A method for integrated production allocation and dynamic evaluation of a tight gas well throughout its life cycle

Abstract

This invention discloses an integrated production allocation and dynamic evaluation method for the entire life cycle of tight gas wells, belonging to the field of gas well development. The method includes the following steps: S1, constructing a basic parameter dataset and seepage constraints for the target area; S2, establishing a standard for dividing the gas well's entire life cycle into stages; S3, outputting qualitative results of fracture morphology and orientation; S4, outputting quantitative parameters of the total number of fracturing fractures; S5, outputting dynamic parameters of the gas leakage radius at each production stage; S6, outputting dynamic reserve parameters for a single gas well; S7, outputting a staged production allocation benchmark chart; S8, outputting the full life cycle production prediction results; S9, solving for and outputting the optimal production allocation implementation scheme for the gas well; S10, iterative updating. Using this integrated production allocation and dynamic evaluation method for the entire life cycle of tight gas wells, refined dynamic evaluation and scientific production allocation are achieved throughout the entire process from commissioning to abandonment, significantly improving reservoir development efficiency and ultimate recovery rate.

Description

Technical Field

[0001] This invention relates to the field of gas well development technology, and in particular to an integrated production allocation and dynamic evaluation method for tight gas wells throughout their entire life cycle. Background Technology

[0002] Tight sandstone gas reservoirs are characterized by low porosity, low permeability, strong heterogeneity, and significant stress sensitivity, resulting in extremely low natural production capacity. Large-scale hydraulic fracturing is necessary to create an artificial fracture network in order to obtain industrial gas flow. The seepage process in fracturing gas wells is complex, involving dual-medium flow between fractures and matrix in the fracturing zone, stress-sensitive nonlinear seepage in the unfracturing zone, and multi-stage flow regime transitions. This presents significant challenges to the dynamic evaluation and rational production allocation of gas wells.

[0003] Existing technologies for tight gas well production allocation and dynamic evaluation mainly have the following shortcomings: 1. Inaccurate division of the entire life cycle stage: Existing technologies mostly use a single empirical indicator of output or pressure to divide the production stage, which cannot accurately identify the transition nodes of unstable flow, quasi-steady state, and decay and abandonment, making it difficult to guide phased differentiated development.

[0004] 2. Low accuracy of fracturing fracture parameter inversion and impact on production: Traditional fracture parameter inversion is highly dependent on shut-in pressure recovery testing, which requires production to be shut down for several days to several weeks, seriously affecting the continuous production of gas wells; moreover, the inversion model mostly adopts the assumption of homogeneous single medium, without considering the dual-pore medium characteristics of the modified zone and the stress sensitivity effect of the non-modified zone, resulting in a large deviation between the fracture half-length and conductivity obtained by inversion and the actual values. Summary of the Invention

[0005] The purpose of this invention is to provide an integrated production allocation and dynamic evaluation method for tight gas wells throughout their entire life cycle, thereby solving the aforementioned technical problems.

[0006] To achieve the above objectives, this invention provides an integrated production allocation and dynamic evaluation method for tight gas wells throughout their entire lifecycle, comprising the following steps: S1. Collect geological structural parameters, sedimentary characteristic parameters, reservoir physical property parameters, natural gas fluid parameters, gas well static parameters, gas well production dynamic data, well test data and multi-well interference data of the target area, carry out seepage mechanism analysis of tight sandstone gas reservoir, and construct basic parameter dataset and seepage constraint conditions of the target area; S2. Based on the basic parameter dataset and seepage constraint conditions constructed in S1, seepage mathematical models for fractured vertical wells and fractured horizontal wells are constructed respectively. The bottom hole pressure and pressure derivative double logarithmic curves are obtained by solving them. Combined with reservoir physical parameters, fracture parameters and boundary control flow characteristics, a standard for dividing the full life cycle stages of gas wells is established. S3, based on the well test data of S1, multi-well interference data and the gas well life cycle stage discrimination criteria output by S2, uses the multi-well interference theory and the bottom hole pressure superposition principle to analyze the dynamic response characteristics corresponding to different fracture morphologies, fracture symmetry and fracture orientation. The grey relational analysis method is used to complete the qualitative discrimination of the directionality and symmetry of the fracturing fracture, and output the qualitative results of fracture morphology and orientation. S4. Based on the gas well production dynamic data and well test data of S1, as well as the qualitative results of fracture morphology and orientation output by S3, numerical well testing method and non-stop variable flow well testing technology are used to carry out quantitative inversion of fracturing fracture parameters in combination with production dynamic fitting method. The fracture half length and fracture conductivity are solved, and the accuracy of the inversion parameters is verified. The full quantitative parameters of fracturing fracture are output. S5. Based on the reservoir physical parameters of S1, the gas well life cycle stage boundary parameters output by S2, and the full quantitative parameters of fracturing fractures output by S4, define dimensionless parameters, establish a method for calculating the gas leakage radius of different production stages of the gas well, and output the dynamic parameters of the gas leakage radius of each production stage. S6. Based on the gas well production dynamic data of S1, the gas well life cycle stage boundary parameters output by S2, and the gas leakage radius dynamic parameters output by S5, determine the dynamic reserve calculation method for quasi-steady-state production wells and non-quasi-steady-state production wells, and output the dynamic reserve parameters of a single gas well. Based on the reservoir and fluid parameters of S1, the quantitative parameters of the fracturing fracture output by S4, and the dynamic parameters of the venting radius output by S5, the gas well free flow rate is calculated using the simulated modified isochronous well test method. The reasonable production allocation technology charts for the unstable flow stage and the quasi-steady state stage, as well as the corresponding production limits, are constructed respectively. The phased production allocation benchmark charts and production limits are output. S8, based on the gas well life cycle stage boundary parameters output by S2, the full quantitative parameters of fracturing fractures output by S4, the dynamic parameters of gas leakage radius output by S5, the dynamic reserves parameters of a single well output by S6, and the staged production allocation benchmark chart output by S7, respectively establish an unstable flow production calculation model and a quasi-steady-state production calculation model to predict the gas well production decline rate and recovery degree, and output the full life cycle production prediction results. S9. Based on the phased production allocation benchmark chart output by S7 and the full life cycle production prediction results output by S8, a multi-objective production allocation optimization model is established, and the optimal production allocation implementation plan for gas wells is output after solving the model. S10. Execute the optimal production allocation implementation plan output by S9, continuously collect on-site gas well operation data, and iteratively update the stage discrimination model of S2, the fracture inversion model from S3 to S4, the production allocation chart of S7, and the production operation evaluation model of S8.

[0007] Therefore, the beneficial effects of the above-mentioned integrated production allocation and dynamic evaluation method for the entire life cycle of tight gas wells in this invention are as follows: 1. Precise division of production stages supports differentiated development in stages: Based on the composite seepage model of "double hole in the modified area + single hole in the non-modified area" to solve the double logarithmic curve of bottom hole pressure-pressure derivative, the well is divided into seven sub-stages of seepage and three macro-stages of production. The formula for calculating the boundary control flow time is derived and corrected by field production data. The error of the stage boundary node is small, which provides a scientific basis for the formulation of production strategies for different development stages. 2. Highly efficient and accurate fracture parameter inversion while ensuring production continuity: It integrates non-stop variable flow testing technology and numerical testing methods, and can invert core parameters such as fracture half-length and conductivity without shutting down the well. At the same time, it uses synchronous shut-down pressure recovery test data to verify the inversion accuracy and calculate the compliance rate of individual parameters and the overall average compliance rate, which not only ensures continuous gas well production, but also significantly improves the reliability of fracture parameter inversion. 3. Dynamic calculation of venting radius makes reserve evaluation more realistic: Six types of dimensionless parameters are defined and their exponential time-series variation laws are clarified. A phased dynamic venting radius calculation method is established, which fully considers the effects of stress sensitivity during production, such as crack closure and matrix permeability decay. This solves the problems of overestimation and distortion of reserve utilization evaluation caused by traditional static calculation methods. 4. Refined production allocation by well type and stage to maximize production capacity and reserve utilization: The gas well unobstructed flow rate is calculated by using a one-point method for preliminary estimation and fitting the binomial production capacity equation. Dedicated production allocation technical charts are constructed for unstable flow (constrained gas leakage radius damage rate <10%) and quasi-steady state (with production maximization as the goal). Differentiated production allocation schemes are formulated for gas wells of different production capacity levels of Class I / II / III, which effectively avoids the problem of high-yield wells being over-produced and prematurely exhausted, and low-yield wells being under-produced and wasting production capacity. 5. Integrated closed-loop iteration with strong long-term adaptability: A closed-loop technical process of "parameter inversion - dynamic evaluation - production optimization - real-time update" is formed. During the execution of the optimal production plan, on-site operation data is continuously collected, and the stage discrimination model, crack inversion model, production plan and output prediction model are iteratively updated to ensure that the production plan is dynamically adjusted with the development process and maintains the best development effect in the long term.

[0008] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0009] Figure 1 This is a flowchart of an integrated production allocation and dynamic evaluation method for the entire life cycle of a tight gas well, according to the present invention. Figure 2This is a schematic diagram of the seepage physical model of an integrated production allocation and dynamic evaluation method for the entire life cycle of a tight gas well according to the present invention. Figure 3 This is a schematic diagram of the fracture discretization process in a tight gas well integrated production allocation and dynamic evaluation method throughout its entire life cycle, as described in this invention. Figure 4 This is a schematic diagram of a fracturing vertical well numerical model for an integrated production allocation and dynamic evaluation method for the entire life cycle of a tight gas well, as described in this invention. Figure 5 This is a comparison chart of numerical model results for a fractured vertical well using a tight gas well integrated production allocation and dynamic evaluation method throughout its entire life cycle, as described in this invention. Figure 6 This is a typical curve of pressure and pressure derivative of a fractured vertical well, which is a method for integrated production allocation and dynamic evaluation of tight gas wells throughout their entire life cycle, according to the present invention. Figure 7 The graphs show the dimensionless discharge radius over time for a tight gas well integrated production allocation and dynamic evaluation method throughout its entire life cycle, as presented in this invention. (a) is the dimensionless discharge radius over time for Class I wells, (b) is the dimensionless discharge radius over time for Class II wells, (c) is the dimensionless discharge radius over time for Class III wells, and (d) is the discharge radius over time for all wells. Figure 8 The graphs show the dimensionless average pressure permeability variation curves of a tight gas well's integrated production allocation and dynamic evaluation method throughout its entire life cycle, as presented in this invention. (a) is the dimensionless average pressure permeability variation curve for Class I wells, (b) is the dimensionless average pressure permeability variation curve for Class II wells, (c) is the dimensionless average pressure permeability variation curve for Class III wells, and (d) is the dimensionless average pressure permeability variation curve for all wells. Figure 9 The graphs show the dimensionless correction time versus time curves of a tight gas well integrated production allocation and dynamic evaluation method throughout its entire life cycle, as presented in this invention. (a) is the dimensionless correction time versus time curve for Class I wells, (b) is the dimensionless correction time versus time curve for Class II wells, (c) is the dimensionless correction time versus time curve for Class III wells, and (d) is the dimensionless correction time versus time curve for all wells. Figure 10 The graphs show the dimensionless inner zone radius over time for a tight gas well integrated production allocation and dynamic evaluation method throughout its entire life cycle, as presented in this invention. (a) shows the dimensionless inner zone radius over time for Class I wells, (b) shows the dimensionless inner zone radius over time for Class II wells, (c) shows the dimensionless inner zone radius over time for Class III wells, and (d) shows the dimensionless inner zone radius over time for all wells. Figure 11 The diagram shows the dimensionless fracture conductivity variation curves of a tight gas well's integrated production allocation and dynamic evaluation method throughout its entire life cycle, as presented in this invention. (a) is the dimensionless fracture conductivity variation curve for Class I wells, (b) is the dimensionless fracture conductivity variation curve for Class II wells, (c) is the dimensionless fracture conductivity variation curve for Class III wells, and (d) is the dimensionless fracture conductivity variation curve for all wells. Figure 12 The diagram shows the stress sensitivity analysis results of a Type I vertical well for the test case. (a) shows the variation of the unobstructed flow rate of the Type I vertical well over time, (b) shows the variation of the unobstructed flow rate of the Type I vertical well over pressure, and (c) shows the loss of unobstructed flow rate of the Type I vertical well caused by stress sensitivity. Figure 13 The diagram shows the stress sensitivity analysis results of a Type II vertical well for the test case. (a) shows the variation of the unobstructed flow rate of the Type II vertical well over time, (b) shows the variation of the unobstructed flow rate of the Type II vertical well over pressure, and (c) shows the loss of unobstructed flow rate of the Type II vertical well caused by stress sensitivity. Figure 14 The diagram shows the stress sensitivity analysis results of a Class III vertical well for the test case. (a) shows the variation of the unobstructed flow rate of the Class III vertical well over time, (b) shows the variation of the unobstructed flow rate of the Class III vertical well over pressure, and (c) shows the loss of unobstructed flow rate of the Class III vertical well caused by stress sensitivity. Figure 15 This is a schematic diagram of the controlled and dynamic reserves distribution for the test case. Detailed Implementation

[0010] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are merely illustrative of the embodiments of the present invention and are not intended to limit the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of this application. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout.

[0011] It should be noted that the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion, such as a process, method, system, product, or server that includes a series of steps or units, not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such process, method, product, or device.

[0012] The embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0013] like Figure 1 As shown, a method for integrated production allocation and dynamic evaluation throughout the entire life cycle of tight gas wells includes the following steps: S1. Collect geological structural parameters, sedimentary characteristic parameters, reservoir physical property parameters, natural gas fluid parameters, gas well static parameters, gas well production dynamic data, well test data and multi-well interference data of the target area, carry out seepage mechanism analysis of tight sandstone gas reservoirs, and construct basic parameter dataset and seepage constraint conditions for the target area.

[0014] S2. Based on the basic parameter dataset and seepage constraint conditions constructed in S1, seepage mathematical models for fractured vertical wells and fractured horizontal wells are constructed respectively. The bottom hole pressure and pressure derivative double logarithmic curves are obtained. Combined with reservoir physical parameters, fracture parameters and boundary control flow characteristics, a standard for dividing the gas well life cycle stages is established.

[0015] S3, based on the well test data of S1, multi-well interference data, and the gas well life cycle stage discrimination criteria output by S2, uses the multi-well interference theory and the bottom hole pressure superposition principle to analyze the dynamic response characteristics corresponding to different fracture morphologies, fracture symmetry, and fracture orientation. The grey relational analysis method is used to complete the qualitative discrimination of the directionality and symmetry of the fracturing fractures, and output the qualitative results of fracture morphology and orientation.

[0016] S4. Based on the gas well production dynamic data and well test data from S1, as well as the qualitative results of fracture morphology and orientation output from S3, numerical well testing methods and non-stop variable flow well testing technology are used, combined with production dynamic fitting methods to carry out quantitative inversion of fracturing fracture parameters, solve for fracture half-length and fracture conductivity, complete the accuracy verification of inversion parameters, and output the full quantitative parameters of fracturing fractures.

[0017] Based on the reservoir physical parameters of S1, the gas well life cycle stage boundary parameters output by S2, and the full quantitative parameters of fracturing fractures output by S4, dimensionless parameters are defined, a method for calculating the gas leakage radius at different production stages of the gas well is established, and dynamic parameters of the gas leakage radius at each production stage are output.

[0018] S6, based on the gas well production dynamic data of S1, the gas well life cycle stage boundary parameters output by S2, and the gas leakage radius dynamic parameters output by S5, determines the dynamic reserve calculation method for quasi-steady-state production wells and non-quasi-steady-state production wells, and outputs the dynamic reserve parameters of a single gas well.

[0019] Based on the reservoir and fluid parameters of S1, the quantitative parameters of fracturing fractures output by S4, and the dynamic parameters of venting radius output by S5, the gas well free flow rate is calculated using the simulated modified isochronous well test method. The reasonable production allocation technology charts for the unstable flow stage and the quasi-steady-state stage, as well as the corresponding production limits, are constructed respectively. The staged production allocation benchmark charts and production limits are output.

[0020] Based on the gas well life cycle stage boundary parameters output by S2, the full quantitative parameters of fracturing fractures output by S4, the dynamic parameters of gas leakage radius output by S5, the dynamic reserves parameters of a single well output by S6, and the staged production allocation benchmark chart output by S7, an unstable flow production calculation model and a quasi-steady-state production calculation model are established respectively to predict the gas well production decline rate and recovery degree, and output the full life cycle production prediction results.

[0021] Based on the phased production allocation benchmark chart output by S7 and the full life cycle production prediction results output by S8, a multi-objective production allocation optimization model is established, and the optimal production allocation implementation plan for gas wells is output after solving the model.

[0022] S10. Execute the optimal production allocation implementation plan output by S9, continuously collect on-site gas well operation data, and iteratively update the stage discrimination model of S2, the fracture inversion model from S3 to S4, the production allocation chart of S7, and the production operation evaluation model of S8.

[0023] Step S1 specifically includes the following steps: S11. Simultaneously acquire geological structural parameters, sedimentary characteristic parameters, reservoir physical property parameters, natural gas fluid parameters, gas well static parameters, gas well production dynamic data, well test data, and multi-well interference data of the target area to obtain the original multidimensional dataset. Among them, the geological structural parameters include basin structural units, formation dip angle, and structural morphology; the sedimentary characteristic parameters include target strata, sedimentary facies, spatial distribution of gas layers, and gas layer thickness; the reservoir physical property parameters include rock type, pore type, porosity, and permeability; the natural gas fluid parameters include natural gas viscosity, compressibility factor, and comprehensive compressibility coefficient; the gas well static parameters include well type, wellbore radius, well-reservoir coefficient, skin coefficient, and designed fracture geometry parameters; the gas well production dynamic data includes daily gas production per well, cumulative gas production, formation pressure, wellhead casing pressure, pressure drop, and production decline rate; the well test data includes bottomhole pressure and pressure derivative time-series monitoring data; and the multi-well interference data includes synchronous change sequence data of production and pressure of adjacent wells.

[0024] S12. Perform outlier removal, temporal alignment, and format unification on the original multidimensional dataset in sequence to obtain a standardized dataset.

[0025] S13. Conduct separate analyses of the gas slippage effect mechanism, the aqueous phase initiation pressure gradient mechanism, the reservoir stress sensitivity effect mechanism, and the high-speed non-Darcy effect mechanism. Determine that the main control factors of seepage are the stress sensitivity effect and the aqueous phase initiation pressure gradient. It is determined that the slippage effect and the high-speed non-Darcy effect can be ignored under field conditions.

[0026] The specific mechanism analysis of the gas slip effect involves using the formula for calculating the tight gas slip effect to quantify the degree of influence of this effect. ; In the formula, For gas permeability; Equivalent liquid permeability; The slip coefficient; Mean pressure of the formation; Based on the calculation results and on-site conditions, it was determined that when the gas permeability was measured... When the depth is greater than 0.1 mD and the average formation pressure is greater than 5 MPa, the effect of the slippage effect on the gas seepage flow is less than 5%, and this effect can be ignored under the on-site production conditions in the target area. The reservoir stress sensitivity effect mechanism analysis specifically involves analyzing six major influencing factors: original reservoir permeability, rock type, cement type, bound water saturation, clay and impurity content, and artificial fracturing effect. It is determined that a decrease in formation pressure will induce deformation of the rock skeleton and closure of pores and artificial fractures, thereby causing a decrease in matrix permeability and fracture conductivity. This effect is a key factor affecting gas well seepage. The specific mechanism of the high-speed non-Darcy effect is as follows: combining the permeability of the tight reservoir in the target area and the gas flow velocity, it is determined that the high-speed non-Darcy effect has no significant impact under the field conditions and can be directly ignored.

[0027] S14. Based on the main control factors of seepage determined in S13, define the seepage constraint conditions for the entire process of technical modeling, numerical simulation, and dynamic analysis.

[0028] S15, based on the standardized dataset of S11 and the seepage constraints determined in S14, unifies data fields and association rules to construct a basic parameter dataset for the target area.

[0029] Step S2 specifically includes the following steps: S21. Based on the basic parameter dataset and seepage constraint conditions constructed in S1, build physical models of fractured vertical wells and fractured horizontal wells.

[0030] By combining reservoir physical parameters, natural gas fluid parameters, and gas well static parameters in S1, a physical model of seepage in a fractured vertical well is constructed; for example... Figure 2As shown, the physical model of seepage in a fractured vertical well is divided into a modified zone and a non-modified zone. The modified zone is a fracture-matrix dual-medium system, while the non-modified zone is a homogeneous single-medium system. The artificial hydraulic main fracture penetrates the reservoir.

[0031] Based on the physical model framework of the seepage in a fractured vertical well and combined with the structural parameters of the horizontal well, a physical model of the seepage in a fractured horizontal well was constructed.

[0032] In this embodiment, the basic assumptions are uniformly set for the mathematical models of seepage in fractured vertical wells and fractured horizontal wells: (1) Single-phase microcompressible fluid undergoes planar radial seepage in an infinitely large reservoir; (2) Gravity and capillary force are ignored; (3) Fluid flow satisfies linear Darcy flow; (4) The stirred zone is a dual-pore medium, consisting of a fracture system and a matrix system, with the fracture system serving as the fluid flow channel (permeability is 100%). Porosity is The matrix system is a reservoir for fluids (with a permeability of...). Porosity is The unmodified area is a single homogeneous reservoir (with a permeability of ), Porosity is (5) Oil wells are used to determine production rates. Production, wellbore flow considerations, wellbore storage and epidermal coefficient (6) There is no pressure drop at the seepage interface between the inner and outer zones; (7) The pressure at all points in the formation before the test is the original reservoir pressure. (8) Formation fluid first flows from the outer zone single-pore medium system into the inner zone double-pore medium system, then from the inner zone double-pore medium system into the hydraulic main fracture, and then from the hydraulic main fracture into the vertical wellbore, with pressure drop along the fracture.

[0033] S22. Based on the fracturing vertical well model and the fracturing horizontal well physical model built in step S21, establish the fracturing vertical well seepage mathematical model and the fracturing horizontal well seepage mathematical model, respectively.

[0034] S221. Define the following dimensionless quantity: Dimensionless bottom hole pressure ; Dimensionless crack production ; Dimensionless Time ; Dimensionless well reservoir coefficient ; Dimensionless fracture conductivity ; Storage ratio ; Crossflow coefficient ; Flow ratio ; Transformation coefficient ratio ; In the formula, The permeability of cracks in the redevelopment area; The effective thickness of the reservoir; For gas well production; The dynamic viscosity of natural gas in the redevelopment area; This is the gas volume coefficient; This represents the original formation pressure; for Constant formation pressure; The length of the crack is half its length; For the production of crack micro-elements; For matrix porosity; The overall compressibility coefficient of the matrix; For crack porosity; The crack's overall compressibility coefficient; The wellbore storage coefficient; The overall porosity of the transformation area; The comprehensive compression coefficient of the redevelopment area; The permeability of the hydraulic fracture; The width of the crack; The current churn constant; For matrix permeability; Permeability in non-renovated areas; The dynamic viscosity of natural gas in the non-modified area; Porosity of the unmodified area; This is the comprehensive compression coefficient for the non-renovation area.

[0035] S222. Based on the fracturing vertical well model and fracturing horizontal well physical model built in S21, dimensional seepage control equations are established for each zone: Dimensional seepage control equation for the modified area: ; Dimensional seepage control equations for the unmodified zone: ; Dimensional seepage equation for hydraulic fractures: ; In the formula, This refers to the instantaneous pressure of the formation. Radial distance; To modify the temporal stratigraphic pressure in the transformation area; For the non-reformed area, the temporal stratigraphic pressure; The pressure inside the crack; Standard pressure; Formation temperature; For the production of crack micro-elements; The equivalent permeability of the crack; The width of the crack; Standard temperature; It is the dimensional permeability modulus.

[0036] S223. Based on the dimensionless parameters defined in step S221, the dimensional equation in step S222 is transformed into a dimensionless seepage control equation, and the corresponding general solution is derived.

[0037] S2231. Establish the following dimensionless seepage control equations for the modified area: ; The general solution of the modified area is derived. : ; in, ; In the formula, For dimensionless pressure in the transformed region under the Laplace transform domain; For the Laplace transform operator; , All of these are undetermined coefficients for the general solution of the transformation area; It is a zero-order modified Bessel function of the second kind; It is a zero-order modified Bessel function of the first kind; For auxiliary functions; It is a dimensionless radial distance.

[0038] S2232. Establish the following original dimensionless seepage control equations for the unmodified zone: ; The original dimensionless seepage control equations for the unmodified zone are simplified by perturbation to obtain the simplified dimensionless seepage control equations for the unmodified zone: ; in, ; The general solution for the non-modified region is derived. : ; In the formula, There is no dimensional pressure in the non-renovation area; To assist in dimensionless well reservoir coefficient; The comprehensive seepage coefficient; The non-modified region has dimensionless pressure after the perturbation transformation; For perturbation pressure in Laplace space; , All of these are undetermined coefficients for the general solution of the non-renovation area.

[0039] S2233. Establish the dimensionless seepage equation for hydraulic fractures: ; In the formula, The output of dimensionless crack micro-element; The pressure is a dimensionless crack.

[0040] S224. Based on the global characteristics of the physical model, establish the boundary conditions corresponding to the mathematical model, including initial conditions, boundary conditions, and coupling conditions of regional interfaces.

[0041] S2241. Establish global initial conditions: Dimensional initial conditions: ; Dimensionless initial conditions: ; In the formula, This represents the original formation pressure; The initial dimensionless pressure.

[0042] S2242. Establish boundary conditions: Boundary conditions within the modification area: Boundary conditions outside the non-modified area: ; In the formula, The modified area has a dimensionless radial pressure gradient; For the dimensionless crack yield in the Laplace domain; For the dimensionless perturbation pressure of the non-modified region at infinity under the Laplace domain.

[0043] S2243. Establish coupling conditions at the interface between the modified zone and the non-modified zone: ; In the formula, For the transformation of dimensionless pressure within the Laplace domain; For dimensionless perturbation pressure in the non-modified region under the Laplace domain; The dimensionless outer radius of the transformation area; The modified area has a dimensionless radial pressure gradient; The non-modified region has a dimensionless radial pressure gradient.

[0044] To verify the establishment of the present invention, as shown below. Figure 4 To verify the reliability of the results of the hydraulic main fracture + dual-hole + single-hole two-zone composite model, a numerical model was built using the well testing software Saphir to compare and verify this semi-analytical model.

[0045] Table 1 Model Parameters

[0046] The results are as follows Figure 5 As shown, the pressure and pressure derivative curves obtained under the two algorithms basically overlap, proving the reliability of the hydraulic main fracture + dual-hole + single-hole two-zone composite well test model established in this invention.

[0047] S23. Perform Laplace transformation and numerical solution on the dimensionless governing equations of step S223 and the boundary conditions of step S224 to obtain the numerical solutions of the bottom hole pressure and pressure derivative.

[0048] S231. Discretize the hydraulic fracture in S224 into elements, establish the seepage relationship equation of the fracture micro-element, and solve the one-dimensional Darcy flow equation inside the fracture.

[0049] like Figure 3 As shown, in this embodiment, it is assumed that the flow in the crack is a one-dimensional Darcy linear flow, and the Fredholm integral equation and boundary element method are used to perform integration and then discretization.

[0050] Specifically, according to Darcy's law of seepage, the first The grid and the first The seepage relationship between the grids is as follows: (1); In the formula, For the first Pressure at each grid point The length of each grid, The linear density flux of the crack is expressed as follows: (2); Substituting equation (2) into equation (1) and integrating, we get: (3); (4); (5); Combining equations (3), (4), and (5) with the flow normalization condition, we can obtain the following matrix equation: (6); The above matrix equation describes the fluid seepage process in a fracture. For a homogeneous, uniformly high fracture, if the flow inside the fracture is one-dimensional linear, then the coefficient matrix... It is a constant matrix, and its dimension changes with the number of discrete crack elements.

[0051] S232. Perform a Laplace transform on the dimensionless seepage equation in S22 to convert the time-domain equation into a complex frequency-domain equation, and solve the complex frequency-domain pressure solution for the modified zone, the unmodified zone, and the hydraulic fracture zone respectively.

[0052] S233. Combining the formulas in steps S223-S224, we obtain the pressure of the point sink at any location in the reservoir in Laplace space: ; in, ; In the formula, The yield of dimensionless crack infinitesimal elements in the Laplace domain; These are the combination coefficients of the Bessel functions; Infiltrating the redevelopment area; It is a first-order modified Bessel function of the first kind.

[0053] S234. The pressure at any location in the reservoir under the control of the main fracture is obtained by using the superposition principle. : ; S235, The pressure at the crack wall is derived. : ; S236. Obtain the expression for the pressure at each crack element: ; In the formula, The coupling matrix of the crack element; - They are respectively the 1st- The dimensionless product of the Laplace domain of a crack infinitesimal element; - They are respectively the 1st- The Laplace domain dimensionless pressure of a crack element; The dimensionless bottom hole pressure in the Laplace domain.

[0054] S237. Using the Stehfest numerical inversion algorithm, the complex frequency domain solution is restored to the real domain solution, and finally the numerical results of the bottom hole pressure and pressure derivative at different times are obtained.

[0055] S24. Based on the numerical solutions of bottom hole pressure and pressure derivative obtained from S23, plot the following with dimensionless time as the horizontal axis and dimensionless pressure and dimensionless pressure derivative as the vertical axis: Figure 6 The diagram shows a double logarithmic curve of bottom hole pressure versus pressure derivative. Based on the curve shape and slope characteristics, it is divided into seven subdivided seepage stages, and the identification criteria for each stage are clearly defined: Bilinear flow stage in cracks: The slope of the pressure derivative curve is 1 / 4.

[0056] Linear flow stage perpendicular to the crack: the slope of the pressure derivative curve is 1 / 2.

[0057] The pseudo-radial flow stage of the crack: the pressure derivative curve shows a horizontal segment for a set time period.

[0058] During the stage of matrix flow into microcracks: the pressure derivative curve shows a concave shape.

[0059] Radial flow stage of the modified system: horizontal section with a pressure derivative of 0.5.

[0060] During the transition from the modified area to the non-modified area: the pressure curve and the pressure derivative curve rise synchronously.

[0061] Radial flow stage of reservoir system: pressure derivative is numerically equal to The horizontal segment.

[0062] S25. Based on the detailed seepage stages defined in S24, and combined with the reservoir physical parameters, fracture parameters, and boundary control flow response characteristics in S1, the production stages of the gas well's entire life cycle are divided as follows: Unstable flow stage: Before the boundary control flow appears, the pressure wave has not reached the outer boundary of the reservoir, and the venting radius continues to expand dynamically.

[0063] Quasi-steady-state stage: The boundary control flow continues within a certain range, the venting radius remains fixed, and the formation experiences uniform pressure drop throughout the region.

[0064] Exhaustion and abandonment stage: After the boundary control flow ends, the formation energy continues to be depleted, and the production and pressure continue to decline until the conditions for abandonment are met.

[0065] S26. Based on seepage theory and the stage division logic in S25, derive the formula for calculating the boundary control flow time: ; In the formula, The time when the boundary control flow appears is the time that marks the boundary between the unstable flow phase and the quasi-steady state phase. The length of the crack is half its length; This represents the reservoir matrix permeability.

[0066] S27. Retrieve the gas well production decline data collected in S1, and compare, verify and correct the initial stage division criteria in S25 and the boundary control flow time calculation formula in S26.

[0067] Step S4 specifically includes the following steps: S41. Using the non-stop well testing technology with variable flow rate, calculate the following in sequence: Dimensionless pressure for well test analysis ; Dimensionless time for well test analysis ; stratigraphic coefficient ; Gas well skin coefficient ; Pressure recovery time to extreme values ​​under variable production conditions ; In the formula, This represents the change in pressure. Production output during the unstable flow phase; This is the gas volume coefficient; The slope of the pressure-time fitting curve; This represents the production output during the quasi-steady-state phase. This refers to the continuous production time during the unstable flow phase. The overall porosity of the formation; This refers to the dynamic viscosity of natural gas.

[0068] S42. Based on the basic formation parameters obtained in S41 and combined with the fracture qualitative results in S3, a radial composite formation numerical well test model is constructed.

[0069] S421 adopts a fixed-well reservoir, limited-flow fractured vertical well, radial composite reservoir and circular closed boundary model architecture as the overall framework of the model.

[0070] S422. Based on the qualitative results of crack morphology and orientation in S3, input the crack geometric conditions into the model.

[0071] At the same time, input the S1 basic parameters and complete the model mesh generation, medium partitioning, and internal and external boundary condition settings.

[0072] S43. Based on the numerical well test model built in S42, quantitative inversion of core parameters of the fracturing fracture is carried out by combining the dynamic fitting method of production output, solving the fracture half-length and fracture conductivity, and obtaining wellbore and reservoir parameters.

[0073] S431. Use the production dynamic analysis tool to import the full-time production and pressure data from S1, and perform historical curve fitting for pressure and production.

[0074] S432. Iteratively adjust the crack-related parameters within the model until the fitted curve matches the measured curve.

[0075] S433. Extract the parameter results after fitting convergence to obtain the two core fracture parameters: fracture half-length and fracture conductivity. At the same time, obtain the wellbore and reservoir parameters, including the wellbore reservoir coefficient, inner and outer zone permeability, inner zone radius and discharge radius.

[0076] S44. Based on the inversion results of the well test without shutting down the well, the parameter accuracy was compared and verified using the shut-in pressure recovery test data, and the parameter compliance rate was calculated.

[0077] S441. Retrieve the shut-in pressure recovery test data conducted simultaneously in S1, and use the shut-in well test method to solve for the dimensional fracture half-length of the same well group. Dimensional fracture conductivity Dimensional stratigraphic porosity Dimensional discharge radius : ; ; ; ; In the formula, The semi-logarithmic characteristic time of the shut-in pressure recovery curve; The reservoir pressure conductivity coefficient; This refers to the well shut-in pressure recovery time.

[0078] S442. Compare the parameters obtained from the continuous flow test and numerical test with the parameters obtained from the shut-in test one by one, and calculate the individual compliance rate and the overall average compliance rate for fracture half-length, fracture conductivity, porosity, and discharge radius.

[0079] S443. Determine the accuracy of the inversion. When the overall average compliance rate reaches the allowable range of the project, the inversion parameters are deemed valid.

[0080] S45. Summarize all parameters obtained from the inversion in S43 and the accuracy verification results in S44, organize and classify them, and output the full quantitative parameters of the fracturing fractures. The full quantitative parameters of the fracturing fractures include fracture half-length, fracture conductivity and related wellbore and reservoir parameters.

[0081] Step S5 specifically includes the following steps: S51. Define the dimensionless discharge radius respectively. Dimensionless crack half length Dimensionless average pressure conductivity Dimensionless correction time Dimensionless inner radius Dimensionless fracture conductivity : ; ; ; ; ; ; In the formula, For production time The corresponding real-time discharge radius; The discharge radius is the radius of the first year of production. For production time The corresponding real-time crack half-length; The crack length is half that of the first year of production; The weighted average penetration rate of the inner and outer zones, and , The penetration rate of the redevelopment area; Permeability in non-renovated areas; The radius of the transformation area; This refers to the real-time discharge radius; For production time The corresponding real-time correction coefficient, and , The correction period is for the first year of production; For production time The corresponding real-time modification zone radius; The radius of the modified area during the first year of production; The real-time crack flow conduction capacity corresponding to production time t; To improve the crack flow capacity for the first year of production.

[0082] S52. Extract full-time production data and complete the processing of dimensionless parameter time-series samples.

[0083] S521. Combining the stage boundary time nodes output by S2, divide the time nodes for different production durations (1 year, 2 years... up to the end of production), and extract the values ​​of the six types of dimensionless parameters defined by S52 under each node.

[0084] S522. Group the sample data according to the categories of Class I, Class II, and Class III gas wells to form a classified time series dataset.

[0085] Among them, Class I gas wells meet the following quantitative indicators: Unobstructed flow rate greater than 5×10 4 m 3 / d.

[0086] The final cumulative gas extraction volume is greater than 3500×10 4 m 3 .

[0087] The three-year average daily gas production is greater than 1.8 × 10 4 m 3 / d.

[0088] The total thickness of the gas layer is greater than 10m.

[0089] The maximum thickness of a single layer shall not be less than 3m.

[0090] The period of stable production shall not be less than 3 years.

[0091] Class II gas wells meet the following quantitative indicators: Unobstructed flow: .

[0092] Final cumulative gas production: .

[0093] Three-year average daily gas production: .

[0094] Total cumulative gas layer thickness: .

[0095] The maximum thickness of a single layer shall not be less than 3m.

[0096] The period of stable production shall not be less than 3 years.

[0097] Class III gas wells meet the following quantitative indicators.

[0098] Unobstructed flow rate less than 3×10 4 m 3 / d; The final cumulative gas production is less than 1350×10 4 m 3 .

[0099] The three-year average daily gas production is less than 0.8 × 10 4 m 3 / d.

[0100] The total thickness of the gas layer is less than 4m.

[0101] The maximum thickness of a single layer shall not exceed 3m.

[0102] The period of stable production is less than 3 years.

[0103] S53, such as Figures 7-11 As shown, the variation patterns of six types of dimensionless parameters with production time are analyzed, and it is determined that all six types of dimensionless parameters conform to the time-series variation pattern of exponential functions.

[0104] S54. Based on the changing patterns obtained in S53, establish time series regression formulas for various dimensionless parameter-free exponential functions: ; In the formula, For any type of dimensionless parameter; , All are regression coefficients.

[0105] By fitting the sample data using Class I, Class II, and Class III gas well classifications, six categories of dimensionless parameters were obtained. , The coefficients form a set of time-series regression equations for well types and parameters.

[0106] S55. Based on the dimensional real-time venting radius calculation formulas for the unstable flow stage, quasi-steady-state stage, and decay and abandonment stage as defined in S2, the venting radii for the three production stages are obtained; the dimensional real-time venting radius calculation formulas are as follows: ; S56. Based on the type of gas well, retrieve the corresponding time series regression coefficients, substitute them one by one into the S55 formula, calculate the leakage radius at different time nodes, and verify the calculation results in conjunction with the constraints of each stage, eliminate abnormal values, and determine the dynamic value of the leakage radius at each stage.

[0107] S57. Summarize the full-time and phased vent radius calculation results, organize the parameter ledger, and output the dynamic parameters of the vent radius for each production stage.

[0108] Step S6 specifically includes the following steps: S61. Based on the S2 gas well life cycle stage discrimination standard, the target gas well is classified into operating conditions: wells in the unstable flow stage are classified as non-steady-state production wells, and wells in the quasi-steady-state stage are classified as quasi-steady-state production wells.

[0109] S62. Establish the Arps declining output method calculation model: ; In the formula, This represents the cumulative gas production of the gas well. This represents the initial gas production of the gas well. A decreasing exponent; This is the initial decrease rate.

[0110] S63. Establish a production instability analysis model and calculate the pseudo-pressure of natural gas. Material balance pseudo-time and dynamic reserves of a single well : ; ; ; In the formula, Formation pressure; Bottom hole flowing pressure; The compressibility factor of natural gas; The viscosity of natural gas under the original formation conditions; The overall compressibility coefficient of the original gas; This is the product of the time-averaged viscosity and the compressibility factor. This is a combined term of viscosity, compressibility coefficient, and compressibility factor beneath the original strata. To fit the slope of the straight line.

[0111] S64. Establish a material balance calculation model: ; In the formula, This is the original formation compression factor.

[0112] S65. Establish an elastic two-phase method calculation model and derive the pressure relationship formula and dynamic storage calculation formula: ; ; In the formula, and All are fitting constants; Daily gas production; To supply pressure to the formation; The slope of the pressure square curve; This is the overall compression coefficient.

[0113] S66. Based on the well types classified in S61, clarify the applicable scenarios for each method: for non-steady-state production wells, use the production instability analysis method and use the results of the elastic two-phase method as deviation correction; for quasi-steady-state production wells, use the Arps production decline method or the material balance method as the main method and use the results of the elastic two-phase method as deviation correction.

[0114] During the calculation process, the dynamic parameters of the S5 venting radius are combined to verify whether the reserve value is within the reasonable utilization range, abnormal calculation results are eliminated, and the dynamic reserve parameters of the gas well are output.

[0115] Step S7 specifically includes the following steps: S71. Preliminary estimation of gas well unobstructed flow rate using the one-point method: ; In the formula, Estimating the unobstructed flow rate of a gas well using the one-point method; To measure the stable gas production; This refers to the static pressure of the formation.

[0116] S72. Based on the gas well open flow range estimated in S71, and with the bottom hole flowing pressure approaching 0, the final gas well open flow rate is obtained by fitting the tight gas binomial productivity equation. The binomial energy production equation for tight gas is expressed as follows: ; In the formula, To simulate formation pressure; Simulated pressure at the bottom of the well; The laminar flow coefficient; The turbulence coefficient; This refers to the gas production of a gas well.

[0117] S73. Set production constraints for unstable flow phases: venting radius damage rate ; Among them, the damage rate of the vent radius. The expression is as follows: ; In the formula, This refers to the venting radius under ideal operating conditions. This refers to the venting radius under actual production conditions.

[0118] Meanwhile, a production allocation constraint is set for the quasi-steady-state stage: the optimization objective is to maximize the production of a single well.

[0119] S74. Construct a nonlinear seepage control equation for tight gas that considers the starting pressure gradient of the aqueous phase, as the basic equation for production simulation: ; In the formula, This is a correction factor; The starting pressure gradient for the aqueous phase.

[0120] S75. Based on the constraints of the unsteady flow stage and the seepage equation in S74, construct a reasonable production allocation technical diagram for the unsteady flow stage and determine the production allocation limit.

[0121] S751. Retrieve different crack sizes and crack parameter combinations from S4, as well as the dynamic venting radius parameters from the unsteady flow stage in S5, and divide them into multiple sets of simulation conditions.

[0122] S752, Substituting the S74 nonlinear seepage equation, conducted multiple sets of numerical simulations, traversing different production schemes, and selecting the one that meets the requirements. Effective production output.

[0123] S753. Using crack parameters and venting radius as the horizontal and vertical axes, and effective production capacity as the vertical axis, draw a technical chart of reasonable production capacity allocation for the unstable flow stage; and define the upper limit value and reasonable production capacity allocation range for this stage to determine the production capacity limit value for the unstable flow stage.

[0124] S76. Based on the constraints of the quasi-steady-state stage and the seepage equation in S74, construct a reasonable production allocation technical diagram for the quasi-steady-state stage and determine the production allocation limit.

[0125] S761. Retrieve the quantitative parameters of the crack in S4 and the constant venting radius parameters in the quasi-steady-state stage in S5, and divide the quasi-steady-state exclusive simulation condition group.

[0126] S762. Conduct nonlinear seepage numerical simulations with the goal of maximizing production, and select the optimal production ratio within the reservoir's tolerance range.

[0127] S763. Based on the crack size, vent radius, and unobstructed flow rate, draw a reasonable production allocation technical chart for the quasi-steady-state stage; and divide the quasi-steady-state optimal production allocation range and warning production allocation range.

[0128] S77. Classify and organize the production allocation technology charts for two types: unstable flow and quasi-steady state. Mark the applicable well type, fracture parameter range, gas leakage radius range and constraint conditions of the charts to obtain the staged production allocation benchmark charts and production allocation limits.

[0129] Step S8 specifically includes the following steps: S81. Establish the unstable flow rate calculation model and the quasi-steady-state flow rate calculation model respectively: ; ; in, ; In the formula, Unstable flow phase Instantaneous gas production at any given moment; Production limits for the unstable flow phase determined by S7; This represents the maximum venting radius during the unsteady flow phase. This is a stress-sensitive correction function. The dimensionless permeability modulus; For the corrected quasi-steady-state stage Instantaneous gas production at any given moment; The quasi-steady-state stage before correction Instantaneous gas production at any given moment; for Constant formation pressure; The initial gas production rate is the quasi-steady-state rate (taken from the optimal production rate of S7).

[0130] S82, Calculate the gas well production decline rate The recovery rates were calculated for the unsteady flow stage, the quasi-steady state stage, the depletion and abandonment stage, and the overall recovery rate throughout the gas well's lifecycle. : ; ; In the formula, for Instantaneous daily output.

[0131] S83, Output the full life cycle production forecast results.

[0132] The multi-objective production optimization model expression described in step S9 is as follows: ; in, ; ; ; ; In the formula, Optimize the overall objective function for multiple objectives; To optimize decision variables, factors include phased output allocation, production system, and timing of intervention measures; The objective function for reservoir protection; The objective function is the production capacity. To develop an economic objective function; The objective function is resource sustainability; Capacity compliance rate; This represents the actual stable gas production corresponding to the production allocation plan; The final unobstructed flow rate of the gas well calculated for S7; For the entire life cycle of gas well development; For the first Annual cash inflow; For the first Annual cash outflow; The benchmark discount rate is used.

[0133] Add the following constraints: ; ; ; ; In the formula, for Production output at any given time; and These are the lower limit and upper limit of production allocation, respectively.

[0134] Test case This test case uses the Yan'an tight sandstone gas field as an example for illustration.

[0135] Stratigraphic characteristics: The Yan'an gas field is stratigraphically comprised of Quaternary, Cretaceous, Jurassic, Triassic, Permian, Carboniferous, and Ordovician strata. Among these, the Lower Shihezi Formation and Shanxi Formation of the Permian, and the Benxi Formation of the Carboniferous are the main target formations of the gas field. The Benxi Formation is a barrier island-lagoon deposit, which can be divided into Ben 1 and Ben 2 sections; the Shanxi Formation is a delta front deposit, which can be divided into Shan 1 and Shan 2 sections; and the Lower Shihezi Formation is a delta front deposit.

[0136] Table 2. Simplified stratigraphic table of the Upper Paleozoic strata in the Yan'an Gas Field

[0137] Effective gas layer distribution characteristics: ① Planar distribution characteristics of effective gas layers: The Benxi Formation gas layers are all isolated and scattered in an approximately elliptical shape. The Benxi 2 sublayer gas layer is well developed in the central and southern parts, with a thickness generally between 3-6m, an average thickness of 4.2m, and locally exceeding 8m. It is thinner in the north, with a thickness of about 3m. The Benxi 1 sublayer gas layer is relatively well developed in the south, with a thickness mainly distributed between 3-5.5m, an average thickness of 3.9m. It is thinner in the north and central parts, with a thickness generally around 3m. The Shan 2 member gas layer extends in a north-south direction in the study area, with a thickness mainly distributed between 6-10m, an average thickness of 8.2m, and locally exceeding 12m. It is mainly distributed in the central and upper-middle parts, and overall has a strip-like distribution in the north-south direction. The Shan 1 member gas layer is generally less developed than Shan 2, with a thickness mainly distributed between 3-6m, an average thickness of about 4.8m, and locally exceeding 8m. It is scattered in the central area of ​​the gas field in the north-south direction, and the distribution area is small. The lower gas layer of Box 8 is generally well-developed, appearing in the north, central, and south of the study area. Its thickness is mainly between 6-9m, with an average thickness of 7.7m, and locally exceeding 12m. It is mainly distributed in the central and lower-middle parts. The upper gas layer of Box 8 is less developed than the lower layer, with a thickness mainly between 4-8m, an average thickness of 5.7m, and locally exceeding 12m, and is scattered. ② Vertical distribution characteristics of effective gas layers: Vertically, the gas layers in this area are best developed in Shan 23 and the lower gas layer of Box 8, with a single layer thickness generally around 8m. Ben 2, Shan 13, Shan 12, Shan 11, Shan 21, and the upper layer of Box 8 are less developed than Shan 23 and the lower layer of Box 8, with a thickness generally around 5m. Ben 1 and Shan 22 are the least developed, with a thickness of around 3m, scattered, and the overall scale of the gas layers is relatively small.

[0138] Reservoir physical characteristics: (1) Rock type: Petrological analysis shows that the rock type of Benxi Formation and Shan 2 Member reservoir is mainly quartz sandstone and lithic quartz sandstone, while the He 8 Member and Shan 1 Member reservoir is mainly lithic quartz sandstone with a small amount of quartz sandstone. (2) Pore type: Through core thin section analysis, the pore type of sandstone in Benxi, Shanxi and He 8 Members of Yan'an Gas Field is mainly primary intergranular pores and dissolution intergranular pores, followed by intragranular dissolution pores, intercrystalline pores and microfractures. (3) Reservoir physical characteristics: The porosity of Yan'an Gas Field reservoir is between 4.0% and 12.0%, and the permeability is between 0.01mD and 3.0mD. The porosity is mainly between 4% and 9%, and the permeability is mainly between 0.1 and 0.5mD, which belongs to low-permeability tight reservoir.

[0139] Gas well production dynamics data: Since its development, the Yan'an Gas Field has experienced four large-scale production launches: April 2012, November 2014, October 2015, and November 2018. During this period, the average daily gas production was 1.5 million cubic meters per day from April 2012 to November 2014; 6.3 million cubic meters per day from November 2014 to November 2018; and 7 million cubic meters per day from November 2018 to the present. Furthermore, gas production was relatively low from its initial launch in 2012 until 2014, but increased rapidly from 2015 onwards, maintaining an annual production of over 2 billion cubic meters for the past four years and continuing to grow steadily, reaching 2.467 billion cubic meters in 2019. Gas well production profiles show that the Shan 2 gas layer is the main gas-producing layer, contributing 37.3% of the total gas production, the Shan 1 gas layer contributes 25.5%, the Benxi gas layer contributes 19.0%, and the He 8 gas layer contributes 18.4%.

[0140] At the individual well level, although the Yan'an Gas Field has continuously increased its production capacity, and overall production is in a stable upward phase, some wells in the Yanqi 2 and Yanqi 128 well areas, which were developed earlier, have already entered a production decline phase. The Yanqi 145 well area, although put into production recently, has also experienced production decline due to factors such as small reservoir sand bodies and poor reservoir properties, making it difficult for a few wells to maintain stable production. Based on the production decline rate defined by Arps, and using gas field well production data to calculate the annual production decline rate for individual wells, approximately 79.5% of the wells in the Yan'an Gas Field are in a state of no decline or early decline (annual decline rate of 10%). Among these, 65 wells, accounting for 11.2% of the total number of wells, are experiencing severe decline (annual decline rate > 30%).

[0141] Statistical analysis of formation pressure and well casing pressure in the Yan'an Gas Field reveals that the original average formation pressure was 21.73 MPa, while the current average formation pressure is 13.83 MPa, representing an overall decrease of 36.35%. The average formation pressure drop rate across the entire area is 0.0063 MPa / d. The overall casing pressure in the study area has decreased steadily. From 2012 to 2014, the average decrease rate was 1.25 MPa / year. From 2016 to 2019, the average casing pressure decrease rate was 0.92 MPa / year, and the current average casing pressure is 9.01 MPa.

[0142] Under the above conditions, the result obtained after processing using the method described in this invention is as follows: Figures 12-15 As shown.

[0143] Table 3. Characteristics of flow rate variation in different types of wells

[0144] It can be seen that as development progresses, the unobstructed flow rate of Class III vertical wells shows a decreasing trend, but the rate of decrease is constantly slowing down. After three years of production, the unobstructed flow rate of Class III vertical wells decreased by 10,900 cubic meters per day compared to when stress sensitivity was not considered. The unobstructed flow rate exhibits an exponential relationship with formation pressure, and the difference in unobstructed flow rate has an inflection point over time. The annual deceleration rate of unobstructed flow rate for Class I / II / III vertical wells (within 3 years) is approximately 20% and 35%, respectively, and the deceleration rate is continuously decreasing as development progresses. The impact of stress sensitivity on Class I / II / III wells increases sequentially, with the annual decrease rates of unobstructed flow rate caused by stress sensitivity for Class I / II / III vertical wells being 5.55%, 6.12%, and 8.9%, respectively.

[0145] Based on this, the production operation patterns of different types of wells in the target area were obtained.

[0146] Class I well lifecycle stages: Following the classification approach for typical wells, the lifecycle of a Class I well can also be divided into 5 stages. The initial production period lasts 0.25 years, with predicted cumulative production accounting for 4% of the total predicted cumulative production. At the end of the period, the casing pressure is approximately 17 MPa, and the production is 24,000 cubic meters per day. The continuous production period lasts 6.75 years, with predicted cumulative production accounting for 66% of the total predicted cumulative production. At the end of the period, the casing pressure is 5.2 MPa, and the production is 7,000 cubic meters per day. The continuous production period with measures lasts 4 years, with predicted cumulative production accounting for 15% of the total predicted cumulative production. At the end of the period, the casing pressure is 3.4 MPa, and the production is 4,000 cubic meters per day. The intermittent production period lasts 12 years, with predicted cumulative production accounting for 15% of the total predicted cumulative production. At the end of the period, the casing pressure is 1.5 MPa, and the production is 1,000 cubic meters per day. At the time of abandonment, the cumulative production accounts for 91% of the active reserves.

[0147] Class II well lifecycle stages: Following the classification approach for typical wells, the lifecycle of a Class II well can also be divided into 5 stages. The initial production period lasts 0.25 years, with predicted cumulative production accounting for 5% of the total predicted cumulative production. At the end of the period, the casing pressure is approximately 16 MPa, and the production is 11,000 cubic meters per day. The continuous production period lasts 3.25 years, with predicted cumulative production accounting for 45% of the total predicted cumulative production. At the end of the period, the casing pressure is 6.6 MPa, and the production is 7,000 cubic meters per day. The continuous production period with measures lasts 2.5 years, with predicted cumulative production accounting for 20% of the total predicted cumulative production. At the end of the period, the casing pressure is 5.0 MPa, and the production is 4,000 cubic meters per day. The intermittent production period lasts 9 years, with predicted cumulative production accounting for 30% of the total predicted cumulative production. At the end of the period, the casing pressure is 3 MPa, and the production is 1,000 cubic meters per day. At the time of abandonment, the cumulative production accounts for 76% of the active reserves.

[0148] Class III well lifecycle stages: Following the classification approach for typical wells, the lifecycle of a Class III well can also be divided into 5 stages. The initial production period lasts 0.25 years, with predicted cumulative production accounting for 7% of the total predicted cumulative production. At the end of the period, the casing pressure is approximately 13.9 MPa, and the production is 8,000 cubic meters per day. The continuous production period lasts 1.25 years, with predicted cumulative production accounting for 33% of the total predicted cumulative production. At the end of the period, the casing pressure is 10 MPa, and the production is 5,000 cubic meters per day. The continuous production period lasts 2 years, with predicted cumulative production accounting for 20% of the total predicted cumulative production. At the end of the period, the casing pressure is 8.5 MPa, and the production is 3,000 cubic meters per day. The intermittent production period lasts 7.5 years, with predicted cumulative production accounting for 40% of the total predicted cumulative production. At the end of the period, the casing pressure is 6.2 MPa, and the production is 1,000 cubic meters per day. Upon abandonment, the cumulative production accounts for 64% of the active reserves.

[0149] The following conclusions were drawn: (1) Gas wells are mainly developed for depletion. During the development process, high-permeability layers will be sufficiently utilized, while low-permeability layers will be utilized less or even not utilized at all. Low-permeability layers are the main areas for the utilization of future residual gas. It is recommended to increase gas production profile testing to determine the utilization status of each layer in the vertical direction. (2) Planar residual gas is mainly distributed between wells or in the sweep blind zone caused by anisotropy of physical properties. In this study, it was found that there is a certain mismatch between reservoir heterogeneity and well network setting. It is recommended to carry out reservoir numerical simulation research to determine the distribution law of planar residual gas. (3) Gas reservoirs are mainly developed for depletion. In the middle and late stages of depletion development, gas will be trapped due to radial throttling losses or water locks.

[0150] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the technical solutions of the present invention, and these modifications or equivalent substitutions cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for integrated production allocation and dynamic evaluation throughout the entire life cycle of tight gas wells, characterized in that: Includes the following steps: S1. Collect geological structural parameters, sedimentary characteristic parameters, reservoir physical property parameters, natural gas fluid parameters, gas well static parameters, gas well production dynamic data, well test data and multi-well interference data of the target area, carry out seepage mechanism analysis of tight sandstone gas reservoir, and construct basic parameter dataset and seepage constraint conditions of the target area; S2. Based on the basic parameter dataset and seepage constraint conditions constructed in S1, seepage mathematical models for fractured vertical wells and fractured horizontal wells are constructed respectively. The bottom hole pressure and pressure derivative double logarithmic curves are obtained by solving them. Combined with reservoir physical parameters, fracture parameters and boundary control flow characteristics, a standard for dividing the full life cycle stages of gas wells is established. S3, based on the well test data of S1, multi-well interference data and the gas well life cycle stage discrimination criteria output by S2, uses the multi-well interference theory and the bottom hole pressure superposition principle to analyze the dynamic response characteristics corresponding to different fracture morphologies, fracture symmetry and fracture orientation. The grey relational analysis method is used to complete the qualitative discrimination of the directionality and symmetry of the fracturing fracture, and output the qualitative results of fracture morphology and orientation. S4. Based on the gas well production dynamic data and well test data of S1, as well as the qualitative results of fracture morphology and orientation output by S3, numerical well testing method and non-stop variable flow well testing technology are used to carry out quantitative inversion of fracturing fracture parameters in combination with production dynamic fitting method. The fracture half length and fracture conductivity are solved, and the accuracy of the inversion parameters is verified. The full quantitative parameters of fracturing fracture are output. S5. Based on the reservoir physical parameters of S1, the gas well life cycle stage boundary parameters output by S2, and the full quantitative parameters of fracturing fractures output by S4, define dimensionless parameters, establish a method for calculating the gas leakage radius of different production stages of the gas well, and output the dynamic parameters of the gas leakage radius of each production stage. S6. Based on the gas well production dynamic data of S1, the gas well life cycle stage boundary parameters output by S2, and the gas leakage radius dynamic parameters output by S5, determine the dynamic reserve calculation method for quasi-steady-state production wells and non-quasi-steady-state production wells, and output the dynamic reserve parameters of a single gas well. Based on the reservoir and fluid parameters of S1, the quantitative parameters of the fracturing fracture output by S4, and the dynamic parameters of the venting radius output by S5, the gas well free flow rate is calculated using the simulated modified isochronous well test method. The reasonable production allocation technology charts for the unstable flow stage and the quasi-steady state stage, as well as the corresponding production limits, are constructed respectively. The phased production allocation benchmark charts and production limits are output. S8, based on the gas well life cycle stage boundary parameters output by S2, the full quantitative parameters of fracturing fractures output by S4, the dynamic parameters of gas leakage radius output by S5, the dynamic reserves parameters of a single well output by S6, and the staged production allocation benchmark chart output by S7, respectively establish an unstable flow production calculation model and a quasi-steady-state production calculation model to predict the gas well production decline rate and recovery degree, and output the full life cycle production prediction results. S9. Based on the phased production allocation benchmark chart output by S7 and the full life cycle production prediction results output by S8, a multi-objective production allocation optimization model is established, and the optimal production allocation implementation plan for gas wells is output after solving the model. S10. Execute the optimal production allocation implementation plan output by S9, continuously collect on-site gas well operation data, and iteratively update the stage discrimination model of S2, the fracture inversion model from S3 to S4, the production allocation chart of S7, and the production operation evaluation model of S8.

2. The integrated production allocation and dynamic evaluation method for the entire life cycle of tight gas wells according to claim 1, characterized in that: Step S1 specifically includes the following steps: S11. Simultaneously acquire geological structural parameters, sedimentary characteristic parameters, reservoir physical property parameters, natural gas fluid parameters, gas well static parameters, gas well production dynamic data, well test data, and multi-well interference data of the target area to obtain the original multidimensional dataset. Among them, the geological structural parameters include basin structural units, formation dip angle, and structural morphology; the sedimentary characteristic parameters include target strata, sedimentary facies, gas layer spatial distribution, and gas layer thickness; the reservoir physical property parameters include rock type, pore type, porosity, and permeability; the natural gas fluid parameters include natural gas viscosity, compressibility factor, and comprehensive compressibility coefficient; the gas well static parameters include well type, wellbore radius, well-reservoir coefficient, skin coefficient, and designed fracture geometry parameters; the gas well production dynamic data includes daily gas production per well, cumulative gas production, formation pressure, wellhead casing pressure, pressure drop, and production decline rate; the well test data includes bottomhole pressure and pressure derivative time-series monitoring data; and the multi-well interference data includes synchronous change sequence data of production and pressure of adjacent wells. S12. Perform outlier removal, temporal alignment, and format unification on the original cube in sequence to obtain a standardized dataset; S13. Conduct separate analyses of the gas slippage effect mechanism, the aqueous phase initiation pressure gradient mechanism, the reservoir stress sensitivity effect mechanism, and the high-speed non-Darcy effect mechanism. Determine that the main control factors of seepage are the stress sensitivity effect and the aqueous phase initiation pressure gradient. It is determined that the slippage effect and the high-speed non-Darcy effect are negligible under field conditions. S14. Based on the main control factors of seepage determined in S13, define the seepage constraint conditions for the entire process of technical modeling, numerical simulation, and dynamic analysis. S15, based on the standardized dataset of S11 and the seepage constraints determined in S14, unifies data fields and association rules to construct a basic parameter dataset for the target area.

3. The integrated production allocation and dynamic evaluation method for the entire life cycle of tight gas wells according to claim 2, characterized in that: Step S2 specifically includes the following steps: S21. Based on the basic parameter dataset and seepage constraints constructed in S1, build physical models for fractured vertical wells and fractured horizontal wells: Based on the reservoir physical parameters, natural gas fluid parameters, and gas well static parameters in S1, a physical model of seepage in a fractured vertical well is constructed. The physical model of seepage in a fractured vertical well is divided into a modified zone and a non-modified zone. The modified zone is a dual-medium system of fracture and matrix, while the non-modified zone is a homogeneous single-medium system. The artificial hydraulic main fracture penetrates the reservoir. Based on the physical model framework of the seepage in a fractured vertical well and combined with the structural parameters of a horizontal well, a physical model of the seepage in a fractured horizontal well is constructed. S22. Based on the fracturing vertical well model and the fracturing horizontal well physical model built in step S21, respectively establish the fracturing vertical well seepage mathematical model and the fracturing horizontal well seepage mathematical model. S221. Define the following dimensionless quantity: Dimensionless wellbore pressure ; Dimensionless crack production ; Dimensionless Time ; Dimensionless well reservoir coefficient ; Dimensionless fracture conductivity ; Storage ratio ; Crossflow coefficient ; Flow ratio ; Transformation coefficient ratio ; In the formula, The permeability of cracks in the redevelopment area; The effective thickness of the reservoir; For gas well production; The dynamic viscosity of natural gas in the redevelopment area; This is the gas volume coefficient; This represents the original formation pressure; for Constant formation pressure; The length of the crack is half its length; For the production of crack micro-elements; For matrix porosity; The overall compressibility coefficient of the matrix; For crack porosity; The crack's overall compressibility coefficient; The wellbore storage coefficient; The overall porosity of the transformation area; The comprehensive compression coefficient of the redevelopment area; The permeability of the hydraulic fracture; The width of the crack; The current churn constant; For matrix permeability; This refers to the penetration rate in the non-renovation area. The dynamic viscosity of natural gas in the non-modified area; Porosity of the unmodified area; The comprehensive compression coefficient for the non-renovation area; S222. Based on the fracturing vertical well model and fracturing horizontal well physical model built in S21, dimensional seepage control equations are established for each zone: Dimensional seepage control equation for the modified area: ； Dimensional seepage control equations for the unmodified zone: ； Dimensional seepage equation for hydraulic fractures: ； In the formula, This refers to the instantaneous pressure of the formation. Radial distance; To modify the temporal stratigraphic pressure in the transformation area; For the non-reformed area, the temporal stratigraphic pressure; The pressure inside the crack; Standard pressure; Formation temperature; For the production of crack micro-elements; The equivalent permeability of the crack; The width of the crack; Standard temperature; It is the dimensional permeability modulus; S223. Based on the dimensionless parameters defined in step S221, the dimensional equation in step S222 is transformed into a dimensionless seepage control equation, and the corresponding general solution is derived. S2231. Establish the following dimensionless seepage control equations for the modified area: ； The general solution of the modified area is derived. : ； in, ； In the formula, For dimensionless pressure in the transformed region under the Laplace transform domain; For the Laplace transform operator; , All of these are undetermined coefficients for the general solution of the transformation area; It is a zero-order modified Bessel function of the second kind; It is a zero-order modified Bessel function of the first kind; For auxiliary functions; The radial distance is dimensionless. S2232. Establish the following original dimensionless seepage control equations for the unmodified zone: ； The original dimensionless seepage control equations for the unmodified zone are simplified by perturbation to obtain the simplified dimensionless seepage control equations for the unmodified zone: ； in, ； The general solution for the non-modified region is derived. : ； In the formula, There is no dimensional pressure in the non-renovation area; To assist in dimensionless well reservoir coefficient; The comprehensive seepage coefficient; The non-modified region has dimensionless pressure after the perturbation transformation; For perturbation pressure in Laplace space; , All are undetermined coefficients for the general solution in the non-renovation area; S2233. Establish the dimensionless seepage equation for hydraulic fractures: ； In the formula, The output of dimensionless crack micro-element; The pressure is a dimensionless crack. S224. Based on the global characteristics of the physical model, establish the boundary conditions corresponding to the mathematical model, including initial conditions, boundary conditions, and coupling conditions of regional interfaces. S2241. Establish global initial conditions: Dimensional initial conditions: ; Dimensionless initial conditions: ; In the formula, This represents the original formation pressure; The initial dimensionless pressure; S2242. Establish boundary conditions: Boundary conditions within the modification area: Boundary conditions outside the non-modified area: ; In the formula, The modified area has a dimensionless radial pressure gradient; For the dimensionless crack production of the Laplace domain; For the dimensionless perturbation pressure in the non-modified region at infinity under the Laplace domain; S2243. Establish coupling conditions at the interface between the modified zone and the non-modified zone: ； In the formula, For the dimensionless pressure under the Laplace domain; For dimensionless perturbation pressure in the non-modified region under the Laplace domain; The dimensionless outer radius of the transformation area; The modified area has a dimensionless radial pressure gradient; The non-modified region has a dimensionless radial pressure gradient. S23. Perform Laplace transformation and numerical solution on the dimensionless governing equations of step S223 and the boundary conditions of step S224 to obtain the numerical solutions of the bottom hole pressure and pressure derivative. S231. Discretize the hydraulic fracture in S224 into elements, establish the seepage relationship equation of the fracture micro-element, and solve the one-dimensional Darcy flow equation inside the fracture. S232. Perform Laplace transform on the dimensionless seepage equation in S22 to convert the time-domain equation into a complex frequency domain equation, and solve the complex frequency domain pressure solution in the modified zone, the unmodified zone, and the hydraulic fracture zone respectively. S233. Combining the formulas in steps S223-S224, we obtain the pressure at any location in the reservoir using the point sink in Laplace space: ； in, ； In the formula, The yield of dimensionless crack infinitesimal elements in the Laplace domain; These are the combination coefficients of the Bessel functions; Infiltrating the redevelopment area; It is a first-order modified Bessel function of the first kind; S234. The pressure at any location in the reservoir under the control of the main fracture is obtained by using the superposition principle. : ； S235, The pressure at the crack wall is derived. : ； S236. Obtain the expression for the pressure at each crack element: ； In the formula, The coupling matrix of the crack micro-element; - They are respectively the 1st- The dimensionless product of the Laplace domain of a crack infinitesimal element; - They are respectively the 1st- The Laplace domain dimensionless pressure of a crack element; The dimensionless bottom hole pressure in the Laplace domain; S237. Using the Stehfest numerical inversion algorithm, the complex frequency domain solution is restored to the real domain solution, and finally the numerical results of the bottom hole pressure and pressure derivative at different times are obtained. S24. Based on the numerical solutions of bottom hole pressure and pressure derivative obtained from S23, plot a double logarithmic curve of bottom hole pressure versus pressure derivative with dimensionless time as the horizontal axis and dimensionless pressure and dimensionless pressure derivative as the vertical axis. Then, based on the curve shape and slope characteristics, divide the seepage into seven subdivisions and define the identification criteria for each stage: Bilinear flow stage in cracks: The slope of the pressure derivative curve is 1 / 4; Linear flow stage perpendicular to the crack: the slope of the pressure derivative curve is 1 / 2; The pseudo-radial flow stage of the crack: the pressure derivative curve shows a horizontal segment for a set time period; During the stage of matrix flow into microcracks: the pressure derivative curve shows a concave shape; Radial flow stage of the modified system: horizontal section with a pressure derivative of 0.5; During the transition from the modified area to the non-modified area: the pressure curve and the pressure derivative curve rise synchronously; Radial flow stage of reservoir system: pressure derivative is numerically equal to Horizontal segment; S25. Based on the detailed seepage stages defined in S24, and combined with the reservoir physical parameters, fracture parameters, and boundary control flow response characteristics in S1, the production stages of the gas well's entire life cycle are divided as follows: Unstable flow stage: Before the boundary control flow appears, the pressure wave has not reached the outer boundary of the reservoir, and the gas leakage radius continues to expand dynamically; Quasi-steady-state stage: During the continuous range of boundary control flow, the venting radius remains fixed, and the formation experiences uniform pressure drop across the entire area; Exhaustion and abandonment stage: After the boundary control flow ends, the formation energy continues to be depleted, and the production and pressure continue to decline until the abandonment conditions are met. S26. Based on seepage theory and the stage division logic in S25, derive the formula for calculating the boundary control flow time: ； In the formula, For the occurrence time of boundary control flow; The length of the crack is half its length; The reservoir matrix permeability; S27. Retrieve the gas well production decline data collected in S1, and compare, verify and correct the initial stage division criteria in S25 and the boundary control flow time calculation formula in S26.

4. The integrated production allocation and dynamic evaluation method for the entire life cycle of tight gas wells according to claim 3, characterized in that: Step S4 Specifically, the following steps are included: S41. Using the non-stop well testing technology with variable flow rate, calculate the following in sequence: Dimensionless pressure for well test analysis ; Dimensionless time for well test analysis ; stratigraphic coefficient ; Gas well skin coefficient ; Pressure recovery time to extreme values ​​under variable production conditions ; In the formula, This represents the change in pressure. Production output during the unstable flow phase; This is the gas volume coefficient; The slope of the pressure-time fitting curve; This represents the production output during the quasi-steady-state phase. This refers to the continuous production time during the unstable flow phase. The overall porosity of the formation; The dynamic viscosity of natural gas; S42. Based on the basic formation parameters obtained in S41 and combined with the fracture qualitative results in S3, construct a radial composite formation numerical well test model. S421. The overall framework of the model is based on a fixed-well reservoir, a limited-flow fractured vertical well, a radial composite reservoir, and a circular closed boundary model. S422. Based on the qualitative results of crack morphology and orientation in S3, input the crack geometric conditions into the model. At the same time, input the S1 basic parameters and complete the model mesh generation, medium partitioning, and internal and external boundary condition settings. S43. Based on the numerical well test model built on S42, quantitative inversion of core parameters of fracturing fractures is carried out by combining production dynamic fitting method, solving fracture half-length and fracture conductivity, and obtaining wellbore and reservoir parameters. S431. Call the production dynamic analysis tool, import the full-time production and pressure data of S1, and perform historical curve fitting of pressure and production. S432. Iteratively adjust the crack-related parameters within the model until the fitted curve matches the measured curve. S433. Extract the parameter results after fitting convergence to obtain the two core fracture parameters: fracture half-length and fracture conductivity. At the same time, obtain the wellbore and reservoir parameters, including the wellbore reservoir coefficient, inner and outer zone permeability, inner zone radius and discharge radius. S44. Based on the inversion results of the well test without shutting down the well, the parameter accuracy was compared and verified using the shut-in pressure recovery test data, and the parameter compliance rate was calculated. S441. Retrieve the shut-in pressure recovery test data conducted simultaneously in S1, and use the shut-in well test method to solve for the dimensional fracture half-length of the same well group. Dimensional fracture conductivity Dimensional stratigraphic porosity Dimensional discharge radius : ； ； ； ； In the formula, The semi-logarithmic characteristic time of the shut-in pressure recovery curve; The reservoir pressure conductivity coefficient; This refers to the well shut-in pressure recovery time. S442. Compare the inversion parameters of the continuous flow test and numerical test with the solution parameters of the shut-in test one by one, and calculate the individual compliance rate of fracture half-length, fracture conductivity, porosity, and discharge radius, as well as the overall average compliance rate. S443. Determine the accuracy of the inversion. When the overall average compliance rate reaches the allowable range of the project, the inversion parameters are deemed valid. S45. Summarize all parameters obtained from the inversion in S43 and the accuracy verification results in S44, organize and classify them, and output the full quantitative parameters of the fracturing fractures. The full quantitative parameters of the fracturing fractures include fracture half-length, fracture conductivity and related wellbore and reservoir parameters.

5. The integrated production allocation and dynamic evaluation method for the entire life cycle of tight gas wells according to claim 4, characterized in that: Step S5 specifically includes the following steps: S51. Define the dimensionless discharge radius respectively. Dimensionless crack half length Dimensionless average pressure conductivity Dimensionless correction time Dimensionless inner radius Dimensionless fracture conductivity : ； ； ； ； ； ； In the formula, For production time The corresponding real-time discharge radius; The discharge radius is the radius of the first year of production. For production time The corresponding real-time crack half-length; The crack length is half that of the first year of production; The weighted average penetration rate of the inner and outer zones, and , This refers to the penetration rate in the non-renovation area. The radius of the transformation area; This refers to the real-time discharge radius; For production time The corresponding real-time correction coefficient, and , This is the correction period for the first year of production; For production time The corresponding real-time modification zone radius; The radius of the modified area during the first year of production; The real-time crack flow conduction capacity corresponding to production time t; To ensure the crack conduction capacity in the first year of production; S52. Extract full-time production data and complete the processing of dimensionless parameter time-series samples; S521. Combining the stage boundary time nodes output by S2, divide the time nodes for different production durations and extract the values ​​of the six types of dimensionless parameters defined by S52 under each node. S522. Group the sample data according to the categories of gas wells I, II, and III to form a classified time-series dataset; Among them, Class I gas wells meet the following quantitative indicators: Unobstructed flow rate greater than 5×10 4 m 3 / d; The final cumulative gas extraction volume is greater than 3500×10 4 m 3 ; The three-year average daily gas production is greater than 1.8 × 10 4 m 3 / d; The total cumulative gas layer thickness is greater than 10m; The maximum thickness of a single layer shall not be less than 3m; The period of stable production shall not be less than 3 years; Class II gas wells meet the following quantitative indicators: Unobstructed flow: ; Final cumulative gas production: ; Three-year average daily gas production: ; Total cumulative gas layer thickness: ; The maximum thickness of a single layer shall not be less than 3m; The period of stable production shall not be less than 3 years; Class III gas wells meet the following quantitative indicators: Unobstructed flow rate less than 3×10 4 m 3 / d; The final cumulative gas extraction volume is less than 1350×10 4 m 3 ; The three-year average daily gas production is less than 0.8 × 10 4 m 3 / d; The total cumulative gas layer thickness is less than 4m; The maximum thickness of a single layer shall not exceed 3m; Stable production duration is less than 3 years; S53. Analyze the variation law of six types of dimensionless parameters with production time, and determine that all six types of dimensionless parameters conform to the time series variation law of exponential function; S54. Based on the changing patterns obtained in S53, establish time series regression formulas for various dimensionless parameter-free exponential functions: ； In the formula, For any type of dimensionless parameter; , All are regression coefficients; By fitting the sample data using Class I, Class II, and Class III gas well classifications, six categories of dimensionless parameters were obtained. , The coefficients form a set of time-series regression equations for well types and parameters; S55. Based on the dimensional real-time venting radius calculation formulas for the unstable flow stage, quasi-steady-state stage, and decay and abandonment stage as defined in S2, the venting radii for the three production stages are obtained; the dimensional real-time venting radius calculation formulas are as follows: ； S56. Based on the type of gas well, retrieve the corresponding time series regression coefficients, substitute them one by one into the S55 formula, calculate the leakage radius at different time points, and check the calculation results in conjunction with the constraints of each stage, eliminate abnormal values, and determine the dynamic value of the leakage radius at each stage. S57. Summarize the full-time and phased vent radius calculation results, organize the parameter ledger, and output the dynamic parameters of the vent radius for each production stage.

6. The integrated production allocation and dynamic evaluation method for the entire life cycle of a tight gas well according to claim 5, characterized in that: Step S6 specifically includes the following steps: S61. Based on the S2 gas well life cycle stage discrimination standard, the target gas well is classified into operating conditions: wells in the unstable flow stage are classified as non-steady-state production wells, and wells in the quasi-steady-state stage are classified as quasi-steady-state production wells. S62. Establish the Arps declining output method calculation model: ； In the formula, This represents the cumulative gas production of the gas well. This represents the initial gas production of the gas well. A decreasing exponent; This is the initial decrease rate; S63. Establish a production instability analysis model and calculate the pseudo-pressure of natural gas. Material balance pseudo-time and dynamic reserves of a single well : ； ； ； In the formula, Formation pressure; Bottom hole flowing pressure; The compressibility factor of natural gas; The viscosity of natural gas under the original formation conditions; The overall compressibility coefficient of the original gas; This is the product of the time-averaged viscosity and the compressibility factor. This is a combined term of viscosity, compressibility coefficient, and compressibility factor beneath the original strata. To fit the slope of the straight line; S64. Establish a material balance calculation model: ； In the formula, The original strata compression factor; S65. Establish an elastic two-phase method calculation model and derive the pressure relationship formula and dynamic storage calculation formula: ； ； In the formula, and All are fitting constants; Daily gas production; To supply pressure to the formation; The slope of the pressure square curve; The overall compression coefficient; S66. Based on the well types classified in S61, clarify the applicable scenarios for each method: for non-steady-state production wells, use the production instability analysis method and use the results of the elastic two-phase method as a deviation correction; for quasi-steady-state production wells, use the Arps production decline method or the material balance method as the main method and use the results of the elastic two-phase method as a deviation correction. During the calculation process, the dynamic parameters of the S5 venting radius are combined to verify whether the reserve value is within the reasonable utilization range, abnormal calculation results are eliminated, and the dynamic reserve parameters of the gas well are output.

7. The integrated production allocation and dynamic evaluation method for the entire life cycle of tight gas wells according to claim 6, characterized in that: Step S7 specifically includes the following steps: S71. Preliminary estimation of gas well unobstructed flow rate using the one-point method: ； In the formula, Estimating the unobstructed flow rate of a gas well using the one-point method; To measure the stable gas production; For formation static pressure; S72. Based on the gas well open flow range estimated in S71, and with the bottom hole flowing pressure approaching 0, the final gas well open flow rate is obtained by fitting the tight gas binomial productivity equation. The binomial energy production equation for tight gas is expressed as follows: ； In the formula, To simulate formation pressure; Simulated pressure at the bottom of the well; The laminar flow coefficient; The turbulence coefficient; This refers to the gas production of the gas well. S73. Set production constraints for unstable flow phases: venting radius damage rate ; Among them, the damage rate of the vent radius. The expression is as follows: ； In the formula, This refers to the venting radius under ideal operating conditions. This refers to the venting radius under actual production conditions. At the same time, a production allocation constraint is set for the quasi-steady-state stage: the optimization objective is to maximize the production of a single well; S74. Construct a nonlinear seepage control equation for tight gas that considers the starting pressure gradient of the aqueous phase, as the basic equation for production simulation: ； In the formula, This is a correction factor; The starting pressure gradient for the aqueous phase; S75. Based on the constraints of the unsteady flow stage and the seepage equation in S74, construct a reasonable production allocation technical chart for the unsteady flow stage and determine the production allocation limit. S751. Retrieve different crack sizes and crack parameter combinations from S4, as well as the dynamic venting radius parameters from the unsteady flow stage in S5, and divide them into multiple sets of simulation conditions. S752, Substituting the S74 nonlinear seepage equation, conducted multiple sets of numerical simulations, traversing different production schemes, and selecting the one that meets the requirements. Effective production capacity; S753. Using crack parameters and venting radius as the horizontal and vertical axes, and effective production rate as the vertical axis, draw a technical chart of reasonable production rate allocation for the unstable flow stage; and define the upper limit value and reasonable production range for this stage, and determine the production limit value for the unstable flow stage. S76. Based on the constraints of the quasi-steady-state stage and the seepage equation in S74, construct a reasonable production allocation technical chart for the quasi-steady-state stage and determine the production allocation limit. S761. Retrieve the quantitative parameters of the crack in S4 and the constant venting radius parameters of the pseudo-steady-state stage in S5, and divide the pseudo-steady-state exclusive simulation working condition group. S762. Conduct nonlinear seepage numerical simulation with the goal of maximizing production, and select the optimal production ratio within the reservoir's tolerance range. S763. Based on the crack size, vent radius, and unobstructed flow rate, draw a reasonable production allocation technical chart for the quasi-steady-state stage; and divide the quasi-steady-state optimal production allocation range and warning production allocation range. S77. Classify and organize the production allocation technology charts for two types: unstable flow and quasi-steady state. Mark the applicable well type, fracture parameter range, gas leakage radius range and constraint conditions of the charts to obtain the staged production allocation benchmark charts and production allocation limits.

8. The integrated production allocation and dynamic evaluation method for the entire life cycle of tight gas wells according to claim 7, characterized in that: Step S8 specifically includes the following steps: S81. Establish the unstable flow rate calculation model and the quasi-steady-state flow rate calculation model respectively: ； ； in, ； In the formula, Unstable flow phase Instantaneous gas production at any given moment; Production limits for the unstable flow phase determined by S7; This represents the maximum venting radius during the unsteady flow phase. This is a stress-sensitive correction function. The dimensionless permeability modulus; For the corrected quasi-steady-state stage Instantaneous gas production at any given moment; The quasi-steady-state stage before correction Instantaneous gas production at any given moment; for Constant formation pressure; This represents the initial gas production rate at a near-steady state. S82, Calculate the gas well production decline rate The recovery rates were calculated for the unsteady flow stage, the quasi-steady state stage, the depletion and abandonment stage, and the overall recovery rate throughout the gas well's lifecycle. : ； ； In the formula, for Instantaneous daily output; S83, Output the full life cycle production forecast results.

9. The integrated production allocation and dynamic evaluation method for the entire life cycle of a tight gas well according to claim 8, characterized in that: The expression for the multi-objective production allocation optimization model described in step S9 is as follows: ； in, ； ； ； ； In the formula, Optimize the overall objective function for multiple objectives; To optimize decision variables; The objective function for reservoir protection; The objective function is the production capacity. To develop an economic objective function; The objective function is resource sustainability; Capacity compliance rate; This represents the actual stable gas production corresponding to the production allocation plan; The final unobstructed flow rate of the gas well calculated for S7; For the entire life cycle of gas well development; For the first Annual cash inflow; For the first Annual cash outflow; The benchmark discount rate; Add the following constraints: ； ； ； ； In the formula, for Production output at any given time; and These are the lower limit and upper limit of production allocation, respectively.

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