Method for determining intelligent intermittent opening and closing system of gas well

Abstract

The invention discloses a method for determining an intelligent intermittent opening and closing system of a gas well, and particularly relates to the field of gas production technology.The method for determining the intelligent intermittent opening and closing system of the gas well comprises the steps that according to an established mathematical model, the production dynamic state and the liquid accumulation condition of the gas well in the critical liquid accumulation state of the gas well are determined; establishing an intermittent well opening formation, a shaft unsteady seepage mathematical model and a formation shaft coupling unsteady mathematical model according to an intermittent well opening shaft and a flow mechanism in the formation, and determining a gas well pressure recovery condition; and determining an intelligent intermittent opening and closing system of the gas well according to the liquid accumulation and pressure recovery conditions of the gas well. According to the method, intelligent analysis and dynamic adjustment functions of the low-pressure low-yield gas well intermittent switching system can be realized, so that the actual application requirements of gas fields and mine fields for rapid, efficient, safe and stable production are met, and the measure implementation rate and the effective rate of low-pressure gas well intermittent switching are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of gas production technology, and is a method for determining an intelligent switching system applicable to intermittent switching production of low-pressure and low-yield gas wells in water-producing gas reservoirs without manual parameter adjustment and system setting. More precisely, the present invention is a method for determining an intelligent intermittent switching system for gas wells. Background Art

[0002] During the production process of gas wells, with the extension of production time, the reduction of production pressure, and the intensification of wellbore liquid accumulation, it is mainly divided into three production stages: high-pressure continuous production period, measure drainage continuous production period, and low-pressure intermittent pressure recovery drainage production period. Among them, the low-pressure intermittent pressure recovery drainage production period accounts for more than 60% of the production stages in the entire life cycle of gas wells, and the cumulative gas production accounts for 40% of the total cumulative gas production of gas wells, which is crucial in the production stage of gas wells. The existing intermittent switching systems for gas wells mainly rely on the manual experience method and the indoor simulation method. Among them, the manual experience method mainly relies on technicians to determine the intermittent switching system of gas wells on-site according to the law of gas well pressure recovery rate and execute it on-site. This method has different single-well systems, a large on-site execution workload, poor adaptability of system adjustment to the production dynamics of gas wells, and the system execution rate is greatly affected by factors such as weather and roads; the indoor simulation method mainly relies on establishing a gas reservoir dynamic model to simulate the production law of gas wells, and its accuracy depends on the previous production data of gas wells and the production laws of similar wells, and it is difficult to accurately represent the relationship between pressure reduction, wellbore liquid accumulation, and productivity recovery during the gas well production process. Both of these methods rely on manual implementation, have limitations in application, and targeted system customization for different situations of gas wells, which greatly limits the effective drainage and productivity of low-pressure intermittent gas wells.

[0003] In order to achieve the precise formulation and accurate execution of the intermittent switching system of gas wells, improve the accuracy, efficiency, and timeliness of the intermittent gas well system execution, the present invention has developed a method for determining an intelligent intermittent switching system, realizing the effective execution and large-scale application of intermittent switching production of gas wells, which can meet the effective drainage of gas wells for pressure recovery, improve the gas reservoir recovery rate, greatly reduce the manual workload, and improve the labor efficiency of employees. Summary of the Invention

[0004] In order to overcome the above-mentioned defects of the prior art, the present invention provides a method for determining an intelligent intermittent switching system for gas wells to achieve effective drainage during the intermittent switching production period of low-pressure and low-yield gas wells in water-producing gas reservoirs, give full play to the productivity of gas wells, improve the cumulative recovery rate and production of gas wells, extend the effective production time of gas wells, and reduce the manual labor intensity, so as to solve the problems raised in the above background art.

[0005] To achieve the above object, the present invention provides the following technical solution: a method for determining an intelligent intermittent switching regime for a gas well, which collects static parameters of the gas well, installs sensors and monitoring devices to collect relevant data during the production process of the gas well, collects pressure by a wellhead pressure sensor, collects gas well flow data by a gas-liquid two-phase flowmeter, establishes a prediction model for liquid holdup in the gas wellbore to obtain the liquid holdup state in the gas wellbore, and predicts the liquid holdup volume in the wellbore by the liquid holdup prediction model; by establishing an unsteady seepage mathematical model for the formation and wellbore of an intermittently switched gas well and a coupled unsteady mathematical model for the formation and wellbore, fitting the historical pressure data and historical flow data, iteratively obtaining the relationship curves between the gas well pressure recovery rate, pressure drop rate and gas well production time, determining the shut-in time of the gas well, and then calculating the open well time of the gas well from the relationship between the liquid holdup volume and the open well time; by comparing the relationship curves between different open well times, shut-in times and the reduction of the liquid level in the gas wellbore, determining the optimal intelligent intermittent switching regime for the gas well, and finally realizing the intelligent determination of the intermittent production regime of the gas well.

[0006] A method for determining an intelligent intermittent switching regime for a gas well includes the following steps:

[0007] S1: Collect static parameters of the gas well, including the well depth H of the gas well w , the tubing radius r ti , the casing radius r ai , the tubing submerged well depth H s , the liquid density ρ of natural gas l , the gas density ρ of natural gas g ;

[0008] S2: Data collection and processing, install sensors and monitoring devices to collect relevant data during the production process of the gas well;

[0009] S3: Establish a prediction model, establish a prediction model for liquid holdup in the gas wellbore to obtain the liquid holdup state in the gas wellbore, and predict the liquid holdup volume in the wellbore by the liquid holdup prediction model;

[0010] S4: Establish a mathematical model, establish an unsteady seepage mathematical model for the formation and wellbore of an intermittently switched gas well and a coupled unsteady mathematical model for the formation and wellbore, and fit the historical pressure data and historical flow data;

[0011] S5: Develop an intermittent switching regime, determine the optimal intelligent intermittent switching regime for the gas well by comparing the relationship curves between different open well times, shut-in times and the reduction of the liquid volume in the gas wellbore;

[0012] S6: Optimization and improvement, continuously collect and analyze the production data of the gas well, and continuously improve and optimize the formulation and control method of the intermittent switching regime to finally determine the intelligent intermittent switching regime of the gas well.

[0013] Preferably, in step S2, the minimum casing pressure p of the gas well is captured by the oil pressure sensor, casing pressure sensor, and gas-liquid two-phase flowmeter installed at the wellhead of the gas well during the production of the gas well cb , the minimum tubing pressure p cb , the maximum flow rate data Q gt ; during the shut-in of the gas well, the maximum casing pressure p ct , the maximum tubing pressure p ct are captured.

[0014] Preferably, the fluid volume Q wt_upper in the upper section of the tubing, the fluid volume Q wt_beneath in the lower section of the tubing, the fluid volume Q wa in the annulus between the tubing and the casing, and the fluid volume Q ws in the space below the shoe are determined through the mathematical model established in step S3.

[0015] Preferably, by establishing the unsteady seepage mathematical models of the intermittent switched gas well formation and wellbore and the coupled unsteady mathematical model of the formation and wellbore in step S4, the historical pressure data and historical flow rate data are fitted, and the relationship curves between the pressure recovery rate △p t , the pressure drawdown rate △p b and the production time t o of the gas well are obtained through iteration, and the open well time t oi of the gas well is determined.

[0016] Preferably, according to the relationship curve of the change of the wellbore liquid accumulation volume Q oi corresponding to different open well times t w , the shut-in time t ci of the gas well is determined.

[0017] Preferably, by comparing the relationship curves of the reduction of the wellbore liquid volume Q oi corresponding to different open well times t ci and shut-in times t w of the gas well, the optimal intermittent switching regime T oi , T ci of the gas well is determined.

[0018] Preferably, when Q w(n)＞ Q w(n-1) , steps S2 to S5 are repeated, the well is opened and closed repeatedly, and the intermittent switching regime is optimized; when Q w(n) > Q w(n+1) , the previous regime is continued. Finally, by comparing the relationship curves of different open well times, shut-in times and the reduction of the wellbore liquid volume of the gas well, the optimal intermittent switching regime of the gas well is determined, and finally the intelligent intermittent switching regime of the gas well is determined.

[0019] Preferably, in S3, the liquid holdup in the wellbore of the current gas well is generated based on the pre-acquired static parameters of the current gas well and the data captured in S2. If the liquid holdup Qw in the gas well wellbore is ≤ 0, the liquid holdup state of the gas well cannot be determined, and S2 is performed to capture real-time data again until the liquid holdup > 0.

[0020] Advantages of the present invention:

[0021] The method for determining the intelligent intermittent switching regime of a gas well provided by the present invention first determines the liquid holdup change curve during the open well period of the gas well according to the established liquid holdup model, then determines the shut-in time according to the unsteady seepage mathematical model of the gas well and the unsteady mathematical model of the formation-wellbore coupling, and finally repeats the optimization according to the gas well pressure recovery degree and the liquid holdup change degree to determine the intermittent switching regime of the gas well, and obtains the optimal regime to further promote the discharge of liquid holdup in the wellbore, exert the gas production capacity of the gas well, and improve the open well rate and production of the intermittent gas well. By implementing the present invention, the daily production of the intermittent gas well can be increased, and the workload per capita can be reduced. Specific embodiments

[0022] Based on the embodiments in the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the scope of protection of the present invention.

[0023] Embodiment 1

[0024] A method for determining the intelligent intermittent switching regime of a gas well provided by Embodiment 1 of the present invention includes the following steps:

[0025] S1: Collect the static parameters of the gas well, including the gas well depth H w , tubing radius r ti , casing radius r ai , tubing submerged depth H s , liquid density of natural gas ρ l , gas density of natural gas ρ g ;

[0026] S2: Data acquisition and processing. By installing sensors and monitoring devices, relevant data during the production process of the gas well is collected. When the gas well is in production, the minimum casing pressure p cb , minimum tubing pressure p cb , and maximum flow rate data Q gt of the gas well are captured through the oil pressure sensor, casing pressure sensor, and gas-liquid two-phase flowmeter installed at the wellhead of the gas well; when the gas well is shut in, the maximum casing pressure p ct , maximum tubing pressure p ct of the gas well are captured;

[0027] S3: Establish a prediction model. By establishing a prediction model for liquid loading in the gas wellbore, obtain the liquid loading state of the gas wellbore. Predict the liquid volume of the wellbore liquid loading by the liquid loading prediction model, and determine the fluid liquid volume Q in the upper section of the tubing wt_upper ; the fluid liquid volume Q in the lower section wt_beneath ; the liquid volume Q in the annulus between the tubing and the casing wa ; the liquid volume Q in the space below the tubing shoe ws ;

[0028] The liquid loading volume of the wellbore is the sum of the liquid volumes in the tubing, the annulus between the tubing and the casing, and the space below the tubing shoe. Its expression is

[0029] Q w = Q wt_upper + Q wt_beneath + Q wa + Q ws (1)

[0030] In the formula, Q wt_upper is the fluid liquid volume in the upper section, m 3 ; Q wt_beneath is the fluid liquid volume in the upper section, m 3 ; Q wa is the liquid volume in the annulus between the tubing and the casing, m 3 ; Q ws is the liquid volume in the space below the tubing shoe, m 3

[0031] The liquid volume in the upper section of the fluid can be expressed as:

[0032]

[0033] In the formula, Q wt_upper is the fluid liquid volume in the upper section, m 3 ; r ti is the inner radius of the tubing, m; H tI is the well depth of the inner interface of the tubing, m; φ l (h) is the liquid holdup function

[0034] The liquid volume in the lower section of the fluid is the sum of the liquid contents in each flow pattern section:

[0035]

[0036] In the formula, Q wt_beneath is the fluid liquid volume in the upper section, m 3 ; r ti is the inner radius of the tubing, m; H tI is the well depth of the inner interface of the tubing, m; H W is the well depth, m; N is the number of flow patterns; H bi is the lower interface depth of the i-th flow pattern section, m; H ui is the upper interface depth of the i-th flow pattern section, m; φli (h) is the liquid holdup function for the i-th flow regime segment.

[0037] All the liquid in the annulus exists in the lower static liquid column, and the liquid volume in the annulus is expressed as

[0038]

[0039] In the formula, Q wa is the liquid volume in the annulus, m 3 ; r ai is the inner radius of the casing, m; r to is the outer radius of the tubing, m; H W is the well depth, m; H aI is the well depth of the gas-liquid interface in the annulus, m.

[0040] All the liquid in the annulus exists in the lower static liquid column, and the liquid volume in the annulus is expressed as

[0041]

[0042] In the formula, Q ws is the liquid volume in the annulus, m 3 ; r ai is the inner radius of the casing, m; H W is the well depth, m; H aI is the well depth of the gas-liquid interface in the annulus, m; H s is the well depth of the tubing shoe, m;

[0043] S4: Establish a mathematical model. By establishing the unsteady seepage mathematical model of the intermittent switched gas well formation and wellbore and the coupled unsteady mathematical model of the formation and wellbore, fit the historical pressure data and historical flow rate data, and iteratively obtain the relationship curves of the gas well pressure recovery rate △p t , pressure drawdown rate △p b and the gas well production time t o to determine the gas well open time t oi ;

[0044] In specific implementation, the process of establishing the unsteady seepage mathematical model of the intermittent switched gas well formation and wellbore and the coupled unsteady mathematical model of the formation and wellbore is as follows: It is assumed that there are only gas and water phases in the wellbore of the gas well intermittent switch model. All the gas components in the wellbore exist in the gas phase in the form of free gas, all the water exists in the liquid phase, there is no condensate water, the gas and water in the wellbore are immiscible, and the wellbore is incompressible.

[0045] In the calculation of the pressure drop in the gas-liquid two-phase pipe flow, it is based on the basic equation of the one-dimensional steady pipe flow pressure gradient of the single-phase fluid. The pressure gradient equation is

[0046]

[0047] In the formula, the two-phase flow density ρ of the gravity, friction, and kinetic energy pressure drop gradient terms m 、ρ fr and ρ are all uniformly expressed as the two-phase mixture density of the gravity term in some empirical correlation formulas, that is

[0048] ρ m =ρ L H L +ρ g (1 - H L ) (8)

[0049] All the fluid property parameters involved in Equation (7) are expressed as functions of the flow state (pressure, temperature). The solution of the pressure gradient equation (7) is treated as an initial value problem of an ordinary differential equation

[0050]

[0051] where F(z, p) is the right function of the pressure gradient equation (8). The initial value condition is formed by the flowing pressure p0 at the known starting point z0 (wellhead or bottom hole).

[0052] Considering the basic geometric differences in the flow, for the developed slug flow and the developing slug flow, taking a developed slug flow unit, the mass balance relationships of all the gas and liquid are respectively

[0053] v sg =φ l v gtb (1 - H ltb )+(1 - φ)v gls (1 - H lls ) (10)

[0054] v sl =(1 - φ l )v lls H lls +φlv ltb H ltb (11)

[0055]

[0056] In the formula, L tb is the Taylor bubble length in the slug unit, m; L su is the slug unit length, m.

[0057] When two flow patterns appear in the wellbore, the water production of the gas well approaches zero. The upper section of the fluid can be regarded as a pure flowing gas column and calculated using the single-phase flow model. Ignoring the kinetic energy pressure drop gradient, the pressure gradient equation of the vertical gas well is

[0058] By studying the mass balance of the liquid and gas separately from the liquid slug to the Taylor bubble, the following equations can be obtained:

[0059] (v lls -v tb )H lls =[v tb -(-v ltb )]H ltb (13)

[0060] (v tb -v gls )(1-H lls )=(v tb -v gtb )(1-H ltb ) (14)

[0061] In the equations, v tb is the rising velocity of the Taylor bubble, in m / s, which is equal to the axial velocity plus the rising velocity of the bubble in the static liquid column, that is

[0062]

[0063] The velocity of the bubble in the liquid slug is

[0064]

[0065] v ltb can be expressed by the void fraction φ tb of the Taylor bubble section as follows

[0066]

[0067] In the equations, φ tb —the void fraction of the Taylor bubble section, dimensionless.

[0068] The void fraction φ ls of the liquid slug is

[0069]

[0070] In the equations, φ ls —the void fraction of the liquid slug, dimensionless.

[0071] Finally, by solving the 8 equations of Equation (9), Equation (10), Equation (11), Equation (12), Equation (13), Equation (14), Equation (17), and Equation (18) using the iterative method, the 8 unknowns v gtb 、v ltb 、H ltb 、v tb 、v gls 、v tb 、v gls 、vlls , H lls , and φ l . According to the derivation, the solution of the above 8 equations can be transformed into a functional equation. The simplified equation is only a function of the void fraction φ tb of the Taylor bubble-liquid film region L tb (i.e., 1 - φ tb ), expressed as

[0072]

[0073] where

[0074]

[0075]

[0076] where, v ngtb and H nltb are calculated using the limiting liquid film thickness δ n :

[0077]

[0078] And

[0079]

[0080]

[0081]

[0082] According to experience, the length of the Taylor bubble is

[0083]

[0084]

[0085] where

[0086]

[0087]

[0088]

[0089] After obtaining L * tb , other local parameters can be calculated according to the following formulas:

[0090]

[0091]

[0092]

[0093]

[0094] The frictional pressure gradient only considers the liquid slug part and is calculated by the following formula:

[0095]

[0096] where the friction coefficient f of the liquid slug ls , is calculated according to the following Reynolds number:

[0097]

[0098]

[0099] where can be obtained according to the average liquid holdup of the Taylor bubble section that varies with the liquid film thickness,

[0100]

[0101] where can be obtained through L * tb and is obtained

[0102]

[0103] The frictional pressure gradient is calculated by the following formula:

[0104]

[0105] S5: Formulate an intermittent switching regime. By comparing the relationship curves of different well-opening times, well-shutting times, and the reduction of liquid volume in the gas wellbore, determine the optimal intermittent switching regime for the gas well;

[0106] According to the relationship curve of the corresponding liquid holdup Q oi in the wellbore with different well-opening times t w , determine the well-shutting time t ci of the gas well;

[0107] By comparing the relationship curves of different well-opening times t oi , well-shutting times t ci and the reduction of liquid volume Q w in the gas wellbore, determine the optimal intermittent switching regime T oi 、T ci ;

[0108] S6: Optimization and improvement. By continuously collecting and analyzing the production data of gas wells, the formulation and control method of the intermittent switching system are continuously improved and optimized to finally determine the intelligent gas well intermittent switching system;

[0109] When Q w(n) > Q w(n-1) , repeat S2 to S5, repeat opening and closing the well, and optimize the intermittent switching system; when Q w(n) > Q w(n+1) , continue to execute the previous system. Finally, by comparing the relationship curves of different well opening times, well shut-in times and the reduction of liquid volume in the gas well borehole, determine the optimal gas well intermittent switching system, and finally determine the intelligent gas well intermittent switching system.

[0110] Embodiment 2

[0111] This Embodiment 2 provides that before implementing the method for determining the intelligent intermittent switching system of this gas well, when determining the optimal gas well intermittent switching system, at the production site, control devices such as cage-type control valves are installed in the gas well to monitor and adjust the gas well production process in real time;

[0112] Specifically, during implementation, through control devices such as cage-type control valves, the gas well production process is monitored and adjusted in real time. According to the real-time data and the requirements of the intermittent switching system, the control strategy is adjusted in a timely manner to ensure the stability and high efficiency of gas well production, and the formation pressure drop is controlled within the range of 0.01 - 0.1 MPa, thereby realizing the improvement of the single-well recovery rate.

[0113] Embodiment 3

[0114] This Embodiment 3 provides that when implementing the method for determining the intelligent intermittent switching system of this gas well, establish state equations and observation equations for the data collected by the sensors, and use the Kalman filtering algorithm to estimate the state;

[0115] Specifically, during implementation, various parameters of the gas well production state collected by the sensors are matched into the state equations. The observation equations include various data measured by the sensors. Calculate the Kalman gain according to the state equations and observation equations. When the Kalman gain is larger, the filtering effect is better, which reflects that the accuracy of the sensors is higher. Thus, when the accuracy is the highest, take the value and include it in the algorithm model to reduce the error caused by sensor measurement, thereby improving the time accuracy of determining the intelligent gas well intermittent switching system;

[0116] Embodiment 4

[0117] This Embodiment 4 provides that in the data collected in S2 of the method for determining the intelligent intermittent switching system of this gas well, preprocess the collected data, including data cleaning, data conversion, feature extraction, and data standardization.

[0118] In specific implementation, data cleaning: perform cleaning operations such as duplicate removal, missing value processing, and outlier processing on the collected data to ensure the quality and accuracy of the data.

[0119] Data conversion: convert the format of the collected data, such as converting time series data into stationary time series data for subsequent analysis and modeling.

[0120] Feature extraction: extract key feature parameters according to the characteristics of gas well production. For example, when the gas well is in production, the minimum casing pressure p cb , the minimum tubing pressure p cb , and the maximum flow rate data Q gt ; when the gas well is shut in, capture the maximum casing pressure p ct , the maximum tubing pressure p ct , which serve as the basis for subsequent analysis and modeling.

[0121] Data standardization: perform standardization processing on the collected data to make it conform to a unified scale and range, so as to improve the accuracy and stability of analysis and modeling.

[0122] The above are only the preferred embodiments of the present invention and are not used to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for determining an intelligent intermittent switching regime of a gas well, characterized in that: Including the following steps: S1: Collect static parameters of the gas well, including the gas well depth H w , the tubing radius r ti , the casing radius r ai , the tubing submerged depth H s , the liquid-phase density ρ of natural gas l , the gas-phase density ρ of natural gas g ; S2: Data collection and processing, collecting relevant data during the production process of the gas well by installing sensors and monitoring devices; S3: Establishing a prediction model, obtaining the liquid accumulation state in the gas wellbore by establishing a liquid accumulation prediction model for the gas wellbore, and predicting the liquid volume of liquid accumulation in the wellbore by the liquid accumulation prediction model; S4: Establishing a mathematical model, fitting historical pressure data and historical flow rate data by establishing an unsteady seepage mathematical model for the formation and wellbore of an intermittent switched gas well and a coupled unsteady mathematical model for the formation and wellbore; S5: Formulating an intermittent switching regime, determining the optimal intermittent switching regime for the gas well by comparing the relationship curves between different open well times, shut-in times and the reduction of the liquid volume in the gas wellbore; S6: Optimization and improvement, continuously collecting and analyzing the production data of the gas well, continuously improving and optimizing the formulation and control methods of the intermittent switching regime to finally determine the intelligent intermittent switching regime for the gas well.

2. The method for determining an intelligent intermittent switching regime for a gas well according to claim 1, characterized in that: The above-mentioned S2, through the oil pressure sensor, casing pressure sensor, and gas-liquid two-phase flowmeter installed at the wellhead of the gas well, captures the minimum casing pressure p of the gas well during the production of the gas well when it is open for production cb , the minimum tubing pressure p cb , and the maximum flow rate data Q gt ; during the shutdown of the gas well, it captures the maximum casing pressure p of the gas well ct , the maximum tubing pressure p ct .

3. The method for determining an intelligent intermittent switching regime for a gas well according to claim 1, wherein: Determine the fluid volume Q in the upper section of the tubing through the mathematical model established in S3 wt_upper ; the fluid volume Q in the lower section wt_beneath ; the fluid volume Q in the tubing-casing annulus wa ; the fluid volume Q in the space below the shoe ws .

4. A method for determining an intelligent intermittent switching regime for a gas well according to claim 1, characterized in that: By establishing an unsteady seepage mathematical model of the formation and wellbore of the intermittent switch gas well and a coupled unsteady mathematical model of the formation and wellbore in S4, fitting the historical pressure data and historical flow rate data, and iteratively obtaining the pressure recovery rate △p of the gas well t , the pressure drop rate △p b and the relationship curve between the production time t of the gas well o are determined to obtain the open well time t of the gas well oi .

5. The method for determining an intelligent intermittent switching regime of a gas well according to claim 1, characterized in that: According to different open - well times \(t\) oi The corresponding liquid holdup \(Q\) in the wellbore w Based on the relationship curve of the change, determine the shut - in time \(t\) of the gas well ci .

6. The method for determining an intelligent intermittent switching regime of a gas well according to claim 1, characterized in that: By comparing different opening well times t oi , shut-in times t ci and the liquid volume Q in the gas well bore w to determine the relationship curve of reduction, the optimal intermittent switch system T oi , T ci .

7. A method for determining an intelligent intermittent switching regime for a gas well according to claim 1, characterized in that: At the said Q w(n) > Q w(n-1) , repeat S2 to S5, repeat opening and closing the well, and optimize the intermittent switching regime; when Q w(n) > Q w(n+1) , continue to execute the previous regime. Finally, by comparing the relationship curves of different well-opening times, well-shutting times and the reduction of the liquid volume in the gas wellbore, determine the optimal intermittent switching regime for the gas well, and finally determine the intelligent intermittent switching regime for the gas well.

8. A method for determining an intelligent intermittent switching regime of a gas well according to claim 1, characterized in that: In the above S3, the liquid accumulation volume of the current gas well is generated with the pre-acquired static parameters of the current gas well and the data captured in S2. If the liquid accumulation volume Qw of the gas wellbore ≤ 0, the liquid accumulation state of the gas wellbore cannot be judged, and S2 is carried out to re-capture real-time data until the liquid accumulation volume > 0.

Images