Deep condensate gas well blowout productivity and drainage and mining process integrated design method

Abstract

The invention provides a deep condensate gas well blowout productivity and drainage and production process integrated design method. The deep condensate gas well blowout productivity and drainage and production process integrated design method comprises the steps that 1, a deep condensate gas phase state experiment and phase diagram measurement are conducted; 2, establishing and fitting a deep condensate gas phase state model; 3, establishing a deep condensate gas reservoir numerical simulation characteristic model; 4, carrying out deep condensate gas well production dynamic data preprocessing and numerical simulation model correction; 5, establishing a dynamic IPR curve library of the deep condensate gas well; and step 6, carrying out deep condensate gas well related discharge and recovery process design. According to the integrated design method for the blowout productivity and the drainage and mining process of the deep condensate gas well, dynamic IPR curve prediction, productivity determination and drainage and mining process optimization are integrally designed through phase state change characteristics and development characteristics of the deep condensate gas well, and therefore the development benefits of an oil field are improved.

Description

Technical Field

[0001] The invention relates to the technical field of oilfield development, and in particular to an integrated design method for the self-flowing production capacity and drainage and production process of a deep condensate gas well. Background Art

[0002] Deep condensate gas reservoir is a special gas reservoir with high economic value, which has the dual characteristics of oil reservoir and gas reservoir. The complex phase changes of condensate oil and gas reservoirs accompany the whole process of field development, which brings great difficulties and challenges to efficient development. Especially in the later stage of development, due to the continuous decrease of reservoir pressure, the damage of retrograde condensation will become more and more serious. Therefore, the research on deep condensate gas drainage technology has always been the most basic and most critical part of related research work. For deep condensate gas fields with different fracturing development conditions, the production capacity and tubing optimization research are carried out, and then applied to field development, and the occurrence of retrograde condensation damage on site is studied and improved. This is of great significance to formulate reasonable development methods, continuously improve the development level of deep condensate gas fields, and increase development benefits.

[0003] The productivity of deep condensate gas wells is a parameter that reflects the current production capacity of gas wells. In order to scientifically develop gas fields, it is necessary to predict gas well productivity, analyze gas well dynamics, and understand the characteristics of gas layers and wellbores. Even in new gas fields that have not been developed and gas fields with a low degree of development, gas well productivity analysis is necessary. In the early stages of development and when formal productivity tests cannot be implemented, appropriate productivity equations can provide experience and methods for evaluating gas well productivity to meet the needs of development plan preparation and production management. At present, most condensate gas reservoirs in my country belong to deep low-permeability condensate gas reservoirs. The productivity of gas wells decreases rapidly, the stable production time is short, and the development effect is poor. Slowing down the impact of formation retrograde condensation on productivity is the key to improving the development effect of such gas reservoirs. Establishing a reasonable productivity evaluation method for different production stages of condensate gas well fracturing development and optimizing its design is an effective means of productivity analysis and one of the key technologies for condensate gas production productivity evaluation and design.

[0004] In the Chinese patent application with application number: CN202011507563.1, a method and device for distinguishing multi-phase and multi-flow states in deep condensate gas reservoirs are involved. The method includes: obtaining the required number of seepage images during the condensate gas seepage experiment; processing the obtained seepage images to obtain the numerical ranges of various shape parameters corresponding to each condensate oil flow state; establishing a corresponding relationship between each condensate oil flow state and the numerical range of the dimensionless number; obtaining the value of the dimensionless number corresponding to the condensate oil flow state according to the newly obtained seepage image; determining the condensate oil flow state in the newly obtained seepage image according to the corresponding relationship between the numerical range of the dimensionless number and each condensate oil flow state. The invention introduces the numerical range of the dimensionless number to form a corresponding relationship with each condensate oil flow state, and distinguishes different condensate oil forms through the numerical value of the dimensionless number obtained by subsequent calculation; the calculation efficiency is high, and accurate discrimination of multi-phase and multi-flow states of condensate gas reservoirs is achieved.

[0005] In the Chinese patent application with application number: CN202110824787.3, a method for exploiting deep condensate gas reservoirs is involved, which includes: constructing a geological model of the oil field and the phase characteristics of the formation fluid; determining the position of the horizontal section of the horizontal well in the oil field according to the geological model and the phase characteristics; determining the length of the horizontal section according to the determined position of the horizontal section; determining the exploitation rate of the bottom oil of the oil field according to the position of the horizontal section and the length of the horizontal section; exploiting the bottom oil based on the position, length and exploitation rate of the horizontal section. The exploitation method of this invention can effectively avoid the rapid coning of the overlying gas cap and the underlying bottom water, and realize the balanced movement of the oil-gas-water interface.

[0006] In the Chinese patent application with application number: CN202111511442.9, a method for developing condensate gas reservoirs is involved. It includes adopting appropriate development methods for different production stages of condensate gas reservoirs, carrying out exhaustion development in the early stage of condensate gas reservoir development until the condensate gas reservoir reaches the set exhaustion development lower limit; switching to air injection development, selecting at least one production well from the condensate gas reservoir according to the set rules, changing the selected production well to an air injection well, and injecting catalysts and combustion aids into the air injection well; determining the air injection rate based on the effective oil layer parameters of the condensate gas reservoir, and injecting air into the air injection well according to the determined air injection rate. It can effectively develop condensate gas reservoirs during the full cycle development process, improving development efficiency and recovery rate.

[0007] At present, the relevant research published in the public is mainly focused on conventional condensate gas reservoirs, and there are few relevant design methods for deep condensate gas wells. At the same time, the relevant research has not considered the dynamic IPR curve changes to combine the production capacity and drainage technology for integrated research. The present invention proposes a deep condensate gas well production capacity and drainage technology design method based on the dynamic IPR curve through the phase change characteristics and development characteristics of deep condensate gas reservoirs. Summary of the invention

[0008] The purpose of the present invention is to provide a method for integrating the prediction of dynamic IPR curve with the determination of production capacity and optimization of production process, thereby improving the development efficiency of oil fields and integrating the design of deep condensate gas well self-flowing production capacity and production process.

[0009] The purpose of the present invention can be achieved by the following technical measures: a method for designing the self-flowing capacity and drainage and production technology of a deep condensate gas well, which includes:

[0010] Step 1, conducting deep condensate gas phase state experiment and phase diagram determination;

[0011] Step 2, establishing and fitting the deep condensate gas phase model;

[0012] Step 3, establishing a numerical simulation characteristic model for deep condensate gas reservoirs;

[0013] Step 4, preprocessing the production dynamic data of deep condensate gas wells and calibrating the numerical simulation model;

[0014] Step 5, establishing a dynamic IPR curve library for deep condensate gas wells;

[0015] Step 6, design relevant drainage and production processes for deep condensate gas wells.

[0016] The purpose of the present invention can also be achieved by the following technical measures:

[0017] In step 1, based on the deep condensate gas field samples, the pressure-volume-temperature PVT experimental test is carried out on the deep condensate gas related phase state, and its original phase state and condensate phase state phase diagram are tested at the same time.

[0018] In step 2, based on the tested deep condensate gas phase experimental data, considering the influence of the deep condensate gas condensation process on the phase change, a phase model that conforms to the deep condensate gas is constructed and relevant fitting is performed.

[0019] In step 3, the characteristic parameters of the deep condensate gas reservoir are statistically analyzed, and a gas reservoir model that can truly reflect the characteristics of the deep condensate gas reservoir is established using the reservoir numerical simulation method. The theoretical production curves of gas production, oil production, and water content are obtained by calculating through input parameters.

[0020] In step 3, the deep condensate gas reservoir numerical simulation model library includes three modules: model construction and attribute input module, model generation module, and model operation module.

[0021] In step 3, the model construction and attribute input module directly inputs the well trajectory, layering and logging curve data of the target well based on the understanding of the geological attribute characteristics of different deep condensate gas reservoirs, and uses the interpolation method to predict the characteristic information of parameters such as inter-well porosity, permeability and gas saturation to establish a geological model that meets the target block.

[0022] In step 3, the model generation module establishes and generates a deep condensate gas reservoir numerical simulation model that truly reflects specific information based on the deep condensate gas phase model.

[0023] In step 3, the model operation module operates the established numerical simulation model to predict the dynamic IPR curve during the development of deep condensate gas.

[0024] In step 4, the deep condensate gas production data has the characteristics of strong continuity and large data fluctuations. It is necessary to first preprocess the curve outliers to improve the data quality, mainly including the supplement of missing data, outlier correction and curve smoothing, so as to form production dynamic data that can be applied to historical fitting; based on the preprocessed production data, the numerical simulation model is corrected to make it more consistent with the actual deep condensate gas reservoir related characteristics.

[0025] In step 5, based on the corrected numerical simulation model, the dynamic IPR curve of the production well at any time and the reasonable production capacity of the well under the current production conditions are predicted, and the corresponding phase parameters and condensate oil / gas saturation distribution are output at the same time to provide a data basis for the design of the production process.

[0026] In step 6, first, the multiphase flow pressure gradient and production nozzle flow calculation method are optimized according to the actual production data and well test data; secondly, a sensitivity analysis is performed on the wellbore pressure drop, erosion resistance and liquid carrying capacity under different tubing and gas nozzle sizes to determine the influence of tubing size on the tubing pressure drop, erosion resistance and liquid carrying capacity and the production requirements of gas nozzles of different sizes; finally, considering the wellbore pressure drop, erosion resistance, liquid carrying capacity and economy comprehensively, the self-flowing production string structure in the design stage is optimized, and the sizes of the tubing and gas nozzles used are determined to meet the production requirements.

[0027] The present invention belongs to the development of deep condensate gas reservoirs in the field of oil and gas field development engineering, and is specifically a method for designing the production capacity and drainage process of deep condensate gas wells based on dynamic IPR curves. Through the phase change characteristics and development characteristics of deep condensate gas, the dynamic IPR curve prediction, production capacity determination and drainage process optimization are integrated into a design, thereby improving the development efficiency of the oil field.

[0028] In view of the problems of unreasonable production allocation and unclear drainage and production process in the current deep condensate gas self-flowing production and development process, the present invention innovatively proposes a deep condensate gas well production capacity and drainage and production process design method based on dynamic IPR curve. The method is easy to understand and simple and quick to design. The corresponding dynamic IPR curve library can be established according to the reservoir conditions of the target block. Based on the curve library, the reasonable production capacity and corresponding drainage and production process of the production well at this stage can be quickly designed, which has certain guiding significance for the deep condensate gas self-flowing exploitation. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 It is a schematic diagram of constant mass expansion experimental data and fitting results in a specific embodiment of the present invention;

[0030] Figure 2 It is a schematic diagram of isovolumetric exhaustion experimental data and fitting results in a specific embodiment of the present invention;

[0031] Figure 3 It is a schematic diagram of compression factor experimental data and fitting results in a specific embodiment of the present invention;

[0032] Figure 4 It is a schematic diagram of the experimental data and fitting results of the PVT phase diagram in a specific embodiment of the present invention;

[0033] Figure 5 It is a schematic diagram of a gas saturation model of a deep condensate gas reservoir in Fengshen 1 Well in a specific embodiment of the present invention;

[0034] Figure 6 It is a schematic diagram of the actual numerical simulation model of the Houfengshen 1 well after fitting in a specific embodiment of the present invention;

[0035] Figure 7 A comparison diagram of a theoretical production curve and an actual production curve in a specific embodiment of the present invention;

[0036] Figure 8 A comparison diagram of the model pressure and the actual pressure measuring point in a specific embodiment of the present invention;

[0037] Fig. 9 This is the IPR curve diagram of Fengshen 1 Well on January 1, 2022 in Example 1 of the present invention;

[0038] Fig.10 This is the IPR curve diagram of Fengshen 1 Well on January 1, 2024 in Example 3 of the present invention;

[0039] Fig.11 The present invention is a flow chart of a specific embodiment of the method for integrated design of deep condensate gas well self-flowing capacity and drainage and production technology. DETAILED DESCRIPTION

[0040] It should be noted that the following detailed descriptions are exemplary and are intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present invention belongs.

[0041] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit exemplary embodiments according to the present invention. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprising" and / or "including" are used in this specification, it indicates the presence of features, steps, operations and / or combinations thereof.

[0042] like Fig.11 As shown, Fig.11 The flowchart of the integrated design method of the deep condensate gas well self-flowing capacity and drainage and production process of the present invention. The integrated design method of the deep condensate gas well self-flowing capacity and drainage and production process includes:

[0043] Step 101, deep condensate gas phase state experiment and phase diagram determination: based on the deep condensate gas field sample, the deep condensate gas related phase state is subjected to PVT experimental test, and its original phase state and condensate phase state phase diagram are tested at the same time.

[0044] Step 102, deep condensate gas phase model establishment and fitting: based on the deep condensate gas phase experimental data tested above, considering the influence of the deep condensate gas condensation process on the phase change, a phase model that conforms to the deep condensate gas is constructed and relevant fitting is performed.

[0045] Step 103, establish a deep condensate gas reservoir numerical simulation characteristic model: statistically analyze the characteristic parameters of the deep condensate gas reservoir, and use the reservoir numerical simulation method to establish a gas reservoir model that can truly reflect the characteristics of the deep condensate gas reservoir. Calculate by inputting parameters to obtain theoretical production curves such as gas production, oil production, and water content. The deep condensate gas reservoir numerical simulation model library includes three modules: model construction and attribute input, model generation, and model operation. Module 1, based on the understanding of the geological attribute characteristics of different deep condensate gas reservoirs, directly input the well trajectory, layering and logging curve data of the target well, use the interpolation method to predict the characteristic information of parameters such as interwell porosity, permeability and gas saturation, and establish a geological model that meets the target block; Module 2, based on the above-mentioned phase model, establish and generate a deep condensate gas reservoir numerical simulation model that truly reflects specific information; Module 3, run the established numerical simulation model to predict the dynamic IPR curve during the development of deep condensate gas.

[0046] Step 104, preprocessing of production dynamic data of deep condensate gas wells and correction of numerical simulation model: The production data of deep condensate gas has the characteristics of strong continuity and large data fluctuation, so it is necessary to preprocess the curve outliers first to improve the data quality, mainly including the supplement of missing data, outlier correction and curve smoothing, so as to form production dynamic data that can be applied to historical fitting. Based on the above preprocessed production data, the numerical simulation model is corrected to make it more consistent with the relevant characteristics of the actual deep condensate gas reservoir.

[0047] Step 105, establish a dynamic IPR curve library for deep condensate gas wells: Based on the above-mentioned corrected numerical simulation model, predict the dynamic IPR curve of the production well at any time and the reasonable production capacity of the well under the current production conditions, and output the corresponding phase parameters and condensate oil / gas saturation distribution at the same time, providing a data basis for the design of drainage and production process.

[0048] Step 106, design of related drainage and production processes for deep condensate gas wells: First, optimize the multiphase flow pressure gradient and production nozzle flow calculation method based on actual production data and well test data. Secondly, conduct a sensitivity analysis on the wellbore pressure drop, erosion resistance and liquid carrying capacity under different tubing and nozzle sizes to determine the influence of tubing size on tubing pressure drop, erosion resistance and liquid carrying capacity and the production requirements of nozzles of different sizes. Finally, comprehensively consider factors such as wellbore pressure drop, erosion resistance, liquid carrying capacity and economy, optimize the self-flowing production string structure in the design stage, and determine the sizes of the tubing and nozzles used to meet production requirements.

[0049] The following are several specific embodiments of the present invention.

[0050] Example 1

[0051] In a specific embodiment 1 of the present invention, the integrated design method of the deep condensate gas well self-flowing capacity and drainage process includes the following steps:

[0052] The first step is deep condensate gas phase state experiment and phase diagram determination. Relevant samples from Fengshen 1 well in Fengshen 101 block of Shengli Oilfield were selected for PVT experimental test and phase state phase diagram test.

[0053] The second step is to establish and fit the deep condensate gas phase state model. Based on the deep condensate gas phase state experimental data tested above, considering the impact of the deep condensate gas condensation process on the phase state change, a phase state model that conforms to the Fengshen 1 well in the Fengshen 101 block is constructed and relevant fitting is performed. The relevant experimental data and fitting results are shown in Figure 2. Figure 1-Figure 4 shown.

[0054] The third step is to establish a numerical simulation characteristic model for deep condensate gas reservoirs. Figure 5, a gas saturation model for deep condensate gas reservoirs at a depth of 4316-4500m in Shengli Oilfield is given.

[0055] The fourth step is to preprocess the production dynamic data of deep condensate gas wells and calibrate the numerical simulation model. Figure 6 To adjust the actual numerical model range after fitting, Figure 7 is the fitting effect of the theoretical production curve and the actual production curve, Figure 8 This is a comparison chart between the actual pressure measuring point and the model pressure.

[0056] The fifth step is to establish a dynamic IPR curve library for deep condensate gas wells. Based on this dynamic IPR curve library, the IPR curve changes of Fengshen 1 well at any time can be predicted. Taking a certain moment as an example, Fig. 9 This is the IPR curve of Fengshen 1 well on January 1, 2022. We can conclude that the current reasonable production pressure of the well is 25 MPa and the maximum production capacity is 11.09×10 4 square.

[0057] The sixth step is to design the relevant drainage and production process for deep condensate gas wells. The multiphase flow pressure gradient and production nozzle flow calculation method are optimized based on the actual production data and well test data. The preferred calculation formula for the condensate gas well production pressure drop for Fengshen 1 well is the Ansari method, and the preferred gas nozzle calculation method is the Baxendale method. Among them, Table 1 is an analysis and comparison of sensitivity factors of different tubings in Fengshen 1 well, and Table 2 is an analysis and comparison of sensitivity factors of different gas nozzles in Fengshen 1 well. Finally, based on the comprehensive analysis of the effects of different tubing sizes on wellbore pressure drop, erosion resistance, liquid carrying capacity and economy, it is recommended to select 73mm tubing and 7mm nozzles. Among them, 60mm tubing is difficult to meet the depth requirements, 89mm tubing is less economical, and the gas production of 6mm nozzles is difficult to meet the production requirements.

[0058] Table 1 Comparison of sensitivity factors of different tubings in Fengshen 1 Well

[0059]

[0060] Table 2 Comparison of sensitivity factors of different gas nozzles in Fengshen 1 Well

[0061] Air nozzle size <![CDATA[Gas production (10 4 Sm 3 / d)]]> 7mm 13.22 6mm 9.71

[0062] Example 2

[0063] In the specific embodiment 2 of the present invention, the multiphase flow pressure gradient and the production nozzle flow calculation method are optimized, which mainly includes the following steps:

[0064] The first step is deep condensate gas phase state experiment and phase diagram determination. Relevant samples from Fengshen 1 well in Fengshen 101 block of Shengli Oilfield were selected for PVT experimental test and phase state phase diagram test.

[0065] The second step is to establish and fit the deep condensate gas phase state model. Based on the deep condensate gas phase state experimental data tested above, considering the impact of the deep condensate gas condensation process on the phase state change, a phase state model that conforms to the Fengshen 1 well in the Fengshen 101 block is constructed and relevant fitting is performed. The relevant experimental data and fitting results are shown in Figure 2. Figure 1-Figure 4 shown.

[0066] The third step is to establish a numerical simulation characteristic model for deep condensate gas reservoirs. Figure 5 , a gas saturation model for deep condensate gas reservoirs at a depth of 4316-4500m in Shengli Oilfield is given.

[0067] The fourth step is to preprocess the production dynamic data of deep condensate gas wells and calibrate the numerical simulation model. Figure 6 To adjust the actual numerical model range after fitting, Figure 7 is the fitting effect of the theoretical production curve and the actual production curve, Figure 8 This is a comparison chart between the actual pressure measuring point and the model pressure.

[0068] The fifth step is to establish a dynamic IPR curve library for deep condensate gas wells. Based on this dynamic IPR curve library, the IPR curve changes of Fengshen 1 well at any time can be predicted. Taking a certain moment as an example, Fig. 9 This is the IPR curve of Fengshen 1 well on January 1, 2022. We can conclude that the current reasonable production pressure of the well is 25MPa and the maximum production capacity is 11.09×104 cubic meters.

[0069] The sixth step is to determine the calculation method for multiphase flow in deep condensate gas wellbore. There are many calculation methods for calculating the pressure gradient and production nozzle flow of multiphase flow in condensate gas wellbore. Therefore, it is necessary to optimize them according to the actual production data and well test data, and select the calculation method that is most suitable for the study block to optimize the corresponding production process. Table 3 is the error analysis of the multiphase pipe flow calculation method of Fengshen 1 Well. It can be seen that the preferred calculation formula for the production pressure drop of condensate gas wells for Fengshen 1 Well is the Ansari method. Table 4 is the error analysis of the gas nozzle calculation method of Fengshen 1 Well. It can be seen that the preferred gas nozzle calculation method is the Baxendale method.

[0070] Table 3 is the error analysis table of the calculation method of multiphase pipe flow in Fengshen 1 Well

[0071]

[0072] Table 4 shows the error analysis of the calculation method of the gas nozzle of Fengshen 1 Well

[0073]

[0074] The seventh step is to determine the structure of the self-flowing production string for deep condensate gas wells. Based on the reasonable production capacity of the deep gas wells selected in the fifth step, and taking into account the wellbore pressure drop, erosion resistance, liquid carrying capacity and economy, it is recommended to select 73mm tubing and 7mm nozzles for Fengshen 1 well at this stage.

[0075] Example 3

[0076] In the specific embodiment 3 of the present invention, based on the embodiment 1, the next stage of the deep condensate gas well's self-flowing capacity and drainage process are integratedly designed, mainly including the following steps:

[0077] The first step is deep condensate gas phase state experiment and phase diagram determination. Relevant samples from Fengshen 1 well in Fengshen 101 block of Shengli Oilfield were selected for PVT experimental test and phase state phase diagram test.

[0078] The second step is to establish and fit the deep condensate gas phase state model. Based on the deep condensate gas phase state experimental data tested above, considering the impact of the deep condensate gas condensation process on the phase state change, a phase state model that conforms to the Fengshen 1 well in the Fengshen 101 block is constructed and relevant fitting is performed. The relevant experimental data and fitting results are shown in Figure 2. Figure 1-Figure 4 shown.

[0079] The third step is to establish a numerical simulation characteristic model for deep condensate gas reservoirs. Figure 5 , a gas saturation model for deep condensate gas reservoirs at a depth of 4316-4500m in Shengli Oilfield is given.

[0080] The fourth step is to preprocess the production dynamic data of deep condensate gas wells and calibrate the numerical simulation model. Figure 6 To adjust the actual numerical model range after fitting, Figure 7 is the fitting effect of the theoretical production curve and the actual production curve, Figure 8 This is a comparison chart between the actual pressure measuring point and the model pressure.

[0081] The fifth step is to establish a dynamic IPR curve library for deep condensate gas wells. Based on the dynamic IPR curve library, the IPR curve changes of Fengshen 1 well at any time can be predicted. After two years of production according to the production parameters optimized in Example 1, the IPR curve of Fengshen 1 well on January 1, 2024 is as follows: Fig.10 , we can conclude that the current reasonable production pressure of the well is 20 MPa and the maximum production capacity is 6.13×10 4 , the optimal production period is three years.

[0082] Step 6: Design of drainage and production technology for deep condensate gas wells. Based on all the preferred multiphase flow pressure gradients and production nozzle flow calculation methods, and comprehensive analysis of the effects of different tubing sizes on wellbore pressure drop, erosion resistance, liquid carrying capacity, and economic efficiency, the relevant design of the tubing structure for the five-year production period of Fengshen 1 Well with optimized production parameters is recommended as shown in Table 5.

[0083] Table 5 is the optimization table of the pipe string structure of Fengshen 1 well from 2022 to 2026

[0084]

[0085] Finally, it should be noted that the above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions recorded in the aforementioned embodiments or replace some of the technical features therein with equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

[0086] Except for the technical features described in the specification, all other technical features are known technologies to those skilled in the art.

Claims

1. A method for designing the self-flowing capacity and drainage and production technology of deep condensate gas wells, characterized in that: The integrated design method for the deep condensate gas well self-flowing capacity and drainage and production process includes: Step 1, conducting deep condensate gas phase state experiment and phase diagram determination; Step 2, establishing and fitting the deep condensate gas phase model; Step 3, establishing a numerical simulation characteristic model for deep condensate gas reservoirs; Step 4, preprocessing the production dynamic data of deep condensate gas wells and calibrating the numerical simulation model; Step 5, establishing a deep condensate gas well inflow dynamic IPR curve library; Step 6, design relevant drainage and production processes for deep condensate gas wells.

2. The method for integrated design of deep condensate gas well self-flowing capacity and drainage and production process according to claim 1, characterized in that: In step 1, based on the deep condensate gas field samples, the pressure-volume-temperature PVT experimental test is carried out on the deep condensate gas related phase state, and its original phase state and condensate phase state phase diagram are tested at the same time.

3. The method for integrated design of deep condensate gas well self-flowing capacity and drainage and production process according to claim 1, characterized in that: In step 2, based on the tested deep condensate gas phase experimental data, considering the influence of the deep condensate gas condensation process on the phase change, a phase model that conforms to the deep condensate gas is constructed and relevant fitting is performed.

4. The method for integrated design of deep condensate gas well self-flowing capacity and drainage and production technology according to claim 1, characterized in that: In step 3, the characteristic parameters of the deep condensate gas reservoir are statistically analyzed, and a gas reservoir model that can truly reflect the characteristics of the deep condensate gas reservoir is established using the reservoir numerical simulation method. The theoretical production curves of gas production, oil production, and water content are obtained by calculating through input parameters.

5. The method for integrated design of deep condensate gas well self-flowing capacity and drainage and production process according to claim 4, characterized in that: In step 3, the deep condensate gas reservoir numerical simulation model library includes three modules: model construction and attribute input module, model generation module, and model operation module.

6. The method for integrated design of deep condensate gas well self-flowing capacity and drainage and production technology according to claim 5, characterized in that: In step 3, the model construction and attribute input module directly inputs the well trajectory, layering and logging curve data of the target well based on the understanding of the geological attribute characteristics of different deep condensate gas reservoirs, and uses the interpolation method to predict the characteristic information of parameters such as inter-well porosity, permeability and gas saturation to establish a geological model that meets the target block.

7. The method for integrated design of deep condensate gas well self-flowing capacity and drainage and production process according to claim 5, characterized in that: In step 3, the model generation module establishes and generates a deep condensate gas reservoir numerical simulation model that truly reflects specific information based on the deep condensate gas phase model.

8. The method for integrated design of deep condensate gas well self-flowing capacity and drainage and production process according to claim 5, characterized in that: In step 3, the model operation module operates the established numerical simulation model to predict the dynamic IPR curve during the development of deep condensate gas.

9. The method for integrated design of deep condensate gas well self-flowing capacity and drainage and production process according to claim 1, characterized in that: In step 4, the deep condensate gas production data has the characteristics of strong continuity and large data fluctuations. It is necessary to first preprocess the curve outliers to improve the data quality, mainly including the supplement of missing data, outlier correction and curve smoothing, so as to form production dynamic data that can be applied to historical fitting; based on the preprocessed production data, the numerical simulation model is corrected to make it more consistent with the actual deep condensate gas reservoir related characteristics.

10. The method for integrated design of deep condensate gas well self-flowing capacity and drainage and production technology according to claim 1, characterized in that: In step 5, based on the corrected numerical simulation model, the dynamic IPR curve of the production well at any time and the reasonable production capacity of the well under the current production conditions are predicted, and the corresponding phase parameters and condensate oil / gas saturation distribution are output at the same time to provide a data basis for the design of the production process.

11. The method for integrated design of deep condensate gas well self-flowing capacity and drainage and production process according to claim 1, characterized in that: In step 6, first, the multiphase flow pressure gradient and production nozzle flow calculation method are optimized according to the actual production data and well test data; secondly, a sensitivity analysis is performed on the wellbore pressure drop, erosion resistance and liquid carrying capacity under different tubing and gas nozzle sizes to determine the influence of tubing size on the tubing pressure drop, erosion resistance and liquid carrying capacity and the production requirements of gas nozzles of different sizes; finally, considering the wellbore pressure drop, erosion resistance, liquid carrying capacity and economy comprehensively, the self-flowing production string structure in the design stage is optimized, and the sizes of the tubing and gas nozzles used are determined to meet the production requirements.

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