Method for constructing carbon dioxide flooding flow field of mud pattern type shale oil reservoir

Abstract

The invention relates to the technical field of petroleum low-carbon exploitation, in particular to a mud pattern type shale oil reservoir carbon dioxide flooding flow field construction method which comprises the steps that the CO2 gas injection speed, the production well flow pressure and the oil change rate in the CO2 oil flooding process are obtained; the flow pressure change condition of the production well is analyzed to construct a flow pressure fluctuation value, the flow pressure fluctuation influence degree is obtained according to the difference between the change condition of the flow pressure fluctuation value and the change condition of the gas injection speed, the change degree of the oil change rate is combined, and the optimization control strength of each optimization stage is constructed. And a gas injection speed optimization value is obtained through the difference between the gas injection speed at each sampling moment in each optimization stage and a preset gas injection speed expected value, and a CO2 gas source is injected into a gas injection well based on the gas injection speed optimization value, so that a CO2 drive flow field is formed. According to the method, the shale oil recovery rate can be increased.

Description

Technical Field

[0001] The present application relates to the technical field of low-carbon petroleum mining, and in particular to a method for constructing a carbon dioxide flooding flow field in a muddy shale reservoir. Background Art

[0002] Muddy shale reservoirs differ from conventional reservoirs in that they are primarily composed of micro- and nano-scale pores, resulting in low permeability and porosity. Large-scale fracturing and depletion development using horizontal wells is widely used both domestically and internationally, with primary recovery rates typically ranging from 2% to 8%, rarely exceeding 10%. The abundant reserves and relatively low recovery rates of shale oil provide significant potential for the development of shale oil enhanced recovery technologies, leading to active research.

[0003] The use of CO2 (carbon dioxide) to improve the recovery of shale oil reservoirs is currently the main research direction, but there are still some problems. First, although the injection of CO2 as a displacement medium after large-scale fracturing of horizontal wells is not a problem, the CO2 injection rate is difficult to set, and due to the low permeability of the matrix, the throughput range is limited and the oil displacement effect is poor, making it difficult to significantly increase the shale oil recovery rate; second, after large-scale fracturing of horizontal wells, the displacement of cross-wells is easy to flow through the fractures due to the interconnection between the fractures, making the matrix difficult to mobilize and the affected volume limited, making it difficult to significantly increase the shale oil recovery rate; third, due to the extremely low permeability of the shale reservoirs in muddy shale oil reservoirs, it is difficult to establish an effective displacement system between wells in traditional vertical well injection and production patterns.

[0004] Therefore, for the injection and production wells of muddy shale oil reservoirs, CO2 is injected after conventional fracturing. How to optimize the CO2 injection rate and effectively control the flow pressure of the production wells to form a stable and reliable CO2 flooding field and an effective injection and production well displacement system is the key to solving the problem of low shale oil recovery efficiency. Summary of the Invention

[0005] In order to solve the above technical problems, the present application provides a method for constructing a carbon dioxide flooding flow field in a muddy shale oil reservoir to solve the existing problems.

[0006] The present invention discloses a method for constructing a carbon dioxide flooding flow field in a muddy shale reservoir using the following technical solutions:

[0007] One embodiment of the present application provides a method for constructing a carbon dioxide flooding flow field in a muddy shale reservoir, comprising the following steps:

[0008] Numerical simulation of CO2 flooding after conventional fracturing of shale oil vertical wells was conducted to obtain the CO2 injection rate, production and oil change rate during the CO2 flooding process, and the CO2 flooding process was divided into multiple optimization stages;

[0009] Based on the change of production well flow pressure at each sampling moment relative to other sampling moments in each optimization stage, the flow pressure fluctuation value at each sampling moment in each optimization stage is constructed. According to the difference between the change of flow pressure fluctuation value in each optimization stage and the change of CO2 injection rate, the flow pressure fluctuation influence degree at each sampling moment in each optimization stage is obtained.

[0010] According to the average level of the flow pressure fluctuation influence in each optimization stage and the difference in the flow pressure fluctuation influence at different sampling moments, and combined with the degree of change of the oil change rate at all sampling moments in each optimization stage, the optimization control strength of each optimization stage is constructed;

[0011] By utilizing the optimization control strength of each optimization stage and combining the difference between the CO2 injection rate at each sampling moment in each optimization stage and the preset CO2 injection rate expectation value, the optimized injection rate value at each sampling moment in each optimization stage is obtained. This value is used as the injection rate in the injection well during the CO2 flooding process to inject the CO2 gas source into the injection well and form a CO2 flooding flow field.

[0012] Preferably, the optimization stage division process is: dividing the CO2 flooding process into multiple time periods, each time period corresponding to an optimization stage.

[0013] Preferably, the calculation method of the flow pressure fluctuation value at each sampling moment in each optimization stage is:

[0014] Where, DP t,j is the flow pressure fluctuation value at the jth sampling moment in the tth optimization stage, H is the number of sampling moments in the tth optimization stage, P t,j and P t,i are the production well flowing pressures at the j-th and i-th sampling moments in the t-th optimization stage, respectively.

[0015] Preferably, the method for calculating the flow pressure fluctuation influence degree includes:

[0016] According to the change rate of the flow pressure fluctuation value and the change rate of the CO2 injection rate in each optimization stage, the gradient change vector of the injection rate and the gradient change vector of the flow pressure fluctuation in each optimization stage are constructed;

[0017] The difference vector between the gradient change vector of the gas injection velocity and the flow pressure fluctuation in each optimization stage is calculated, and the inverse of the absolute value of each element in the difference vector is obtained as the flow pressure fluctuation influence degree at each sampling moment in each optimization stage.

[0018] Preferably, the construction of the gradient change vector of the gas injection velocity and the gradient change vector of the flow pressure fluctuation in each optimization stage includes:

[0019] The CO2 injection velocity change slope and the flow pressure fluctuation value change slope at each sampling moment in each optimization stage are calculated respectively. The CO2 injection velocity change slopes at all sampling moments in each optimization stage are arranged in chronological order to form the gradient change vector of the injection velocity in each optimization stage. The flow pressure fluctuation value change slopes at all sampling moments in each optimization stage are arranged in chronological order to form the gradient change vector of the flow pressure fluctuation in each optimization stage.

[0020] Preferably, the process of obtaining the CO2 injection velocity change slope and the flow pressure fluctuation value change slope is as follows:

[0021] Curve fitting was performed on the CO2 injection rate and flow pressure fluctuation values ​​at all sampling moments in each optimization stage, and the slopes of the CO2 injection rate and flow pressure fluctuation values ​​at each sampling moment on the fitting curve were counted as the change slopes of the CO2 injection rate and flow pressure fluctuation values ​​at each sampling moment.

[0022] Preferably, the calculation method for the optimization control strength of each optimization stage is:

[0023] Where Vg t is the optimization control strength of the tth optimization stage, Gs t is the probability of gas channeling intensification in the t-th optimization stage, H is the number of sampling moments in the t-th optimization stage, Xc t is the average value of all flow pressure fluctuation influences in the tth optimization stage, fc t,k and fc t,k-1 are the flow pressure fluctuation influence degrees at the kth and k-1th sampling moments in the tth optimization stage, and ∈ is a constant to avoid the denominator being zero.

[0024] Preferably, the method for calculating the probability of gas channeling aggravation further includes:

[0025] Gs t =1-exp(-Xu t ), where exp() is an exponential function with a natural constant as the base, Xu t is the significant change value of the oil change rate in the t-th optimization stage, which is obtained by the change of the oil change rate at all sampling moments in the t-th optimization stage.

[0026] Preferably, the oil change rates at all sampling moments in the t-th optimization stage are combined into an oil change rate vector, the cumulative sum of all negative values ​​in the first-order difference vector of the oil change rate vector is statistically calculated, and the absolute value of the cumulative sum is used as the significant value of the oil change rate change in the t-th optimization stage.

[0027] Preferably, the calculation method of the optimized value of the gas injection velocity at each sampling moment in each optimization stage is:

[0028] V t,j =Vr t,j -(Vr t,j -Vp)×norm(Vg t ), where V t,j 、Vr t,j are respectively the optimized value of gas injection velocity and CO2 injection velocity at the jth sampling moment in the tth optimization stage, Vg t is the optimization control strength of the tth optimization stage, norm() is the normalization function, and Vp is the preset CO2 injection rate expectation.

[0029] This application has at least the following beneficial effects:

[0030] This application is based on the analysis of the fluctuation characteristics of the flow pressure of the production well, constructs a flow pressure fluctuation value, and the flow pressure fluctuation value reflects the fluctuation characteristics of the flow pressure of the production well caused by gas channeling due to excessive CO2 injection rate during CO2 oil recovery. According to the difference between the injection rate and the gradient change of flow pressure fluctuation in each optimization stage, the flow pressure fluctuation influence degree is constructed. The flow pressure fluctuation influence degree reflects the degree of influence of the injection rate on the flow pressure fluctuation in the bottom of the production well, which is used to more accurately analyze the influence relationship between the CO2 injection rate and the change of the fluctuation characteristics of the flow pressure of the production well during CO2 oil recovery, so as to more accurately determine the CO2 injection rate during CO2 oil recovery;

[0031] At the same time, based on the analysis of the significant probability of the gas channeling aggravation characteristics of CO2 fluid in the fractures between the production well and the gas injection well, the gas channeling aggravation probability is constructed, and combined with the influence of the flow pressure fluctuation, the optimization control strength is constructed. The optimization control strength reflects the magnitude of the CO2 injection rate adjustment strength during the CO2 flooding process. The greater the optimization control strength, the higher the weight of the optimization adjustment of the CO2 injection rate in the optimization stage. Ultimately, the gas injection rate in the CO2 flooding process is optimized and adjusted, so that CO2 is evenly distributed in the shale reservoir of the muddy shale oil reservoir and a stable and reliable CO2 flooding flow field is formed, making the optimized control gas injection rate more suitable for shale oil recovery in the muddy shale oil reservoir.

[0032] Therefore, this application injects CO2 into the injection and production wells of the muddy shale oil reservoir after conventional fracturing. By optimizing the CO2 injection rate, the CO2 is evenly distributed in the shale reservoir of the muddy shale oil reservoir and the oil is efficiently driven, forming a stable and reliable CO2 drive flow field and an effective injection and production well displacement system, solving the problem of low shale oil recovery efficiency in the existing technology, thereby greatly improving the shale oil recovery efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present application or the prior art, the following is a brief introduction to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0034] Figure 1 A flowchart of the steps of a method for constructing a carbon dioxide flooding flow field in a muddy shale reservoir provided in this application;

[0035] Figure 2 Schematic diagram of vertical well fracturing and main fracture displacement provided in this application. DETAILED DESCRIPTION

[0036] To further illustrate the technical means and effectiveness of this application's implementation of the intended invention, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effectiveness of a method for constructing a CO2 flooding flow field in a muddy shale reservoir proposed in this application. In the following description, references to different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.

[0037] Unless otherwise defined, terms such as "comprises," "comprising," or any other variants thereof are intended to encompass non-exclusive inclusion, such that a circuit structure, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such article or device. In the absence of further restrictions, an element defined by the phrase "comprising a ..." does not exclude the presence of additional identical elements in the article or device comprising the element. In addition, the term "and\or" as used herein includes any and all combinations of one or more related listed items. All technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application pertains.

[0038] The specific scheme of the method for constructing a carbon dioxide flooding flow field in a muddy shale oil reservoir provided by the present application is described in detail below with reference to the accompanying drawings.

[0039] An embodiment of the present application provides a method for constructing a carbon dioxide flooding flow field in a muddy shale reservoir. For details, please refer to Figure 1 , including the following steps:

[0040] Step 1: Numerical simulation of CO2 flooding after conventional fracturing of shale oil vertical wells is performed to obtain the CO2 injection rate, production well flow pressure and oil change rate during the CO2 flooding process, and the CO2 flooding process is divided into multiple optimization stages.

[0041] The purpose of the present invention is to inject CO2 into the injection and production wells of the muddy shale oil reservoir after conventional fracturing. By accurately optimizing and controlling the CO2 injection rate, the CO2 is evenly distributed in the shale reservoir of the muddy shale oil reservoir and the oil is efficiently displaced, forming a stable and reliable CO2 displacement field and an effective injection and production well displacement system, thereby solving the problem of low shale oil recovery efficiency in the existing technology and greatly improving the shale oil recovery efficiency.

[0042] Muddy shale reservoirs include injection wells and production wells, all of which are developed using conventional fracturing technology. The reservoir sections of the injection wells and production wells are all perforated and fractured to form a fracture network. The fracture network allows the CO2 injection fluid to flow in the reservoir and come into contact with the crude oil, thereby improving the fluidity and recovery rate of the crude oil.

[0043] In this embodiment, the schematic diagram of vertical well fracturing and main fracture displacement is as follows: Figure 2 As shown, Figure 2 The figure includes injection wells and production wells on both sides. The blue arrow in the fracture network indicates the displacement direction, the red arrow indicates the fracture extension direction, and the cube represents the underground reservoir for storing crude oil. The injection well is used to inject CO2 fluid into the reservoir using an injection pump to increase the reservoir pressure, and drive the crude oil to the production well through the effect of CO2 oil displacement, and the production well is used to produce oil using an oil pump.

[0044] At the same time, the muddy shale oil reservoir adopts vertical well pattern to inject CO2 fluid. The injection well row is consistent with the direction of the maximum horizontal principal stress of the reservoir. The injection well spacing is determined according to the length of the fracture stimulation. The injection well spacing is equal to the fracture length, and the row spacing is determined according to the horizontal permeability of the reservoir.

[0045] However, since it is difficult to set the CO2 injection rate, it is impossible to effectively control the flow pressure of the oil wells, and thus it is impossible to form a stable and reliable CO2 flooding field and an effective injection-production well displacement system, resulting in a low shale oil recovery rate in muddy shale reservoirs.

[0046] In order to optimize the CO2 injection rate, form a stable and reliable CO2 flooding flow field and an effective injection-production well displacement system, a formation fluid model is established using geological data and logging data from the muddy shale oil reservoir area. The geological data and logging data include reservoir porosity, permeability, fracture half-length, reservoir temperature, formation oil viscosity, etc., and CMG numerical simulation software (Computer Modelling Group) is used to perform numerical simulation of CO2 oil displacement, and simulated results of CO2 injection rate, production well flow pressure, and oil change rate during the CO2 oil displacement process are obtained. Among them, the construction of the formation fluid model and the numerical simulation of CO2 oil displacement are both well-known technologies, and the specific process will not be repeated here.

[0047] In this embodiment, the CO2 flooding process is divided into multiple optimization stages, that is, the duration of the CO2 flooding process is divided into multiple optimization stages. In this embodiment, the optimization stages are evenly divided into K stages, where K is 18. It should be noted that in actual application scenarios, implementers can make their own divisions based on actual conditions.

[0048] Step 2: Based on the changes in the flow pressure of the production wells at each sampling moment relative to other sampling moments in each optimization stage, the flow pressure fluctuation value at each sampling moment in each optimization stage is constructed. According to the difference between the changes in the flow pressure fluctuation value in each optimization stage and the changes in the CO2 injection rate, the flow pressure fluctuation influence at each sampling moment in each optimization stage is obtained.

[0049] Generally speaking, optimizing and controlling the CO2 injection rate is crucial in CO2 flooding technology for muddy shale reservoirs. Optimizing and controlling a reasonable CO2 injection rate can form a stable and reliable CO2 flooding flow field, control the flow pressure of the oil well, and avoid pressure sensitivity damage caused by unreasonable injection-production pressure differentials. This is of great significance for replenishing formation energy and increasing oil production rates. Furthermore, dividing the CO2 flooding process for muddy shale reservoirs into different optimization stages facilitates more accurate optimization and control of the CO2 injection rate, thereby significantly improving shale oil recovery.

[0050] At the same time, if the CO2 injection rate is too low during the CO2 fluid injection process, it will affect the oil production rate, while if the CO2 injection rate is too high, it will easily lead to gas channeling, causing the flow pressure of the production well to fluctuate unstably, which will reduce the oil change rate and have the risk of fracturing the formation.

[0051] The suitable flow pressure characteristics during the CO2 fluid injection process are measured to more accurately optimize and control the CO2 injection rate. Based on the change in flow pressure of the production well at each sampling moment relative to other sampling moments in each optimization stage, the flow pressure fluctuation value at each sampling moment in each optimization stage is constructed. In this embodiment, the specific calculation formula is:

[0052] Where, DP t,j is the flow pressure fluctuation value at the jth sampling moment in the tth optimization stage, H is the number of sampling moments in the tth optimization stage, P t,j and P t,i are the production well flowing pressures at the j-th and i-th sampling moments in the t-th optimization stage, respectively.

[0053] Among them, the flow pressure fluctuation value reflects the fluctuation characteristics of the flow pressure of the production well caused by gas channeling due to excessive CO2 injection rate during CO2 oil recovery. The greater the difference in the flow pressure of the production well between different sampling times, the more significant the fluctuation characteristics of the flow pressure of the production well caused by gas channeling due to excessive CO2 injection rate, and the more it reflects the poor suitability of CO2 injection, and the greater the flow pressure fluctuation value.

[0054] Therefore, the flow pressure fluctuation values ​​at all sampling moments in each optimization stage can be obtained. The flow pressure fluctuation values ​​at all sampling moments in each optimization stage reflect the changes in the fluctuation characteristics of the flow pressure of the production well during the CO2 flooding process. The greater the fluctuation characteristics, the more likely it is to be affected by the excessively high CO2 injection rate, which is prone to gas channeling and affects the efficiency of CO2 flooding.

[0055] Furthermore, the influence relationship between the CO2 injection rate and the change in the fluctuation characteristics of the flow pressure of the production well during the CO2 oil recovery process is analyzed. In this embodiment, the CO2 injection rate change slope and the flow pressure fluctuation value change slope at each sampling moment in the t-th optimization stage are calculated respectively, and the vector composed of the CO2 injection rate change slopes at all sampling moments in the t-th optimization stage in chronological order is recorded as the gradient change vector of the injection rate in the t-th optimization stage.

[0056] Similarly, the vector consisting of the slopes of the flow pressure fluctuation values ​​at all sampling moments in the t-th optimization stage, in chronological order, is recorded as the gradient change vector of the flow pressure fluctuation in the t-th optimization stage. It should be noted that the slope of the CO2 injection rate change and the slope of the flow pressure fluctuation value change at each sampling moment in each optimization stage are obtained using existing techniques. By performing curve fitting on the CO2 injection rate and flow pressure fluctuation values ​​at all sampling moments in the optimization stage, the slope of the CO2 injection rate change and the slope of the flow pressure fluctuation value change corresponding to each sampling moment can be obtained.

[0057] Among them, the gradient change vectors of the injection rate and flow pressure fluctuation in the t-th optimization stage reflect the gradient change of the injection rate and the gradient change of the flow pressure fluctuation in the bottom of the production well during the CO2 oil recovery process, respectively. If the difference between the two is smaller, it means that the injection rate has a greater impact on the flow pressure fluctuation in the bottom of the production well during this optimization stage, reflecting that the CO2 injection rate is more unsuitable at this time, and a stable and reliable CO2 flooding flow field cannot be effectively formed. The calculation of the slope is a well-known technology, and the specific process will not be repeated here.

[0058] Furthermore, in this embodiment, the difference vector between the gradient change vectors of the gas injection velocity and the flow pressure fluctuation in the t-th optimization stage is calculated, and the inverse of the absolute value of each element in the difference vector is obtained and recorded as the flow pressure fluctuation influence degree at each sampling moment in the t-th optimization stage.

[0059] It should be noted that, to avoid the denominator being zero during the reciprocal calculation, a constant is added to the denominator to prevent it from being zero. The value range is 0 to 0.1, and in this embodiment, the value is 0.001. In actual application scenarios, the implementer can set it at will. The flow pressure fluctuation influence degree reflects the degree of influence of the injection rate on the flow pressure fluctuation in the bottom of the production well. The greater the flow pressure fluctuation influence degree, the more unsuitable the CO2 injection rate is at that time, and the less likely it is to effectively form a stable and reliable CO2 flooding flow field.

[0060] Step 3: Based on the average level of the flow pressure fluctuation influence in each optimization stage and the difference in the flow pressure fluctuation influence at different sampling moments, and combined with the degree of change in the oil change rate at all sampling moments in each optimization stage, the optimization control strength of each optimization stage is constructed.

[0061] Generally speaking, the stronger the continuity between the flow pressure fluctuation influence degrees within the optimization stage, and the higher the average level of all flow pressure fluctuation influence degrees within the optimization stage, the longer-term impact of the injection rate on the production well flow pressure fluctuation characteristics during the CO2 flooding stage is. At this time, the higher the risk of fracturing the formation, the more necessary it is to optimize the injection rate within the optimization stage. At the same time, the more significant the downward trend in the oil exchange rate during the CO2 flooding process, the greater the impact of formation heterogeneity during the CO2 fluid injection process. The higher the CO2 injection rate, the more severe the CO2 fluid gas channeling, causing the CO2 oil exchange rate to show a downward trend.

[0062] Based on the above analysis, the oil change rates at all sampling moments in the t-th optimization stage are combined into an oil change rate vector. The cumulative sum of all negative values ​​in the first-order difference vector of the oil change rate vector is calculated, and the absolute value of the cumulative sum is used as the oil change rate change significance value of the t-th optimization stage. Based on the oil change rate change significance value of each optimization stage, the probability of gas channeling aggravation in each optimization stage is calculated. In this embodiment, the specific calculation formula is:

[0063] Gs t =1-exp(-Xu t ), where Gs t is the probability of gas channeling intensification in the t-th optimization stage, exp() is an exponential function with a natural constant as the base, Xu t is the significant value of oil change rate change in the tth optimization stage.

[0064] Among them, the probability of gas channeling aggravation reflects the significance probability of the gas channeling aggravation feature of CO2 fluid in the fractures between the production well and the gas injection well. The greater the significance value of the oil change rate change, the more significant the downward trend of the oil change rate during the CO2 oil displacement process, and the more likely it is to aggravate the gas channeling feature of the CO2 fluid. In other words, the greater the significance probability of the gas channeling aggravation feature, the greater the probability of gas channeling aggravation, and the more necessary it is to optimize the gas injection rate in this optimization stage.

[0065] According to the average level of all flow pressure fluctuation influences in each optimization stage and the differences in the influences of different flow pressure fluctuations, and combined with the probability of gas channeling aggravation in each optimization stage, the optimization control strength of each optimization stage is constructed. In this embodiment, the specific calculation formula is:

[0066] Where Vg t is the optimization control strength of the t-th optimization stage, H is the number of sampling moments in the t-th optimization stage, Xc t is the average value of all flow pressure fluctuation influences in the tth optimization stage, fc t,k and fc t,k-1 are the flow pressure fluctuation influence degrees at the kth and k-1th sampling moments in the tth optimization stage, respectively. ∈ is a constant to avoid the denominator being zero, and its value range is 0 to 0.1. In this embodiment, it is 0.001.

[0067] Among them, the smaller the difference between different flow pressure fluctuation influence degrees in the optimization stage, the stronger the continuity between the flow pressure fluctuation influence degrees, and the higher the average level of flow pressure fluctuation influence degrees and the greater the probability of gas channeling. At this time, the gas injection rate in the CO2 oil recovery stage has a long-term impact on the fluctuation characteristics of the flow pressure of the production well. At this time, the risk of fracturing the formation is higher, the more necessary it is to optimize the gas injection rate in the optimization stage, and the greater the optimization control intensity.

[0068] Step 4: Utilize the optimization control strength of each optimization stage, combine the difference between the CO2 injection rate at each sampling moment in each optimization stage and the preset CO2 injection rate expectation value, obtain the injection rate optimization value at each sampling moment in each optimization stage, and use it as the injection rate in the injection well during the CO2 flooding process to inject the CO2 gas source into the injection well to form a CO2 flooding flow field.

[0069] Furthermore, in this embodiment, based on the optimization control strength of the CO2 injection rate in each optimization stage, combined with the difference between the CO2 injection rate at each sampling moment in each optimization stage and the preset CO2 injection rate expected value, the injection rate optimization value at each sampling moment in each optimization stage is obtained. The specific calculation formula is:

[0070] V t,j =Vr t,j -(Vr t,j -Vp)×norm(Vg t ), where Vt ,j is the optimized value of the gas injection velocity at the jth sampling moment in the tth optimization stage, Vr t,j is the CO2 injection rate at the jth sampling moment in the tth optimization stage, Vp is the preset expected value of the CO2 injection rate, in this embodiment, Vp is 15,000 cubic meters per day, and norm() is the normalization function.

[0071] Furthermore, the injection velocity optimization values ​​at all sampling moments in each optimization stage constitute the CO2 injection velocity optimization adjustment vector of each optimization stage, specifically: V(t)=(V t,1 ,V t,2 ,V t,3 ,…,V t,n ), where V(t) is the optimized adjustment vector of CO2 injection rate in the tth optimization stage, V t,1 、V t,2 、V t,3 and V t,n are the optimized injection velocity values ​​at the first, second, third, and nth sampling moments in the CO2 injection velocity subvector of the tth optimization stage, respectively, where V t,n is the optimized value of the injection rate at the last sampling moment in the CO2 injection rate subvector of the tth optimization stage.

[0072] It can be understood that in this embodiment, V t,j In the process of obtaining Vr, the normalized result of the optimization control strength is used as the adjustment weight to optimize the CO2 injection rate in the optimization stage, where (Vr t,j -Vp) has positive and negative directions. If the CO2 injection rate is higher than the expected value of the CO2 injection rate, it is optimized and adjusted downward; if the CO2 injection rate is lower than the expected value of the CO2 injection rate, it is optimized and adjusted upward, so that the injection rate after optimization control can significantly reduce the gas channeling phenomenon between fractures in the formation, making it more convenient to recover shale oil in muddy shale oil reservoirs, improving the oil exchange rate of shale oil, and preventing the risk of formation fracture pressure caused by excessive injection rate.

[0073] In this embodiment, in order to form a stable and reliable CO2 flooding flow field and an effective injection-production well displacement system during the CO2 flooding process, the optimization adjustment vectors of the CO2 injection rate in each optimization stage are composed of a vector in chronological order, which is recorded as the CO2 injection rate optimization vector in the CO2 flooding process after optimized control.

[0074] Perforation fracturing was performed in a reservoir with an effective thickness of 94.5 meters, forming east-west main fractures with a half-fracture length of 150 meters and a fracture height equal to the effective thickness of 94.5 meters. Furthermore, the injection pressure at the injection well did not exceed 32 MPa, while the wellbore pressure at the production well was 20 MPa. The injection rate within the optimized CO2 injection velocity vector during the optimized CO2 flooding process was used as the actual injection rate during the CO2 flooding process. The CO2 source gas was injected into the injection well via the injection pump in the CO2 flooding system, ensuring uniform distribution of CO2 within the shale reservoir of the muddy shale reservoir and forming a stable and reliable CO2 flooding flow field. The shale oil in the production well was then recovered by the production pump in the CO2 flooding system. The CO2 flooding system was equipped with an oil-gas separator, which recycled the separated CO2 fluid back into the injection well, improving reservoir control and oil washing efficiency, significantly increasing shale oil recovery.

[0075] It is understood that references to "one embodiment" or "some embodiments" in the present specification mean that one or more embodiments of the present application include a particular feature, structure, or characteristic described in conjunction with that embodiment. Thus, if "in one embodiment," "in some embodiments," "in other embodiments," or "in other embodiments" appear in different places in this specification, they do not necessarily refer to the same embodiment, but rather mean "one or more but not all embodiments," unless otherwise specifically emphasized. The terms "including," "comprising," "having," and their variations all mean "including but not limited to," unless otherwise specifically emphasized.

[0076] It should be noted that the above-mentioned sequence of the embodiments of the present application is for description only and does not represent the advantages and disadvantages of the embodiments. The above description is of a specific embodiment of this specification. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multi-tasking and parallel processing are also possible or may be advantageous. At the same time, the size of the sequence number of each step in the embodiment does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments in this specification.

[0077] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present application, and should all be included in the scope of protection of the present application.

Claims

1. A method for constructing a carbon dioxide flooding flow field in a muddy shale reservoir, characterized in that: The following steps are involved: Numerical simulation of CO2 flooding after conventional fracturing of shale oil vertical wells was conducted to obtain the CO2 injection rate, production well flow pressure, and oil change rate during the CO2 flooding process, and the CO2 flooding process was divided into multiple optimization stages. Based on the change of production well flow pressure at each sampling moment relative to other sampling moments in each optimization stage, the flow pressure fluctuation value at each sampling moment in each optimization stage is constructed. According to the difference between the change of flow pressure fluctuation value in each optimization stage and the change of CO2 injection rate, the flow pressure fluctuation influence degree at each sampling moment in each optimization stage is obtained. According to the average level of the flow pressure fluctuation influence in each optimization stage and the difference in the flow pressure fluctuation influence at different sampling moments, and combined with the degree of change of the oil change rate at all sampling moments in each optimization stage, the optimization control strength of each optimization stage is constructed; By utilizing the optimization control strength of each optimization stage and combining the difference between the CO2 injection rate at each sampling moment in each optimization stage and the preset CO2 injection rate expectation value, the optimized injection rate value at each sampling moment in each optimization stage is obtained. This value is used as the injection rate in the injection well during the CO2 flooding process to inject the CO2 gas source into the injection well and form a CO2 flooding flow field.

2. The method for constructing a carbon dioxide flooding flow field in a muddy shale reservoir according to claim 1, wherein: The optimization stage division process is as follows: the CO2 flooding process is divided into multiple time periods, each time period corresponding to an optimization stage.

3. The method for constructing a carbon dioxide flooding flow field in a muddy shale reservoir according to claim 1, wherein: The calculation method of the flow pressure fluctuation value at each sampling moment in each optimization stage is: Where, DP t,j is the flow pressure fluctuation value at the jth sampling moment in the tth optimization stage, H is the number of sampling moments in the tth optimization stage, P t,j and P t,i are the production well flowing pressures at the j-th and i-th sampling moments in the t-th optimization stage, respectively.

4. The method for constructing a carbon dioxide flooding flow field in a muddy shale reservoir according to claim 1, wherein: The calculation method of the flow pressure fluctuation influence degree includes: According to the change rate of the flow pressure fluctuation value and the change rate of the CO2 injection rate in each optimization stage, the gradient change vector of the injection rate and the gradient change vector of the flow pressure fluctuation in each optimization stage are constructed; The difference vector between the gradient change vector of the gas injection velocity and the flow pressure fluctuation in each optimization stage is calculated, and the inverse of the absolute value of each element in the difference vector is obtained as the flow pressure fluctuation influence degree at each sampling moment in each optimization stage.

5. The method for constructing a carbon dioxide flooding flow field in a muddy shale reservoir according to claim 4, wherein: The construction of the gradient change vector of the gas injection velocity and the gradient change vector of the flow pressure fluctuation in each optimization stage includes: The CO2 injection velocity change slope and the flow pressure fluctuation value change slope at each sampling moment in each optimization stage are calculated respectively. The CO2 injection velocity change slopes at all sampling moments in each optimization stage are arranged in chronological order to form the gradient change vector of the injection velocity in each optimization stage. The flow pressure fluctuation value change slopes at all sampling moments in each optimization stage are arranged in chronological order to form the gradient change vector of the flow pressure fluctuation in each optimization stage.

6. The method for constructing a carbon dioxide flooding flow field in a muddy shale reservoir according to claim 5, wherein: The process of obtaining the CO2 injection velocity change slope and the flow pressure fluctuation value change slope is as follows: Curve fitting was performed on the CO2 injection rate and flow pressure fluctuation values ​​at all sampling moments in each optimization stage, and the slopes of the CO2 injection rate and flow pressure fluctuation values ​​at each sampling moment on the fitting curve were counted as the change slopes of the CO2 injection rate and flow pressure fluctuation values ​​at each sampling moment.

7. The method for constructing a carbon dioxide flooding flow field in a muddy shale reservoir according to claim 1, wherein: The corresponding calculation method for the optimization control strength of each optimization stage is: Where Vg t is the optimization control strength of the tth optimization stage, Gs t is the probability of gas channeling intensification in the t-th optimization stage, H is the number of sampling moments in the t-th optimization stage, Xc t is the average value of all flow pressure fluctuation influences in the tth optimization stage, fc t,k and fc t,k-1 are the flow pressure fluctuation influence degrees at the kth and k-1th sampling moments in the tth optimization stage, and ∈ is a constant to avoid the denominator being zero.

8. The method for constructing a carbon dioxide flooding flow field in a muddy shale reservoir according to claim 7, wherein: The method for calculating the probability of gas channeling aggravation further includes: Gs t =1-exp(-Xu t ), where exp() is an exponential function with a natural constant as the base, Xu t is the significant change value of the oil change rate in the t-th optimization stage, which is obtained by the change of the oil change rate at all sampling moments in the t-th optimization stage.

9. The method for constructing a carbon dioxide flooding flow field in a muddy shale reservoir according to claim 8, wherein: The oil change rates at all sampling moments in the t-th optimization stage are combined into an oil change rate vector, the cumulative sum of all negative values ​​in the first-order difference vector of the oil change rate vector is calculated, and the absolute value of the cumulative sum is used as the significant value of the oil change rate change in the t-th optimization stage.

10. The method for constructing a carbon dioxide flooding flow field in a muddy shale reservoir according to claim 1, wherein: The calculation method of the optimized value of the gas injection velocity at each sampling moment in each optimization stage is: V t,j =Vr t,j -(Vr t,j -Vp)×norm(Vg t ), where V t,j 、Vr t,j are respectively the optimized value of gas injection velocity and CO2 injection velocity at the jth sampling moment in the tth optimization stage, Vg t is the optimization control strength of the tth optimization stage, norm() is the normalization function, and Vp is the preset expected value of CO2 injection rate.

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