisition module synchronously acquires multiple parameters, the closed-loop control module dynamically regulates and controls system parameters, and the data processing module calculates errors and stores data. According to the system and the method, the medium purity and the detection precision are improved, and the detection requirements of diversified fuel gas components can be met.

The invention discloses an intelligent natural gas productivity prediction method and device for a logging small layer joint test, and the method comprises the steps: dividing a plurality of target small layers of a target gas well reservoir according to the obtained various logging curve data of a target gas well, constructing corresponding productivity prediction machine learning models, and carrying out the prediction of the productivity of the target gas well. Predicting single-layer daily gas yield and single-layer daily water yield; for the plurality of target small layers, determining an interference coefficient representing interlayer interference of the plurality of target small layers; according to the interference coefficient and the single-layer daily gas production rate and the single-layer daily water production rate of each target small layer, obtaining a combined test productivity prediction result of the logging small layer after the interference loss is deducted; and / or, a deep learning algorithm is adopted to establish a well logging small layer combined test productivity prediction model, and a combined test productivity prediction result corresponding to the target small layer combined test is output. The method is used for improving the productivity prediction efficiency and accuracy of the natural gas combined test well.

The invention relates to the technical field of fuel gas mixing, and discloses a biological natural gas mixing control method and system.The method comprises the steps that a natural gas branch, a synthesis gas branch and a mixed gas outlet are each provided with a multi-mode sensor unit; carrying out data fusion on the detection data and the detection data of an on-line chromatographic instrument and a mixed gas rapid calorific value instrument, and estimating the low calorific value, the bloom index and the gas component percentage of the mixed gas in real time based on a constraint model and Kalman filtering; establishing a prediction controller, setting input to predict gas characteristics required by a future gas turbine, and outputting a synthesis gas valve opening degree and a natural gas valve fine tuning signal; calculating an allowable mixing proportion upper limit to form a dynamic mixing window, and adjusting the mixing proportion of the natural gas and the synthesis gas based on the dynamic mixing window when a hard boundary condition is met; and when the instability state occurs, the safety interlocking is triggered. According to the invention, rapid detection is realized, active adjustment of rapid working condition fluctuation is realized, and safety interlocking is arranged, so that the overall operation safety is improved.

The invention relates to the technical field of oil and gas field and coal bed gas field mining equipment, in particular to a wellhead suspension centrifugal pump drive double-pipe jet flow drainage and mining device and a using method. According to the technical scheme, a lower tubing head four-way joint, a middle tubing head four-way joint and an upper tubing head four-way joint are sequentially installed on a bottom flange, a motor is installed on the upper portion of the upper tubing head four-way joint, and an inner pipe plug-in pump core catcher is installed at the lower end of a submersible water injection centrifugal pump; the lower end of the inner pipe inserted pump core catcher is movably connected with an inner layer oil pipe, and a pump core installed in the double-pipe jet pump is arranged in a pump cylinder of the jet pump. The device has the advantages that due to the fact that a packer is omitted and the device is connected with the double-pipe jet pump, sand-containing liquid in a well can be sucked, and exploitation of natural gas or coal bed gas can be achieved; the inner pipe is inserted into an elastic clamping jaw of the pump core catcher to catch the pump core; and the submersible water injection centrifugal pump and the pump core can be lifted to the ground at one time by hoisting the motor at a ground wellhead, so that the maintenance is convenient.

The invention discloses a thermal-fluid-solid medium seismic wave simulation method, device, program and medium, and relates to the technical field of oil and gas resource geophysical exploration, and the method comprises the following steps: constructing a first-order thermal-fluid-solid coupling wave equation in an equation coupling form; constructing a coupling wave equation staggered network finite difference discrete format; analyzing numerical stability conditions; constructing a complete matching layer absorption boundary; and performing forward modeling simulation of seismic waves in the three-layer heat-fluid-solid coupling model according to the model parameters and the seismic source parameters. The method breaks through the assumption that the classical seismic wave propagation theory is completely elastic under the isothermal or adiabatic deformation condition, considers the influence of temperature change on the propagation of seismic waves in fluid and solid media, and improves the description precision of the propagation process of the seismic waves in the heat-fluid-solid media. And the capability of inverting the underground temperature field based on seismic wave data in the later period can be effectively improved.