Gas well digital intelligent plug removal method, system and equipment

Abstract

The invention relates to the technical field of oil and gas field intelligent development, in particular to a gas well digital intelligent plug removal method, system and equipment. The gas well digital intelligent plug removal method comprises the steps that plug feature information and gas well working environment information are obtained; the blockage feature information comprises at least one of components, physical features, chemical features and biological features of the blockage; the blockage feature information and the gas well working environment information are input into a gas well blockage removal analysis model, and the gas well blockage removal analysis model determines blockage removal agent reference component information according to the blockage feature information and determines blockage removal construction conditions according to the gas well working environment information; and according to the blocking remover reference component information and the blocking removal construction conditions, generating a blocking removal scheme of the gas well, and outputting the blocking removal scheme to obtain a gas well blocking removal analysis result. According to the invention, the generation efficiency of the unblocking scheme can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent development of oil and gas fields, and particularly to a digital and intelligent plugging removal method, system and equipment for gas wells. Background Art

[0002] A gas well is a surface drilling channel for extracting natural gas resources, and realizes the exploration and production of natural gas by connecting to underground reservoirs. Gas well plugging refers to the phenomenon that natural gas flow is blocked in the gas production system from the bottom of the well to the surface gas pipeline. Broadly speaking, it covers flow obstacles in the whole process (including downhole pipe strings, Christmas trees and pipelines, etc.), and specifically refers to the flow restriction in the gas production pipe string in a narrow sense. Gas well plugging is a complex process. The types of gas well plugging substances are diverse and involve various physical, chemical and geological factors. According to the plugging mechanism, downhole plugging specifically includes types such as corrosion plugging, chemical plugging, and physical plugging. Plugging will lead to problems such as a sharp drop in gas well production or even production shutdown, an increase in the oil casing pressure difference, difficulty in operation, and aggravated pipeline corrosion, and it is necessary to prevent and control it by means of optimizing production parameters, injecting inhibitors or physical plugging removal.

[0003] During the gas well production process, plugging of the wellbore and reservoir is one of the core problems leading to a decline in production capacity. At present, the detection and plugging removal plan formulation for gas well plugging in the industry mainly relies on the following technologies:

[0004] (1) A detection process dominated by manual experience: By monitoring the changes in parameters such as pressure and flow rate, and combining downhole tools (such as coiled tubing, ultrasonic detectors) to obtain local plugging information, and relying on manual experience to judge the type and location of plugging. This method has problems such as scattered data and low analysis efficiency, and the diagnostic accuracy for complex composite plugging (such as coexistence of sulfur deposition and inorganic scale) is insufficient.

[0005] (2) The limitations of a single plugging removal strategy: Traditional plugging removal solutions are mostly based on fixed processes (such as mechanical cleaning → chemical plugging removal → acid fracturing), and do not fully consider the differences in plugging substance types, formation physical properties and fluid dynamics. For example, in the scenario of coexistence of sulfur deposition and wax plugging, the existing technology lacks quantitative analysis of the synergistic effect of multiple types of plugging removal agents, resulting in poor measure pertinence and high cost.

[0006] Manually analyzing downhole detection data and laboratory test results is time-consuming and laborious. Especially in the scenarios of deep wells and ultra-deep wells, the data acquisition delay is significant, and it cannot meet the rapid response requirements. Summary of the Invention

[0007] This application aims to at least solve the technical problems existing in the prior art, and provides a digital and intelligent plugging removal method, system and equipment for gas wells.

[0008] In the first aspect, a digital and intelligent plugging removal method for gas wells provided by the present invention includes:

[0009] Obtain plugging feature information and gas well working environment information; the plugging feature information includes at least one of the composition, physical characteristics, chemical characteristics, and biological characteristics of the plugging material;

[0010] Input the plugging feature information and gas well working environment information into the gas well plug removal analysis model. The gas well plug removal analysis model determines the reference composition information of the plug remover according to the plugging feature information, determines the plug removal construction conditions according to the gas well working environment information, generates a plug removal plan for the gas well based on the reference composition information of the plug remover and the plug removal construction conditions, and outputs the plug removal plan to obtain the gas well plug removal analysis result.

[0011] In a second aspect, to solve the above problems, the present invention also provides a gas well plug removal analysis system, which includes:

[0012] An acquisition module for obtaining plugging feature information and gas well working environment information; the plugging feature information includes at least one of the composition, physical characteristics, and chemical characteristics of the plugging material;

[0013] An analysis module for inputting the plugging feature information and gas well working environment information into the gas well plug removal analysis model. The gas well plug removal analysis model determines the reference composition information of the plug remover according to the plugging feature information, determines the plug removal construction conditions according to the gas well working environment information, generates a plug removal plan for the gas well based on the reference composition information of the plug remover and the plug removal construction conditions, and outputs the plug removal plan to obtain the gas well plug removal analysis result.

[0014] In a third aspect, the present invention provides an electronic device, which includes:

[0015] At least one processor; and,

[0016] A memory communicatively connected to the at least one processor; wherein,

[0017] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the above-mentioned gas well digital plug removal method.

[0018] In summary, the present application includes the following beneficial technical effects:

[0019] After inputting the plugging feature information into the gas well plug removal analysis model, the gas well plug removal analysis model analyzes the plugging feature information, determines the plugging type according to the plugging feature information, and determines the optional plug removers according to the plugging type; further screen the plug removers that meet the conditions from the optional plug removers according to the plug removal construction conditions, and use the gas well plug removal analysis model to assist in generating a plug removal plan, which can improve the processing efficiency of gas well plugging data;

[0020] Establish a gas well plug removal analysis model through machine learning methods and use historical data to train the gas well plug removal analysis model to improve the accuracy of the prediction results of the gas well plug removal analysis model for plugging types; in the face of different plugging types, a plug removal method can be quickly formed to improve the quality and efficiency of the downhole plug removal solution. Brief Description of the Drawings

[0021] Figure 1 It is a schematic flowchart of the gas well digital intelligent plug removal method provided by an embodiment of the present invention;

[0022] Figure 2 It is a schematic diagram of the neural network structure of the gas well plug removal analysis model provided by an embodiment of the present invention;

[0023] Figure 3 It is a schematic diagram of the structure of an electronic device for implementing the gas well digital intelligent plug removal method provided by an embodiment of the present invention.

[0024] Reference Numerals: 10, processor; 11, memory; 12, communication bus; 13, communication interface.

[0025] The realization, functional features and advantages of the object of the present invention will be further described with reference to the embodiments and the accompanying drawings. Detailed Embodiments

[0026] The embodiments of the present invention will be described in detail below. The examples of the embodiments are shown in the accompanying drawings, where the same or similar reference numerals indicate the same or similar elements or elements with the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention and should not be construed as a limitation of the present invention.

[0027] In the description of the present invention, it should be understood that the orientation or positional relationship indicated by the terms "longitudinal", "transverse", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. is based on the orientation or positional relationship shown in the accompanying drawings, and is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the present invention.

[0028] In the description of the present invention, unless otherwise specified and limited, it should be noted that the terms "installation", "connection", and "connection" should be understood in a broad sense. For example, it can be a mechanical connection or an electrical connection, or it can be the communication inside two elements. It can be directly connected or indirectly connected through an intermediate medium. For those of ordinary skill in the art, the specific meanings of the above terms can be understood according to specific situations.

[0029] Refer toFigure 1 As shown in the figure, it is a schematic flow chart of the intelligent plugging removal method for gas wells provided by an embodiment of the present invention. In this embodiment, the intelligent plugging removal method for gas wells includes:

[0030] S1. Obtain the plugging material characteristic information and the gas well working environment information.

[0031] The plugging material characteristic information includes at least one of the composition, physical characteristics, chemical characteristics, and biological characteristics of the plugging material; the gas well working environment information includes at least one of the gas well pipeline structure, gas well pipeline material, temperature of the formation environment where the gas well is located, pressure of the geological environment where the gas well is located, and soil acidity and alkalinity of the geological environment where the gas well is located.

[0032] The plugging material characteristic information and the gas well working environment information can be manually input by the staff, imported through hardware devices such as USB flash drives or external hard drives, or uploaded through the cloud platform. This application does not make any restrictions.

[0033] The physical characteristics of the plugging material include the shape and size of the plugging material; the physical characteristics of the gas well plugging material are manifested as solid particles (such as debris, inorganic salt crystals) or colloids (such as organic matter aggregates), and their shape is controlled by fluid viscosity, density difference, and formation environment, forming a dense or loose accumulation structure, directly affecting the removal difficulty; the physical characteristics of the plugging material are used to measure the influence of the shape, size, and physical properties of the plugging material on the fluid flow state in the gas well.

[0034] The chemical characteristics of the plugging material include the composition, reactivity, and chemical stability of the plugging material; the chemical characteristics of the plugging material are used to measure the plugging situation mainly caused by inorganic salts (such as FeS, CaCO3), organic matter (asphaltene, paraffin), and corrosive substances (H2S); inorganic salts, organic matter, and corrosive substances cause plugging through chemical reactions (such as salt crystallization, chemical adsorption) or hydrocarbon precipitation.

[0035] The biological characteristics of the plugging material are used to represent the plugging situation caused by the reproduction of gas well microorganisms and the biofilm formed by their metabolites. The biological characteristics are related to microbial activities (such as sulfate-reducing bacteria). Their metabolites (biofilm, sulfide) and the acidic substances produced will promote precipitation and metal corrosion, indirectly accelerating the formation of plugging; by analyzing the influence of the biological characteristics of the plugging material on the gas well plugging state, the gas well plugging situation can be slowed down.

[0036] The plug characteristic information is obtained by analyzing the plug samples acquired from the gas well site. When sampling downhole in the gas well, special sampling tools such as core samplers and fluid samplers are used to obtain plug samples at specific depths downhole. When sampling on the surface of the gas well, plug samples are collected from equipment such as separators and filters. After obtaining the plug samples, it is necessary to remove the impurities on the surface of the plugs to avoid contaminating the analysis results. At the same time, ensure that the samples are in a dry state for subsequent analysis.

[0037] Subsequently, the plug samples after removing impurities are analyzed and processed to determine the plugging type, so as to carry out the plug removal work targeted.

[0038] In the preferred implementation manner of this embodiment, the plug samples after removing impurities are respectively subjected to physical analysis and processing, chemical analysis and processing, biological analysis and processing, and other related analysis techniques to obtain the plug characteristic information;

[0039] Specifically, the physical analysis techniques include the following:

[0040] 1. X-ray diffraction (XRD): Used to determine the crystal structure of solid samples, which helps to identify the types of inorganic minerals;

[0041] 2. Scanning electron microscope (SEM): Provides high-resolution images for observing the microscopic morphology and structure of the plugs;

[0042] 3. Transmission electron microscope (TEM): More refined microscopic structure analysis, which can be used for material analysis at the nanoscale;

[0043] 4. Energy-dispersive X-ray spectroscopy (EDS): Used in combination with a scanning electron microscope to determine the elemental composition of the sample surface;

[0044] 5. Laser Raman spectroscopy: A non-destructive testing technique used to analyze organic and inorganic compounds and identify specific chemical bond vibrations;

[0045] 6. Thermogravimetric analysis (TGA): Monitors the mass loss of the sample with temperature change, which is used to identify volatile and thermally unstable components;

[0046] 7. Differential scanning calorimetry (DSC): Measures the heat released or absorbed by the sample during heating or cooling, which is used to determine the phase transition points and chemical reactions.

[0047] The chemical analysis techniques include the following:

[0048] 1. Gas chromatography-mass spectrometry (GC-MS): Used to analyze low-boiling organic compounds such as hydrocarbons and volatile organic compounds;

[0049] 2. High Performance Liquid Chromatography (HPLC): Used for analyzing non-volatile organic compounds, such as certain polymers and biological macromolecules;

[0050] 3. Fourier Transform Infrared Spectroscopy (FTIR): Identifies functional groups in organic and inorganic compounds, providing chemical fingerprint spectra;

[0051] 4. Inductively Coupled Plasma Mass Spectrometry (ICP-MS): Analyzes trace elements and heavy metals in liquid samples;

[0052] 5. X-ray Fluorescence Spectroscopy (XRF): Rapidly determines the elemental composition of solid, powder or liquid samples.

[0053] Biological analysis techniques include the following:

[0054] 1. Polymerase Chain Reaction (PCR): Used for detecting biogenic blockages, such as bacterial and fungal DNA;

[0055] 2. Microbial culture: Identifies and quantifies the types of microorganisms in blockages through laboratory culture;

[0056] 3. Biofilm analysis: Analyzes the composition of biofilms to understand the role of microorganisms in the blocking process.

[0057] In addition, it is also necessary to conduct fluid compatibility tests, permeability tests, porosity tests, permeability analysis tests, and conductivity measurements on the blockage; fluid compatibility tests can determine the interaction between the blockage and downhole fluids and evaluate the risk of blockage; permeability tests can measure the resistance of the blockage to fluid flow and evaluate the degree of blockage; during porosity and permeability analysis, the pore structure of the blockage is determined by using Nuclear Magnetic Resonance (NMR) or other techniques; conductivity measurements are used to detect the presence of brine or water-containing blockages.

[0058] S2. Input the blockage characteristic information and gas well working environment information into the gas well plug removal analysis model. The gas well plug removal analysis model determines the reference composition information of the plug remover according to the blockage characteristic information, determines the plug removal construction conditions according to the gas well working environment information, generates the plug removal plan for the gas well based on the reference composition information of the plug remover and the plug removal construction conditions, and outputs the plug removal plan to obtain the gas well plug removal analysis result.

[0059] The plug remover for gas wells is a special chemical or biological agent developed for gas well blockages (such as organic matter, inorganic salts, biological metabolites, etc.), which restores the wellbore flow capacity through physical dissolution, chemical reaction or biodegradation, including acidification-type plug removers, bioenzyme-type plug removers or chemical composite plug removers.

[0060] The plug removal plan includes the type of plug remover, the main components of the plug remover, the dosage of the plug remover, the plug removal construction temperature and pressure.

[0061] Gas well blockage can be caused by various reasons, such as water lock, salt scale, asphaltene deposition, microbial blockage, etc. Therefore, the plugging removal agent should have the ability to specifically eliminate these blockages. For example, for the water lock phenomenon, the optional plugging removal agents are demulsifiers or viscosity reducers; for salt scale blockage, the optional plugging removal agents are chemical agents that can effectively dissolve inorganic salts. Determine the blockage type of the gas well according to the blockage characteristic information, and then select the plugging removal agent according to the blockage type, the specific geological conditions and construction conditions of the gas well.

[0062] The plugging removal construction conditions include the temperature, pressure and pH environment of the plugging removal construction environment; the reference composition information of the plugging removal agent includes a list of optional plugging removal agent components that can eliminate the blockages in the gas well; the list of optional plugging removal agent components includes at least one plugging removal agent that can remove the blockages. Preferably, the list of optional plugging removal agent components includes all the plugging removal agents that can remove the blockages.

[0063] Specifically, generate a plugging removal plan for the gas well according to the reference composition information of the plugging removal agent and the plugging removal construction conditions, including:

[0064] S21. Obtain the physical properties and chemical characteristics of the plugging removal agent components in the list of optional plugging removal agent components.

[0065] S22. Screen out the plugging removal agent components that meet the plugging removal construction conditions from the list of optional plugging removal agent components according to the physical properties and chemical characteristics of the plugging removal agent components as the target plugging removal agent components.

[0066] S23. Determine the dosage of the target plugging removal agent components according to the blockage characteristic information.

[0067] S24. Generate a plugging removal plan according to the target plugging removal agent components, the dosage of the target plugging removal agent components and the plugging removal construction conditions.

[0068] The selection and application of the plugging removal agent are the key links in the plugging removal operation. The specificity, pertinence and practicability of the plugging removal agent are the key factors to ensure the plugging removal effect. After obtaining the list of optional plugging removal agent components, screen out the inappropriate plugging removal agents according to the plugging removal construction conditions and design a plugging removal plan specifically.

[0069] Different gas wells may be in different geological environments, such as high temperature, high pressure, acidic or alkaline environments. The plugging removal agent must be able to remain stable and effective under these specific conditions. In addition, the plugging removal agent should not damage the structural materials of the gas well, such as casing, cement sheath, etc., and at the same time should minimize the damage to the formation and avoid the occurrence of secondary blockage.

[0070] In addition, when selecting a plugging removal agent, its practicability should also be fully considered. The practicability of a plugging removal agent refers to its feasibility and economy in actual operation. On the one hand, the plugging removal agent should be easy to formulate and inject, with simple operation, so as to reduce the operation cost and time consumption. On the other hand, cost control of the plugging removal agent is also crucial. It is necessary to ensure the plugging removal effect while considering economic benefits, and avoid excessive investment leading to too high project costs.

[0071] After determining the preliminary formula of the plugging removal agent, conducting laboratory tests is an important step to verify its performance and optimize the formula. Laboratory tests include but are not limited to the following aspects: formula optimization, performance testing, safety and compatibility testing, and economic analysis; formula optimization means finding the best formula by adjusting the proportion of the components of the plugging removal agent; performance testing refers to evaluating the removal efficiency of the plugging removal agent for specific blockages and its stability under simulated gas well environments (such as temperature, pressure); the purpose of safety and compatibility testing is to ensure that the plugging removal agent will not damage the gas well structure and formation, and at the same time test its compatibility with other downhole chemicals; after screening out the plugging removal agent that meets the plugging removal construction conditions, calculate the usage cost of the plugging removal agent that meets the plugging removal construction conditions, evaluate the economic benefits of the plugging removal plan, and obtain an economic and effective plugging removal plan.

[0072] Through the above process, the plugging removal agent can be both effective and economic in actual application, providing guarantee for the efficient and safe operation of gas wells.

[0073] The gas well plugging removal analysis model can be a neural network model or a support vector machine, etc. In another embodiment of the present application, the digital intelligent plugging removal method for gas wells further includes:

[0074] S31. Obtain historical data.

[0075] The historical data includes the historical plugging data and historical plugging removal plan data of the gas well;

[0076] The historical plugging data includes the daily production, tubing head pressure and flow rate of the gas well during plugging.

[0077] S32. Train the gas well plugging removal analysis model by using the historical plugging data and historical plugging removal plan data.

[0078] In the preferred embodiment of this embodiment, the historical data further includes historical plugging removal effect data;

[0079] The evaluation dimensions of the plugging removal effect include at least one of the gas well production data characteristics, the gas well pressure characteristics, and the residue characteristics. The gas well production data includes the production rate after the plugging removal of the gas well, and the gas well production data characteristics are used to represent the change in the production rate of the product before and after the plugging removal of the gas well; the gas well pressure characteristics are used to represent the pressure drop between the wellhead and the bottom hole before and after the plugging removal of the gas well, and the gas well pressure characteristics are determined by the oil pressure and the flow rate after the plugging removal of the gas well; the residue characteristics are used to represent the residual situation of the plugging removal agent and / or the plugging material.

[0080] Before training the gas well plugging removal analysis model using the historical plugging data and the historical plugging removal solution data, it further includes:

[0081] S310. Screening the historical data using the historical plugging removal effect data.

[0082] Select the historical data with the historical plugging removal effect reaching the preset standard to train the gas well plugging removal analysis model.

[0083] In the preferred implementation manner of this embodiment, in order to implement the above process, the plugging removal effect of the plugging removal solution can be quantified by setting the plugging removal quality score. Specifically, the optimization effect of the plugging removal solution is scored according to the production data characteristics, the gas well pressure characteristics, and the residue characteristics to obtain the plugging removal quality score. Specifically:

[0084] When screening the historical data using the historical plugging removal effect data, first, count the production data characteristics, the gas well pressure characteristics, and the residue characteristics of the gas well after implementing the plugging removal solution; then, determine the optimization degree of the plugging removal solution for the product production rate according to the production data characteristics to obtain the production optimization score; determine the optimization degree of the plugging removal solution for the pressure situation between the wellhead and the bottom hole according to the gas well pressure characteristics to obtain the pressure optimization score, determine the removal effect score of the plugging removal solution for the plugging material according to the residue characteristics; calculate the plugging removal quality score according to the production optimization score, the pressure optimization score, and the removal effect score; the calculation process of the plugging removal quality score can refer to the following formula:

[0085] S Total = ω1·S1 + ω2·S2 + ω3·S3

[0086] Among them, S Total represents the plugging removal quality score, S1 represents the production optimization score, ω1 represents the weight of the production optimization score, S2 represents the pressure optimization score, ω2 represents the weight of the pressure optimization score, S3 represents the removal effect score, and ω3 represents the weight of the removal effect score;

[0087] When calculating the plugging removal quality score, the score weights corresponding to each evaluation dimension of the plugging removal effect can be adjusted according to the situation, and this embodiment does not make any restrictions.

[0088] Specifically, step S32 for training the gas well plugging removal analysis model using historical plugging data and historical plugging removal solution data includes:

[0089] S321. Construct the network structure of the gas well plugging removal analysis model;

[0090] In the preferred embodiment of this embodiment, the gas well plugging removal analysis model is a BP neural network model.

[0091] The full Chinese name of BP (back propagation) neural network is back propagation neural network. The basic algorithm principle of BP neural network is mainly to capture the difference between the output result and the expected result, and then compare the error in the algorithm. If the error is within the established error range, the result is directly output; otherwise, the error signal of each node is calculated in reverse, and the weight values at different nodes are corrected until the error requirement is met. This method solves the problem that the hidden layer is not easy to determine and has strong practical value. BP neural network is a multi-layer feedforward neural network. The three-layer BP neural network model adopted in this embodiment is as Figure 2 shown.

[0092] S322. Use historical data to train the network of the gas well plugging removal analysis model. During each training, the network of the gas well plugging removal analysis model processes the historical plugging data according to a preset rule to output a plugging removal solution prediction result; calculate the loss function of the gas well plugging removal analysis model according to the plugging removal solution prediction result and the historical plugging removal solution data, and optimize the network parameters of the gas well plugging removal analysis model according to the loss function to obtain the final gas well plugging removal analysis model.

[0093] The basic steps for using historical data to train the network of the gas well plugging removal analysis model are as follows:

[0094] Step 1: Complete the normalization processing of input parameters to eliminate the dimension difference.

[0095]

[0096] Among them, X k represents the input sample set, that is, the historical plugging data, and k represents the input layer index; represents the feature corresponding to the nth historical plugging data in the input sample set, n ∈ [1, m], and m represents the total number of historical plugging data in the input sample set; C k represents the feature corresponding to the nth historical plugging data in the normalized input sample set; represents a feature of the normalized input sample.

[0097] Step 2: Calculate the input and output of each neuron in the hidden layer and the output layer.

[0098] Specifically, the input layer directly passes the preprocessed data to the hidden layer, and each hidden layer neuron calculates the input weighted sum:

[0099]

[0100] Among them, represents the output of the j-th neuron in the k-th hidden layer, is the weight from the input layer to the hidden layer, represents the input value.

[0101] Among them, represents the output of the neuron in the k-th hidden layer;

[0102] The input value of the j-th neuron in the hidden layer The calculation formula is:

[0103]

[0104] Among them, x i represents the input value (i.e., input feature) of the i-th neuron in the input layer.

[0105] represents the connection weight from the i-th neuron in the input layer to the j-th neuron in the hidden layer.

[0106] represents the bias term of the j-th neuron in the hidden layer, and n is the number of neurons in the input layer

[0107] Step 3: Calculate the errors of the output layer and the hidden layer.

[0108] Optimize the network parameters of the gas well plug removal analysis model according to the loss function

[0109] In this embodiment, the core purpose of calculating the first moment (mean) and the second moment (uncentered variance) of the gradient is to dynamically adjust the parameter update direction and step size, thereby improving the stability and convergence efficiency of the optimization algorithm.

[0110] The calculation formula for the first moment (mean) of the gradient is:

[0111] m t = β1·m t-1 +(1 - β1)·g t

[0112] Among them, m t represents the first moment estimate at the current time step t, β1 represents the first moment decay rate (usually taken as 0.9), m t-1 represents the first moment estimate at the previous time step t - 1, and g t represents the gradient at the current time step.

[0113] The calculation formula for the gradient second moment (uncentered variance) is as follows:

[0114] v t = β2·v t-1 +(1 - β2)·g t 2

[0115] v t represents the second moment estimate at the current time step t, β2 represents the second moment decay rate (usually taken as 0.999), v t-1 represents the second moment estimate at the previous time step t - 1, and g t 2 represents the gradient at the current time step.

[0116] According to the bias correction of the first moment m t of the gradient and the bias correction of the second moment v t of the gradient, update the network parameters of the gas well plugging removal analysis model.

[0117] Bias correction of the first moment The calculation formula is:

[0118]

[0119] represents the first moment decay rate at time step t;

[0120] Bias correction of the second moment

[0121]

[0122] represents the second moment decay rate at time step t;

[0123] The parameter update formula is:

[0124]

[0125] where, represents the bias correction value of the first moment m t of the gradient, represents the bias correction value of the second moment v t of the gradient, η is the learning rate. ∈ is a small constant (usually 1e - 8) used to prevent division by zero errors.

[0126] Step 4: Re - select the weights and thresholds.

[0127] Step 5: Let k = k + 1 and repeat Steps 2 to 4 until all k values are trained.

[0128] Step 6: Repeat Steps 2 to 5 until the loss function value Loss of the gas well plugging removal analysis model is less than the pre-set error value, or the number of training times is greater than the pre-set value; in actual operations, since the structure of the BP neural network is simplified and only one hidden layer is set, in order to maintain accuracy, generally a relatively large number of learning times and a relatively small Loss value are set to ensure the accuracy of the calculation results.

[0129]

[0130] Among them, Loss represents the error value; E k represents the single error value, t represents the time step, and q represents the total number of time steps; represents the feature input by the normalized input sample set at time step t; represents the input value of the hidden layer at time step t.

[0131] Based on the same inventive concept, an embodiment of the present invention provides a gas well plugging removal analysis system.

[0132] The gas well plugging removal analysis system described in the present invention can be installed in an electronic device. According to the functions achieved, the gas well plugging removal analysis system includes an acquisition module and an analysis module. The acquisition module can acquire the plugging material characteristic information and the gas well working environment information; the plugging material characteristic information includes at least one of the composition, physical characteristics, and chemical characteristics of the plugging material;

[0133] The analysis module can input the plugging material characteristic information and the gas well working environment information into the gas well plugging removal analysis model. The gas well plugging removal analysis model determines the reference composition information of the plugging removal agent according to the plugging material characteristic information, determines the plugging removal construction conditions according to the gas well working environment information, generates a plugging removal plan for the gas well according to the reference composition information of the plugging removal agent and the plugging removal construction conditions, and outputs the plugging removal plan to obtain the gas well plugging removal analysis result. The module described in the present invention can also be referred to as a unit, which refers to a series of computer program segments that can be executed by the processor of an electronic device and can complete fixed functions, and are stored in the memory of the electronic device.

[0134] The various change methods and specific examples in the gas well digital plugging removal method provided in the above embodiment are equally applicable to the gas well plugging removal analysis system in this embodiment. Through the foregoing detailed description of the gas well digital plugging removal method, those skilled in the art can clearly know the implementation method of the gas well plugging removal analysis system in this embodiment. For the sake of brevity of the specification, it will not be described in detail here.

[0135] This application also discloses an electronic device, such as Figure 3As shown in the figure, it is a schematic structural diagram of an electronic device for the intelligent plugging removal method of gas wells provided by an embodiment of the present invention. The electronic device may include at least one processor 10, a memory 11 communicatively connected to the at least one processor, a communication bus 12, and a communication interface 13. It may also include a computer program stored in the memory 11 and executable on the processor 10, such as a method program for gas well plugging removal analysis.

[0136] Among them, the processor 10 may be composed of integrated circuits in some embodiments. For example, it may be composed of a single packaged integrated circuit, or may be composed of multiple integrated circuits with the same or different functions packaged, including a combination of one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and various control chips. The processor 10 is the control core (Control Unit) of the electronic device, connecting various components of the entire electronic device through various interfaces and lines. By running or executing programs or modules stored in the memory 11 (such as executing the method for gas well plugging removal analysis, etc.), and by calling data stored in the memory 11, it performs various functions of the electronic device and processes data.

[0137] The memory 11 includes at least one type of readable storage medium. The readable storage medium includes flash memory, mobile hard disks, multimedia cards, card-type memories (such as SD or DX memories, etc.), magnetic memories, magnetic disks, optical disks, etc. The memory 11 may be an internal storage unit of the electronic device in some embodiments, such as the mobile hard disk of the electronic device. The memory 11 may also be an external storage device of the electronic device in other embodiments, such as a plug-in mobile hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the electronic device. Further, the memory 11 may include both the internal storage unit and the external storage device of the electronic device. The memory 11 can not only be used to store application software installed on the electronic device and various types of data, such as the code of the method program for gas well plugging removal analysis, etc., but also be used to temporarily store data that has been output or will be output.

[0138] The communication bus 12 can be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. This bus can be divided into an address bus, a data bus, a control bus, etc. The bus is configured to implement the connection communication between the memory 11 and at least one processor 10, etc.

[0139] The communication interface 13 is used for the communication between the above-mentioned electronic device and other devices, including a network interface and a user interface. Optionally, the network interface can include a wired interface and / or a wireless interface (such as a WI-FI interface, a Bluetooth interface, etc.), which is generally used to establish a communication connection between this electronic device and other electronic devices. The user interface can be a display, an input unit (such as a keyboard), and optionally, the user interface can also be a standard wired interface, a wireless interface. Optionally, in some embodiments, the display can be an LED display, a liquid crystal display, a touch liquid crystal display, and an OLED (Organic Light-Emitting Diode) toucher, etc. Among them, the display can also be appropriately referred to as a display screen or a display unit, which is used to display the information processed in the electronic device and to display a visual user interface.

[0140] Figure 3 Only the electronic device with components is shown. Those skilled in the art can understand that Figure 3 the shown structure does not constitute a limitation on the electronic device, and it can include fewer or more components than shown, or combine certain components, or have different component arrangements. For example, although not shown, the electronic device can also include a power source (such as a battery) for powering each component. Preferably, the power source can be logically connected to at least one processor 10 through a power management device, so as to implement functions such as charge management, discharge management, and power consumption management through the power management device. The power source can also include any components such as one or more DC or AC power sources, a recharge device, a power failure detection circuit, a power converter or an inverter, a power status indicator, etc. The electronic device can also include various sensors, a Bluetooth module, a Wi-Fi module, etc., which will not be elaborated here.

[0141] It should be understood that the embodiments are only for illustration purposes and are not limited by this structure in the scope of the patent application.

[0142] Furthermore, if the modules / units integrated in the electronic device are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. The computer-readable storage medium can be volatile or non-volatile.

[0143] In the description of this specification, the descriptions referring to terms such as "one embodiment", "some embodiments", "example", "specific example", "one implementation manner", "one preferred implementation manner" or "some examples", etc. mean that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in a suitable manner in any one or more embodiments or examples.

[0144] Although the embodiments of the present invention have been shown and described, those of ordinary skill in the art can understand that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the claims and their equivalents.

Claims

1. A digital intelligent plugging removal method for gas wells, characterized in that, The method includes: Obtaining plugging material characteristic information and gas well working environment information; the plugging material characteristic information includes at least one of the composition, physical characteristics, chemical characteristics, and biological characteristics of the plugging material; Inputting the plugging material characteristic information and the gas well working environment information into a gas well plug removal analysis model. The gas well plug removal analysis model determines reference plug removal agent composition information according to the plugging material characteristic information, determines plug removal construction conditions according to the gas well working environment information, generates a plug removal plan for the gas well based on the reference plug removal agent composition information and the plug removal construction conditions, and outputs the plug removal plan to obtain a gas well plug removal analysis result.

2. The intelligent plugging removal method for gas wells according to claim 1, wherein The reference plug removal agent composition information includes a list of optional plug removal agent components that can eliminate the gas well plugging material; The generating of the gas well plug removal plan according to the reference plug removal agent composition information and the plug removal construction conditions includes: Obtaining the physical properties and chemical characteristics of the plug removal agent components in the list of optional plug removal agent components; Screening out the plug removal agent components that meet the plug removal construction conditions from the list of optional plug removal agent components according to the physical properties and chemical characteristics of the plug removal agent components as the target plug removal agent components; Determining the dosage of the target plug removal agent components according to the plugging material characteristic information; Generating a plug removal plan according to the target plug removal agent components, the dosage of the target plug removal agent components, and the plug removal construction conditions.

3. The intelligent plugging removal method for gas wells according to claim 2, characterized in that, The gas well working environment information includes at least one of the gas well pipeline structure, gas well pipeline material, temperature of the geological environment where the gas well is located, pressure of the geological environment where the gas well is located, and soil acidity and alkalinity of the geological environment where the gas well is located.

4. The intelligent plugging removal method for gas wells according to claim 1, characterized in that, The gas well plug removal analysis model is a neural network model.

5. The intelligent plugging removal method for gas wells according to claim 4, wherein, The method further includes: Obtaining historical data, where the historical data includes historical plugging data and historical plug removal plan data of the gas well; Training the gas well plug removal analysis model using the historical plugging data and the historical plug removal plan data.

6. The intelligent plugging removal method for gas wells according to claim 5, wherein, The training of the gas well plug removal analysis model using the historical plugging data and the historical plug removal plan data includes: Constructing the network structure of the gas well plug removal analysis model; Training the network of the gas well plug removal analysis model using the historical data. In each training, the network of the gas well plug removal analysis model processes the historical plugging data according to a preset rule to output a plug removal plan prediction result; calculating the loss function of the gas well plug removal analysis model according to the plug removal plan prediction result and the historical plug removal plan data, and optimizing the network parameters of the gas well plug removal analysis model according to the loss function to obtain the final gas well plug removal analysis model.

7. The gas well digital intelligent plug removal method according to claim 5 or 6, wherein The historical data further includes historical plug removal effect data; selecting the historical data with the historical plug removal effect reaching a preset standard to train the gas well plug removal analysis model.

8. The intelligent plugging removal method for gas wells according to claim 7, characterized in that The evaluation dimensions of the historical plug removal effect include at least one of gas well production data characteristics, gas well pressure characteristics, and residue characteristics. The gas well production data characteristics are used to represent the change in the production of the product before and after the gas well plug removal, and the gas well pressure characteristics are used to represent the pressure drop at the wellhead and bottom hole before and after the gas well plug removal.

9. A gas well plugging removal analysis system for implementing the gas well digital plugging removal method described in any one of claims 1 to 8, characterized in that, Including: An acquisition module for obtaining plugging material characteristic information and gas well working environment information; The plugging material characteristic information includes at least one of the composition, physical characteristics, chemical characteristics, and biological characteristics of the plugging material; An analysis module is configured to input plugging feature information and gas well working environment information into a gas well plugging removal analysis model. The gas well plugging removal analysis model determines reference component information of a plugging removal agent according to the plugging feature information, determines plugging removal construction conditions according to the gas well working environment information, generates a plugging removal plan for the gas well based on the reference component information of the plugging removal agent and the plugging removal construction conditions, outputs the plugging removal plan, and obtains a gas well plugging removal analysis result.

10. An electronic device, characterized in that, The electronic device includes: at least one processor (10); and, a memory (11) communicatively connected to the at least one processor (10); wherein the memory (11) stores a computer program executable by the at least one processor (10), and the computer program is executed by the at least one processor (10) so that the at least one processor (10) can execute the gas well digital plugging removal method according to any one of claims 1 to 8.

Images