A co2 flooding storage regulation optimization decision method and system

Abstract

The application provides a CO2 oil displacement storage regulation optimization decision method and system, the method obtains a three-dimensional geological model, production dynamic data and monitoring data of a target working area; a component numerical simulation technology is used to fit a CO2 injection production dynamic history of the target working area, so that target operation parameters of a simulation operation model are adjusted and determined to obtain a matched production simulation operation model; a gas-oil ratio is determined according to the production dynamic data, and then a gas channeling index is calculated, and a target well group meeting the conditions of the gas channeling index is selected; a relationship curve distribution between a Peclet number, an oil increment and a component sweep efficiency is determined by simulating different injection speeds to determine an optimized target injection speed; and development parameters corresponding to different injection modes are simulated, and the target injection mode is determined in combination with the gas channeling index, the sweep efficiency and the miscibility degree. The scheme can overcome the defects of the prior art that the parameter optimization is not in place and the precision is insufficient, and can consider the particularity of the CO2 oil displacement mechanism to establish a regulation optimization strategy based on dimensionless parameters.

Description

Technical Field

[0001] This invention relates to the field of oilfield development and optimization technology, and in particular to a CO2 flooding and storage regulation optimization decision-making method and system, providing a method to improve the CO2 flooding effect by utilizing gas channeling index, Peckle number, component sweep efficiency and component numerical simulation. Background Technology

[0002] Because CO2 flooding can achieve a win-win situation of increasing oil production and reducing carbon emissions, CO2 flooding technology has attracted widespread attention. Petrochemical companies have launched numerous CCUS demonstration projects, with the number of related projects implemented both domestically and internationally consistently exceeding 100. Compared to other enhanced oil recovery (EOR) studies, the mechanism of CO2 flooding technology is more complex. For example, CO2 has strong diffusion capabilities in crude oil, resulting in two fronts in CO2 flooding: a component front and a gas front. This leads to inconsistencies in CO2 encounter time and gas channeling time, and the gas-oil ratio variation is more complex than that of water cut variations. When the formation pressure exceeds the minimum miscibility pressure, miscible displacement is achieved, with displacement efficiency approaching 100%, but abrupt changes in the gas-oil ratio are possible. Furthermore, CO2 has low viscosity, and the oil-gas viscosity ratio is much greater than the oil-water viscosity ratio, resulting in prominent viscous fingering, which severely affects the CO2 sweep efficiency.

[0003] Meanwhile, CO2 sequestration is a key focus, as there is often a conflict between sequestration, oil recovery, and CO2 exchange rate during CO2 flooding. For example, when a scheme aims for a high exchange rate, it often requires injecting less CO2 to extract more oil, resulting in a lower sequestration. Due to the complexity of CO2 flooding implementation, current optimization or adjustment of CO2 flooding and storage field schemes primarily focuses on increasing oil recovery or sequestration, utilizing component numerical simulation techniques. However, this approach fails to effectively coordinate oil recovery efficiency with storage effectiveness and does not fully consider the dynamic changes during CO2 displacement. In particular, it lacks the use of dimensionless parameters to describe the CO2 displacement process for optimization and adjustment. This leads to insufficient accuracy in the analysis results, discrepancies with actual data, and consequently, unsatisfactory implementation of reservoir engineering or comprehensive adjustment schemes.

[0004] Therefore, CO2-driven oil recovery and storage regulation needs to start from the CO2-driven oil recovery mechanism, consider the special characteristics of CO2-driven oil recovery, and establish a regulation and improvement method based on comprehensive optimization considerations.

[0005] The information disclosed in the background section of this invention is intended only to enhance the understanding of the general background of this invention, and should not be construed as an admission or in any way implying that such information constitutes prior art known to those skilled in the art. Summary of the Invention

[0006] To address the aforementioned problems, this invention provides a CO2 flooding and oil storage control optimization decision-making method. The purpose of this invention is to address the issues of prominent viscosity fingering, low sweep efficiency, and especially the gradual deterioration of effectiveness after gas encounter in CO2 flooding. This method aims to improve the control and storage effect of CO2 flooding in target reservoirs. This approach overcomes the shortcomings of existing technologies, such as inadequate parameter optimization and insufficient precision. Starting from the CO2 flooding mechanism and considering the unique characteristics of CO2 flooding, it establishes a control optimization strategy based on dimensionless parameters. This method uses changes in gas channeling index, Peckley number, and component sweep efficiency as a basis, and utilizes component numerical simulation technology to optimize control measures. The method involves: using component numerical simulation technology to fit the production dynamic history of CO2 injection in the target work area, adjusting and determining the target operation parameters of the simulation operation model to obtain a matching production simulation operation model; determining the gas-oil ratio based on production dynamic data, then calculating the gas channeling index, and selecting target well groups that meet the gas channeling index requirements; analyzing the Peckle number corresponding to different injection rates, simulating different injection rates to determine the relationship curve distribution between the Peckle number, oil increase, and component sweep efficiency, and determining the optimized target injection rate; simulating the development parameters corresponding to different injection modes, and combining the gas channeling index, sweep efficiency, and miscibility to determine the target injection mode for the well group. Preferably, in one embodiment, the method includes:

[0007] Data collection steps: Identify the target work area, obtain production-related data and a three-dimensional geological model of the target work area, including production dynamic data and monitoring data;

[0008] Production simulation model determination steps: Using component numerical simulation technology, the production dynamic history of CO2 injection in the target work area is fitted to adjust and determine the target operation parameters of the simulation operation model, so as to obtain a production simulation operation model that matches the actual reservoir.

[0009] Gas channeling index calculation steps: Determine the gas-oil ratio of each well in the target work area based on production dynamic data, and then calculate the corresponding gas channeling index based on the gas-oil ratio;

[0010] Well group selection steps: Select well groups whose gas channeling index meets the set conditions as target well groups;

[0011] Injection rate optimization steps: For the target well group, analyze the Peckle number corresponding to different injection rates, and determine the relationship curve distribution between the Peckle number of CO2 injection, oil increase and component sweep efficiency through simulation analysis of different injection rates, and determine the target injection rate for optimization.

[0012] Injection mode optimization steps: Based on the target injection rate, adjust the CO2 injection mode, simulate and analyze the development parameters corresponding to different injection modes, and then determine the target injection mode of the well group according to the gas channeling index, sweep efficiency and miscibility corresponding to the development parameters.

[0013] Optionally, in one embodiment, the data collection step includes the acquisition of production dynamic data such as oil production, water production, gas production, water injection, and gas injection data of each production well in the target work area; and monitoring data such as production profile data, water and gas intake profile data, wellhead test data, and perforation data.

[0014] Furthermore, in one embodiment, the production simulation model determination step includes:

[0015] A component numerical simulation model was established based on a three-dimensional geological model of the target work area using numerical simulation software.

[0016] The production dynamics data, perforation data, relative permeability data, high pressure physical property data, and monitoring data of the loading well are used to fit the production dynamics history of CO2 injection in the target work area;

[0017] Based on the fitted data, the target operational parameters of the simulation model are adjusted and determined to obtain a component numerical simulation model that matches the actual reservoir, which serves as the production simulation model.

[0018] In a preferred embodiment, during the production simulation model determination step, the numerical simulation results are compared with the actual production dynamic data. If the error exceeds the set conditions, the permeability and relative permeability data of each well need to be adjusted according to the monitoring data and error situation, and the numerical simulation is carried out again until the error between the numerical calculation results and the actual production data meets the set conditions.

[0019] In one embodiment, the gas channeling index is calculated using the following formula:

[0020]

[0021] Where λ represents the gas channeling index; HCPV is the ratio of injected CO2 to the pore volume of hydrocarbons in the reservoir; and GOR is the gas-oil ratio.

[0022] Furthermore, in one embodiment, during the injection rate optimization step, the Peckle number G of a certain well group is calculated according to the following formula:

[0023]

[0024] Where D is the diffusion coefficient, v inj Where L is the injection rate, L is the well spacing, and φ is the porosity.

[0025] In an optional embodiment, the injection rate optimization step is characterized by analyzing the relationship curve between the plotted Peclet number and the component sweep efficiency to determine the distribution of inflection points on the curve, and taking the injection rate at the inflection point as the target injection rate.

[0026] Furthermore, in one embodiment, in the injection mode selection step, the scheme in which the gas channeling index is lower than the set requirement and the sweep efficiency and miscibility are higher than the set conditions under the set optimization development index target is selected as the target injection mode.

[0027] The development indicators are one or more, and are set according to the relevant guidelines of the oil and gas industry standards based on development needs; the development indicators include cumulative oil production, cumulative liquid production, cumulative gas production, gas-oil ratio, water cut, annual oil production, annual liquid production, and annual gas production.

[0028] Based on other aspects of the methods described in any one or more of the foregoing embodiments, the present invention also provides a storage medium storing program code that can implement the methods described in any one or more of the foregoing embodiments.

[0029] Based on the application aspects of the methods described in any one or more of the above embodiments, the present invention also provides a CO2 enhanced oil recovery and storage regulation optimization decision system, which executes the methods described in any one or more of the above embodiments.

[0030] Compared with the closest prior art, the present invention also has the following beneficial effects:

[0031] This invention provides a CO2-driven oil recovery and storage control optimization decision-making method and system. Based on the gas channeling index, which evaluates the degree of gas channeling, and combined with component numerical simulation technology, the system analyzes the characteristics of gas channeling index changes under different adjustment schemes to identify well groups with adjustment needs. Then, using component numerical simulation technology, the system optimizes the injection rate and injection mode of the adjustment scheme by analyzing the Peckle number and component sweep efficiency under different adjustment schemes, thus achieving optimization of the adjustment scheme. This scheme starts from the CO2-driven oil recovery mechanism, considers the special characteristics of CO2-driven oil recovery, takes the dimensionless parameters of CO2-driven oil recovery as the core, and uses the changes in gas channeling index, Peckle number, and component sweep efficiency as the basis. It utilizes component numerical simulation technology to optimize control measures, effectively determining a reasonable injection rate to reduce the influence of viscosity fingering, providing reliable guidance and basis for improving CO2-driven oil recovery performance.

[0032] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the description, claims, and drawings. Attached Figure Description

[0033] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with the embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0034] Figure 1 This is a flowchart illustrating the CO2 enhanced oil recovery and storage regulation optimization decision-making method provided in an embodiment of the present invention;

[0035] Figure 2 This is a schematic diagram of the gas channeling index as a function of injection volume in the CO2 oil recovery and storage regulation optimization decision-making method provided in this embodiment of the invention.

[0036] Figure 3 This is a schematic diagram of the relationship between Pelet number and component sweep efficiency in the CO2 enhanced oil recovery and storage regulation optimization decision-making method provided in this embodiment of the invention.

[0037] Figure 4 This is a schematic diagram of the CO2 enhanced oil recovery and storage regulation and optimization decision-making system provided in another embodiment of the present invention. Detailed Implementation

[0038] The embodiments of the present invention will be described in detail below with reference to the accompanying drawings and examples. Those skilled in the art will then fully understand how the present invention uses technical means to solve technical problems and achieve technical effects, and will be able to implement the present invention specifically based on the above-described implementation process. It should be noted that, as long as there is no conflict, the various embodiments and features of the present invention can be combined with each other, and the resulting technical solutions are all within the protection scope of the present invention.

[0039] Although the flowchart describes the operations as sequential processes, many of these operations can be performed in parallel, concurrently, or simultaneously. The order of the operations can be rearranged. A process can terminate when its operation is complete, but it may also have additional steps not included in the diagram. A process can correspond to a method, function, procedure, subroutine, subroutine, etc.

[0040] Computer equipment includes user equipment and network equipment. User equipment or clients include, but are not limited to, computers, smartphones, and PDAs (Personal Digital Assistants); network equipment includes, but is not limited to, a single network server, a server group consisting of multiple network servers, or a cloud based on cloud computing consisting of a large number of computers or network servers. Computer equipment can operate independently to implement this invention, or it can connect to a network and implement this invention through interaction with other computer devices within the network. The network in which the computer equipment resides includes, but is not limited to, the Internet, wide area networks (WANs), metropolitan area networks (MANs), local area networks (LANs), and VPN networks.

[0041] The terms “first,” “second,” etc., may be used herein to describe various units, but these units should not be limited by these terms; they are used merely to distinguish one unit from another. The term “and / or” as used herein includes any and all combinations of one or more of the associated listed items. When a unit is referred to as “connected” or “coupled” to another unit, it may be directly connected or coupled to said other unit, or there may be intermediate units present.

[0042] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the exemplary embodiments. Unless the context clearly indicates otherwise, the singular forms “a” and “an” as used herein are also intended to include the plural. It should also be understood that the terms “comprising” and / or “including” as used herein specify the presence of the stated features, integers, steps, operations, units, and / or components, without excluding the presence or addition of one or more other features, integers, steps, operations, units, components, and / or combinations thereof.

[0043] Because CO2 injection flooding can achieve a win-win situation of increasing oil production and reducing carbon emissions, CO2 injection flooding technology has attracted widespread attention. Petrochemical companies have launched numerous CCUS demonstration projects, with the number of related projects implemented both domestically and internationally consistently exceeding 100.

[0044] Compared to other studies on enhanced oil recovery, the mechanism of CO2 flooding technology is more complex. For example, CO2 has strong diffusion capabilities in crude oil, resulting in two fronts for CO2 flooding: a component front and a gas front. This leads to inconsistencies in CO2 encounter time and gas channeling time, and the gas-oil ratio variation is more complex than that of water cut. When the formation pressure exceeds the minimum miscibility pressure, miscible displacement is achieved, with displacement efficiency approaching 100%, but abrupt changes in the gas-oil ratio are possible. Furthermore, CO2 has low viscosity, and the oil-gas viscosity ratio is much greater than the oil-water viscosity ratio, resulting in prominent viscous fingering, which severely affects the CO2 sweep efficiency.

[0045] Meanwhile, CO2 sequestration is a key focus, and there is often a conflict between sequestration, oil recovery, and CO2 oil exchange rate during CO2 enhanced oil recovery. For example, when a scheme aims for a high oil exchange rate, it often requires injecting less CO2 to extract more oil, resulting in a lower sequestration.

[0046] Based on the aforementioned technical issues, and due to the complexity of CO2 flooding implementation, current optimization or adjustment of CO2 flooding and storage field schemes primarily aims to increase oil production or storage volume, utilizing component numerical simulation techniques. However, this approach fails to effectively coordinate and unify oil displacement efficiency and storage effects, and does not fully consider the dynamic changes during the CO2 displacement process. In particular, it lacks the use of dimensionless parameters that describe the CO2 displacement process for optimization and adjustment. This results in insufficient accuracy of analysis results, discrepancies with actual data, and consequently, unsatisfactory implementation of reservoir engineering schemes or comprehensive adjustment schemes. To address these problems, CO2 flooding and storage control needs to start from the CO2 flooding mechanism, consider the unique characteristics of CO2 flooding, and establish a control and optimization method based on dimensionless parameters.

[0047] Dimensionless parameters proposed by some scholars can effectively describe CO2 displacement characteristics and reflect the CO2 displacement mechanism. For example, the Peckley number can reflect the relative proportion of diffusion and displacement, and effectively measure the impact of CO2 diffusion on the displacement effect. Studies on the Peckley number show that the influence of viscous fingering can be reduced or even eliminated by leveraging diffusion. Therefore, relevant dimensionless parameters have certain guiding significance for reservoir engineering scheme design or scheme optimization.

[0048] Based on this, this invention addresses the problems of prominent viscosity fingering, low sweep efficiency, and especially the gradual deterioration of the effect after gas discovery in CO2 flooding. It provides a regulation and optimization method to improve the CO2 flooding and storage effect in target oil reservoirs. A new parameter for evaluating gas channeling (gas channeling index) is proposed. Based on the changes in the gas channeling index, Peckle number, and component sweep efficiency, component numerical simulation technology is used to optimize the regulation measures. By analyzing the gas channeling index variation characteristics of different adjustment schemes, the development mode of the adjustment scheme is determined. Using component numerical simulation technology, the injection rate of the adjustment scheme is optimized by analyzing the Peckle number and component sweep efficiency of different adjustment schemes. Finally, the adjustment scheme is optimized, and the CO2 displacement effect is improved.

[0049] The following describes the detailed flow of the method according to an embodiment of the present invention with reference to the accompanying drawings, the steps of which can be executed in a computer system containing, for example, a set of computer-executable instructions. Although the logical order of the steps is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than that shown here.

[0050] Example 1

[0051] Figure 1 This diagram illustrates the flow chart of the CO2 enhanced oil recovery and storage regulation optimization decision-making method provided in Embodiment 1 of the present invention. (Refer to...) Figure 1 As can be seen, the method includes the following steps.

[0052] Data collection steps: Identify the target work area, obtain production-related data and a three-dimensional geological model of the target work area, including production dynamic data and monitoring data;

[0053] Production simulation model determination steps: Using component numerical simulation technology, the production dynamic history of CO2 injection in the target work area is fitted to adjust and determine the target operation parameters of the simulation operation model, so as to obtain a production simulation operation model that matches the actual reservoir.

[0054] Gas channeling index calculation steps: Determine the gas-oil ratio of each well based on production dynamic data, and then calculate the corresponding gas channeling index based on the gas-oil ratio;

[0055] Well group selection steps: Select well groups whose gas channeling index meets the set conditions as target well groups;

[0056] Injection rate optimization steps: For the target well group, analyze the Peckle number corresponding to different injection rates, and analyze the relationship curve distribution between the Peckle number of CO2 injection, oil increase and component sweep efficiency at different injection rates through simulation analysis to determine the optimal target injection rate;

[0057] Injection mode optimization steps: Based on the target injection rate, adjust the CO2 injection mode, simulate and analyze the development parameters corresponding to different injection modes, and then determine the target injection mode of the well group according to the gas channeling index, sweep efficiency and miscibility corresponding to the development parameters.

[0058] The present invention provides a regulation and optimization method for improving the CO2 flooding and storage effect in a target oil reservoir. This method is based on changes in the gas channeling index, Peckle number, and component sweep efficiency, and utilizes component numerical simulation technology to optimize regulation measures. The present invention proposes a new parameter for evaluating the degree of gas channeling (gas channeling index), and combines it with component numerical simulation technology to determine the development mode of the adjustment scheme by analyzing the gas channeling index variation characteristics of different adjustment schemes. Using component numerical simulation technology, the injection rate of the adjustment scheme is optimized by analyzing the Peckle number and component sweep efficiency of different adjustment schemes. Finally, the adjustment scheme is optimized, and the CO2 displacement effect is improved.

[0059] First, perform the data collection step to determine the target work area and obtain production-related data and a three-dimensional geological model of the target work area. The production-related data includes production dynamic data and monitoring data.

[0060] In an optional embodiment, the production dynamic data includes the oil production, water production, and gas production of each production well, the water injection and gas injection of injection wells, and the monitoring data includes production fluid profiles, water and gas intake profiles, wellhead test data, perforation data, etc.

[0061] Further, the production simulation model determination step is performed. Using component numerical simulation technology, the production dynamic history of CO2 injection in the target work area is fitted to adjust and determine the target operation parameters of the simulation operation model, so as to obtain a component numerical simulation model that matches the actual reservoir and serves as the production simulation operation model.

[0062] In practical applications, a component numerical simulation model is established based on the three-dimensional geological model of the target work area. That is, on the basis of the three-dimensional geological model, the production dynamic data, perforation data, relative permeability data, high pressure physical property data and monitoring data of the well are further loaded, and a three-dimensional component numerical simulation model is established using numerical simulation software to carry out component numerical simulation and historical fitting calculation.

[0063] Furthermore, by utilizing component numerical simulation technology, the production dynamic history of CO2 injection in the target work area is fitted based on the component numerical simulation model, achieving historical fitting of the CO2 flooding stage, thereby obtaining a component numerical simulation model that conforms to the actual reservoir conditions after CO2 injection. Historical fitting involves comparing the calculation results of the component numerical model with the actual production dynamic data using component numerical simulation technology until the error between the two is minimized.

[0064] Specifically, after conducting numerical simulation through the following operations, the numerical simulation results are obtained. The numerical simulation results are then compared with the actual production dynamic data. If the error exceeds the set conditions, the permeability, relative permeability, and other data of each well need to be adjusted accordingly based on the monitoring data and the error situation. The numerical simulation is then carried out again until the error between the numerical calculation results and the actual production data meets the set conditions. In practical applications, this can be set to less than 15%. This completes the historical fitting.

[0065] The embodiments of the present invention utilize component simulation technology to perform historical fitting and combine it with error analysis to optimize model parameters, which can effectively obtain the correct component numerical simulation model and ensure the accuracy of subsequent predictions.

[0066] Next, the gas channeling index calculation step is performed. Based on the production dynamic data, the gas-oil ratio of each well in the target work area is determined, and then the corresponding gas channeling index is calculated based on the gas-oil ratio.

[0067] The gas-oil ratio data can be calculated based on the oil production and gas production data of each well during actual production. The gas-oil ratio can be obtained by dividing the gas production by the oil production.

[0068] Furthermore, in a preferred embodiment, the gas channeling index is calculated according to the following formula:

[0069]

[0070] Where λ represents the gas channeling index; HCPV is the ratio of injected CO2 (underground conditions) to the pore volume of hydrocarbons in the reservoir; GOR is the gas-oil ratio, and the larger the gas channeling index value, the higher the future gas-oil ratio.

[0071] Furthermore, well groups whose gas channeling index meets the set conditions are selected as target well groups through a well group screening step.

[0072] In practical applications, in the optional embodiments, the well groups that need to be adjusted are clearly identified. That is, if the gas channeling index is higher than a certain threshold, it means that the current gas-oil ratio is increasing too fast and gas channeling will occur soon, so adjustment is required; if it is lower than a certain threshold or the gas channeling index is 0, no adjustment is required.

[0073] Well groups that do not require adjustment shall use the original scheme, while well groups that require adjustment shall obtain an optimized scheme according to the subsequent schemes of this invention and adopt the optimized scheme.

[0074] For target well groups requiring adjustment, the development mode of the adjustment scheme is determined by analyzing the gas channeling index variation characteristics of different adjustment schemes using component numerical simulation technology. By analyzing the Peckle number and component sweep efficiency of different adjustment schemes using component numerical simulation technology, the injection rate of the adjustment scheme is optimized, thereby achieving the optimization of the control scheme.

[0075] Specifically, the injection rate optimization steps are as follows: For the target well group, the Peckle number corresponding to different injection rates is analyzed. The relationship curve distribution between the Peckle number, oil increase and component sweep efficiency of CO2 injection is realized by simulation analysis at different injection rates, and the target injection rate is determined.

[0076] In practical applications, using component numerical simulation technology, with other conditions unchanged, only the injection rate is changed to calculate the oil gain and component sweep efficiency of CO2 injected under different Pelet numbers. The relationship curves between Pelet number and oil gain and component sweep efficiency are plotted to determine the target injection rate after optimization.

[0077] In practical applications, the relationship curve between the Peclet number (oil increase) and the component sweep efficiency is analyzed to determine the distribution of the inflection points of the curve, and the injection rate at the inflection point is taken as the target injection rate.

[0078] The difference between the cumulative oil production calculated using the component numerical simulation model at the corresponding injection rate and the cumulative oil production calculated using the original injection rate is the increase in oil production.

[0079] The component sweep efficiency is the ratio of the number of grid cells that can be obtained at the corresponding velocity in the numerical simulation of CO2 at the end of the simulation.

[0080] The Peckle number G of a well group at a certain injection rate is calculated using the following formula:

[0081]

[0082] Where D is the diffusion coefficient, v inj Where L is the injection rate, L is the well spacing, and φ is the porosity.

[0083] Furthermore, an injection mode optimization step is performed. Based on the optimized target injection rate, the CO2 injection mode is adjusted, and the development parameters corresponding to different injection modes are simulated and analyzed. Then, the target injection mode of the well group is determined according to the gas channeling index, sweep efficiency, and miscibility corresponding to the development parameters.

[0084] Based on the optimized injection rate, the CO2 injection mode is changed. The main changes in the injection mode are included, but are not limited to, those shown in the table below:

[0085] Current injection mode Adjusted injection mode Continuous gas injection Water-gas alternation / periodic gas injection Water vapor alternation Alternating pattern of variable block size Water-air alternation / continuous gas injection Based on multiple rounds of chemical sealing and water-gas alternation Water-air alternation / continuous gas injection Chemical-assisted water-air alternation mode Water-air alternation / continuous gas injection Water vapor alternation after carbon dioxide thickening Water-air alternation / continuous gas injection Multi-round small-segment water-gas alternation mode

[0086] Furthermore, the established component numerical simulation technology is used to predict development indicators after the injection mode change and to calculate gas channeling index, sweep efficiency, and miscibility. The optimal scheme is selected when the gas channeling index is below a certain threshold and the sweep efficiency and miscibility are above the set conditions under the set optimization development indicator target.

[0087] The development indicators can be one or more, and can be set according to the relevant guidelines of the oil and gas industry standards based on development needs. In optional embodiments, development indicators generally include cumulative oil production, cumulative liquid production, cumulative gas production, gas-oil ratio, water cut, annual oil production, annual liquid production, annual gas production, etc.

[0088] Generally speaking, the setting of optimized development indicators refers to the situation where both the recovery rate and the oil exchange rate are improved to the set optimization target.

[0089] The present invention will be further described below with reference to specific embodiments. The scope of the present invention is not limited to the embodiments, but is defined in the claims.

[0090] Taking Block B of Oilfield A as an example, the reservoir permeability of this block is 3mD, the reservoir microfractures are not well developed, CO2 flooding has been implemented for one year, and some wells are facing gas channeling problems. Based on the actual situation of the work area, the following optimizations are carried out:

[0091] (1) Data collection

[0092] Collect original data for the target work area, including production dynamic data, various monitoring data, and three-dimensional geological models.

[0093] (2) Production dynamics historical fitting

[0094] The production history of depletion production and CO2 injection in the target work area was fitted to obtain a numerical simulation model of the components after CO2 injection that conforms to the actual reservoir conditions.

[0095] (3) Calculation of gas channeling index

[0096] Based on the production data of the entire region and each well, the gas channeling index variation curves for the entire region and each well were calculated, see [link to data]. Figure 2 .

[0097] (4) Determine the adjustment well group

[0098] Well groups with a gas channeling index greater than 100 were identified as those requiring adjustment, with well groups No. 2 and No. 3 specifically identified as requiring adjustment.

[0099] (5) Injection speed adjustment

[0100] By varying only the injection rate, the increase in oil production and component sweep efficiency of CO2 injection under different Pelet numbers were calculated. The relationship curves between Pelet number and increase in oil production and component sweep efficiency were plotted. (See...) Figure 3 The injection rate for well group 2 was adjusted from 35 tons / day to 28 tons / day; the injection rate for well group 3 was adjusted from 32 tons / day to 20 tons / day.

[0101] (6) Injection method adjustment

[0102] Based on the aforementioned adjustments, the injection method for Well Group 2 will be changed to periodic gas injection, with a 30-day injection period followed by a 10-day shutdown; the injection method for Well Group 3 will be changed to alternating water and gas injection.

[0103] (7) Determine the best solution.

[0104] The gas channeling index based on adjustment measures was calculated, and the optimal solution was selected based on a gas channeling index below a certain threshold and a high sweep efficiency and miscibility. It was found that under the optimal solution, after a period of time, the gas channeling index changed from stable to negative, indicating a certain degree of reduction in the gas-oil ratio, demonstrating the significant effect of the adjustment measures.

[0105] (8) Development indicators of the forecasting scheme

[0106] Numerical simulation of components was used to predict development indicators. Compared with the original scheme, the adjusted scheme improved the recovery rate by 2.1 percentage points, which is a significant effect.

[0107] This invention addresses the problems of prominent viscosity fingering and low sweep efficiency in CO2 flooding by providing a regulation and optimization method to improve the sealing effect of CO2 flooding in target reservoirs. The method first proposes a new parameter for evaluating gas channeling (gas channeling index) and, combined with component numerical simulation technology, analyzes the characteristics of gas channeling index changes under different adjustment schemes to determine whether adjustment is necessary. Second, using component numerical simulation technology, the injection rate of the work area is determined by calculating different Peckle numbers and component sweep efficiency. Finally, based on the optimized injection rate, component numerical simulation technology is used to determine or adjust the injection mode of the work area and predict the development indicators of the work area.

[0108] For the foregoing method embodiments, in order to simplify the description, they are all described as a series of actions. However, those skilled in the art should understand that the present invention is not limited to the described order of actions, because according to the present invention, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to the present invention.

[0109] It should be noted that, in other embodiments of the present invention, the method can also combine one or more of the above embodiments to obtain a new CO2 flooding and storage regulation optimization decision-making method, so as to achieve comprehensive and high-quality optimization of CO2 flooding technology.

[0110] Example 2

[0111] It should be noted that, based on the methods in any one or more embodiments of the present invention described above, the present invention also provides a storage medium storing program code that can implement the methods described in any one or more embodiments. When the program code is executed by the operating system, it can implement the CO2 oil recovery and storage regulation optimization decision-making method as described above.

[0112] Example 3

[0113] The methods described in detail in the above-disclosed embodiments of the present invention can be implemented using various forms of devices or systems. Therefore, based on other aspects of the methods described in any one or more of the above embodiments, the present invention also provides a CO2 enhanced oil recovery and storage regulation optimization decision-making system, which is used to execute the CO2 enhanced oil recovery and storage regulation optimization decision-making method described in any one or more of the above embodiments. Specific embodiments are given below for detailed description.

[0114] Specifically, Figure 4 The diagram shows a schematic representation of the CO2 enhanced oil recovery and storage regulation optimization decision-making system provided in an embodiment of the present invention. Figure 4 As shown, the system includes:

[0115] The data collection module is configured to acquire production-related data and a three-dimensional geological model of the target work area after the target work area is determined. The production-related data includes production dynamic data and monitoring data.

[0116] The production simulation model determination module is configured to use component numerical simulation technology to fit the production dynamic history of CO2 injection in the target work area, so as to adjust and determine the target operation parameters of the simulation operation model and obtain a production simulation operation model that matches the actual reservoir.

[0117] The gas channeling index calculation module is configured to determine the gas-oil ratio of each well in the target work area based on production dynamic data, and then calculate the corresponding gas channeling index based on the gas-oil ratio.

[0118] The well group screening module is configured to select well groups whose gas channeling index meets the set conditions as target well groups.

[0119] The injection rate optimization module is configured to analyze the Peckle number corresponding to different injection rates for the target well group. By simulating and analyzing different injection rates, it determines the relationship curve distribution between the Peckle number of CO2 injection, the amount of oil added, and the component sweep efficiency, and determines the target injection rate for optimization.

[0120] The injection mode optimization module is configured to adjust the CO2 injection mode based on the target injection rate, simulate and analyze the development parameters corresponding to different injection modes, and then determine the target injection mode of the well group based on the gas channeling index, sweep efficiency and miscibility corresponding to the development parameters.

[0121] Optionally, in one embodiment, the data collection module is configured to acquire production dynamic data including oil production, water production, gas production, water injection, and gas injection data of each production well in the target work area; and monitoring data including production profile data, water and gas intake profile data, wellhead test data, and perforation data.

[0122] Furthermore, in one embodiment, the production simulation model determination module is configured as follows:

[0123] A component numerical simulation model was established based on a three-dimensional geological model of the target work area using numerical simulation software.

[0124] The production dynamics data, perforation data, relative permeability data, high pressure physical property data, and monitoring data of the loading well are used to fit the production dynamics history of CO2 injection in the target work area;

[0125] Based on the fitted data, the target operational parameters of the simulation model are adjusted and determined to obtain a component numerical simulation model that matches the actual reservoir, which serves as the production simulation model.

[0126] In a preferred embodiment, the production simulation model determination module is configured to: compare the numerical simulation results with the actual production dynamic data; if the error exceeds the set conditions, the permeability and relative permeability data of each well need to be adjusted according to the monitoring data and the error situation, and then the numerical simulation is carried out again until the error between the numerical calculation results and the actual production data meets the set conditions.

[0127] In one embodiment, the gas channeling index calculation module calculates the gas channeling index according to the following formula:

[0128]

[0129] Where λ represents the gas channeling index; HCPV is the ratio of injected CO2 to the pore volume of hydrocarbons in the reservoir; and GOR is the gas-oil ratio.

[0130] Furthermore, in one embodiment, the injection rate optimization module calculates the Peckle number G of a well group according to the following formula:

[0131]

[0132] Where D is the diffusion coefficient, v inj Where L is the injection rate, L is the well spacing, and φ is the porosity.

[0133] In an optional embodiment, the injection rate optimization module analyzes the relationship curve between the plotted Peclet number and the component sweep efficiency to determine the distribution of inflection points on the curve, and sets the injection rate at the inflection point as the target injection rate.

[0134] Furthermore, in one embodiment, the injection mode selection module is configured to: select a scheme in which the gas channeling index is lower than the set requirement and the sweep efficiency and miscibility are higher than the set conditions under the set optimization development target as the target injection mode;

[0135] The development indicators are one or more, and are set according to the relevant guidelines of the oil and gas industry standards based on development needs; the development indicators include cumulative oil production, cumulative liquid production, cumulative gas production, gas-oil ratio, water cut, annual oil production, annual liquid production, and annual gas production.

[0136] In the CO2 enhanced oil recovery and storage regulation optimization decision system provided in this embodiment of the invention, each module or unit structure can operate independently or in combination according to actual data processing needs and simulation calculation needs, so as to achieve the corresponding technical effects.

[0137] It should be understood that the embodiments disclosed herein are not limited to the specific structures, processing steps, or materials disclosed herein, but should be extended to equivalent substitutions of these features as understood by those skilled in the art. It should also be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting.

[0138] The phrase "an embodiment" in the specification means that a specific feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the invention. Therefore, the phrase "an embodiment" appearing in various places throughout the specification does not necessarily refer to the same embodiment.

[0139] While the embodiments disclosed in this invention are as described above, the content is merely for the purpose of facilitating understanding of the invention and is not intended to limit the invention. Any person skilled in the art to which this invention pertains may make any modifications and variations in form and detail of the implementation without departing from the spirit and scope disclosed herein; however, the scope of patent protection for this invention shall still be determined by the scope defined in the appended claims.

Claims

1. A CO2-enhanced oil recovery and storage regulation optimization decision-making method, characterized in that, The method includes: Data collection steps: Identify the target work area, obtain production-related data and a three-dimensional geological model of the target work area, including production dynamic data and monitoring data; Production simulation model determination steps: Using component numerical simulation technology, the production dynamic history of CO2 injection in the target work area is fitted to adjust and determine the target operation parameters of the simulation operation model, so as to obtain a production simulation operation model that matches the actual reservoir. Gas channeling index calculation steps: Determine the gas-oil ratio of each well in the target work area based on production dynamic data, and then calculate the corresponding gas channeling index based on the gas-oil ratio; Well group selection steps: Select well groups whose gas channeling index meets the set conditions as target well groups; Injection rate optimization steps: For the target well group, analyze the Peckle number corresponding to different injection rates, and determine the relationship curve distribution between the Peckle number of CO2 injection, oil increase and component sweep efficiency through simulation analysis of different injection rates, and determine the target injection rate for optimization. Injection mode optimization steps: Based on the target injection rate, adjust the CO2 injection mode, simulate and analyze the development parameters corresponding to different injection modes, and then determine the target injection mode of the well group according to the gas channeling index, sweep efficiency and miscibility corresponding to the development parameters.

2. The method according to claim 1, characterized in that, In the data collection step, the acquired production dynamic data includes the oil production, water production, gas production, water injection, and gas injection data of each production well in the target work area; the monitoring data includes production profile data, water and gas intake profile data, wellhead test data, and perforation data.

3. The method according to claim 1, characterized in that, The steps for determining the production simulation model include: A component numerical simulation model was established based on a three-dimensional geological model of the target work area using numerical simulation software. The production dynamics data, perforation data, relative permeability data, high pressure physical property data, and monitoring data of the loading well are used to fit the production dynamics history of CO2 injection in the target work area; Based on the fitted data, the target operational parameters of the simulation model are adjusted and determined to obtain a component numerical simulation model that matches the actual reservoir, which serves as the production simulation model.

4. The method according to claim 3, characterized in that, In the production simulation model determination step, the numerical simulation results are compared with the actual production dynamic data. If the error exceeds the set conditions, the permeability and relative permeability data of each well need to be adjusted according to the monitoring data and error situation, and the numerical simulation is carried out again until the error between the numerical calculation results and the actual production data meets the set conditions.

5. The method according to claim 1, characterized in that, In the calculation of the gas channeling index, the gas channeling index is calculated according to the following formula: Where λ is the gas channeling index; HCPV is the ratio of injected CO2 to reservoir hydrocarbon pore volume; and GOR is the gas-oil ratio.

6. The method according to claim 1, characterized in that, In the injection rate optimization step, the Peckle number G of a certain well group is calculated according to the following formula: Where D is the diffusion coefficient, v inj Where L is the injection rate, L is the well spacing, and φ is the porosity.

7. The method according to claim 1, characterized in that, In the injection rate optimization step, the relationship curve between the Peclet number and the component sweep efficiency is analyzed to determine the distribution of inflection points on the curve, and the injection rate at the inflection point is taken as the target injection rate.

8. The method according to claim 1, characterized in that, In the injection mode selection step, the scheme with a gas channeling index lower than the set requirements and a sweep efficiency and miscibility higher than the set conditions under the set optimization development target is selected as the target injection mode. The development indicators are one or more, and are set according to the relevant guidelines of the oil and gas industry standards based on development needs; the development indicators include cumulative oil production, cumulative liquid production, cumulative gas production, gas-oil ratio, water cut, annual oil production, annual liquid production, and annual gas production.

9. A storage medium, characterized in that, The storage medium stores program code that can implement the method as described in any one of claims 1 to 8.

10. A CO2-enhanced oil recovery and storage regulation optimization decision-making system, characterized in that, The system performs the method as described in any one of claims 1 to 8.

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