Safe and economical double-constrained intelligent distribution method for salt cavern compressed air energy storage gas injection and production shaft

Abstract

The invention provides a safety and economy double-constrained salt cavern compressed gas energy storage gas injection and production shaft intelligent distribution method, which comprises the following steps: collecting historical data of a to-be-calculated salt cavern reservoir group cavity, and dividing the historical data into a first data set and a second data set; preprocessing the first data set and the second data set; performing model training by using the preprocessed data in the first data set to obtain a random forest regression model; using a random forest regression model to predict an input tubular column combination to obtain a plurality of tubular column combination schemes sorted according to a preset rule; data in the preprocessed second data set is used for model training, and a salt cavern reservoir group injection-production string injection-production gas flow calculation model is obtained; and the pipe column combination scheme is input into a salt cavern reservoir group injection and production pipe column injection and production gas flow calculation model for calculation processing, and the optimal salt cavern compressed gas energy storage injection and production gas shaft intelligent distribution scheme is determined. According to the method, the accuracy and efficiency of intelligent distribution of the salt cavern compressed gas energy storage gas injection and production shaft are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent allocation calculation of injection-production wellbores in a salt cavern storage group, and particularly to an intelligent allocation method for injection-production gas wellbores in a salt cavern compressed air energy storage with dual constraints of safety and economy. Background Art

[0002] Generally, a salt cavern storage group contains multiple salt cavities, and each salt cavity contains one or more injection-production wells. In order to achieve the safe and efficient injection-production gas process of multiple cavities and multiple injection-production strings in the salt cavern storage group, while ensuring the safety and stability of the cavities, it is first necessary to select multiple injection-production wells for operation. This approach can extend the service life of the injection-production wells, improve the utilization efficiency of the cavities, and also reduce waste of resources and environmental impact. Therefore, during the injection-production gas process of the injection-production wells, it is necessary to accurately calculate how many injection-production gas wells are required and make a reasonable allocation, so as to ensure safety, maximize economic benefits in the injection-production gas operation of the salt cavern storage group, and perform calculations for subsequent other work.

[0003] Traditional methods mainly rely on experience and practice for the allocation calculation of simple pipelines. This method usually requires the experience and professional knowledge of professional engineers, which is difficult for operators without professional knowledge to operate, and the accuracy and efficiency of the allocation scheme are both low. Summary of the Invention

[0004] In view of this, the present invention provides an intelligent allocation method for injection-production gas wellbores in a salt cavern compressed air energy storage with dual constraints of safety and economy to solve the above problems.

[0005] The present invention provides an intelligent allocation method for injection-production gas wellbores in a salt cavern compressed air energy storage with dual constraints of safety and economy, including: collecting historical data of the cavities in the salt cavern storage group to be calculated and dividing them into a first data set and a second data set; performing data preprocessing on the first data set and the second data set, and the preprocessing includes data cleaning, data smoothing, data transformation, and data partitioning; using the data in the preprocessed first data set for model training to obtain a random forest regression model; using the random forest regression model to predict the input string combinations to obtain multiple string combination schemes sorted according to a preset rule; using the data in the preprocessed second data set for model training to obtain an injection-production gas flow calculation model for the injection-production strings in the salt cavern storage group; inputting the string combination schemes into the injection-production gas flow calculation model for the injection-production strings in the salt cavern storage group for calculation processing, and determining the optimal intelligent allocation scheme for injection-production gas wellbores in the salt cavern compressed air energy storage from them.

[0006] In another implementation manner of the present invention, the first dataset includes data on the number of cavities, the number of injection and production gas pipelines for each cavity, and related influencing factors; the second dataset includes data on the number of cavities, the depth of each injection and production gas well for each cavity, the number of each injection and production gas well for each cavity, and the communication situation data between cavities.

[0007] In another implementation manner of the present invention, the preset rules include: sorting the tubing string combination schemes according to the total number of tubing strings in each tubing string combination scheme; sorting each tubing string in each tubing string combination scheme according to the erosion flow rate priority.

[0008] In another implementation manner of the present invention, the step of inputting the tubing string combination scheme into the injection and production gas flow calculation model of the salt cavern storage group injection and production tubing string for calculation and processing, and determining the optimal intelligent allocation scheme for the injection and production gas wellbore of the salt cavern compressed air energy storage from it, includes: inputting the tubing string combination scheme into the injection and production gas flow calculation model of the salt cavern storage group injection and production tubing string; performing calculation and processing on the tubing string combination scheme and the corresponding injection or production gas conditions to obtain the wellhead pressure and flow rate of different tubing strings; calculating the maximum diameter of rock-carrying of the tubing string based on the wellhead pressure; determining the optimal intelligent allocation scheme for the injection and production gas wellbore of the salt cavern compressed air energy storage from the tubing string combination scheme based on the flow rate and the maximum diameter of rock-carrying.

[0009] In another implementation manner of the present invention, it further includes: respectively calculating the equivalent spherical diameter and the starting diameter of the rock cuttings suspension of each tubing string; selecting the smaller diameter among the equivalent spherical diameter and the starting diameter as the maximum rock-carrying diameter.

[0010] In another implementation manner of the present invention, the equivalent spherical diameter is expressed as:

[0011]

[0012] wherein, V is the volume of the suspended rock cuttings, m 3 .

[0013] In another implementation manner of the present invention, the starting diameter is expressed as:

[0014]

[0015] wherein, d s is the starting diameter of the rock cuttings, m; C D is the Stokes drag coefficient, dimensionless; ρ s is the density of the rock cuttings, kg / m 3 ; g is the acceleration due to gravity, m / s 2 ; cs1 is the starting coefficient, dimensionless; v is the bottom-hole gas velocity, m / s; f t is the starting velocity.

[0016] In another implementation manner of the present invention, determining an optimal intelligent allocation scheme for the injection and production gas wells of salt cavern compressed air energy storage from the pipe string combination scheme based on the flow rate and the maximum diameter of the rock carried includes: respectively determining whether the flow rate and the maximum diameter of the rock carried simultaneously meet the requirements of the critical erosion flow rate, the minimum flow rate, and the requirement for processing the maximum diameter of the rock carried on the ground; and determining the pipe string combination scheme that simultaneously meets the above requirements as the optimal intelligent allocation scheme for the injection and production gas wells of salt cavern compressed air energy storage.

[0017] In another implementation manner of the present invention, respectively determining whether the flow rate and the maximum diameter of the rock carried simultaneously meet the requirements of the erosion flow rate, the minimum flow rate, and the requirement for processing the maximum diameter of the rock carried on the ground includes: determining whether the flow rate simultaneously meets the requirements of the critical erosion flow rate and the minimum flow rate; if the flow rate does not simultaneously meet the requirements of the critical erosion flow rate and the minimum flow rate, then input the next pipe string combination scheme into the injection and production gas flow calculation model of the salt cavern reservoir group according to the sorting for re-calculation and processing until all the pipe strings in the pipe string combination scheme simultaneously meet the requirements of the critical erosion flow rate and the minimum flow rate; if the flow rate simultaneously meets the requirements of the critical erosion flow rate and the minimum flow rate, then determine whether the maximum diameter of the rock carried meets the requirement for processing the maximum diameter of the rock carried on the ground; if the maximum diameter of the rock carried does not meet the requirement for processing the maximum diameter of the rock carried on the ground, then input the next pipe string combination scheme into the injection and production gas flow calculation model of the salt cavern reservoir group according to the sorting for re-calculation and processing until the maximum diameter of the rock carried in the pipe string combination scheme meets the requirement for processing the maximum diameter of the rock carried on the ground; if the maximum diameter of the rock carried meets the requirement for processing the maximum diameter of the rock carried on the ground, then output the current pipe string combination scheme as the optimal intelligent allocation scheme for the injection and production gas wells of salt cavern compressed air energy storage.

[0018] In another implementation manner of the present invention, the formula for calculating the critical erosion flow rate is as follows:

[0019]

[0020]

[0021] Wherein, S is the cross-sectional area of the pipeline, m 2 ; D is the outer diameter of the pipeline, mm; t is the wall thickness of the pipeline, mm; Q flow is the critical erosion flow rate, 10,000 m³ / h; ρ g is the gas density, kg / m 3 ; C is the critical flow coefficient, a dimensionless quantity; a is the air pressure coefficient, a dimensionless quantity.

[0022] The intelligent allocation method for injection-production gas wells in salt cavern compressed air energy storage with dual constraints of safety and economy according to the present invention combines the random forest calculation method, fully considers the cuttings starting ability, the wellbore's ability to carry cuttings, the ground cuttings handling ability, and also takes into account the situation that extremely small flow values will result in the economic benefit being less than the wellbore maintenance cost. By using relevant theoretical calculation formulas and iterative calculation methods, etc., it can realize the intelligent allocation of injection-production gas wells in salt cavern compressed air energy storage automatically. It can calculate the specific number of pipelines required for the total injection-production gas pipelines for different numbers of cavities, different numbers of injection-production gas pipe strings, and different pipe string depths, and can provide a more accurate and efficient allocation scheme. Brief Description of the Drawings

[0023] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. By reading the detailed description of the following embodiments, the advantages and benefits in the solutions will become clear to those skilled in the art. The drawings are only for the purpose of showing the preferred embodiments and are not considered to be a limitation of the present invention. In the drawings:

[0024] Figure 1 It is a schematic flow diagram of the intelligent allocation method for injection-production gas wells in salt cavern compressed air energy storage with dual constraints of safety and economy according to an embodiment of the present invention.

[0025] Figure 2 It is a schematic diagram of the intelligent allocation model for injection-production gas wells in salt cavern compressed air energy storage according to an embodiment of the present invention.

[0026] Figure 3 It is a schematic diagram of the accumulation state of cuttings deposition according to an embodiment of the present invention.

[0027] Figure 4 It is a schematic diagram of the force analysis of cuttings in suspension state according to an embodiment of the present invention.

[0028] Figure 5 It is a schematic diagram of the operation with a total injection-production gas volume of 438 kg / s under the injection condition according to an embodiment of the present invention.

[0029] Figure 6 It is a schematic diagram of the operation with a total injection-production gas volume of 297 kg / s under the injection condition according to an embodiment of the present invention.

[0030] Figure 7 It is a schematic diagram of the operation with a total injection-production gas volume of 258 kg / s under the production condition according to an embodiment of the present invention.

[0031] Figure 8 It is a schematic diagram of the operation with a total injection-production gas volume of 228 kg / s under the production condition according to an embodiment of the present invention. Detailed Embodiments

[0032] To enable those skilled in the art to better understand the technical solutions in the embodiments of the present invention, the following will clearly and detailedly describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments in the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art shall fall within the scope of protection of the embodiments of the present invention.

[0033] Figure 1 It is a schematic flow diagram of an intelligent allocation method for injection and production gas wells in a salt cavern compressed air energy storage with dual constraints of safety and economy provided by an embodiment of the present invention. As Figure 1 shown, this embodiment mainly includes:

[0034] Collect historical data of the cavities in the salt cavern storage group to be calculated, and divide it into a first data set and a second data set.

[0035] Exemplarily, the historical data includes data such as the number of cavities, the number of injection and production gas pipelines for each cavity, data of relevant influencing factors, the depth of injection and production gas wells for each cavity, and the connection situation between cavities.

[0036] Perform data preprocessing on the first data set and the second data set. The preprocessing includes data cleaning, data smoothing, data transformation, and data partitioning.

[0037] Exemplarily, perform data cleaning on the data, process problems such as errors, missing values, outliers, and duplicate values in the original data, perform various arithmetic and logical operations on the data to obtain further information, etc. Convert the data that needs to be used into international units for subsequent modeling and analysis.

[0038] Use the data in the preprocessed first data set for model training to obtain a random forest regression model.

[0039] Use the random forest regression model to predict the input string combination to obtain multiple string combination schemes sorted according to preset rules.

[0040] Use the data in the preprocessed second data set for model training to obtain a calculation model for the injection and production gas flow of the injection and production strings in the salt cavern storage group.

[0041] Input the string combination scheme into the calculation model for the injection and production gas flow of the injection and production strings in the salt cavern storage group for calculation and processing, and determine the optimal intelligent allocation scheme for the injection and production gas wells in the salt cavern compressed air energy storage from it.

[0042] The intelligent allocation method for the injection and production gas wellbores of salt cavern compressed air energy storage with dual constraints of safety and economy according to the present invention combines the random forest calculation method, fully considers the cuttings starting ability, the wellbore cuttings carrying ability, the surface cuttings treatment ability, and takes into account the situation that an extremely small flow value will result in the economic benefit being less than the wellbore maintenance cost. By using relevant theoretical calculation formulas and iterative calculation methods, etc., it can realize the intelligent allocation of the injection and production gas wellbores of salt cavern compressed air energy storage automatically, and can calculate the specific pipeline quantity required for the total injection and production gas pipelines for different numbers of cavities, different numbers of injection and production pipe strings, and different pipe string depths, and can provide a more accurate and efficient allocation scheme.

[0043] In another implementation manner of the present invention, the first data set includes the number of cavities, the number of injection and production gas pipelines for each cavity, and data on related influencing factors; the second data set includes the number of cavities, the depth of the injection and production gas wells for each cavity, the number of injection and production gas wells for each cavity, and data on the connection situation between cavities.

[0044] Exemplarily, the first data set and the second data set are respectively divided into a training set, a validation set, and a test set for model development, tuning, and evaluation.

[0045] In another implementation manner of the present invention, the preset rules include: sorting the pipe string combination schemes according to the total number of pipe strings in each pipe string combination scheme; sorting each pipe string in each pipe string combination scheme according to the erosion flow priority.

[0046] Exemplarily, a random forest regression model is used to predict the total gas volume of different pipe string combinations. The trained random forest model is used to predict the input pipe string combination. First, sort according to the total number of pipe strings, and then sort the erosion flow of each well to obtain the erosion flow priority. Sort each pipe string in each pipe string combination scheme according to the erosion flow priority to obtain multiple pipe string combination schemes sorted according to the preset rules, that is, the pipe string combination schemes from good to bad. In order to ensure the economical use of pipelines, it is set that the injection and production capacity of the finally obtained pipe string combination scheme should be less than 1.5 times the required total injection and production flow rate.

[0047] In another implementation manner of the present invention, as Figure 2As shown, inputting the tubing string combination plan into the injection and production gas flow calculation model of the salt cavern storage group injection and production tubing string for calculation and processing, and determining the optimal intelligent allocation plan for the injection and production wellbores of salt cavern compressed air energy storage from it, includes: inputting the tubing string combination plan into the injection and production gas flow calculation model of the salt cavern storage group injection and production tubing string; performing calculation and processing on the tubing string combination plan and the corresponding injection or production conditions to obtain the wellhead pressure and flow rate of different tubing strings; calculating the maximum diameter of rock-carrying of the tubing string based on the wellhead pressure; and determining the optimal intelligent allocation plan for the injection and production wellbores of salt cavern compressed air energy storage from the tubing string combination plan based on the flow rate and the maximum diameter of rock-carrying.

[0048] Exemplarily, the input data for the injection condition is shown in Table 1.

[0049] Table 1 Input Data Table for Injection Condition

[0050]

[0051] The output data is shown in Table 2, and the operation results are as Figure 5 and Figure 6 shown.

[0052] Table 2 Output Data Table for Injection Condition

[0053]

[0054]

[0055] The input data for the production condition is shown in Table 3.

[0056] Table 3 Input Data Table for Production Condition

[0057]

[0058] The output data is shown in Table 4, and the operation results are as Figure 7 and Figure 8 shown.

[0059] Table 4 Output Data Table for Production Condition

[0060]

[0061] It should be understood that using the trained calculation model to predict the intelligent allocation of the injection and production wellbores of salt cavern compressed air energy storage in the future, reasonable planning and decision-making can be carried out according to the prediction results, so as to ensure the safety, maximize the economic benefits in the injection and production operations of the salt cavern storage group, and the calculation of subsequent other work.

[0062] In another implementation of the present invention, it further includes: calculating the equivalent spherical diameter and the starting diameter of the cuttings suspension in each string respectively; and selecting the smaller diameter of the equivalent spherical diameter and the starting diameter as the maximum cuttings-carrying diameter.

[0063] In another implementation of the present invention, the equivalent spherical diameter is expressed as:

[0064]

[0065] where V is the volume of the suspended cuttings, m 3 。

[0066] Exemplarily, a non-linear equation is used to solve for the volume V of the suspended cuttings, and the force analysis diagram is as Figure 4 shown.

[0067] First, calculate the bottom-hole temperature, and the calculation formula is as follows:

[0068] T bottom =T initial +temperature_gradient×depth

[0069] where T bottom is the bottom-hole temperature, K; T initial is the wellhead temperature, K; temperature_gradient is the temperature gradient, a dimensionless quantity; depth is the well depth, m.

[0070] Next, calculate the bottom-hole gas density, and the calculation formula is as follows:

[0071]

[0072] where P is the bottom-hole pressure, Pa; P 0 is the standard atmospheric pressure, 101000 Pa; temperature_gradient is the temperature gradient, a dimensionless quantity; depth is the well depth, m; ρ f is the bottom-hole gas density, kg / m 3 。

[0073] Calculate the gravity acting on the cuttings as:

[0074] F G =ρ p ×V×g

[0075] where F G is the gravity acting on the cuttings, N; V is the volume of the suspended cuttings, m 3 。

[0076] Calculate the buoyancy acting on the cuttings as:

[0077] F b = ρ f × V × g

[0078] where F b is the buoyancy force on the cuttings, in N.

[0079] The fluid drag force on the cuttings is calculated as:

[0080] F d = 0.5 × ρ f × C D × v 2 × A t

[0081] where F d is the fluid drag force on the cuttings, in N; A t is the projected area of the cuttings, in m 2 .

[0082] The pressure gradient force on the cuttings is calculated as:

[0083] F t = -ρ f × g × v × t × V

[0084] where F t is the pressure gradient force on the cuttings, in N; t is the time interval, in s.

[0085] The volume V of the suspended cuttings when the cuttings reach the equilibrium state is calculated by the following formula:

[0086] F t + F d + F b - F G = 0

[0087] In another implementation of the present invention, the starting diameter is expressed as:

[0088]

[0089] where d s is the starting diameter of the cuttings, in m; C D is the Stokes drag coefficient, dimensionless; ρ s is the density of the cuttings, in kg / m 3 ; g is the acceleration due to gravity, in m / s 2 ; cs1 is the starting coefficient, dimensionless; v is the bottom-hole gas velocity, in m / s; f t is the starting velocity.

[0090] Exemplarily, the bottom-hole gas velocity v is calculated by the following formula:

[0091]

[0092] Among them, Q v is the gas volume flow rate, m 3 / s; A is the cross-sectional area of the pipe string, m 2 ; v is the gas velocity, m / s.

[0093] The cuttings appear in the form of accumulation at the bottom of the cavity. As Figure 3 shown, the starting velocity calculation formula is as follows:

[0094]

[0095] Among them, f 1 is the internal friction coefficient of the cuttings, a dimensionless quantity; x is the proportion of the triangular pile accumulation method, a dimensionless quantity.

[0096] In another implementation manner of the present invention, the optimal intelligent allocation scheme for the injection and production gas wellbore of the salt cavern compressed air energy storage is determined from the pipe string combination scheme based on the flow rate and the maximum diameter of the cuttings carried, including: respectively judging whether the flow rate and the maximum diameter of the cuttings carried simultaneously meet the critical erosion flow rate requirement, the minimum flow rate requirement, and the ground maximum cuttings diameter processing requirement; and determining the pipe string combination scheme that simultaneously meets the above requirements as the optimal intelligent allocation scheme for the injection and production gas wellbore of the salt cavern compressed air energy storage.

[0097] In another implementation manner of the present invention, respectively judging whether the flow rate and the maximum diameter of the cuttings carried simultaneously meet the erosion flow rate requirement, the minimum flow rate requirement, and the ground maximum cuttings diameter processing requirement includes: judging whether the flow rate simultaneously meets the critical erosion flow rate requirement and the minimum flow rate requirement; if the flow rate does not simultaneously meet the critical erosion flow rate requirement and the minimum flow rate requirement, then input the next pipe string combination scheme into the injection and production gas flow calculation model of the injection and production pipe string of the salt cavern reservoir group according to the sorting for re-calculation and processing until all the pipe strings in the pipe string combination scheme simultaneously meet the critical erosion flow rate requirement and the minimum flow rate requirement; if the flow rate simultaneously meets the critical erosion flow rate requirement and the minimum flow rate requirement, then judge whether the maximum diameter of the cuttings carried meets the ground maximum cuttings diameter processing requirement; if the maximum diameter of the cuttings carried does not meet the ground maximum cuttings diameter processing requirement, then input the next pipe string combination scheme into the injection and production gas flow calculation model of the injection and production pipe string of the salt cavern reservoir group according to the sorting for re-calculation and processing until the maximum diameter of the cuttings carried in the pipe string combination scheme meets the ground maximum cuttings diameter processing requirement; if the maximum diameter of the cuttings carried meets the ground maximum cuttings diameter processing requirement, then output the current pipe string combination scheme as the optimal intelligent allocation scheme for the injection and production gas wellbore of the salt cavern compressed air energy storage.

[0098] Exemplarily, first check whether the current string flow rate is less than the critical erosion flow rate. If it is less than the critical erosion flow rate of the current string, continue to judge the next string until all strings meet the requirements. If the current string flow rate is greater than the erosion flow rate, reselect the next string recommendation scheme output by the random forest regression model and recalculate.

[0099] Check whether the flow rate of each string meets the minimum flow rate requirement. First, check whether the flow rate of the current string is less than the minimum flow rate. If it is greater than the minimum flow rate, continue to judge the next string until all strings meet the requirements. If the flow rate of the current string is less than the minimum flow rate, reselect the next string recommendation scheme output by the random forest regression model and recalculate.

[0100] Check whether each string meets the requirement for handling the maximum cuttings-carrying diameter on the ground, and check them in turn until all strings meet the requirements. If the maximum cuttings-carrying diameter of the current string does not meet the ground requirement, reselect the next string recommendation scheme output by the random forest regression model and recalculate.

[0101] It should be understood that in this application, considering the situation where an extremely small flow rate value will result in the economic benefit being less than the wellbore maintenance cost, economic constraints are imposed on the minimum flow rate value of the wellbore. At the same time, full consideration is given to the cuttings initiation ability, the wellbore cuttings-carrying ability, and the ground cuttings handling ability, providing constraints for the safe handling of cuttings in the wellbore.

[0102] In another implementation manner of the present invention, calculate the critical erosion flow rate of each string according to the set string size, pressure coefficient, and critical flow coefficient on site. The formula for calculating the critical erosion flow rate is as follows:

[0103]

[0104] Where S is the cross-sectional area of the pipeline, m 2 ; D is the outer diameter of the pipeline, mm; t is the wall thickness of the pipeline, mm; Q flow is the critical erosion flow rate, 10,000 m³ / h; ρ g is the gas density, kg / m 3 ; C is the critical flow coefficient, a dimensionless quantity; a is the pressure coefficient, a dimensionless quantity.

[0105] In another implementation manner of the present invention, evaluate and optimize the above two models. By writing algorithms in the Python editing software, compare the differences between the model prediction results and the actual pipeline allocation data, evaluate the accuracy and prediction ability of the model, and perform parameter tuning or model adjustment for the poorly performing calculation models. Using Python programming tools for calculation greatly improves the efficiency of solving complex engineering problems.

[0106] Compared with traditional methods that require manual simulation, measurement, experiment, and analysis, the intelligent allocation method for injection and production gas wells in salt cavern compressed air energy storage proposed by the present invention is based on a salt cavern reservoir group that considers the rock-carrying capacity, minimum operating flow rate, different depths, number of cavities, number of pipelines, and bottom-hole pressure on the ground. Considering multiple factors such as safety and economy, by fixing the pressure of the ground inlet manifold (i.e., the wellhead pressure of the injection and production gas wells), the optimal pipe string allocation scheme under different conditions can be obtained more quickly, and it also has strong flexibility and accuracy.

[0107] On the other hand, the electronic device of the present invention includes: a processor, a memory, a communication bus, and a communication interface.

[0108] Wherein:

[0109] The processor, the memory, and the communication interface complete communication with each other through the communication bus.

[0110] The communication interface is used to communicate with other electronic devices or servers.

[0111] The processor is used to execute a program, specifically, it can execute the steps of the intelligent allocation method for injection and production gas wells in salt cavern compressed air energy storage with dual constraints of safety and economy in any of the above embodiments.

[0112] Specifically, the program may include program code, and the program code includes computer operation instructions.

[0113] The processor may be a central processing unit (CPU) or a graphics processing unit (GPU). One or more processors included in the intelligent device may be of the same type of processor, such as one or more CPUs; or they may be of different types of processors, such as one or more CPUs and one or more GPUs.

[0114] The memory is used to store the program. The memory may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk memory.

[0115] The program is specifically used to cause the processor to execute to implement the steps of the intelligent allocation method for injection and production gas wells in salt cavern compressed air energy storage with dual constraints of safety and economy described in any of the embodiments. The specific implementation of each step in the program can refer to the corresponding descriptions in the steps and units of the intelligent allocation method for injection and production gas wells in salt cavern compressed air energy storage with dual constraints of safety and economy in any of the above steps, which will not be elaborated here. Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working processes of the above-described devices and modules can refer to the corresponding process descriptions in the foregoing method embodiments.

[0116] The method according to the embodiments of the present invention can be implemented in a server equipped with a central processing unit (CPU) and a graphics processing unit (GPU).

[0117] So far, specific embodiments of the present invention have been described. Other embodiments are within the scope of the appended claims. In some cases, the actions recited in the claims may be performed in a different order and still achieve the desired results. Additionally, in the drawings, the sample types corresponding to the training dataset do not necessarily require the specific order or consecutive order shown to achieve the desired results.

[0118] It should be noted that all directional indications (such as up, down, left, right, back...) in the embodiments of the present invention are only used to explain the relative positional relationship between components in a certain specific order (as shown in the drawings). If this specific order changes, the directional indications will change accordingly.

[0119] In the description of the present invention, the terms "first" and "second" are only used for the convenience of describing different components or names, and cannot be understood as indicating or implying an order relationship, relative importance, or implicitly indicating the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include at least one of such features.

[0120] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which the present invention belongs. The terms used in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention.

[0121] It should be noted that although the specific embodiments of the present invention have been described in detail in conjunction with the accompanying drawings, it should not be construed as a limitation on the protection scope of the present invention. Within the scope described in the claims, various modifications and deformations that can be made by those skilled in the art without creative efforts still belong to the protection scope of the present invention.

[0122] The examples of the embodiments of the present invention are intended to briefly illustrate the technical features of the embodiments of the present invention, so that those skilled in the art can intuitively understand the technical features of the embodiments of the present invention, and are not intended as an improper limitation on the embodiments of the present invention.

[0123] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A safe and economic dual-constrained salt cavern gas storage injection and production wellbore intelligent allocation method, characterized in that: include: Collect historical data of the salt cavern reservoir group cavity to be calculated, and divide it into a first data set and a second data set; Performing data preprocessing on the first data set and the second data set, wherein the preprocessing includes data cleaning, data smoothing, data conversion, and data division; Use the preprocessed data in the first data set to perform model training to obtain a random forest regression model; Using the random forest regression model to predict the input string combination, a plurality of string combination schemes are obtained that are sorted according to preset rules; The data in the preprocessed second data set is used for model training to obtain a calculation model for the injection and production gas flow rate of the injection and production pipe string of the salt cavern reservoir group; The pipe string combination scheme is input into the injection and production gas flow calculation model of the salt cavern storage group injection and production pipe string for calculation and processing, thereby determining the optimal salt cavern compressed gas energy storage injection and production gas wellbore intelligent allocation scheme.

2. The method according to claim 1, characterized in that The first data set includes data on the number of cavities, the number of gas injection and production pipelines in each cavity, and related influencing factors; The second data set includes the number of cavities, the depth of the injection and production wells in each cavity, the number of the injection and production wells in each cavity, and the connectivity data between cavities.

3. The method according to claim 1, characterized in that The preset rules include: sorting the tubing string combination schemes according to the total number of tubing strings in each tubing string combination scheme; The individual strings in each string combination scheme are ranked according to the erosion flow priority.

4. The method according to claim 1, characterized in that: The step of inputting the pipe string combination scheme into the injection and production gas flow calculation model of the salt cavern reservoir group injection and production pipe string for calculation and processing, thereby determining the optimal salt cavern compressed gas energy storage injection and production gas wellbore intelligent allocation scheme, including: Inputting the pipe string combination scheme into the injection and production gas flow calculation model of the injection and production pipe string of the salt cavern reservoir group; Calculating and processing the tubing string combination scheme and the corresponding gas injection or gas production conditions to obtain the wellhead pressure and flow rate of different tubing strings; Calculate the maximum rock-carrying diameter of the pipe string based on the wellhead pressure; Based on the flow rate and the maximum rock-carrying diameter, an optimal intelligent allocation scheme for the injection and production wellbore of the salt cavern gas compression energy storage is determined from the pipe string combination scheme.

5. The method according to claim 4, characterized in that Also includes: Calculate the equivalent spherical diameter and starting diameter of the cuttings suspension for each string respectively; The smaller diameter between the equivalent spherical diameter and the starting diameter is selected as the maximum rock-carrying diameter.

6. The method according to claim 5, characterized in that The equivalent spherical diameter is expressed as: Where V is the volume of suspended cuttings, m 3 .

7. The method according to claim 5, characterized in that The starting diameter is expressed as: Among them, d s is the cuttings starting diameter, m; C D is the Stokes drag coefficient, a dimensionless quantity; ρ s is the density of rock cuttings, kg / m 3 ; g is the acceleration due to gravity, m / s 2 ; cs1 is the start-up coefficient, dimensionless; v is the bottom hole gas velocity, m / s; f t For startup speed.

8. The method according to claim 4, characterized in that The method of determining the optimal intelligent allocation scheme of the injection and production wellbore for the compressed gas storage in the salt cavern based on the flow rate and the maximum rock-carrying diameter from the pipe string combination scheme includes: respectively judging whether the flow rate and the maximum rock carrying diameter simultaneously meet the critical erosion flow rate requirement, the minimum flow rate requirement and the maximum rock carrying diameter processing requirement on the ground; The tubing combination scheme that meets the above requirements at the same time is determined as the optimal salt cavern gas compression energy storage and injection and production gas wellbore intelligent allocation scheme.

9. The method according to claim 8, characterized in that Determining whether the flow rate and the maximum rock carrying diameter simultaneously meet the erosion flow rate requirement, the minimum flow rate requirement, and the maximum rock carrying diameter processing requirement on the ground includes: Determining whether the flow rate satisfies both the critical erosion flow rate requirement and the minimum flow rate requirement; If the flow rate does not meet the critical erosion flow rate requirement and the minimum flow rate requirement at the same time, then input the next tubing string combination scheme into the injection and production gas flow rate calculation model of the salt cavern reservoir group injection and production tubing according to the ranking to recalculate and process until all tubing strings in the tubing string combination scheme meet the critical erosion flow rate requirement and the minimum flow rate requirement at the same time; If the flow rate satisfies both the critical erosion flow rate requirement and the minimum flow rate requirement, then it is determined whether the maximum rock carrying diameter satisfies the maximum rock carrying diameter processing requirement on the ground; If the maximum rock-carrying diameter does not meet the processing requirements of the maximum rock-carrying diameter on the ground, then the next pipe string combination scheme is input into the injection and production gas flow calculation model of the injection and production pipe string of the salt cavern reservoir group according to the ranking to recalculate and process until the maximum rock-carrying diameter in the pipe string combination scheme meets the processing requirements of the maximum rock-carrying diameter on the ground; If the maximum rock-carrying diameter meets the maximum rock-carrying diameter processing requirement on the ground, the current pipe string combination scheme is output as the optimal salt cavern gas compression energy storage injection and production gas wellbore intelligent allocation scheme.

10. The method according to claim 9, characterized in that The critical erosion flow calculation formula is as follows: Where S is the cross-sectional area of ​​the pipe, m 2 ; D is the outer diameter of the pipe, mm; t is the wall thickness of the pipe, mm; Q flow is the critical erosion flow rate, ten thousand cubic meters per hour; ρ g is the gas density, kg / m 3 ; C is the critical flow coefficient, a dimensionless quantity; a is the air pressure coefficient, a dimensionless quantity.

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