Method for improving development efficiency of thin and poor oil layer by different well and asynchronous injection-production

Abstract

The application relates to the technical field of intelligent control, in particular to a method for improving injection-production development efficiency of thin and poor oil layers in different wells, which comprises the following steps: collecting the bottom hole flowing pressure data of each injection well and each production well in real time during the injection-production development of the thin and poor oil layers; setting an injection pressure adjustment period of the injection well, decomposing the difference between the bottom hole flowing pressure data of each injection well and each adjacent production well in each period in time sequence, obtaining a high-frequency disturbance coefficient of each decomposition layer, obtaining an injection-production high-frequency disturbance degree between each injection well and each adjacent production well in each period, and then obtaining a disturbance accumulation degree of each injection well in each period; obtaining a disturbance severity of each injection well in each period; and controlling the injection pressure of each injection well in the next period. The application aims to control and adjust the injection pressure during the injection-production development, so as to improve the injection-production development efficiency of the thin and poor oil reservoirs.

Description

Technical Field

[0001] This application relates to the field of intelligent control technology, specifically to a method for improving the efficiency of asynchronous injection and production development in thin-layer oil reservoirs. Background Technology

[0002] Daqing Oilfield has entered a high water-cut stage. The development time for the main high-permeability oil layers is relatively long, and the production decline trend is obvious. To ensure the high and stable production momentum of Daqing Oilfield, the focus of waterflooding development has gradually shifted from medium-to-high permeability oil layers to thin-permeability oil layers. However, due to the complex geological conditions of these thin-permeability oil layers, their development is more difficult, reducing their development efficiency. With the continuous advancement of oil and gas field development technology, hundreds of millions of tons of proven reserves exist in low-permeability thin-permeability oil layers. Therefore, it is necessary to tap the potential of these thin-permeability oil layer reserves and further improve the development efficiency of asynchronous injection and production in different wells within these layers, thereby improving the water injection development efficiency of thin-permeability oil reservoirs.

[0003] However, in the process of developing thin-diameter reservoirs using asynchronous injection and production in separate wells, the problem of insufficient injection can easily occur. Current technologies generally control and regulate the injection pressure during the development process to ensure the stability of the injection-production pressure differential and improve the water injection development efficiency of thin-diameter reservoirs. However, because the injection-production pressure differential is affected by the interaction of permeability, porosity, and water saturation, and current technologies do not accurately measure the disturbance of these factors, it is impossible to accurately control and regulate the injection pressure during the development process, thus affecting the water injection development efficiency of thin-diameter reservoirs. Summary of the Invention

[0004] In view of the above, it is necessary to provide a method to improve the efficiency of asynchronous injection and production development in thin-differential oil reservoirs. Compared with traditional methods to improve the efficiency of injection and production development in thin-differential oil reservoirs, this method improves the efficiency of injection and production development in thin-differential oil reservoirs by controlling and adjusting the water injection pressure during the injection and production development process.

[0005] The method for improving the efficiency of asynchronous injection and production development in thin, poor-quality oil layers using different wells in this application adopts the following technical solution: One embodiment of this application provides a method for improving the efficiency of asynchronous injection-production development in thin, poor-quality oil reservoirs using different wells. The method includes the following steps: During the injection and production development of thin-layer oil reservoirs, bottom hole flowing pressure data of each injection well and each production well are collected in real time. The adjustment cycle of the injection pressure of the injection well is set. The difference of bottom hole flowing pressure data between each injection well and its neighboring production wells in each cycle is decomposed in time series. By comparing the high-frequency detail components and low-frequency approximation components of each decomposition layer, the high-frequency disturbance coefficient of each decomposition layer is obtained. Combined with the abrupt change of the high-frequency detail components of each decomposition layer, the injection-production high-frequency disturbance degree between each injection well and its neighboring production wells in each cycle is obtained. Thus, the disturbance accumulation degree of each injection well in each cycle is obtained. The predicted value of the cumulative disturbance degree of each injection well in each cycle is obtained. The disturbance severity of each injection well in each cycle is obtained by the cumulative disturbance degree and the difference between the cumulative disturbance degree and the predicted value. The injection pressure of each injection well in the next cycle is controlled by the distribution of the disturbance severity of all injection wells in each cycle.

[0006] In one embodiment, the high-frequency perturbation coefficient is the ratio of the L2 norm of the high-frequency detail component to the L2 norm of the low-frequency approximation component of each decomposition layer.

[0007] In one embodiment, the process of obtaining the high-frequency perturbation degree of the injection and sampling is as follows: The high-frequency mutation degree of each decomposition layer is obtained by analyzing the mutation patterns of its high-frequency detail components. Calculate the product of the high-frequency perturbation coefficient and the high-frequency abrupt change degree; The high-frequency disturbance degree of injection and production is the average of the products of all the decomposition layers corresponding to each injection well and its nearest production wells in each cycle.

[0008] In one embodiment, the process of obtaining the high-frequency mutation degree is as follows: Obtain each abrupt change point in the high-frequency detail component of each decomposition layer, calculate the difference between the amplitude of the high-frequency detail component at the location of each abrupt change point and the amplitude of the high-frequency detail component at the location of the previous data point; map the amplitude of the high-frequency detail component at the location of the previous data point to a positive number, and calculate the ratio of the difference value to the positive number. The high-frequency mutation rate is the mean of the ratios corresponding to all mutation points in the high-frequency detail components of each decomposition layer.

[0009] In one embodiment, the cumulative disturbance degree is the sum of the high-frequency disturbance degrees of injection and production between each injection well and all its neighboring production wells in each cycle.

[0010] In one embodiment, the process of obtaining the severity of the disturbance is as follows: The predicted value is mapped to a value greater than 0, and the ratio of the cumulative disturbance degree to the value greater than 0 is denoted as the prediction ratio. The severity of the disturbance is directly proportional to the prediction ratio and the cumulative disturbance, respectively.

[0011] In one embodiment, the severity of the disturbance is calculated as follows: Calculate the sum of 1 and the prediction ratio, whereby the severity of the disturbance is the product of the sum and the cumulative degree of the disturbance.

[0012] In one embodiment, the process of controlling the injection pressure of each injection well in the next cycle of each cycle is as follows: By analyzing the temporal variation trend of the difference in bottom hole flowing pressure data between each injection well and its neighboring production well within each cycle, we can assess whether water channeling occurs between each injection well and its neighboring production well within each cycle. The segmentation threshold is obtained by analyzing the distribution of disturbance severity of all injection wells in each cycle. If no water channeling occurs between each injection well and its neighboring production well within each cycle, the injection pressure of each injection well in the next cycle is controlled by comparing the severity of the disturbance with the segmentation threshold.

[0013] In one embodiment, the method for assessing whether water channeling occurs between each injection well and its neighboring production wells within each cycle is as follows: The trend term of the difference in bottom hole flowing pressure data between each injection well and its neighboring production wells in each period is obtained in time. If the trend term between each injection well and all production wells in each period is in a downward trend, it is determined that water channeling has occurred between each injection well and its neighboring production wells in each period; otherwise, it is determined that water channeling has not occurred between each injection well and its neighboring production wells in each period.

[0014] In one embodiment, the method for controlling the injection pressure of each injection well in the next cycle is as follows: If the disturbance severity of each injection well in each cycle is greater than the segmentation threshold, the injection pressure of each injection well in the next cycle will be increased; if the disturbance severity of all injection wells in each cycle is less than or equal to the segmentation threshold, the injection pressure of the injection wells will not be adjusted in the next cycle.

[0015] This application has at least the following beneficial effects: This application uses wavelet decomposition to accurately measure and analyze the high-frequency disturbances of factors affecting the injection-production pressure difference during the injection-production development process. By using high-frequency disturbances, it can more accurately measure the cumulative degree of high-frequency disturbances between the water injection well and its neighboring oil production wells, and more clearly reflect the interaction between permeability, porosity and water saturation in the injection-production pressure difference between the water injection well and its neighboring oil production wells. This is beneficial for the accurate control and adjustment of water injection pressure during the subsequent injection-production development process. Furthermore, by using model prediction, we can predict and analyze the sudden disturbances of factors affecting the injection-production pressure difference. Based on the results of the prediction and analysis, we can accurately analyze the severity of the influence of the interaction between permeability, porosity and water saturation on the injection-production pressure difference between the injection well and its neighboring production well. This allows for more accurate control and regulation of the injection pressure during the injection-production development process. Furthermore, the segmentation threshold is obtained by analyzing the distribution of disturbance severity of all injection wells in each cycle. The injection pressure during the injection-production development process is controlled and adjusted by analyzing the relationship between the disturbance severity and the segmentation threshold. This avoids affecting the injection development efficiency between each injection well and its neighboring production wells, thereby improving the injection-production development efficiency of thin-difference reservoirs. Attached Figure Description

[0016] To more clearly illustrate the technical solutions and advantages in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 A flowchart illustrating the steps of a method for improving the efficiency of asynchronous injection and production development in thin, poor-quality oil reservoirs provided in this application; Figure 2 This is a schematic diagram of the well locations in the thin oil-bearing layer. Figure 3 This is a schematic diagram illustrating the process of obtaining the severity of disturbance. Figure 4 This is a schematic diagram of the water injection pressure control process. Detailed Implementation

[0018] In the description of the embodiments of this application, the words "exemplary," "or," and "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design scheme described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design schemes. Specifically, the use of the words "exemplary," "or," and "for example" is intended to present the relevant concepts in a specific manner.

[0019] Unless otherwise defined, 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. The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. It should be understood that, unless otherwise stated, " / " in this application means "or".

[0020] It should also be noted that the terms "first" and "second" in this application are used to distinguish similar objects, rather than to describe a specific order or sequence.

[0021] The following, in conjunction with the accompanying drawings, details a specific scheme for improving the efficiency of asynchronous injection and production development in thin, poor-quality oil layers, as provided in this application.

[0022] This application provides an embodiment of a method for improving the efficiency of asynchronous injection-production development in thin-layer oil reservoirs using different wells. Specifically, it provides the following method for improving the efficiency of asynchronous injection-production development in thin-layer oil reservoirs using different wells. Please refer to [link to relevant documentation]. Figure 1 The method includes the following steps: Step 1: Analysis of thin-layer oil reservoir development: Select the test area with the aim of improving the recovery rate of thin-layer oil reservoirs as the target well area for analysis, including the production layer, current development status, injection-production relationship, and oil reservoir activation status, with a focus on clarifying the layer combination and well network deployment of thin-layer oil reservoirs.

[0023] Step 2: Asynchronous injection-production development method in different wells: Research is conducted in the target well area. The asynchronous injection-production development method in different wells includes: Step S1 establishes a phased development principle of first water-flooding poor reservoirs and then chemically flooding good reservoirs. Prioritizing the development of poor reservoirs fully utilizes their remaining potential while laying the foundation for the development of good reservoirs, ultimately achieving a significant improvement in overall oil recovery. Referring to the Daqing Changyuan reservoir classification standard, IIIA reservoirs are defined as good reservoirs, while IIIB and IIIC reservoirs are defined as poor reservoirs.

[0024] Step S2: Combination of good and poor layers. Utilizing the potential to increase production capacity from poor layers outside the target well area, fracturing and production are carried out according to the identified poor layers. Based on the production capacity, some good layers are developed in wells with low production capacity to explore the effective development limits of poor layers. There are 6 good layers in the target well area. These good layers are relatively continuous, thin, few in number, and have limited replacement potential.

[0025] Step S3, selection of well completion method. If the target well area has many poor-quality layers with thin thickness, well fracturing will be used to ensure injection and production capacity and a certain level of productivity. For good-quality layers, conventional perforation completion will generally be used. Based on the dynamic characteristics of the blank water drive stage, fracturing stimulation measures will be selectively adopted.

[0026] Among them, the principles for selectively adopting fracturing measures are as follows: (1) If the oil and gas show is good, and the reservoir is generally interpreted as an oil layer or a poor oil layer, and there is no production or very small production under a large production pressure difference, but the low-permeability reservoir has good pressure recovery ability, it is recommended to carry out fracturing measures; (2) If the oil layer is thick and the low-permeability conglomerate layer has poor porosity due to uneven rock particles, under the condition that its pressure recovery ability is good, the production increase effect after fracturing measures is obvious. The fractures generated by fracturing can effectively connect the permeable zone with good physical properties at a certain distance from the wellbore, it is also recommended to carry out fracturing measures.

[0027] Step S4: Optimize the scheme design. Based on the injection-production well spacing, fault location, and well group development, design two well completion methods for the test area: conventional perforation production and fracturing production.

[0028] The process involves first exploring the location, strike, width, and extent of the fracture zone in the initial exploration test area. Then, injection and production well groups are arranged on both sides of the fault, maintaining a well spacing of no less than twice the fault width. Finally, for well groups with good permeability and low inclination, conventional perforation is used for production completion, while for well groups with poor permeability and requiring increased production capacity, fracturing is used for production completion.

[0029] Step S5: Analyze the utilization status of thin and poor oil layers in a timely manner and make follow-up adjustments. For thin and poor oil layers, improve injection and production capacity by taking measures such as adjusting both injection and production ends and fracturing and acidizing to ensure polymer flooding effect and tap the potential of remaining oil.

[0030] Step S501: During the injection and production development of the thin differential oil layer, the bottom hole flowing pressure data of each injection well and each production well are collected in real time.

[0031] To improve the recovery rate of asynchronous injection and production development in thin-differential oil reservoirs, it is necessary to accurately measure the disturbance of factors affecting the injection-production pressure difference during the injection-production development process. This will allow for more accurate control and regulation of the water injection pressure during the injection-production development process, thereby improving the water injection development efficiency of thin-differential oil reservoirs.

[0032] Therefore, during the injection-production development of thin differential oil layers, downhole pressure gauges are used to collect bottomhole flowing pressure data for each injection well and each production well in real time. A schematic diagram of the well locations in the thin differential oil layer is shown below. Figure 2 As shown, Figure 2 In the table, solid dots represent water injection wells, and circled solid dots represent oil production wells. Table 1 shows the bottom hole flowing pressure data for injection wells, and Table 2 shows the bottom hole flowing pressure data for oil production wells.

[0033] Table 1 Bottomhole flowing pressure data of injection wells

[0034] Table 2 Bottomhole flowing pressure data of oil wells

[0035] In this embodiment, the data acquisition time interval for bottom hole flowing pressure is 1 minute. The acquisition time interval is set manually, and the implementer can set it according to the actual situation. This application does not impose any special restrictions.

[0036] Step S502: Set the adjustment cycle of the injection pressure of the injection well. Perform wavelet decomposition on the bottom hole flowing pressure data difference between each injection well and its neighboring production wells in each cycle. By comparing the high-frequency detail components and low-frequency approximation components of each decomposition layer, obtain the high-frequency disturbance coefficient of each decomposition layer. Combine the abrupt change of the high-frequency detail components of each decomposition layer to obtain the injection-production high-frequency disturbance degree between each injection well and its neighboring production wells in each cycle, and then obtain the disturbance accumulation degree of each injection well in each cycle.

[0037] Generally, the injection-production pressure differential during the injection-production development process is affected by the interaction of permeability, porosity, and water saturation. This interference from permeability, porosity, and water saturation impacts the water injection development efficiency of thin-difference reservoirs. Therefore, it is necessary to accurately measure the disturbance of the injection-production pressure differential caused by these factors, and then accurately control and regulate the water injection pressure during the injection-production development process to improve the water injection development efficiency of thin-difference reservoirs. The adjustment cycle for the water injection pressure of the injection well is set. In this embodiment, the cycle length is 1 hour. The cycle length is manually set, and the implementer can set it according to the actual situation; this application does not impose any special restrictions.

[0038] To analyze the injection-production pressure difference changes between each injection well and its neighboring production wells, neighboring production wells are set up for each injection well. Then, the injection-production pressure difference sequence between each injection well and its neighboring production wells is calculated for each period. The method for obtaining the injection-production pressure difference sequence is as follows: the difference in bottom hole flowing pressure data between each injection well and its neighboring production wells at each sampling time is calculated. These bottom hole flowing pressure differences at all sampling times within each period are then arranged chronologically to form the injection-production pressure difference sequence between each injection well and its neighboring production wells for each period.

[0039] In this embodiment, the method for obtaining the nearest production wells of each water injection well is as follows: calculate the Euclidean distance between each water injection well and each production well, arrange all production wells in ascending order according to the Euclidean distance between them and each water injection well, and take the first two production wells as the nearest production wells of each water injection well. Here, 2 is only one embodiment of this application, and the implementer can set its specific value according to the actual situation. This application does not impose any special restrictions.

[0040] Taking the injection-production pressure difference sequence between each injection well and its j-th nearest neighbor production well in each cycle as an example, the injection-production pressure difference sequence is decomposed, and the high-frequency detail components and low-frequency approximate components of each decomposed layer are obtained.

[0041] In this embodiment, the injection-production pressure difference sequence is decomposed using a wavelet decomposition algorithm. The wavelet decomposition algorithm selects sym5 as the wavelet basis function, and the number of decomposition layers n is 2. The wavelet decomposition algorithm is a well-known technology and will not be described in detail here. As other implementation methods, based on the ability to decompose the injection-production pressure difference sequence and obtain the high-frequency detail components and low-frequency approximate components of each decomposition layer, the implementer may adopt other existing feasible technologies, and this application does not impose any special restrictions.

[0042] Furthermore, the L2 norm of the high-frequency detail components and low-frequency approximation components of each decomposition layer is calculated separately. The ratio of the L2 norm of the high-frequency detail components to the L2 norm of the low-frequency approximation components of each decomposition layer is used as the high-frequency perturbation coefficient of each decomposition layer. Here, the L2 norm represents the energy of the high-frequency detail components and low-frequency approximation components in the decomposition layer. The larger the calculated high-frequency perturbation coefficient, the more the decomposition layer reflects the high-frequency perturbation characteristics of the injection-production pressure difference being affected by short-term perturbations. In this case, the dynamic change complexity of the injection-production pressure difference during the injection-production development process is higher, which further affects the efficiency of asynchronous injection-production development in thin-layer oil reservoirs. The calculation of the L2 norm is a well-known technique and will not be elaborated upon in this application.

[0043] Meanwhile, since the abrupt changes in the high-frequency detail components of each decomposition layer can reflect the high-frequency abrupt change characteristics of the injection-production pressure difference affected by short-term disturbances, the abrupt change points in the high-frequency detail components of each decomposition layer are obtained, and the abrupt change deviation rate of each abrupt change point in the high-frequency detail components of each decomposition layer is calculated. The acquisition process is as follows: Obtain the amplitude of the high-frequency detail component at the location of each mutation point in the high-frequency detail component of each decomposition layer, and the difference value compared with the amplitude of the high-frequency detail component at the location of the previous data point; map the amplitude of the high-frequency detail component at the location of the previous data point to a positive number, and use the ratio of the difference value to the positive number as the mutation deviation rate of each mutation point in the high-frequency detail component of each decomposition layer.

[0044] In this embodiment, the Bernaola Galvan segmentation algorithm is used to obtain each mutation point in the high-frequency detail component of each decomposition layer. The Bernaola Galvan segmentation algorithm is a well-known technology and will not be described in detail here. As other implementation methods, based on the ability to obtain each mutation point in the high-frequency detail component of each decomposition layer, implementers may use other existing technologies, such as the Mann-Kendall mutation point detection algorithm, the Pettitt mutation point detection algorithm, etc. This application does not impose any special restrictions.

[0045] It should be noted that the purpose of mapping data to positive numbers is to avoid the denominator being 0. This can be achieved by calculating the sum of the data and a constant greater than 0, or by treating the data as the exponent of an exponential function with the natural constant as the base. This application does not impose any special restrictions on this.

[0046] In this embodiment, the expression for the mutation deviation rate of each mutation point in the high-frequency detail component of each decomposition layer is as follows: In the formula, This represents the mutation bias rate of the s-th mutation point in the high-frequency detail component of a single decomposition layer. This represents the amplitude of the high-frequency detail component at the location of the s-th mutation point in the high-frequency detail components of a single decomposition layer. This represents the amplitude of the high-frequency detail component at the location of the data point preceding the s-th mutation point in the high-frequency detail component of a single decomposition layer. This indicates the absolute value operation; A constant greater than 0 is used to prevent the denominator from being zero, and also to avoid... The value of affects the calculation result of the mutation deviation rate. In this embodiment... The value is 0.005, and the implementer can set its specific value according to the actual situation. The result of mapping the amplitude of the high-frequency detail component to a positive number is... The difference in amplitude between high-frequency detail components is ; As an alternative implementation, based on the ability to measure the degree of difference between the amplitudes of high-frequency detail components, the implementer may use other calculation methods, such as the square of the difference, the ratio, etc., and this application does not impose any special restrictions.

[0047] Furthermore, if the average level of the mutation deviation rate of mutation points in the high-frequency detail components of each decomposition layer is larger, it indicates that the high-frequency mutation characteristics of the injection-production pressure difference are more significant under the influence of short-term disturbances. Therefore, the average value of the mutation deviation rate of all mutation points in the high-frequency detail components of each decomposition layer is taken as the high-frequency mutation degree of each decomposition layer to reflect the high-frequency mutation characteristics of the injection-production pressure difference under the influence of short-term disturbances.

[0048] Generally, the larger the high-frequency disturbance coefficient of each decomposition layer after decomposition of the injection-production pressure difference sequence, and the greater the high-frequency abrupt change of each decomposition layer, the more it reflects that the injection-production pressure difference will be affected by the interaction of permeability, porosity and water saturation. It is necessary to accurately control and regulate the water injection pressure during the injection-production development process to improve the water injection development efficiency of thin-difference reservoirs.

[0049] Based on the above analysis, the high-frequency disturbance coefficient and high-frequency abrupt change degree of each decomposition layer obtained by decomposing the injection-production pressure difference sequence between each injection well and its j-th nearest neighbor production well in each cycle are used to obtain the injection-production high-frequency disturbance degree between each injection well and its j-th nearest neighbor production well in each cycle. The expression is as follows: In the formula, The value represents the high-frequency disturbance degree between the i-th injection well and its j-th nearest neighbor production well within a single cycle; n represents the wavelet decomposition layer number. , These represent the high-frequency disturbance coefficient and high-frequency abrupt change degree of the r-th decomposition layer corresponding to the i-th injection well and its j-th nearest neighbor production well within a single cycle, respectively.

[0050] It should be noted that: the high-frequency disturbance coefficient can reflect the high-frequency disturbance characteristics of the injection-production pressure difference affected by short-term disturbances, while the high-frequency abrupt change degree reflects the high-frequency abrupt change characteristics of the injection-production pressure difference affected by short-term disturbances; the injection-production high-frequency disturbance degree reflects the high-frequency disturbance of the factors affecting the injection-production pressure difference during the injection-production development process. The larger the calculated injection-production high-frequency disturbance degree, the stronger the high-frequency disturbance of the factors affecting the injection-production pressure difference during the injection-production development process, which is less conducive to the stability of the injection-production pressure difference during the injection-production development process, and requires accurate control and regulation of the water injection pressure during the injection-production development process.

[0051] Based on the calculation method of the injection-production high-frequency disturbance degree between each injection well and its j-th nearest production well in each cycle, the injection-production high-frequency disturbance degree between each injection well and its nearest production well in each cycle is calculated.

[0052] Furthermore, the sum of the high-frequency disturbances between each injection well and all its neighboring production wells within each cycle is taken as the cumulative disturbance degree of each injection well within each cycle. The cumulative disturbance degree reflects the degree of accumulation of high-frequency disturbances between each injection well and all its neighboring production wells within each cycle. The larger the calculated cumulative disturbance degree, the greater the influence of the interaction between permeability, porosity and water saturation on the injection-production pressure difference between each injection well and its neighboring production wells. At this time, the possibility of increased flow resistance or decreased water drive efficiency during the injection-production development process is greater, and the water injection pressure should be adjusted upward during the injection-production development process, i.e., the water injection pressure should be increased, thereby improving the water injection development efficiency of thin-difference reservoirs.

[0053] Step S503: Obtain the predicted value of the cumulative disturbance degree of each injection well in each cycle, and obtain the disturbance severity of each injection well in each cycle by the cumulative disturbance degree and the difference between it and the predicted value.

[0054] To more accurately control and regulate water injection pressure during the injection-production development process, control periods are set for each cycle. Specifically, all historical cycles are arranged in ascending order according to the time interval between each cycle, and the first M cycles are used as control periods for each cycle. The cumulative disturbance degree of each injection well within all control periods of each cycle is arranged chronologically to obtain the historical disturbance characteristic sequence of each injection well within each cycle, reflecting the changes in the cumulative disturbance degree between each injection well and its neighboring production wells throughout history.

[0055] In this embodiment, the value of M is 72. The value of M is set manually, and the implementer can set it according to the actual situation. This application does not impose any special restrictions.

[0056] Furthermore, in order to more clearly highlight the severity of the influence of the interaction between permeability, porosity and water saturation on the injection-production pressure difference between the injection well and its neighboring production well, the predicted value of the cumulative disturbance of each injection well in each period was obtained by using the historical disturbance characteristic sequence of each injection well in each period.

[0057] In this embodiment, the historical disturbance characteristic sequence of each injection well in each period is used as the input of the ARIMA autoregressive moving average model. The number of autoregressive terms p in the ARIMA autoregressive moving average model is 3, the difference degree d is 2, and the number of moving average terms q is 2. The predicted value of the disturbance accumulation of each injection well in each period is output. The ARIMA autoregressive moving average model is a well-known technology and will not be described in detail in this application. Based on the ability to obtain the predicted value of the disturbance accumulation of each injection well in each period, the implementer may use other existing feasible technologies. This application does not impose any special restrictions.

[0058] Generally, if the cumulative disturbance of any injection well in each cycle is higher than its predicted value, it indicates that the sudden disturbance of the factors affecting the injection-production pressure difference between the injection well and its neighboring oil well in each cycle is stronger, reflecting the greater severity of the influence of the interaction between permeability, porosity and water saturation on the injection-production pressure difference between the injection well and its neighboring oil well in each cycle.

[0059] Based on the above analysis, the severity of disturbance for each injection well in each cycle is obtained by analyzing the cumulative disturbance level of each injection well within each cycle and its difference from the predicted value. The specific process is as follows: The predicted value of the cumulative disturbance degree of each injection well in each period is mapped to a value greater than 0. The ratio of the cumulative disturbance degree of each injection well in each period to the value greater than 0 is denoted as the prediction ratio. Calculate the sum of 1 and the predicted ratio, and multiply the sum by the cumulative disturbance degree of each injection well in each cycle to obtain the disturbance severity of each injection well in each cycle.

[0060] In this embodiment, the expression for the severity of disturbance of each injection well in each cycle is as follows: In the formula, This indicates the severity of disturbance in the i-th injection well within a single cycle; This represents the cumulative disturbance degree of the i-th injection well within a single cycle; This represents the predicted cumulative disturbance level of the i-th injection well within each cycle; A constant greater than 0 is used to prevent the denominator from being zero, and also to avoid... The value of affects the calculation result of the disturbance severity. In this embodiment... The value is 0.005, and the implementer can set its specific value according to the actual situation. The result of mapping the predicted value to a value greater than 0 is... There are many ways to map data to values ​​greater than 0, and implementers can choose other feasible methods as needed. Among them, mapping data to values ​​greater than 0... This is denoted as the prediction ratio.

[0061] It should be noted that the disturbance severity reflects the extent to which the injection-production pressure difference between the injection well and its neighboring production well is affected by the interaction of permeability, porosity, and water saturation. The higher the calculated disturbance severity, the more severe the impact of these factors on the injection-production pressure difference. In this case, the increased flow resistance or decreased water drive efficiency in the thin-difference reservoir is more significant, and upward feedback adjustment of the injection pressure during the injection-production development process is more necessary to improve the water injection development efficiency of the thin-difference reservoir. A schematic diagram of the disturbance severity acquisition process is shown below. Figure 3 As shown.

[0062] Step S504: By analyzing the distribution of disturbance severity of all injection wells in each cycle, the injection pressure of each injection well in the next cycle is controlled.

[0063] Furthermore, in order to accurately control and regulate the water injection pressure during the injection-production development process, the segmentation threshold is obtained by analyzing the distribution of disturbance severity of all injection wells in each cycle.

[0064] In this embodiment, the disturbance severity of all injection wells in each cycle is used as the input of the 3sigma anomaly detection algorithm, and the 3sigma range of the disturbance severity is output. The upper limit of the 3sigma range of the disturbance severity is used as the segmentation threshold. The 3sigma anomaly detection algorithm is a well-known technology and will not be described in detail in this application. As other implementation methods, based on the ability to obtain the segmentation threshold of the disturbance severity of all injection wells in each cycle, the implementer may adopt other existing feasible technologies, and this application does not impose any special restrictions.

[0065] Simultaneously, by analyzing the temporal trend of the difference in bottomhole flowing pressure data between each injection well and its neighboring production wells within each cycle, the question of whether water channeling occurs between each injection well and its neighboring production wells within each cycle is assessed. The specific process is as follows: Obtain the trend term of the injection-production pressure difference sequence between each injection well and its nearest production wells in each period. If the trend term between each injection well and all production wells in each period is in a downward trend, it is determined that water channeling has occurred between each injection well and its nearest production wells in each period. In this case, the injection pressure of each injection well in each period needs to be reduced. Otherwise, it is determined that no water channeling has occurred between each injection well and its nearest production wells in each period.

[0066] In this embodiment, the STL (Seasonal and Trend decomposition using Loess) time series decomposition method is used to obtain the trend term of each injection-production pressure difference series. The STL time series decomposition method is a well-known technology and will not be described in detail in this application. As other implementation methods, based on the ability to obtain the trend term of each injection-production pressure difference series, the implementer may use other existing technologies, such as Holt-Winters seasonal adjustment, etc. This application does not impose any special restrictions.

[0067] In this embodiment, the method for evaluating whether each trend item is in a downward trend is as follows: perform linear fitting on the trend item. If the slope of the fitted line is negative, then the trend item is in a downward trend. The least squares method is used to perform linear fitting on the trend item. The least squares method is a well-known technique and will not be described in detail here. As other implementation methods, based on the ability to evaluate whether each trend item is in a downward trend, the implementer may use other existing feasible techniques, which will not be described in detail here.

[0068] In this embodiment, the decrease in water injection pressure is 10%. When the decrease in water injection pressure is within the range of [10%, 20%], the implementer can set the decrease in water injection pressure according to the actual situation.

[0069] Furthermore, assuming no water channeling occurs between any injection well and its nearest production well within each cycle, the injection pressure of any injection well in the next cycle is controlled by comparing the severity of disturbance and the segmentation threshold of any injection well within each cycle. The specific process is as follows: If the disturbance severity of any injection well in any cycle exceeds the segmentation threshold, it indicates that the injection-production pressure difference between that injection well and its neighboring production well is significantly affected by the interaction of permeability, porosity, and water saturation, thus impacting the water injection development efficiency between the injection well and its neighboring production well. Therefore, the injection pressure of that injection well is increased by 0.1 MPa. If the disturbance severity of all injection wells in any cycle is less than or equal to the segmentation threshold, it indicates that the injection-production pressure difference between all injection wells and their neighboring production wells is less affected by the interaction of permeability, porosity, and water saturation, and the water injection development efficiency between the injection wells and their neighboring production wells is good. Therefore, no adjustment of the injection pressure in the next cycle is required. It should be noted that when the injection pressure increase value is within the range [0.1 MPa, 0.2 MPa], the implementer can set the injection pressure increase value according to the actual situation. The control flow diagram of the injection pressure is shown below. Figure 4 As shown.

[0070] In summary, this application uses wavelet decomposition to accurately measure and analyze the high-frequency disturbances of factors affecting the injection-production pressure difference during the injection-production development process. Furthermore, by using high-frequency disturbances, it more accurately measures the cumulative degree of high-frequency disturbances between the injection well and its neighboring production wells, and more clearly demonstrates the interaction between permeability, porosity, and water saturation in the injection-production pressure difference between the injection well and its neighboring production wells. This facilitates accurate control and adjustment of the injection pressure during the subsequent injection-production development process. Furthermore, by using model prediction, we can predict and analyze the sudden disturbances of factors affecting the injection-production pressure difference. Based on the results of the prediction and analysis, we can accurately analyze the severity of the influence of the interaction between permeability, porosity and water saturation on the injection-production pressure difference between the injection well and its neighboring production well. This allows for more accurate control and regulation of the injection pressure during the injection-production development process. Furthermore, the segmentation threshold is obtained by analyzing the distribution of disturbance severity of all injection wells in each cycle. The injection pressure during the injection-production development process is controlled and adjusted by analyzing the relationship between the disturbance severity and the segmentation threshold. This avoids affecting the injection development efficiency between each injection well and its neighboring production wells, thereby improving the injection-production development efficiency of thin-difference reservoirs.

[0071] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than that shown in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. In the descriptions corresponding to the flowcharts and block diagrams in the accompanying drawings, the operations or steps corresponding to different blocks may also occur in a different order than disclosed in the description, and sometimes there is no specific order between different operations or steps. For example, two consecutive operations or steps may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. Each block in a block diagram and / or flowchart, and combinations of blocks in a block diagram and / or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0072] It will be apparent to those skilled in the art that this application is not limited to the details of the exemplary embodiments described above, and that this application can be implemented in other specific forms without departing from its essential characteristics. Therefore, the embodiments described above should be considered exemplary and non-limiting in all respects.

Claims

1. A method for improving the development efficiency of thin and poor oil layers by different well and asynchronous injection and production, characterized in that, The method includes the following steps: During the injection and production development of thin-layer oil reservoirs, bottom hole flowing pressure data of each injection well and each production well are collected in real time. The adjustment cycle of the injection pressure of the injection well is set. The difference of bottom hole flowing pressure data between each injection well and its neighboring production wells in each cycle is decomposed in time series. By comparing the high-frequency detail components and low-frequency approximation components of each decomposition layer, the high-frequency disturbance coefficient of each decomposition layer is obtained. Combined with the abrupt change of the high-frequency detail components of each decomposition layer, the injection-production high-frequency disturbance degree between each injection well and its neighboring production wells in each cycle is obtained. Thus, the disturbance accumulation degree of each injection well in each cycle is obtained. The predicted value of the cumulative disturbance degree of each injection well in each cycle is obtained. The disturbance severity of each injection well in each cycle is obtained by the cumulative disturbance degree and the difference between the cumulative disturbance degree and the predicted value. The injection pressure of each injection well in the next cycle is controlled by the distribution of the disturbance severity of all injection wells in each cycle. The process of obtaining the high-frequency disturbance degree of the injection and extraction is as follows: The high-frequency mutation degree of each decomposition layer is obtained by analyzing the mutation patterns of its high-frequency detail components. Calculate the product of the high-frequency perturbation coefficient and the high-frequency abrupt change degree; The high-frequency disturbance degree of injection and production is the average of the products of all the decomposed layers corresponding to each injection well and its nearest oil production wells in each cycle. The process for obtaining the severity of the disturbance is as follows: The predicted value is mapped to a value greater than 0, and the ratio of the cumulative disturbance degree to the value greater than 0 is denoted as the prediction ratio. The severity of the disturbance is directly proportional to the prediction ratio and the cumulative disturbance, respectively.

2. The method for improving the efficiency of asynchronous injection and production development in thin, poor oil reservoirs according to claim 1, characterized in that, The high-frequency perturbation coefficient is the ratio of the L2 norm of the high-frequency detail component to the L2 norm of the low-frequency approximation component of each decomposition layer.

3. The method for improving the efficiency of asynchronous injection and production development in thin, poor oil layers according to claim 1, characterized in that, The process for obtaining the high-frequency mutation degree is as follows: Obtain each abrupt change point in the high-frequency detail component of each decomposition layer, calculate the difference between the amplitude of the high-frequency detail component at the location of each abrupt change point and the amplitude of the high-frequency detail component at the location of the previous data point; map the amplitude of the high-frequency detail component at the location of the previous data point to a positive number, and calculate the ratio of the difference value to the positive number. The high-frequency mutation rate is the mean of the ratios corresponding to all mutation points in the high-frequency detail components of each decomposition layer.

4. The method for improving the efficiency of asynchronous injection and production development in thin, poor oil layers according to claim 1, characterized in that, The cumulative disturbance degree is the sum of the high-frequency disturbance degrees of injection and production between each injection well and all its neighboring production wells in each cycle.

5. The method for improving the efficiency of asynchronous injection and production development in thin, poor oil layers according to claim 1, characterized in that, The method for calculating the severity of the disturbance is as follows: Calculate the sum of 1 and the prediction ratio, whereby the severity of the disturbance is the product of the sum and the cumulative degree of the disturbance.

6. The method for improving the efficiency of asynchronous injection and production development in thin, poor oil layers according to claim 1, characterized in that, The process of controlling the injection pressure of each injection well in the next cycle is as follows: By analyzing the temporal variation trend of the difference in bottom hole flowing pressure data between each injection well and its neighboring production well within each cycle, we can assess whether water channeling occurs between each injection well and its neighboring production well within each cycle. The segmentation threshold is obtained by analyzing the distribution of disturbance severity of all injection wells in each cycle. If no water channeling occurs between each injection well and its neighboring production well within each cycle, the injection pressure of each injection well in the next cycle is controlled by comparing the severity of the disturbance with the segmentation threshold.

7. The method for improving the efficiency of asynchronous injection and production development in thin, poor oil layers according to claim 6, characterized in that, The method for assessing whether water channeling occurs between each injection well and its neighboring production wells during each cycle is as follows: The trend term of the difference in bottom hole flowing pressure data between each injection well and its neighboring production wells in each period is obtained in time. If the trend term between each injection well and all production wells in each period is in a downward trend, it is determined that water channeling has occurred between each injection well and its neighboring production wells in each period; otherwise, it is determined that water channeling has not occurred between each injection well and its neighboring production wells in each period.

8. The method for improving the efficiency of asynchronous injection and production development in thin, poor oil layers according to claim 6, characterized in that, The method for controlling the injection pressure of each injection well in the next cycle is as follows: If the disturbance severity of each injection well in each cycle is greater than the segmentation threshold, the injection pressure of each injection well in the next cycle will be increased; if the disturbance severity of all injection wells in each cycle is less than or equal to the segmentation threshold, the injection pressure of the injection wells will not be adjusted in the next cycle.

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