A system and method for optimizing the coordinated production of multiple oil recovery wells and water injection wells

Abstract

The present application relates to the field of intelligent oilfield technology, and specifically to a system and method for optimizing the coordinated production of multiple oil wells and water injection wells, the method comprising: respectively collecting the wellhead pressure data of each oil well and water injection well at each time, as well as the water phase flow rate and oil phase flow rate at the wellhead of the oil well at each time; recording both the oil well and the water injection well as underground wells; determining the pressure influencing factors of each underground well at each time; obtaining the flow influencing factors of each oil well at each time; obtaining the comprehensive influencing factors and interference propagation coefficients of each underground well at each time; combining the comprehensive influencing factors with the interference propagation coefficients to determine the interference factors of each underground well; dividing all underground wells in a preset area into groups based on the interference factors, and using an optimization algorithm to obtain the optimal injection and production parameters of all underground wells in each group. This improves the accuracy of determining the injection and production parameters of oil wells and water injection wells.

Description

Technical Field

[0001] The present application relates to the field of intelligent oilfield technology, and in particular to a system and method for optimizing the coordinated production of multiple oil recovery wells and water injection wells. Background Art

[0002] Water injection development is a method widely used in oil field development. By injecting water into the reservoir, the formation energy can be supplemented, the reservoir pressure can be increased, and the fluidity of crude oil can be increased. At the same time, the injected water can also drive the crude oil to the oil wells, thereby increasing the recovery rate of the reservoir. The coordinated production of oil wells and water injection wells can achieve efficient development of oil reservoirs. The injection and production parameters refer to the water injection parameters of the water injection wells and the oil production parameters of the oil production wells. By reasonably adjusting the injection and production parameters, the sweep efficiency of the injected water can be improved, and more crude oil can be driven to the oil wells, thereby increasing the recovery rate of the oil reservoir.

[0003] Usually, the reservoir area in an oil field contains multiple oil production wells and water injection wells, and the injection and production parameters need to be adjusted dynamically and in real time to improve oil production efficiency. In traditional optimization processing, the optimization algorithm is used to combine all the oil production wells and water injection wells in the reservoir area to obtain specific injection and production parameters. However, due to the complexity of the lower crust structure in the reservoir area, the influence degree and correlation between oil production wells and water injection wells are different. In traditional optimization adjustment, the distribution of influences between various oil production wells and water injection wells is ignored, resulting in large errors and slow adjustments when adjusting injection and production parameters. Summary of the invention

[0004] In order to solve the above technical problems, the purpose of this application is to provide a system and method for optimizing the coordinated production of multiple oil wells and water injection wells. The technical solutions adopted are as follows:

[0005] In a first aspect, an embodiment of the present application provides a method for optimizing the coordinated production of multiple oil recovery wells and water injection wells, the method comprising the following steps:

[0006] The wellhead pressure data of each oil production well and water injection well at each time, as well as the water phase flow rate and oil phase flow rate at each time at the wellhead of the oil production well are collected respectively; the oil production well and the water injection well are recorded as underground wells;

[0007] Analyze the discrete degree and distribution range of pressure data at all times in the local time window of each underground well at each time, and determine the pressure influencing factors of each underground well at each time; analyze the difference in oil phase flow rate of each oil production well at each time and the adjacent time, as well as the difference in the ratio of oil phase flow rate to water phase flow rate, and determine the flow influencing factors of each oil production well at each time;

[0008] Combining the pressure influencing factor with the flow influencing factor, a comprehensive influencing factor of each underground well at each time is obtained; based on the correlation between the pressure data trends of each underground well and its nearest oil production well and water injection well, as well as the distance relationship between the underground wells, the interference propagation coefficient of each underground well at each time is determined;

[0009] The interference factor of each underground well is determined by combining the comprehensive influencing factor and the interference propagation coefficient; all underground wells in a preset area are divided into groups based on the interference factor, and the optimal injection and production parameters of all underground wells in each group are obtained by using an optimization algorithm.

[0010] In one embodiment, the construction of the pressure influencing factor includes:

[0011] The pressure data at all times within the local time window of each underground well at any time are combined into a pressure sequence in time sequence;

[0012] The difference between the third quartile and the first quartile of the pressure sequence is calculated, recorded as the first difference, and the ratio of the first difference to the pressure data at any moment is calculated. The fusion normalization result of the ratio and the discrete degree at any moment is used as the pressure influencing factor of each underground well at any moment.

[0013] In one embodiment, the determination of the flow influencing factor includes:

[0014] The ratio of the oil phase flow rate to the water phase flow rate of each oil production well at each time is recorded as the oil-water ratio of each oil production well at each time, and the second difference is determined according to the difference between the oil-water ratio of each oil production well at each time and its adjacent time.

[0015] Calculate the difference between the oil phase flow rate of each oil production well at any time and at each time in its local time window, record it as the third difference, calculate the proportion of the third difference in the oil phase flow rate at any time, and obtain the sum of all the proportions in the local time window at any time;

[0016] The flow rate influencing factor of each oil production well at any time is obtained by combining the summation result and the second difference.

[0017] In one embodiment, the flow impact factor is a normalized result of the sum of the sum result and the second difference.

[0018] In one embodiment, the process of determining the comprehensive impact factor is:

[0019] The flow rate impact factor of each water injection well at each time is set to 0, and the comprehensive impact factor is the sum of the pressure impact factor and the flow rate impact factor of each underground well.

[0020] In one embodiment, determining the interference propagation coefficient includes:

[0021] Perform trend decomposition on the pressure sequence of each underground well at each time to obtain the trend sequence corresponding to the pressure sequence;

[0022] Calculate the correlation of the trend sequence of each underground well and its nearest water injection well at each time, recorded as the first correlation, calculate the correlation of the trend sequence of each underground well and its nearest oil production well at each time, recorded as the second correlation, and calculate the average metric distance between each underground well and all underground wells in the preset area;

[0023] A cumulative sum of the first correlation and the second correlation is obtained, and the interference propagation coefficient is a ratio of the cumulative sum to the average metric distance.

[0024] In one embodiment, the interference factor is the sum of a normalized value of the comprehensive impact factor and a normalized value of the interference propagation coefficient.

[0025] In one embodiment, dividing all underground wells in a preset area into groups based on the interference factor includes:

[0026] The interference factors at all times in the local time window of each underground well at each time are combined into the interference feature vector of each underground well at each time. The interference feature vector is combined with the clustering algorithm to obtain the groups divided into all underground wells in the preset area, wherein each group must include both oil production wells and water injection wells.

[0027] In one embodiment, the optimization algorithm is used to obtain the optimal injection and production parameters of all underground wells in each group, including:

[0028] The optimization algorithm is used to optimize the injection-production parameters of the oil production wells and water injection wells in each group. The optimization goal is to maximize the oil reservoir production. The optimized injection-production parameters are the production pressure difference of the oil production wells, and the injection pressure and water injection volume of the water injection wells.

[0029] In the second aspect, an embodiment of the present application also provides a collaborative production optimization system for multiple oil wells and water injection wells, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor implements the steps of any one of the above methods when executing the computer program.

[0030] This application has at least the following beneficial effects:

[0031] The present application collects the wellhead pressure data of each oil production well and water injection well at each moment, as well as the water phase flow rate and oil phase flow rate at the wellhead of the oil production well at each moment; records both the oil production well and the water injection well as underground wells; analyzes the discrete degree and distribution range of the pressure data of each underground well at all moments within the local time window of each underground well at each moment, and determines the pressure influencing factor of each underground well at each moment; the pressure influencing factor reflects the degree of fluctuation of the pressure data of each underground well, and further reflects the degree of interference of the pressure data of each underground well by other surrounding underground wells, thereby improving the accuracy of subsequent grouping of underground wells; analyzes the difference in oil phase flow rate of each oil production well at each moment and the adjacent moments, as well as the difference in the ratio of oil phase flow rate to water phase flow rate, and determines the flow influencing factor of each oil production well at each moment; the flow influencing factor reflects the degree of change of the oil phase flow rate and water phase flow rate of the oil production well over time, reflects the interference of the oil production well by other surrounding underground wells, and improves the determination of the interference degree of the oil production well reliability; further, combining the pressure influencing factor with the flow influencing factor, obtaining the comprehensive influencing factor of each underground well at each moment; determining the interference propagation coefficient of each underground well at each moment based on the correlation between the pressure data trends of each underground well and the nearest oil production well and water injection well, as well as the distance relationship between the underground wells; the interference propagation coefficient reflects the degree of correlation between the trend of pressure changes between each underground well and other surrounding underground wells, reflects the degree of interference caused by each underground well to other surrounding underground wells, and improves the accuracy of the analysis of interference impacts between underground wells; combining the comprehensive influencing factor with the interference propagation coefficient, determining the interference factor of each underground well; based on the interference factor, dividing all underground wells in the preset area into groups, and using the optimization algorithm to obtain the optimal injection and production parameters of all underground wells in each group; improving the accuracy of underground well classification, and further improving the accuracy of determining the injection and production parameters of underground wells and the timeliness of adjustment. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present application or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0033] Figure 1 A flowchart of the steps of a method for optimizing the coordinated production of multiple oil recovery wells and water injection wells provided in one embodiment of the present application;

[0034] Figure 2 Determine a flow chart for the interference factor;

[0035] Figure 3 This is a schematic diagram of the underground well grouping results. DETAILED DESCRIPTION

[0036] In order to further explain the technical means and effects adopted by the present application to achieve the predetermined invention purpose, the following is a detailed description of the specific implementation method, structure, features and effects of a multi-production oil well and water injection well coordinated production optimization system and method proposed in the present application in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0037] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0038] The specific scheme of a system and method for coordinated production optimization of multiple oil wells and water injection wells provided by the present application is described in detail below with reference to the accompanying drawings.

[0039] See also Figure 1 , which shows a flowchart of a method for optimizing the coordinated production of multiple oil wells and water injection wells provided by an embodiment of the present application, the method comprising the following steps:

[0040] S1, respectively collect the wellhead pressure data of each oil production well and water injection well at each time, as well as the water phase flow rate and oil phase flow rate at the wellhead of the oil production well at each time; the oil production well and the water injection well are both recorded as underground wells.

[0041] In this embodiment, the oil production wells and water injection wells in the oil field are analyzed, and pressure sensors are installed at the wellheads of each oil production well and water injection well to collect the wellhead pressure data of each oil production well and water injection well at each time. The range of the pressure sensor is 0-30MPa and the accuracy is ±0.1MPa. A multiphase flowmeter is installed at the wellhead of the oil production well to simultaneously measure the flow rate of the oil and water mixed phases and their respective phase fractions, and collect the water phase flow rate and oil phase flow rate at the wellhead of the oil production well at each time. The range of the multiphase flowmeter is 0-200 (Oil) and 0-100 (water), with an accuracy of ±2%. In the oil field analyzed in this embodiment, there are M oil production wells and N water injection wells. In this embodiment, M=75 and N=25. The implementer can select the oil field according to the actual situation and determine the number of oil production wells and water injection wells. No special restrictions are made here. In this embodiment, both oil production wells and water injection wells are recorded as underground wells.

[0042] For pressure sensors and multiphase flowmeters, this embodiment collects data every 30 minutes, 24 hours a day, and monitors the pressure and flow changes at the wellhead in real time. The implementer can set the collection frequency according to the actual situation, and this embodiment does not limit it. Secondly, the data collected from various underground wells are preprocessed. First, the collected data is cleaned to remove abnormal values, and then the cleaned data is mean-filled to complete the missing data. Data cleaning and mean-filling are both existing well-known technologies and will not be described in detail here.

[0043] S2, analyze the discrete degree and distribution range of pressure data at all times in the local time window of each underground well at each time, and determine the pressure influencing factors of each underground well at each time; analyze the difference in oil phase flow rate of each oil production well at each time and the adjacent time, as well as the difference in the ratio of oil phase flow rate to water phase flow rate, and determine the flow influencing factors of each oil production well at each time.

[0044] In an oil field developed by water injection, oil production wells are channels for extracting oil from underground reservoirs, and water injection wells are wells that inject water or other fluids into underground reservoirs. The purpose is to maintain reservoir pressure by injecting water. The distribution of reservoir fluids is adjusted and the recovery rate is increased through the coordinated work of oil production wells and water injection wells. In order to optimize the efficiency of coordinated production, the injection and production parameters can be adjusted through optimization algorithm control.

[0045] If the oil field is large, there will be multiple oil production wells and water injection wells, and interference will occur between different underground wells. For example, some oil production wells may have strong pressure interference with specific water injection wells. Changes in water injection pressure will quickly affect the bottom hole pressure of these oil production wells, thereby affecting their production indicators such as production and water content. Other underground wells may also show fluid interference, and the flow direction and speed of injected water play a key role in the change of oil-water ratio in oil production wells.

[0046] For oil production wells, oil production wells may be disturbed by water injection wells. Water injection from water injection wells will increase the formation pressure, which may lead to an increase in the bottom hole pressure of the oil production well, change the production pressure difference of the oil production well, and affect the production of the oil production well. Oil production wells may also be disturbed by other oil production wells. When the surrounding oil production wells increase the production pressure difference for production, the formation pressure will drop, thereby affecting the bottom hole pressure of adjacent oil production wells, reducing their production pressure difference and reducing production.

[0047] Similarly, for water injection wells, water injection wells may be interfered with by oil production wells. When oil production wells are producing, the formation pressure will be reduced, which may affect the injection pressure of water injection wells. If the output of oil production wells is large, the formation pressure will drop significantly, which may reduce the injection pressure of water injection wells and affect the water injection effect. Water injection wells may also be interfered with by other water injection wells. When multiple water injection wells are injecting water at the same time, high-pressure areas may be formed in the formation, causing pressure interference between water injection wells. If the distance between water injection wells is close, the pressure interference may be more obvious. In addition, different injection pressures and injection volumes of different water injection wells may also lead to uneven pressure distribution in the formation.

[0048] Therefore, when each underground well is disturbed, the pressure will change significantly. The pressure change of the underground well can be used as a disturbance feature. This embodiment constructs a local time window at each moment, specifically taking each moment as the last moment in its local time window, and taking 8 hours forward as the local time window at each moment. The length of the local time window can be set by the implementer according to the actual situation, and this embodiment does not limit it. The pressure data of all moments in the local time window of each underground well at each moment are organized into a pressure sequence of each underground well at each moment in time sequence. Based on the pressure sequence of each underground well at each moment, the pressure influence factor of each underground well at each moment is calculated, specifically:

[0049] For each underground well at any moment, the difference between the third quartile and the first quartile of the corresponding pressure sequence is calculated, recorded as the first difference, and the ratio of the first difference to the pressure data at any moment is calculated, recorded as the first ratio, and the fusion normalization result of the first ratio and the discreteness of the pressure sequence at any moment is used as the pressure influencing factor of each underground well at any moment.

[0050] It should be noted that the difference can be calculated by the absolute value of the difference, the square of the difference, the ratio, etc., and this embodiment uses the absolute value of the difference as the calculation method of the difference; the degree of dispersion can be calculated by the variance, the standard deviation, the coefficient of variation, etc., and this embodiment uses the standard deviation as the calculation method of the degree of dispersion; fusion means combining multiple variables, which can be calculated by multiplication, addition, mixed addition and multiplication, etc.

[0051] In this embodiment, the specific calculation method of the pressure influence factor can be:

[0052] ; In the formula, is the pressure influencing factor of any underground well at time t, norm() represents the normalization function, represents the standard deviation of all pressure data in the pressure sequence of any underground well at time t, represents the third quartile of the pressure series of any underground well at time t, represents the first quartile of the pressure series of any underground well at time t, is the pressure data of any underground well at time t. Recorded as the first difference, Recorded as the first ratio.

[0053] In the local time window, the smaller the standard deviation of the pressure data, the smaller the fluctuation of the pressure data, that is, the pressure of the underground well is relatively stable and less disturbed. On the contrary, it means that the disturbance is greater. Secondly, the larger the first difference, the larger the range of pressure data variation, which also means that the underground well is more disturbed. The first ratio reflects the difference between the range of pressure data variation and the pressure data at time t. The larger the first ratio, the greater the fluctuation of pressure data and the greater the pressure influence factor obtained.

[0054] The smaller the pressure influence factor of any underground well at time t, the less interference the underground well is subject to from other underground wells, that is, the probability of the surrounding underground wells changing the injection-production parameters is small, or the injection-production parameters are changed synchronously and a balance is reached, then the underground well and its surrounding underground wells are more suitable to be grouped together; on the contrary, the greater the interference the underground well is subject to from other wells, it may be that there are water injection wells around the underground well that have adjusted the water injection parameters or oil production wells that have changed the oil production pressure, at this time the underground well is less suitable to be grouped together with the surrounding underground wells.

[0055] When an underground well is disturbed, not only the pressure will change, but also the flow rate. The flow rate change of a water injection well is similar to the pressure change. However, the oil produced by an oil production well contains water. When an oil production well is disturbed, even if the overall flow rate remains unchanged, the water phase flow rate may increase and the oil phase flow rate may decrease. Therefore, the flow rate change of each oil production well at each time can be used to calculate the flow rate impact factor of each oil production well at each time to characterize the magnitude of the disturbance to the oil production well. In this embodiment, the specific calculation method of the flow rate impact factor is:

[0056] ; In the formula, is the flow influencing factor of any oil well at time t, norm() represents the normalization function, represents the oil phase flow rate of any oil production well at time t, represents the water phase flow rate of any oil production well at time t, represents the oil-water ratio of any oil production well at time t, represents the absolute value of the difference between the oil-water ratio of any oil production well at time t and the oil-water ratio at time t-1, represents the oil phase flow rate of any oil production well at the i-th moment in the local time window at time t, represents the number of times contained in the local time window of any oil production well at time t. Recorded as the second difference, Recorded as the third difference.

[0057] It should be understood that the greater the difference between the oil-water ratio of the oil production well at each moment and the adjacent moments, the greater the possibility of changes in the water phase flow and the oil phase flow before and after the moment, which further reflects the greater possibility of interference with the oil production well. It may be that the increase in water injection volume of the nearby water injection well leads to an increase in the water phase flow in the current oil production well, or it may be that the pressure increase of the nearby oil production well leads to an increase in the oil phase flow in the current oil production well. The greater the difference between the oil phase flow of the oil production well at each moment and the oil phase flow at other moments in its local time window, the greater the range of change of the oil phase flow, that is, the greater the interference with the oil production well.

[0058] The smaller the calculated flow impact factor, the less interference the corresponding oil well is subject to, and the more suitable it is to be grouped together with the surrounding underground wells; if the calculated flow impact factor is larger, the greater the interference the corresponding oil well is subject to, and the less suitable it is to be grouped together with the surrounding underground wells.

[0059] S3, combining the pressure influencing factor and the flow influencing factor to obtain the comprehensive influencing factor of each underground well at each time; based on the correlation between the pressure data trends of each underground well and its nearest oil production well and water injection well, as well as the distance relationship between the underground wells, determine the interference propagation coefficient of each underground well at each time.

[0060] In this embodiment, for each water injection well, its flow rate impact factor is set to 0; thus, the comprehensive impact factor of each underground well at each time is calculated by combining the pressure impact factor and the flow rate impact factor of each underground well, which represents the degree of interference of each underground well by other surrounding underground wells. The specific calculation method is:

[0061] ; In the formula, represents the comprehensive impact factor of underground wells at time t, represents the pressure influencing factor of each underground well at time t, Represents the flow influencing factor of each underground well at time t.

[0062] It should be understood that by grouping underground wells using comprehensive influencing factors as interference characteristics, underground wells with relatively close injection and production parameter adjustment times can be grouped together so that the interference conditions between them are similar and the injection and production parameter adjustment range is smaller.

[0063] During the oil field production process, when an underground well is interfered with by other underground wells, due to the interaction of interference, the interfered underground well will also interfere with other underground wells, and the interference generated will gradually weaken with the increase of distance. Therefore, this embodiment compares the pressure change trend of the underground well and other underground wells, and calculates the interference propagation coefficient of each underground well at each time in combination with the distance factor to characterize the interference caused by the underground well to other underground wells.

[0064] Specifically, the pressure sequence of each underground well at each time is decomposed by using the STL (Seasonal-Trend Decomposition using LOESS) trend decomposition algorithm to obtain the trend sequence corresponding to the pressure sequence; the correlation between the trend sequence of each underground well and its nearest water injection well at each time is calculated, recorded as the first correlation, the correlation between the trend sequence of each underground well and its nearest oil production well at each time is calculated, recorded as the second correlation, and the average metric distance between each underground well and all underground wells in the preset area is calculated;

[0065] A cumulative sum of the first correlation and the second correlation is obtained, and the interference propagation coefficient is a ratio of the cumulative sum to the average metric distance.

[0066] It should be noted that the calculation of correlation can be specifically performed by Pearson correlation coefficient, cosine similarity, etc. This embodiment uses Pearson correlation coefficient as the calculation method of correlation; the preset area is the oil field area analyzed in this embodiment, and the distance is measured in this embodiment using Euclidean distance. The implementer can choose other distance measurement methods. The STL trend decomposition algorithm is an existing well-known technology. The implementer can choose other existing feasible trend decomposition algorithms at will, and this embodiment does not limit it here.

[0067] In this embodiment, the specific calculation method of the interference propagation coefficient of each underground well at each time is:

[0068] ; In the formula, is the interference propagation coefficient of each underground well at time t, is the trend sequence of the pressure sequence of each underground well at time t, is the trend sequence of the pressure sequence of the oil well closest to each underground well at time t, is the trend sequence of the pressure sequence of the water injection well closest to each underground well at time t, r() represents the function for calculating the Pearson correlation coefficient, represents the average Euclidean distance between each underground well and all underground wells in the oil field. Denoted as the second correlation, It is recorded as the first correlation.

[0069] If the trend sequence correlation between two underground wells is higher, it means that the pressure change trends of the two underground wells are highly synchronized, that is, when the pressure of one underground well shows an upward or downward trend, the other underground well will often show a similar trend change, indicating that there is a greater possibility of interference transmission from one underground well to another underground well. The greater the distance between the underground well and other underground wells, the smaller the interference transmission.

[0070] The larger the interference propagation coefficient of an underground well is, the stronger the interference of the underground well on other underground wells is, and the less suitable the underground well is to be grouped together with the surrounding underground wells. This is because when the injection and production parameters of the underground wells in the same group are subsequently optimized, the parameter changes of the underground well are likely to affect other nearby underground wells, making it difficult to achieve a balance. On the contrary, the weaker the interference of the underground well on other underground wells is, the more suitable it is to be grouped together with the nearby underground wells.

[0071] S4, combining the comprehensive influencing factor and the interference propagation coefficient to determine the interference factor of each underground well; based on the interference factor, all underground wells in the preset area are divided into groups, and an optimization algorithm is used to obtain the optimal injection and production parameters of all underground wells in each group.

[0072] When the underground wells are grouped, this embodiment combines the comprehensive impact factor and the interference propagation coefficient to obtain an interference factor, which represents the interference feature of each underground well. The wells can be grouped according to the interference feature. The interference factor of each underground well at each time is calculated as follows:

[0073] ; In the formula, is the interference factor of each underground well at time t, represents the comprehensive impact factor of underground wells at time t, is the interference propagation coefficient of each underground well at time t, and norm() represents the normalization function. The flow chart for determining the interference factor is as follows: Figure 2 shown.

[0074] The interference factors of all moments in the local time window of each underground well at each moment are arranged in time sequence as the interference feature vector of each underground well at each moment. For each moment, this embodiment uses the fuzzy C-means algorithm (FCM) to cluster the interference feature vectors of all underground wells in the oil field. In this embodiment, the number of clusters C is set to 5, the fuzzification index m is set to 1.5, and the stop threshold is Set to 0.01. The fuzzy C-means algorithm is a well-known technology, and the implementer can choose other feasible clustering algorithms at will, which is not limited in this embodiment.

[0075] Based on the clustering results, all underground wells in the oil field are divided into groups, and each group must contain oil production wells and water injection wells. The schematic diagram of the underground well grouping results is shown in the figure below. Figure 3 As shown, Figure 3 The horizontal axis is the length of the oil field, and the vertical axis is the width of the oil field, the unit is m. Figure 3 The middle square is a water injection well, and the circle is an oil production well. Different colors represent different groups. The blue circle represents the first type of oil production well, the white circle represents the second type of oil production well, the red circle represents the third type of oil production well, the black circle represents the fourth type of oil production well, and the green circle represents the fifth type of oil production well. The blue square represents the first type of water injection well, the white square represents the second type of water injection well, the red square represents the third type of water injection well, the black square represents the fourth type of water injection well, and the green square represents the fifth type of water injection well.

[0076] Finally, the injection and production parameters of the oil production wells and water injection wells in each group are optimized respectively. Taking one group as an example, a genetic algorithm is used, and the optimization goal is to maximize the oil reservoir production. The injection and production parameters that need to be optimized are the production pressure difference of the oil production well and the injection pressure and water injection volume of the water injection well. When using the genetic algorithm, the injection and production parameters are encoded as chromosomes using real number coding, and the initial population is randomly generated. The population size is 180, and the roulette wheel is used for selection operation. The single point crossover is used for crossover operation, and the crossover coefficient is 0.78. The random mutation is used for mutation operation, and the coefficient of variation is 0.08. The maximum number of iterations is set to 100 times. After iteration, the optimal injection and production parameters of each underground well in the group at each time will be obtained. The genetic optimization algorithm is an existing well-known technology and will not be described in detail here. It should be noted that the analysis data in this embodiment is collected every 30 minutes. Therefore, the injection and production parameters of each underground well are also adjusted every 30 minutes. The implementer can set the time interval for adjusting the injection and production parameters according to the actual situation. This embodiment is not limited here.

[0077] Based on the same inventive concept as the above method, an embodiment of the present application also provides a system for collaborative production optimization of multiple oil wells and water injection wells, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of any one of the above-mentioned methods for collaborative production optimization of multiple oil wells and water injection wells.

[0078] It should be noted that the above sequence of the embodiments of the present application is for description only and does not represent the advantages and disadvantages of the embodiments. The above is a description of a specific embodiment of this specification. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0079] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

[0080] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the principles of the present application should be included in the protection scope of the present application.

Claims

1. A method for optimizing the coordinated production of multiple oil wells and water injection wells, characterized in that: The method comprises the following steps: The wellhead pressure data of each oil production well and water injection well at each time, as well as the water phase flow rate and oil phase flow rate at each time at the wellhead of the oil production well are collected respectively; the oil production well and the water injection well are recorded as underground wells; Analyze the discrete degree and distribution range of pressure data at all times in the local time window of each underground well at each time, and determine the pressure influencing factors of each underground well at each time; analyze the difference in oil phase flow rate of each oil production well at each time and the adjacent time, as well as the difference in the ratio of oil phase flow rate to water phase flow rate, and determine the flow influencing factors of each oil production well at each time; Combining the pressure influencing factor with the flow influencing factor, a comprehensive influencing factor of each underground well at each time is obtained; based on the correlation between the pressure data trends of each underground well and its nearest oil production well and water injection well, as well as the distance relationship between the underground wells, the interference propagation coefficient of each underground well at each time is determined; Combining the comprehensive influencing factor with the interference propagation coefficient, determining the interference factor of each underground well; dividing all underground wells in a preset area into groups based on the interference factor, and using an optimization algorithm to obtain the optimal injection and production parameters of all underground wells in each group; The method of dividing all underground wells in a preset area into groups based on the interference factor includes: The interference factors at all times in the local time window of each underground well at each time are combined into the interference feature vector of each underground well at each time. The interference feature vector is combined with the clustering algorithm to obtain the groups divided into all underground wells in the preset area, wherein each group must include both oil production wells and water injection wells.

2. A method for optimizing the coordinated production of multiple oil recovery wells and water injection wells as claimed in claim 1, characterized in that: The construction of the pressure influencing factor includes: The pressure data at all times within the local time window of each underground well at any time are combined into a pressure sequence in time sequence; The difference between the third quartile and the first quartile of the pressure sequence is calculated, recorded as the first difference, and the ratio of the first difference to the pressure data at any moment is calculated. The fusion normalization result of the ratio and the discrete degree at any moment is used as the pressure influencing factor of each underground well at any moment.

3. The method for optimizing the coordinated production of multiple oil recovery wells and water injection wells according to claim 1, characterized in that: The determination of the flow influencing factor includes: The ratio of the oil phase flow rate to the water phase flow rate of each oil production well at each time is recorded as the oil-water ratio of each oil production well at each time, and the second difference is determined according to the difference between the oil-water ratio of each oil production well at each time and its adjacent time. Calculate the difference between the oil phase flow rate of each oil production well at any time and at each time in its local time window, record it as the third difference, calculate the proportion of the third difference in the oil phase flow rate at any time, and obtain the sum of all the proportions in the local time window at any time; The flow rate influencing factor of each oil production well at any time is obtained by combining the summation result and the second difference.

4. A method for optimizing the coordinated production of multiple oil recovery wells and water injection wells as claimed in claim 3, characterized in that: The flow impact factor is a normalized result of the sum of the sum result and the second difference.

5. The method for optimizing the coordinated production of multiple oil recovery wells and water injection wells according to claim 1, characterized in that: The determination process of the comprehensive impact factor is as follows: The flow rate impact factor of each water injection well at each time is set to 0, and the comprehensive impact factor is the sum of the pressure impact factor and the flow rate impact factor of each underground well.

6. A method for optimizing the coordinated production of multiple oil recovery wells and water injection wells as claimed in claim 2, characterized in that: The determination of the interference propagation coefficient includes: Perform trend decomposition on the pressure sequence of each underground well at each time to obtain the trend sequence corresponding to the pressure sequence; Calculate the correlation of the trend sequence of each underground well and its nearest water injection well at each time, recorded as the first correlation, calculate the correlation of the trend sequence of each underground well and its nearest oil production well at each time, recorded as the second correlation, and calculate the average metric distance between each underground well and all underground wells in the preset area; A cumulative sum of the first correlation and the second correlation is obtained, and the interference propagation coefficient is a ratio of the cumulative sum to the average metric distance.

7. The method for optimizing the coordinated production of multiple oil recovery wells and water injection wells according to claim 1, characterized in that: The interference factor is the sum of the normalized value of the comprehensive impact factor and the normalized value of the interference propagation coefficient.

8. The method for optimizing the coordinated production of multiple oil recovery wells and water injection wells according to claim 1, characterized in that: The optimization algorithm is used to obtain the optimal injection and production parameters of all underground wells in each group, including: The optimization algorithm is used to optimize the injection-production parameters of the oil production wells and water injection wells in each group. The optimization goal is to maximize the oil reservoir production. The optimized injection-production parameters are the production pressure difference of the oil production wells, and the injection pressure and water injection volume of the water injection wells.

9. A system for optimizing the coordinated production of multiple oil wells and water injection wells, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 8 are implemented.

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