Downhole flow pressure control method, device, system and electronic equipment for drainage gas recovery of tight sandstone gas reservoir

Abstract

The present application relates to a kind of gas well bottom hole flowing pressure control technical fields, is a kind of well bottom hole flowing pressure control method, device, system and electronic equipment for tight sandstone gas reservoir drainage gas production, including obtaining the relevant data of target well, and input to optimal well bottom hole flowing pressure calculation model, obtain corresponding optimal well bottom hole flowing pressure, and obtain corresponding best drainage gas production execution device operating parameter, according to the first time interval continuously receiving actual well bottom hole flowing pressure, according to the comparison result of actual well bottom hole flowing pressure and optimal well bottom hole flowing pressure dynamically adjusts best drainage gas production execution device operating parameter, generates and sends adjustment instruction to drainage gas production execution device.The present application is combined with artificial intelligence, can quickly adapt to the change of gas well production situation, dynamically adjusts best drainage gas production execution device operating parameter, controls well bottom hole flowing pressure in optimal range, improves the drainage gas production intelligent control degree of well bottom hole flowing pressure, reduces artificial dependence, reduces human operation error.

Description

Technical Field

[0001] This invention relates to the field of bottom-hole flowing pressure control technology for gas wells, and to a method, device, system, and electronic equipment for bottom-hole flowing pressure control in tight sandstone gas reservoirs for drainage and gas production. Background Technology

[0002] Tight gas is an important unconventional natural gas resource and has become a new highlight in the global unconventional oil and gas development. However, due to the poor reservoir properties of tight sandstone gas reservoirs, characterized by low porosity, low permeability, strong heterogeneity, and complex gas-water relationships, development is difficult. During production, bottom-hole fluid accumulation is prone to occur, leading to increased bottom-hole flowing pressure, decreased production, and in severe cases, even production shutdown. Therefore, drainage and gas production play a crucial role in the development of tight sandstone gas reservoirs. Effective drainage and gas production measures can remove formation water, reduce bottom-hole flowing pressure, and ensure continuous and stable gas well production. Thus, reasonable control of bottom-hole flowing pressure is essential for fully utilizing the natural energy of the formation, improving gas well recovery rates, and obtaining optimal economic benefits.

[0003] Existing technologies for bottomhole flowing pressure control in tight sandstone gas reservoirs have significant shortcomings. They largely rely on manual experience and lack automation, resulting in imprecise control, slow response times, and an inability to dynamically optimize and adjust based on actual well production. These problems not only affect the well's stable production capacity and ultimate recovery rate but also increase extraction costs and reduce overall economic efficiency. Furthermore, existing intelligent bottomhole flowing pressure control methods (details below) are not suitable for adjusting bottomhole flowing pressure in tight sandstone gas reservoirs through drainage production processes, and there are no methods for ensuring stable and increased production during drainage production.

[0004] Existing methods for controlling bottom hole flowing pressure are as follows: Existing patent document CN110924935B discloses a method, apparatus, and equipment for determining bottom-hole flowing pressure control schemes in tight oil reservoirs. It establishes a numerical simulation model of target well production to simulate underground oil and water flow, and further establishes a bottom-hole flowing pressure optimization mathematical model. With the goal of maximizing cumulative oil production, it uses a multi-level splitting strategy and an optimization algorithm to solve the bottom-hole flowing pressure optimization mathematical model. Based on the solution results, it determines the bottom-hole flowing pressure control scheme for the target well. This method mainly addresses the determination of reasonable bottom-hole flowing pressure under depletion-type development methods in tight oil reservoirs. It does not discuss the adaptability to tight sandstone gas reservoirs and lacks a bottom-hole flowing pressure control method to ensure stable and increased production during drainage and gas production.

[0005] Existing patent document CN110397425B discloses a bottom-hole flowing pressure control system and method for coalbed methane production wells. The method involves obtaining the current production stage of the coalbed methane production well; setting a reference value for the bottom-hole flowing pressure based on the production system of each stage; obtaining the actual value of the bottom-hole flowing pressure; and generating a first command and / or a second command based on the actual value and the reference value. The first command controls the exhaust control valve to perform an exhaust operation, and the second command controls the injection control valve to perform an injection operation. The first command includes the opening value of the exhaust control valve, and the second command includes the opening value of the injection control valve. However, this method has low integration with the methods used in tight sandstone gas reservoirs for adjusting bottom-hole flowing pressure through drainage and gas production processes. Summary of the Invention

[0006] This invention provides a method that overcomes the shortcomings of the prior art. It can effectively solve the problems of existing tight sandstone gas reservoir bottom-hole flowing pressure control methods, which rely heavily on manual experience, lack automation and intelligent transformation, have inaccurate control, and slow response speed.

[0007] One of the technical solutions of this invention is achieved through the following measures: a bottom-hole flowing pressure control method for drainage gas production in tight sandstone gas reservoirs, comprising: The relevant data of the target well is obtained and input into the optimal bottom hole flow pressure calculation model to obtain the corresponding optimal bottom hole flow pressure. Based on the optimal bottom hole flow pressure and the basic data of the drainage and gas production execution device, the corresponding optimal drainage and gas production execution device operating parameters are obtained and sent. The relevant data includes geological data, production data and operation data. The optimal bottom hole flow pressure calculation model is obtained through machine learning from several samples. Each of the several samples includes historical well geological data, production data and operation data, as well as a label identifying the optimal bottom hole flow pressure. The actual bottom-hole flowing pressure is continuously received according to the first time interval, and the actual bottom-hole flowing pressure is compared with the optimal bottom-hole flowing pressure. Based on the comparison result, the operating parameters of the optimal drainage and gas production execution device are dynamically adjusted, and adjustment instructions are generated and sent to the drainage and gas production execution device.

[0008] The following are further optimizations and / or improvements to the above-mentioned technical solution: The above also includes continuously receiving actual production data, actual gas production, actual water production, and actual operation data according to the second time interval; generating and sending alarm signals when the actual production data and actual operation data are abnormal; and returning to step S210 to update the relevant data of the target well and redetermine the optimal bottom hole flowing pressure when either the actual gas production or the actual water production changes.

[0009] The construction process of the above-mentioned optimal bottom hole flowing pressure calculation model includes: A number of samples were obtained and divided into training and testing sets. Each sample included geological data, production data, and operation data of historical wells, as well as a label indicating the optimal bottom hole flowing pressure. The algorithm structure network is trained using a training set. A loss function is introduced during training. Training ends when the value of the loss function is stable, resulting in the optimal bottom hole pressure calculation model. The algorithm structure network includes a data input layer, a feature extraction layer, a model training layer, and a decision output layer. The data input layer takes samples as input, the feature extraction layer extracts key features from the samples, the model training layer sets the selected algorithm and trains it using the key features, and the decision output layer outputs the optimal bottom hole pressure corresponding to the sample. The optimal bottom hole flowing pressure calculation model after training is tested using a test set. The model parameters of the optimal bottom hole flowing pressure calculation model are optimized, and the optimal bottom hole flowing pressure calculation model that meets the test evaluation requirements is output.

[0010] The above compares the actual bottom-hole flowing pressure with the optimal bottom-hole flowing pressure, and dynamically adjusts the operating parameters of the optimal drainage and gas production actuator based on the comparison results, including: Compare the actual bottom hole flowing pressure with the optimal bottom hole flowing pressure; If the actual bottom-hole pressure is greater than the optimal bottom-hole pressure, the operating parameters of the drainage and gas production actuator need to be adjusted to reduce the actual bottom-hole pressure. If the actual bottom-hole pressure is less than the optimal bottom-hole pressure, the operating parameters of the drainage and gas production actuator need to be adjusted to increase the actual bottom-hole pressure.

[0011] The second technical solution of the present invention is achieved through the following measures: a bottom-hole flowing pressure control device for drainage and gas production in tight sandstone gas reservoirs, comprising: The optimal bottom-hole flowing pressure calculation unit acquires relevant data of the target well and inputs it into the optimal bottom-hole flowing pressure calculation model to obtain the corresponding optimal bottom-hole flowing pressure. Based on the optimal bottom-hole flowing pressure and the basic data of the drainage and gas production execution device, it obtains and sends the corresponding optimal drainage and gas production execution device operating parameters. The relevant data includes geological data, production data, and operation data. The optimal bottom-hole flowing pressure calculation model is obtained through machine learning from several samples. Each of the several samples includes historical well geological data, production data, and operation data, as well as a label identifying the optimal bottom-hole flowing pressure. The bottom-hole flow pressure control unit continuously receives the actual bottom-hole flow pressure according to the first time interval, compares the actual bottom-hole flow pressure with the optimal bottom-hole flow pressure, dynamically adjusts the operating parameters of the optimal drainage and gas production execution device based on the comparison result, and generates and sends adjustment commands to the drainage and gas production execution device.

[0012] The following are further optimizations and / or improvements to the above-mentioned technical solution: The above also includes a bottom-hole flowing pressure control unit, which continuously receives actual production data, actual gas production, actual water production, and actual operating data according to the second time interval. When the actual production data and actual operating data are abnormal, an alarm signal is generated and sent. When either the actual gas production or the actual water production changes, the relevant data of the target well is updated and the optimal bottom-hole flowing pressure is re-determined.

[0013] The third technical solution of the present invention is achieved through the following measures: a bottom-hole flowing pressure control system for drainage and gas production in tight sandstone gas reservoirs, comprising a monitoring and acquisition device, a drainage and gas production execution device, a communication device, and a bottom-hole flowing pressure control device for drainage and gas production in tight sandstone gas reservoirs. The monitoring and data acquisition device is used to collect relevant actual data, including bottom hole flowing pressure, actual production data, actual gas production, actual water production, and actual operation data. The drainage and gas production actuator is used to execute the optimal drainage and gas production actuator operating parameters and adjustment instructions issued by the bottom hole flowing pressure control device for drainage and gas production in tight sandstone gas reservoirs; Bottom-hole flowing pressure control device for drainage and gas production in tight sandstone gas reservoirs is used to implement bottom-hole flowing pressure control methods for drainage and gas production in tight sandstone gas reservoirs. The communication device establishes a data transmission link between the monitoring and acquisition device and the drainage and gas production execution device and the bottom hole flowing pressure control device used for drainage and gas production in tight sandstone gas reservoirs.

[0014] The following are further optimizations and / or improvements to the above-mentioned technical solution: The above also includes a remote control device that communicates with the communication device to obtain all data from the front end and send control commands to the front end.

[0015] The aforementioned drainage and gas extraction actuator includes an intelligent control electric valve, an intelligent dosing device, an intelligent booster gas lift device, an intelligent negative pressure device, and an intelligent plunger; Intelligent control electric valves regulate valve opening to adjust bottom hole pressure. The intelligent dosing device has multiple compartments that store various chemicals and inject them into the target well as needed and in the required amount. Intelligent booster gas lift equipment compresses and pressurizes gas to produce gas and reinjects it into the target well; Intelligent negative pressure device is used to reduce wellhead pressure and increase production pressure differential; The intelligent plunger controls its own flow path to move up and down in the well to discharge liquid and produce gas based on the requirements of flow pressure and gas production.

[0016] The fourth technical solution of the present invention is achieved through the following measures: an electronic device, characterized in that it includes a processor and a memory, wherein the memory stores a computer program, which is loaded and executed by the processor to implement the steps in the bottom hole flowing pressure control method for drainage gas production in tight sandstone gas reservoirs.

[0017] This invention uses an artificial intelligence-based learning model to calculate the optimal bottom-hole flowing pressure of a target well, and obtains corresponding optimal drainage and gas production control measures. Based on the implementation of these optimal measures by the drainage and gas production actuator, the actual bottom-hole flowing pressure is continuously acquired. Based on the relationship between the actual and optimal bottom-hole flowing pressure, the optimal drainage and gas production control measures are dynamically adjusted, thereby controlling the bottom-hole flowing pressure within the optimal range. This ensures the gas well is in optimal production condition, maximizing gas well production and ultimate recovery rate. Furthermore, the integration of this invention with artificial intelligence allows for rapid adaptation to changes in gas well production conditions, enabling dynamic adjustment and optimized control. This improves the automation level of bottom-hole flowing pressure calculation, reduces reliance on manual labor, minimizes human error, enhances production efficiency and safety, and lowers production costs. Attached Figure Description

[0018] Appendix Figure 1 This is a schematic diagram of a bottom hole flowing pressure control method provided in one embodiment of the present invention.

[0019] Appendix Figure 2 This is a schematic diagram of another bottom hole flowing pressure control method provided in an embodiment of the present invention.

[0020] Appendix Figure 3 This is a schematic diagram of a bottom hole flowing pressure control device provided in one embodiment of the present invention.

[0021] Appendix Figure 4 This is a schematic diagram of another wellbore pressure control device provided in an embodiment of the present invention.

[0022] Appendix Figure 5 This is a schematic diagram of a bottom hole flowing pressure control system provided in one embodiment of the present invention.

[0023] Appendix Figure 6 This is a schematic diagram of another bottom hole flowing pressure control system provided in an embodiment of the present invention.

[0024] Appendix Figure 7 This is a schematic diagram of an implementation structure of a bottom hole flowing pressure control system provided in one embodiment of the present invention.

[0025] Appendix Figure 8 This is a schematic diagram of an intelligent dosing device according to an embodiment of the present invention.

[0026] Appendix Figure 9This is a schematic diagram of a PID control system provided in one embodiment of the present invention.

[0027] The codes in the attached diagram are as follows: 201 is the remote control device, 202 is the intelligent dosing device, 203 is the intelligent plunger, 204 is the gas production tree, 205 is the bottom hole sensor, 206 is the intelligent booster gas lift device, 207 is the intelligent control electric valve, 208 is the gas-liquid separator, 209 is the intelligent negative pressure device, and 210 is the bottom hole flowing pressure control device for drainage and gas production in tight sandstone gas reservoirs. Detailed Implementation

[0028] The present invention is not limited to the following embodiments, and the specific implementation can be determined according to the technical solution of the present invention and the actual situation.

[0029] Those skilled in the art will understand that, unless specifically stated otherwise, in the embodiments of the present invention, a "module" or "unit" refers to a computer program or part of a computer program that has a predetermined function and works together with other related parts to achieve a predetermined goal, and can be implemented wholly or partially using software, hardware (such as processing circuitry or memory), or a combination thereof. Similarly, a processor (or multiple processors or memory) can be used to implement one or more modules or units. Furthermore, each module or unit can be part of an overall module or unit that includes the functionality of that module or unit.

[0030] In addition, in the embodiments of the present invention, "multiple" refers to two or more, and "first" and "second" are used to distinguish descriptions and should not be construed as implying relative importance.

[0031] This invention provides a bottom-hole flowing pressure control method, apparatus, system, and electronic device for drainage and gas production in tight sandstone gas reservoirs. The bottom-hole flowing pressure control device for drainage and gas production in tight sandstone gas reservoirs can be integrated into a computer device, which can be a server, a terminal, or other similar device; it can also be executed jointly by a terminal and a server. These examples should not be construed as limiting the invention.

[0032] The aforementioned terminals may include mobile phones, wearable smart devices, tablet computers, laptops, personal computers (PCs), and in-vehicle computers, etc., and this invention does not limit them. This invention also does not limit the number of terminal devices.

[0033] The aforementioned server can be an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms. This invention does not limit these features.

[0034] For example, the computer equipment acquires relevant data of the target well and inputs it into the optimal bottom-hole flowing pressure calculation model to obtain the corresponding optimal bottom-hole flowing pressure. Based on the optimal bottom-hole flowing pressure and the basic data of the drainage and gas production execution device, the corresponding optimal drainage and gas production execution device operating parameters are obtained and sent. The actual bottom-hole flowing pressure is continuously received according to the first time interval, and the actual bottom-hole flowing pressure is compared with the optimal bottom-hole flowing pressure. Based on the comparison results, the optimal drainage and gas production execution device operating parameters are dynamically adjusted, and adjustment instructions are generated and sent to the drainage and gas production execution device.

[0035] The method provided in this embodiment of the invention may involve artificial intelligence (AI) technology and may be implemented based on artificial intelligence technology, such as using deep learning to train a corresponding model using samples.

[0036] Machine Learning (ML) is a multidisciplinary field involving probability theory, statistics, approximation theory, convex analysis, and algorithm complexity theory, among others. It specifically studies how computers can simulate or implement human learning behavior to acquire new knowledge or skills and reorganize existing knowledge structures to continuously improve their performance. Machine learning is the core of artificial intelligence and the fundamental way to endow computers with intelligence; its applications span all areas of artificial intelligence.

[0037] Deep learning (DL) specifically refers to machine learning based on deep neural network models and methods. It has developed based on statistical machine learning, artificial neural network, and other algorithmic models, combined with the development of modern big data and high computing power. The most important technical feature of deep learning is its ability to automatically extract features.

[0038] The aforementioned machine learning and deep learning typically include techniques such as neural networks, belief networks, reinforcement learning, transfer learning, inductive learning, and instructional learning.

[0039] In deep learning, the loss function is used to predict the target value by comparing the predicted value with the target value. This is done by updating the weight vector of each layer of the neural network based on the difference between the two values ​​(usually with an initialization process before the first update, where parameters are pre-configured for each layer) until the network can predict the target value or a value very close to it. Therefore, deep learning requires pre-defining "how to compare the difference between the predicted value and the target value," which is the loss function.

[0040] Based on this, the technical solution of the present invention will be described and explained below with reference to several examples.

[0041] Example 1: As shown in the attached document Figure 1 As shown, this invention discloses a bottomhole flowing pressure control method for drainage gas production in tight sandstone gas reservoirs, comprising: Step S110: Obtain relevant data of the target well and input it into the optimal bottom hole flowing pressure calculation model to obtain the corresponding optimal bottom hole flowing pressure. Based on the optimal bottom hole flowing pressure and the basic data of the drainage and gas production execution device, obtain and send the corresponding optimal drainage and gas production execution device operating parameters. The relevant data includes geological data, production data and operation data. The optimal bottom hole flowing pressure calculation model is obtained through machine learning from several samples. Each of the several samples includes geological data, production data and operation data of historical wells and a label identifying the optimal bottom hole flowing pressure.

[0042] In this embodiment, a database can be used to store relevant data about the target well.

[0043] In this embodiment, the geological data of the target well may include, but is not limited to, at least one of the following: reservoir physical property parameters, rock mechanical parameters, formation pressure parameters, fluid property parameters, and reservoir geometric parameters.

[0044] In this embodiment, the production data of the target well may include, but is not limited to, at least one of the following: gas production data, liquid production data, pressure data, temperature data, flow rate data, water-to-gas ratio data, water cut data, production time data, foaming agent dosage data, drainage and gas production measure record data, well structure data, gas testing data, two-phase metering data, and gas testing data. The pressure data includes bottom hole flowing pressure, bottom hole static pressure, wellhead oil pressure, and wellhead casing pressure.

[0045] In this embodiment, the operational data of the target well may include, but is not limited to, at least one of the following: pressure data, temperature data, flow rate data, liquid level data, valve opening data, power parameter data, reagent parameter data, equipment status data, environmental parameter data, and vibration data.

[0046] In this embodiment, since there are many types of drainage and gas production actuators and different structures of different types of drainage and gas production actuators, it is necessary to obtain the basic data of the drainage and gas production actuators, obtain the corresponding operating parameters of the drainage and gas production actuators based on the basic data of the drainage and gas production actuators, and then obtain the optimal operating parameters of the drainage and gas production actuators for the optimal bottom hole pressure. It should be noted that there are many ways to obtain the optimal operating parameters of the drainage and gas production actuators for the optimal bottom hole pressure, such as referring to formulas, empirical mapping tables, machine learning, etc.

[0047] The basic data of the drainage gas extraction actuator may include, but is not limited to, the structure of the drainage gas extraction actuator and its fixed parameters.

[0048] The experience mapping table is set according to different working conditions and different types of drainage and gas production actuators. Therefore, there can be several experience mapping tables, and the specific embodiments of the present invention are not limited. The machine learning method is to set corresponding models according to different working conditions. The optimal bottom hole pressure can be used as input and the operating parameters of the drainage and gas production actuator can be used as output for training, so that under various working conditions, the appropriate operating parameters of the drainage and gas production actuator can be obtained based on the optimal bottom hole pressure.

[0049] Step S120: Continuously receive the actual bottom hole flow pressure according to the first time interval, compare the actual bottom hole flow pressure with the optimal bottom hole flow pressure, dynamically adjust the operating parameters of the optimal drainage and gas production execution device according to the comparison result, and generate and send the adjustment command to the drainage and gas production execution device.

[0050] In this embodiment, step S120 involves continuously receiving the actual bottom-hole flowing pressure according to the first time interval. For each received actual bottom-hole flowing pressure, it is compared with the optimal bottom-hole flowing pressure. Based on the comparison result, the operating parameters of the optimal drainage and gas production execution device are dynamically adjusted, and an adjustment command is generated and sent to the drainage and gas production execution device. This dynamically controls the bottom-hole flowing pressure to ensure that it is always kept within the optimal range, thereby ensuring that the target well is in the best production state. It should be noted that if the actual bottom-hole flowing pressure is equal to the optimal bottom-hole flowing pressure, no action is taken.

[0051] Specifically, the first time interval can be set according to the time when the drainage and gas extraction actuator executes the corresponding operating parameters of the drainage and gas extraction actuator, and must be greater than this time.

[0052] Specifically, if the actual bottom-hole flowing pressure is greater than the optimal bottom-hole flowing pressure, the operating parameters of the drainage and gas production actuator need to be adjusted to reduce the actual bottom-hole flowing pressure. If the actual bottom-hole flowing pressure is less than the optimal bottom-hole flowing pressure, the operating parameters of the drainage and gas production actuator need to be adjusted to increase the actual bottom-hole flowing pressure. The specific adjustment methods for the operating parameters of the drainage and gas production actuator may include, but are not limited to, directly adjusting according to a set single-time adjustment method, or calculating the difference between the actual bottom-hole flowing pressure and the optimal bottom-hole flowing pressure based on an empirical comparison table of the difference and adjustment methods under different operating conditions, and determining the adjustment method for the operating parameters of the drainage and gas production actuator based on the empirical comparison table.

[0053] This invention discloses a bottom-hole flowing pressure control method for drainage and gas production in tight sandstone gas reservoirs. Based on an optimal bottom-hole flowing pressure calculation model obtained through artificial intelligence learning, the optimal bottom-hole flowing pressure of the target well is calculated, and corresponding optimal drainage and gas production control measures are obtained. While the drainage and gas production execution device implements the optimal drainage and gas production control measures, the actual bottom-hole flowing pressure is continuously acquired. Based on the relationship between the actual bottom-hole flowing pressure and the optimal bottom-hole flowing pressure, the optimal drainage and gas production control measures are dynamically adjusted, thereby controlling the bottom-hole flowing pressure within the optimal range. This ensures that the gas well is in its optimal production state, maximizing gas well production and ultimate recovery rate. Furthermore, this invention, combined with artificial intelligence, can quickly adapt to changes in gas well production conditions, achieving dynamic adjustment and optimized control. This improves the automation level of bottom-hole flowing pressure control, reduces reliance on manual labor, minimizes human error, improves production efficiency and safety, and reduces production costs.

[0054] Example 2: As shown in the attached document Figure 2 As shown, this invention discloses a bottomhole flowing pressure control method for drainage gas production in tight sandstone gas reservoirs, comprising: Step S210: Obtain relevant data of the target well and input it into the optimal bottom hole flowing pressure calculation model to obtain the corresponding optimal bottom hole flowing pressure. Based on the optimal bottom hole flowing pressure and the basic data of the drainage and gas production execution device, obtain and send the corresponding optimal drainage and gas production execution device operating parameters. The relevant data includes geological data, production data and operation data. The optimal bottom hole flowing pressure calculation model is obtained through machine learning from several samples. Each of the several samples includes geological data, production data and operation data of historical wells and a label identifying the optimal bottom hole flowing pressure.

[0055] Step S220: Continuously receive the actual bottom hole pressure according to the first time interval, compare the actual bottom hole pressure with the optimal bottom hole pressure, dynamically adjust the operating parameters of the optimal drainage and gas production execution device according to the comparison result, and generate and send the adjustment command to the drainage and gas production execution device.

[0056] Step S230: Continuously receive actual production data, actual gas production, actual water production, and actual operation data according to the second time interval. When the actual production data and actual operation data are abnormal, generate and send an alarm signal. When either the actual gas production or the actual water production changes, return to step S210 to update the relevant data of the target well and redetermine the optimal bottom hole flowing pressure.

[0057] In this embodiment, the second time interval is set as needed. The actual production data includes wellhead pressure, bottom hole temperature, natural gas flow rate, water flow rate, and bottom hole liquid level. Wellhead pressure provides information on the current wellhead pressure status; bottom hole and wellhead temperatures reveal the physical properties of the gas; natural gas and water flow rates indicate the target well's production capacity and water output; and bottom hole liquid level data reveals the bottom hole liquid status. Furthermore, each received data point can be analyzed and displayed using big data analytics.

[0058] In this embodiment, the actual operating data refers to the actual operating data of each device and equipment. In this embodiment, thresholds are set for various actual production data and actual operating data. Corresponding fault diagnosis is performed based on the thresholds. When the threshold is exceeded, the abnormality is determined, and an alarm signal is generated and sent.

[0059] In this embodiment, the actual gas production and actual water production are measured based on the received actual production data, which is existing technology and will not be described in detail here. Any change in the actual gas production and actual water production means that the gas production and water production corresponding to the previous optimal bottom hole pressure are inconsistent or outside its defined range. Then, return to step S210 to update the relevant data of the target well and redetermine the optimal bottom hole pressure. Updating the relevant data of the target well here means updating the original gas production and water production to the current actual gas production and actual water production.

[0060] Example 3: This is a further optimization of the above examples, wherein the construction process of the optimal bottom hole flowing pressure calculation model includes: Step S310: Obtain several samples and divide them into training set and test set, where each sample includes geological data, production data and operation data of historical wells, as well as a label indicating the optimal bottom hole flowing pressure.

[0061] In this embodiment, the geological data of historical wells may include, but are not limited to, at least one of the following: reservoir physical property parameters, rock mechanical parameters, formation pressure parameters, fluid property parameters, and reservoir geometric parameters.

[0062] In this embodiment, the production data of historical wells may include, but is not limited to, at least one of the following: gas production data, liquid production data, pressure data, temperature data, flow rate data, water-to-gas ratio data, water cut data, production time data, foaming agent dosage data, drainage and gas production measure record data, well structure data, gas testing data, two-phase metering data, and gas testing data. Among these, the pressure data includes bottom hole flowing pressure, bottom hole static pressure, wellhead oil pressure, and wellhead casing pressure.

[0063] In this embodiment, the historical well operation data may include, but is not limited to, at least one of the following: pressure data, temperature data, flow rate data, liquid level data, valve opening data, power parameter data, reagent parameter data, equipment status data, environmental parameter data, and vibration data.

[0064] In this embodiment, after obtaining several samples, they can be preprocessed to facilitate subsequent training. The preprocessing includes cleaning, noise reduction, screening, and normalization.

[0065] Furthermore, the samples mentioned above can be selected from historical wells in the same area as the target well, or the geological data, production data, operation data, and optimal bottom hole flowing pressure of historical wells in the same area as the target well can all be stored in a database, and the samples can be selected from this database according to the set sample size during training.

[0066] Step S320: Train the set algorithm structure network using the training set. Introduce a loss function during training. When the value of the loss function is stable, end the training to obtain the optimal bottom hole pressure calculation model. The algorithm structure network includes a data input layer, a feature extraction layer, a model training layer, and a decision output layer. The data input layer inputs samples, the feature extraction layer extracts key features from the samples, the model training layer sets the selected algorithm and trains it using the key features, and the decision output layer outputs the optimal bottom hole pressure corresponding to the sample.

[0067] In this embodiment, the feature extraction layer may use, but is not limited to, algorithms such as principal component analysis, independent component analysis, and convolutional neural networks to extract features that are highly correlated with the optimal bottom hole flowing pressure from the geological data, production data, and operation data of historical wells, and the selection may be made according to the requirements.

[0068] In this embodiment, the algorithm in the model training layer may be, but is not limited to, neural networks, support vector machines, deep learning, decision trees, genetic algorithms, particle swarm optimization algorithms, simulated annealing algorithms, ant colony optimization algorithms, tabu search algorithms, mayfly optimization algorithms, etc., and may be selected as needed.

[0069] Step S330: Test the trained optimal bottom hole pressure calculation model using the test set, optimize the model parameters of the optimal bottom hole pressure calculation model, and output the optimal bottom hole pressure calculation model that meets the test evaluation requirements.

[0070] In this embodiment, the test evaluation can be performed using, but is not limited to, mean squared error.

[0071] Furthermore, this embodiment uses a training set and a sample set to train the model, and can also introduce cross-validation for training to prevent overfitting. Cross-validation can be, but is not limited to, leave-one-out cross-validation.

[0072] Furthermore, the present invention can continuously update the samples and retrain the optimal bottom hole flowing pressure calculation model to improve the model's adaptability and the accuracy of the optimal bottom hole flowing pressure calculation.

[0073] Example 4: As shown in the appendix Figure 3 As shown, this embodiment of the invention discloses a bottom-hole flowing pressure control device for drainage and gas production in tight sandstone gas reservoirs, comprising: The optimal bottom-hole flowing pressure calculation unit acquires relevant data from the target well and inputs it into the optimal bottom-hole flowing pressure calculation model to obtain the corresponding optimal bottom-hole flowing pressure. Based on the optimal bottom-hole flowing pressure and the basic data of the drainage and gas production execution device, it obtains and sends the corresponding optimal drainage and gas production execution device operating parameters. The relevant data includes geological data, production data, and operational data. The optimal bottom-hole flowing pressure calculation model is obtained through machine learning from several samples. Each of the several samples includes historical well geological data, production data, and operational data, as well as a label identifying the optimal bottom-hole flowing pressure.

[0074] The bottom-hole flow pressure control unit continuously receives the actual bottom-hole flow pressure according to the first time interval, compares the actual bottom-hole flow pressure with the optimal bottom-hole flow pressure, dynamically adjusts the operating parameters of the optimal drainage and gas production execution device based on the comparison result, and generates and sends adjustment commands to the drainage and gas production execution device.

[0075] The specific implementation steps of the above unit are the same as those in Example 1, and will not be repeated here.

[0076] Example 5: As shown in the attached document Figure 4 As shown, this embodiment of the invention discloses a bottom-hole flowing pressure control device for drainage and gas production in tight sandstone gas reservoirs, comprising: The optimal bottom-hole flowing pressure calculation unit acquires relevant data from the target well and inputs it into the optimal bottom-hole flowing pressure calculation model to obtain the corresponding optimal bottom-hole flowing pressure. Based on the optimal bottom-hole flowing pressure and the basic data of the drainage and gas production execution device, it obtains and sends the corresponding optimal drainage and gas production execution device operating parameters. The relevant data includes geological data, production data, and operational data. The optimal bottom-hole flowing pressure calculation model is obtained through machine learning from several samples. Each of the several samples includes historical well geological data, production data, and operational data, as well as a label identifying the optimal bottom-hole flowing pressure.

[0077] The bottom-hole flow pressure control unit continuously receives the actual bottom-hole flow pressure according to the first time interval, compares the actual bottom-hole flow pressure with the optimal bottom-hole flow pressure, dynamically adjusts the operating parameters of the optimal drainage and gas production execution device based on the comparison result, and generates and sends adjustment commands to the drainage and gas production execution device.

[0078] The monitoring unit continuously receives actual production data, actual gas production, actual water production, and actual operation data according to the second time interval. When the actual production data and actual operation data are abnormal, an alarm signal is generated and sent. When either the actual gas production or the actual water production changes, the relevant data of the target well is updated and the optimal bottom hole flowing pressure is re-determined.

[0079] The specific implementation steps of the above unit are the same as those in Example 2, and will not be repeated here.

[0080] Example 6: As shown in the appendix Figure 5 As shown, this embodiment of the invention discloses a bottom-hole flowing pressure control system for drainage and gas production in tight sandstone gas reservoirs, including a monitoring and acquisition device, a drainage and gas production execution device, a communication device, and a bottom-hole flowing pressure control device 210 for drainage and gas production in tight sandstone gas reservoirs as described in Examples 4 and 5. The monitoring and acquisition device is used to collect relevant data, including bottom hole flowing pressure, actual production data, actual gas production, actual water production, and actual operation data.

[0081] In this embodiment, the monitoring and acquisition device includes various sensors such as pressure, temperature, flow rate, and liquid level, which can be installed at the bottom of the target well, the wellhead, or at instrument equipment.

[0082] The drainage and gas production actuator is used to execute the optimal drainage and gas production actuator operating parameters and adjustment instructions issued by the bottom hole flowing pressure control device 210 for drainage and gas production in tight sandstone gas reservoirs.

[0083] The bottom-hole flowing pressure control device 210 for drainage and gas production in tight sandstone gas reservoirs is used to execute the bottom-hole flowing pressure control method for drainage and gas production in tight sandstone gas reservoirs as described in Examples 1 and 2.

[0084] A communication device establishes a data transmission link between the monitoring and acquisition device, the drainage and gas production execution device, and the bottom-hole flowing pressure control device 210 used for drainage and gas production in tight sandstone gas reservoirs. The communication device can support both wired and wireless communication methods, including satellite communication, 4G / 5G mobile communication, and the Internet, ensuring the stability and timeliness of data transmission and guaranteeing the overall efficiency and reliability of the system's data transmission. The specific type is determined based on the transmission distance and range.

[0085] Example 7: As attached Figure 6As shown, this embodiment of the invention discloses a bottom-hole flowing pressure control system for drainage and gas production in tight sandstone gas reservoirs, including a monitoring and acquisition device, a drainage and gas production execution device, a communication device, a remote control device 201, and a bottom-hole flowing pressure control device 210 for drainage and gas production in tight sandstone gas reservoirs as described in embodiments 4 and 5. The monitoring and acquisition device is used to collect relevant data, including bottom hole flowing pressure, actual production data, actual gas production, actual water production, and actual operation data.

[0086] The drainage and gas production actuator is used to execute the optimal drainage and gas production actuator operating parameters and adjustment instructions issued by the bottom hole flowing pressure control device 210 for drainage and gas production in tight sandstone gas reservoirs.

[0087] The communication device establishes a data transmission link between the monitoring and acquisition device, the drainage and gas production execution device, the remote control device 201, and the bottom hole flow pressure control device 210 used for drainage and gas production in tight sandstone gas reservoirs.

[0088] The remote control device 201 communicates with the communication device to obtain all data from the front end and sends control commands to the front end.

[0089] In this embodiment, in order to cooperate with the remote control device 201, the communication device needs to meet the requirements of long-distance transmission. Furthermore, to ensure the security of remote communication, the communication device can adopt data encryption technology to prevent data from being stolen or tampered with, and can convert different communication protocols to achieve compatibility with different devices.

[0090] In this embodiment, the remote control device 201 can be a computer, mobile phone, central control room, etc. The remote control device 201 can acquire all data from the front end through a communication device, including sensor data, equipment operating status, control command execution status, etc., and provides an intuitive and user-friendly remote monitoring interface, allowing operators to conveniently view the production status and equipment operation of the target well in real time. When an abnormal situation is detected in the target well, it can promptly issue alarms and warnings to remind operators to take appropriate measures. Furthermore, it allows remote configuration and adjustment of front-end parameters, enabling remote management of field equipment, including equipment start-up, shutdown, reset, and other operations.

[0091] It should also be noted that the specific type of drainage and gas production actuator is selected according to needs. The drainage and gas production actuator may include, but is not limited to, the following: intelligent control electric valve 207, intelligent chemical dosing device 202, intelligent booster gas lift device 206, intelligent negative pressure device 209, and intelligent plunger 203. The intelligent control electric valve 207 can precisely control the valve opening to regulate the bottom hole flowing pressure; the intelligent chemical dosing device 202 has multiple compartments to store agents such as foaming agents, unblocking agents, water-locking agents, and antifreeze agents, and injects them into the target well as needed and in the required quantities; the intelligent booster gas lift device 206 produces gas by compressing and boosting it and reinjecting it into the target well, increasing the flow rate and fluid carrying capacity, and reducing the bottom hole flowing pressure; the intelligent negative pressure device 209 reduces the wellhead pressure, increasing its production pressure differential and releasing the target well's production capacity; the intelligent plunger 203 controls its own flow path to move up and down within the well according to the requirements of flowing pressure and gas production to drain fluid and produce gas.

[0092] Based on the structure of the drainage and gas production execution device, the operating parameters of the drainage and gas production execution device may include, but are not limited to, at least one of the following: intelligent control electric valve 207 opening degree control, intelligent dosing device 202 reagent selection and dosing volume control, intelligent booster gas lift device 206 compressor booster control, intelligent negative pressure device 209 wellhead pressure reduction control, and intelligent plunger 203 operating system.

[0093] The corresponding adjustment instructions in this invention may include adjusting the operating parameters of the drainage and gas extraction actuator, such as increasing or decreasing the amount of reagent added by the intelligent dosing device 202, adjusting the opening degree of the intelligent control electric valve 207, and optimizing the operating system of the intelligent plunger 203.

[0094] Furthermore, multiple drainage and gas production actuators can be deployed in multiple rows as needed. The optimal single drainage and gas production actuator is activated based on the production stage of the target well, the current geological conditions, and the production conditions. If a single drainage and gas production actuator cannot achieve the optimal bottom hole pressure, two or more drainage and gas production actuators are activated to work together until the bottom hole pressure reaches the optimal level.

[0095] One specific configuration method of this embodiment is as follows: Figure 7 As shown, it includes a remote control device 201, an intelligent dosing device 202, an intelligent plunger 203, a gas production tree 204, a bottom hole sensor 205, an intelligent booster gas lift device 206, an intelligent regulating electric valve 207, a gas-liquid separator 208, an intelligent negative pressure device 209, and a bottom hole flowing pressure control device 210210 for drainage and gas production in tight sandstone gas reservoirs.

[0096] The specifics are as follows: The intelligent dosing device 202 is used to add chemical agents to the target well. It can automatically adjust the amount and timing of the agent addition based on parameters such as bottom hole pressure.

[0097] The intelligent dosing device 202 can precisely control the amount of foaming agent added. The foaming agent enables the bottom-hole fluid and gas to form a stable foam, reducing the density of the liquid and making it easier for the gas flow to carry it out of the well. When the bottom-hole flowing pressure is high, increasing the amount of foaming agent injected can enhance foam formation, improve fluid carrying capacity, thereby reducing the height of the bottom-hole fluid and thus reducing the bottom-hole flowing pressure.

[0098] In particular, in addition to foaming agents, the intelligent dosing device 202 can also add various agents such as unblocking agents, corrosion inhibitors, defreezing agents, corrosion inhibitors, and scale inhibitors as needed.

[0099] The temperature sensor detects an increase in bottom hole temperature, which may affect the performance of the agent. The intelligent dosing device 202 will adjust the injection volume or type of foaming agent according to this change to ensure that it can still effectively adjust the bottom hole flowing pressure under the new temperature conditions.

[0100] When the target well experiences low-temperature freezing and blockage, the intelligent dosing device 202 will add defreezing agents such as methanol.

[0101] The intelligent dosing device 202 can automatically adjust the dosing strategy according to the actual situation. If the effect of the agent is not good or an abnormal situation occurs, the system will automatically switch to the backup agent or adjust the dosing plan.

[0102] Specifically, as shown in the appendix Figure 8 As shown, the intelligent dosing device 202 is equipped with multiple dosing tanks and mixing tanks, which can store various agents. Depending on the specific situation, the proportion of agent components can be adjusted through the mixing tank to change the agent performance to meet specific needs. The mixing tank can also be used as a single agent channel without mixing. Multiple wells can be injected simultaneously through the control of the distributor. It is equipped with an intelligent on / off valve, which can realize the coordinated injection of multiple agents and multiple target wells according to actual needs.

[0103] The intelligent plunger 203 is a special intermittent drainage gas production device. It uses the reciprocating motion of the plunger within the wellbore to discharge accumulated liquid from the bottom of the well. The intelligent plunger 203 controls its own flow path within the well based on requirements such as flow pressure and gas production rate, and can automatically adjust its operating speed and frequency as needed.

[0104] When it is necessary to reduce the bottom hole pressure, the intelligent plunger 203 increases its operating speed and frequency to increase fluid discharge. When the bottom hole pressure approaches or reaches the optimal value, the intelligent plunger 203 decreases its operating speed and frequency to reduce fluid discharge.

[0105] If the intelligent plunger 203 fails to drain properly or malfunctions, the system will automatically adjust its operating parameters or take other measures.

[0106] If the intelligent plunger 203 encounters increased resistance during operation, and this is due to foreign objects in the wellbore or changes in the properties of the accumulated fluid, the system will automatically increase the power output of the intelligent plunger 203 or adjust its stroke to overcome the resistance and continue discharging the fluid.

[0107] The gas production tree 204 is a control device at the wellhead of the target well, used to control the production and safety of the target well. Various valves and instruments are installed on the gas production tree 204. The gas production tree can be connected to other equipment to realize intelligent control of the target well.

[0108] Bottom-hole sensor 205 is used to monitor parameters at the bottom of the well in real time, including but not limited to flowing pressure, temperature and flow rate, and transmit these data to bottom-hole flowing pressure control device 210 for drainage and gas production in tight sandstone gas reservoirs.

[0109] Specifically, the bottom-hole sensor 205 can simultaneously monitor multiple key parameters, including but not limited to bottom-hole flowing pressure, temperature, flow rate, and liquid level. These parameters are crucial for assessing the production status of the target well, optimizing drainage and gas production strategies, and ensuring safe and efficient production.

[0110] In particular, in the harsh environment at the bottom of the well, the bottom sensor 205 needs to have high reliability and stability, be able to withstand harsh conditions such as high temperature, high pressure, and corrosion, and have a long service life and a low failure rate.

[0111] The intelligent booster gas lift device 206 utilizes gas pressure to discharge liquid accumulated at the bottom of the well into the wellbore. It produces gas through compression and boosting and reinjects it into the target well, increasing flow velocity and fluid carrying capacity while reducing bottom-hole flowing pressure. Simultaneously, when the bottom-hole flowing pressure is below the optimal value, it can be increased by injecting high-pressure compressed gas.

[0112] When the bottomhole flowing pressure is higher than the optimal value, gas is produced by compression and pressurization and reinjected into the target well. This increases the pressure and flow rate of the injected gas, improves the lifting capacity, and removes the accumulated fluid from the wellbore, thereby reducing the bottomhole flowing pressure. When the bottomhole flowing pressure is lower than the optimal value, high-pressure compressed gas is injected without circulating the fluid to suppress the pressure and increase the bottomhole flowing pressure.

[0113] Specifically, the gas source for the intelligent booster gas lift device 206 can be the produced gas from this well. After passing through a gas-liquid separator, the liquid is discharged back downstream, and the gas is delivered to the intelligent booster gas lift device 206 for pressurization by a compressor. A certain amount of gas is stored in a storage tank for later use. When the gas source is insufficient, a gas source from a neighboring well can be used.

[0114] The intelligent booster air lift device 206 can precisely adjust the pressure of the injected gas.

[0115] The intelligent control electric valve 207 is a device used to control fluid flow and pressure. In the drainage and gas production system, the intelligent control electric valve 207 can automatically adjust the valve opening according to parameters such as bottom hole pressure and gas production to control the flow of natural gas and water, and achieve precise control of bottom hole pressure.

[0116] The intelligent control electric valve 207 receives control commands and can make precise adjustments based on real-time changes in bottom hole pressure. If the actual bottom hole pressure is higher than the optimal value, the intelligent control electric valve 207 will gradually increase the opening to accelerate the discharge speed of fluid, thereby reducing the bottom hole pressure. Conversely, if the actual bottom hole pressure is lower than the optimal value, the intelligent control electric valve 207 will decrease the opening to reduce the outflow of fluid, causing the bottom hole pressure to rise, so as to ensure that it is always kept within the optimal range.

[0117] The intelligent control electric valve 207 opening control system can be a PID control system, i.e., a proportional-integral-derivative control system. Based on the difference between the optimal bottom-hole flowing pressure value and the measured bottom-hole flowing pressure value, it comprehensively considers proportional, integral, and derivative actions to obtain timely and effective execution commands for the intelligent control electric valve 207, thereby achieving stable control of the bottom-hole flowing pressure. For example, see attached... Figure 9 This is a schematic diagram of a PID control system provided in an embodiment of the present invention. The opening value of the intelligent regulating electric valve 207 under PID control can be determined by three parts: proportional action, integral action, and derivative action. Proportional control can quickly respond to changes in bottom hole flowing pressure, integral control can eliminate long-term deviations, and derivative control can predict the trend of bottom hole flowing pressure changes. The combination of the three can ensure the accuracy, timeliness, and stability of the control system.

[0118] Specifically, the opening value of the intelligent control electric valve can be calculated using the following formula, based on the actual bottom-hole flowing pressure value and the optimal bottom-hole flowing pressure value: Where u represents the control valve opening value; e represents the control error; K represents the proportional coefficient; Ti represents the integral time; Td represents the derivative time; Psp represents the optimal bottom hole flowing pressure value; and P represents the actual bottom hole flowing pressure value.

[0119] The gas-liquid separator 208 is used to separate natural gas and water extracted from the target well. It can separate the gas-liquid mixture into natural gas and water by gravity separation, centrifugal separation and other methods according to the differences in physical properties of gas and liquid.

[0120] The intelligent negative pressure device 209 reduces the wellhead pressure, thereby reducing the bottom hole flowing pressure, increasing the production pressure differential, and releasing the target well's production capacity.

[0121] When the bottom hole pressure is high, the intelligent negative pressure device 209 increases its power to enhance the negative pressure effect, thereby increasing the upward force of the fluid at the bottom hole and reducing the bottom hole pressure. When the bottom hole pressure approaches or reaches the ideal range, the negative pressure intensity is appropriately reduced to avoid excessive suction that could damage the formation or cause other adverse effects.

[0122] Example 8: This embodiment of the invention discloses a storage medium storing a computer program that can be read by a computer. The computer program is configured to execute a bottom hole flowing pressure control method for drainage and gas production in tight sandstone gas reservoirs when it is run.

[0123] The aforementioned storage media may include, but are not limited to, USB flash drives, read-only memory, portable hard drives, magnetic disks, optical disks, and other media capable of storing computer programs.

[0124] Example 9: This embodiment of the invention discloses an electronic device, including a processor and a memory, wherein the memory stores a computer program, which is loaded and executed by the processor to implement a bottom hole flowing pressure control method for drainage gas production in tight sandstone gas reservoirs.

[0125] The processor described above can be a central processing unit (CPU), a general-purpose processor, a digital signal processor (DSP), an ASIC, an FPGA, or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this invention. It can also be a combination that implements computational functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc. The memory can include, but is not limited to, various media capable of storing computer programs, such as USB flash drives, read-only memory, portable hard drives, magnetic disks, or optical disks.

[0126] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. The solutions in the embodiments of the present invention can be implemented using various computer languages, such as the object-oriented programming language Java and the interpreted scripting language JavaScript.

[0127] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0128] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0129] The above content is only a specific embodiment of the present invention, which has strong adaptability and implementation effect. However, the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be covered within the protection scope of the present invention. Therefore, equivalent changes made in accordance with the claims of the present invention are still within the scope of the present invention.

Claims

1. A bottomhole flowing pressure control method for drainage gas production in tight sandstone gas reservoirs, characterized in that, include: The relevant data of the target well is obtained and input into the optimal bottom hole flow pressure calculation model to obtain the corresponding optimal bottom hole flow pressure. Based on the optimal bottom hole flow pressure and the basic data of the drainage and gas production execution device, the corresponding optimal drainage and gas production execution device operating parameters are obtained and sent. The relevant data includes geological data, production data and operation data. The optimal bottom hole flow pressure calculation model is obtained through machine learning from several samples. Each of the several samples includes historical well geological data, production data and operation data, as well as a label identifying the optimal bottom hole flow pressure. The actual bottom-hole flowing pressure is continuously received according to the first time interval, and the actual bottom-hole flowing pressure is compared with the optimal bottom-hole flowing pressure. Based on the comparison result, the operating parameters of the optimal drainage and gas production execution device are dynamically adjusted, and adjustment instructions are generated and sent to the drainage and gas production execution device.

2. The bottom hole flowing pressure control method for drainage and gas production in tight sandstone gas reservoirs according to claim 1, characterized in that, It also includes continuously receiving actual production data, actual gas production, actual water production, and actual operation data according to the second time interval; generating and sending alarm signals when the actual production data and actual operation data are abnormal; and returning to step S210 to update the relevant data of the target well and redetermine the optimal bottom hole flowing pressure when either the actual gas production or the actual water production changes.

3. The bottom hole flowing pressure control method for drainage gas production in tight sandstone gas reservoirs according to claim 1 or 2, characterized in that, The process of constructing the optimal bottom-hole flowing pressure calculation model includes: A number of samples were obtained and divided into training and testing sets. Each sample included geological data, production data, and operation data of historical wells, as well as a label indicating the optimal bottom hole flowing pressure. The algorithm structure network is trained using a training set. A loss function is introduced during training. Training ends when the value of the loss function is stable, resulting in the optimal bottom hole pressure calculation model. The algorithm structure network includes a data input layer, a feature extraction layer, a model training layer, and a decision output layer. The data input layer takes samples as input, the feature extraction layer extracts key features from the samples, the model training layer sets the selected algorithm and trains it using the key features, and the decision output layer outputs the optimal bottom hole pressure corresponding to the sample. The optimal bottom hole flowing pressure calculation model after training is tested using a test set. The model parameters of the optimal bottom hole flowing pressure calculation model are optimized, and the optimal bottom hole flowing pressure calculation model that meets the test evaluation requirements is output.

4. The bottom hole flowing pressure control method for drainage gas production in tight sandstone gas reservoirs according to claim 1 or 2, characterized in that, The actual bottom-hole flowing pressure is compared with the optimal bottom-hole flowing pressure, and the operating parameters of the optimal drainage and gas production actuator are dynamically adjusted based on the comparison results, including: Compare the actual bottom hole flowing pressure with the optimal bottom hole flowing pressure; If the actual bottom-hole pressure is greater than the optimal bottom-hole pressure, the operating parameters of the drainage and gas production actuator need to be adjusted to reduce the actual bottom-hole pressure. If the actual bottom-hole pressure is less than the optimal bottom-hole pressure, the operating parameters of the drainage and gas production actuator need to be adjusted to increase the actual bottom-hole pressure.

5. A bottom-hole flowing pressure control device for drainage and gas production in tight sandstone gas reservoirs, employing the method described in any one of claims 1 to 4, characterized in that, include: The optimal bottom-hole flowing pressure calculation unit acquires relevant data of the target well and inputs it into the optimal bottom-hole flowing pressure calculation model to obtain the corresponding optimal bottom-hole flowing pressure. Based on the optimal bottom-hole flowing pressure and the basic data of the drainage and gas production execution device, it obtains and sends the corresponding optimal drainage and gas production execution device operating parameters. The relevant data includes geological data, production data, and operation data. The optimal bottom-hole flowing pressure calculation model is obtained through machine learning from several samples. Each of the several samples includes historical well geological data, production data, and operation data, as well as a label identifying the optimal bottom-hole flowing pressure. The bottom-hole flow pressure control unit continuously receives the actual bottom-hole flow pressure according to the first time interval, compares the actual bottom-hole flow pressure with the optimal bottom-hole flow pressure, dynamically adjusts the operating parameters of the optimal drainage and gas production execution device based on the comparison result, and generates and sends adjustment commands to the drainage and gas production execution device.

6. The bottom hole flowing pressure control device for drainage and gas production in tight sandstone gas reservoirs according to claim 5, characterized in that, It also includes a bottom-hole flowing pressure control unit, which continuously receives actual production data, actual gas production, actual water production, and actual equipment operation data according to the second time interval. When the actual production data and actual equipment operation data are abnormal, an alarm signal is generated and sent. When either the actual gas production or the actual water production changes, the system returns to update the relevant database of the target well and redetermines the optimal bottom-hole flowing pressure.

7. A bottomhole flowing pressure control system for drainage and gas production in tight sandstone gas reservoirs, characterized in that, It includes a monitoring and acquisition device, a drainage and gas production execution device, a communication device, and a bottom hole flowing pressure control device for drainage and gas production in tight sandstone gas reservoirs as described in claim 5 or 6. The monitoring and data acquisition device is used to collect relevant actual data, including bottom hole flowing pressure, actual production data, actual gas production, actual water production, and actual operation data. The drainage and gas production actuator is used to execute the optimal drainage and gas production actuator operating parameters and adjustment instructions issued by the bottom hole flowing pressure control device for drainage and gas production in tight sandstone gas reservoirs; Bottom-hole flowing pressure control device for drainage and gas production in tight sandstone gas reservoirs, used to execute the bottom-hole flowing pressure control method for drainage and gas production in tight sandstone gas reservoirs as described in any one of claims 1 to 4. The communication device establishes a data transmission link between the monitoring and acquisition device and the drainage and gas production execution device and the bottom hole flowing pressure control device used for drainage and gas production in tight sandstone gas reservoirs.

8. The bottom-hole flowing pressure control system for drainage and gas production in tight sandstone gas reservoirs according to claim 7, characterized in that, It also includes a remote control device that communicates with the communication device to obtain all data from the front end and send control commands to the front end.

9. The bottom-hole flowing pressure control system for drainage and gas production in tight sandstone gas reservoirs according to claim 7 or 8, characterized in that, The drainage and gas extraction actuator includes an intelligent control electric valve, an intelligent dosing device, an intelligent booster gas lift device, an intelligent negative pressure device, and an intelligent plunger; Intelligent control electric valves regulate valve opening to adjust bottom hole pressure. The intelligent dosing device has multiple compartments that store various chemicals and inject them into the target well as needed and in the required amount. Intelligent booster gas lift equipment compresses and pressurizes gas to produce gas and reinjects it into the target well; Intelligent negative pressure device is used to reduce wellhead pressure and increase production pressure differential; The intelligent plunger controls its own flow path to move up and down in the well to discharge liquid and produce gas based on the requirements of flow pressure and gas production.

10. An electronic device, characterized in that, It includes a processor and a memory, the memory storing a computer program, which is loaded and executed by the processor to implement the steps in the bottom hole flowing pressure control method for drainage gas production in tight sandstone gas reservoirs as described in any one of claims 1 to 4.

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