In-layer invalid cycle identification method and device based on oil reservoir displacement unit

Abstract

The invention relates to an in-layer invalid cycle identification method and device based on an oil reservoir displacement unit, and the method comprises the steps: determining the influence degree of each geological factor and each development factor on the occurrence time of an invalid cycle in the oil reservoir displacement unit through a multi-factor and multi-level orthogonal test; according to the influence degree of each geological factor and each development factor on the invalid cycle occurrence opportunity in the oil reservoir displacement unit, establishing an invalid cycle occurrence opportunity prediction model; based on the invalid cycle occurrence opportunity prediction model, a recovery degree prediction value of the actual displacement unit is determined, and a recovery degree actual value of the actual displacement unit is determined through the black oil model; and determining an invalid cycle identification result according to the predicted value of the recovery degree and the actual value of the recovery degree. According to the method, the invalid cycle in the oil reservoir can be quantitatively represented and identified, and the formation opportunity of the invalid cycle in the actual displacement unit can be predicted.

Description

Technical Field

[0001] The invention relates to a method and a device for identifying invalid circulation within a layer based on an oil reservoir displacement unit. Background Art

[0002] Two key characteristics of oilfields entering the extremely high water-cut phase are increasing ineffective circulation and a growing proportion of residual oil within the strata. Therefore, managing ineffective circulation and recovering the remaining oil within the interwell zones have become key areas of focus for future development adjustments. As most mature oilfields enter the high-water-cut phase and ineffective circulation worsens, it is necessary to conduct in-depth research into the specific timing of ineffective water circulation during oilfield development, analyze the factors that may influence its occurrence, identify the primary factors that control its occurrence, and implement timely and effective remediation measures.

[0003] The reservoir displacement unit is the most basic unit for the occurrence of invalid cycles. The study of reservoir displacement units is the starting point for invalid cycle research. To accurately identify and control invalid cycles, it is necessary to analyze and accurately grasp the main controlling factors of invalid cycles in the reservoir displacement unit, such as geology, development dynamics, well patterns, and measures. Characterizing invalid cycles within the reservoir layer is of great significance for accurately determining the formation time of invalid cycles within the reservoir displacement unit. Summary of the Invention

[0004] In order to quantitatively characterize and identify the problem of invalid circulation within the reservoir layer and predict the timing of invalid circulation formation within the actual displacement unit, the present invention proposes a method and device for identifying invalid circulation within the layer based on the reservoir displacement unit. The technical solution proposed by the present invention is as follows:

[0005] In a first aspect, the present invention provides a method for identifying invalid cycles within a layer based on a reservoir displacement unit, comprising:

[0006] Using multi-factor and multi-level orthogonal experiments, we determined the influence of various geological and development factors on the occurrence of invalid cycles within the reservoir displacement unit.

[0007] According to the influence of various geological factors and development factors on the occurrence of invalid cycle in the reservoir displacement unit, a prediction model for the occurrence of invalid cycle is established;

[0008] Determining a predicted value of the recovery degree of an actual displacement unit based on the invalid cycle occurrence timing prediction model, and determining an actual value of the recovery degree of the actual displacement unit through a black oil model;

[0009] An invalid cycle identification result is determined according to the predicted value of the recovery degree and the actual value of the recovery degree.

[0010] In one or some embodiments, the use of multi-factor multi-level orthogonal experiments to determine the degree of influence of various geological factors and development factors on the timing of occurrence of invalid cycles in the reservoir displacement unit includes:

[0011] Establish multiple orthogonal test plans based on the selected combinations of geological factors and development factors at different levels;

[0012] Based on actual formation data, orthogonal test mechanism models corresponding to each of the orthogonal test schemes are established through the black oil model;

[0013] Performing numerical simulation using the orthogonal test mechanism model until an invalid cycle occurs in the reservoir displacement unit, thereby obtaining orthogonal test data;

[0014] The orthogonal test data corresponding to different orthogonal test schemes are analyzed using the range analysis method to determine the degree of influence of various geological factors and development factors on the timing of occurrence of invalid cycles in the reservoir displacement unit.

[0015] In one or some embodiments, the geological factors include permeability gradient, permeability variation coefficient and porosity, and the development factors include injection intensity, injection-production well spacing and well pattern type;

[0016] According to the combination of geological factors and development factors at different levels, multiple orthogonal test schemes are established, including:

[0017] Multiple orthogonal test schemes were established based on the selected combinations of different levels of permeability difference, permeability variation coefficient, porosity, injection intensity, injection-production well spacing and well pattern type.

[0018] In one or some embodiments, the orthogonal test mechanism model is used to perform numerical simulation until an invalid cycle occurs in the reservoir displacement unit to obtain orthogonal test data, including:

[0019] The orthogonal test mechanism model is used to perform numerical simulation until the water content in the reservoir displacement unit reaches the preset limit water content, and invalid circulation is determined in the reservoir displacement unit to obtain orthogonal test data.

[0020] In one or more embodiments, establishing a prediction model for the occurrence of an invalid cycle based on the degree of influence of various geological factors and development factors on the occurrence of an invalid cycle in a reservoir displacement unit includes:

[0021] If the well network type has the greatest impact on the timing of invalid cycle occurrence, then for each well network type, a regression analysis is performed on the orthogonal experimental data corresponding to all permeability differences, permeability variation coefficients, porosity, injection intensity and injection-production well spacing combinations under the well network type to obtain the corresponding invalid cycle occurrence timing prediction model.

[0022] In one or more embodiments, the predicted value of the recovery degree of the actual displacement unit is determined by the following invalid cycle occurrence timing prediction model:

[0023]

[0024] Among them, R is the predicted value of recovery degree, X1 is the permeability difference, X2 is the permeability variation coefficient, X3 is the porosity, X4 is the injection intensity, X5 is the injection-production well spacing, and A, B1, B2, B3, B4, B5, C1, C2, C3, and C4 are all model parameters.

[0025] In one or some embodiments, determining an invalid cycle identification result based on the predicted recovery degree value and the actual recovery degree value includes:

[0026] Determining whether the actual value of the recovery degree is greater than or equal to the predicted value of the recovery degree;

[0027] If so, an ineffective cycle occurs within the actual displacement unit within the reservoir;

[0028] If not, no invalid circulation occurs in the actual displacement unit in the reservoir.

[0029] In a second aspect, the present invention provides an intra-layer invalid cycle identification device based on an oil reservoir displacement unit, comprising:

[0030] The impact degree determination module is used to determine the impact degree of various geological factors and development factors on the timing of invalid cycle occurrence in the reservoir displacement unit using multi-factor and multi-level orthogonal experiments;

[0031] The model building module is used to establish a prediction model for the occurrence of invalid cycles based on the degree of influence of various geological factors and development factors on the occurrence of invalid cycles in the reservoir displacement unit;

[0032] A prediction module, configured to determine a predicted value of the recovery degree of an actual displacement unit based on the invalid cycle occurrence timing prediction model, and determine an actual value of the recovery degree of the actual displacement unit through a black oil model;

[0033] The recognition result determination module is used to determine the invalid cycle recognition result according to the recovery degree prediction value and the recovery degree actual value.

[0034] In a third aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method for identifying invalid cycles within a layer based on reservoir displacement units as described in the first aspect.

[0035] In a fourth aspect, the present invention provides an electronic device comprising a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other via the communication bus;

[0036] Memory for storing computer programs;

[0037] The processor is configured to implement the method for identifying invalid cycles within a layer based on reservoir displacement units as described in the first aspect when executing the program stored in the memory.

[0038] In a fifth aspect, the present invention provides a computer program product, comprising a computer program, which, when executed by a processor, implements the steps of the method for identifying invalid cycles within a layer based on reservoir displacement units as described in the first aspect.

[0039] Based on the above technical solution, the present invention has the following beneficial effects compared with the prior art:

[0040] The present invention provides a method for identifying invalid circulation within a reservoir displacement unit. The method utilizes a multi-factor, multi-level orthogonal test to determine the degree of influence of various geological and development factors on the timing of invalid water circulation. This method can quantitatively characterize the degree of influence of various geological and development factors on the timing of invalid circulation. Based on the degree of influence of various geological and development factors on the timing of invalid circulation, a prediction model for the timing of invalid circulation is regressed. Based on the invalid circulation timing prediction model, a predicted value of the recovery degree of the actual displacement unit is determined, and the actual value of the recovery degree of the actual displacement unit is determined using a black oil model. Based on the predicted and actual recovery degrees, an invalid circulation identification result is determined. This method can quantitatively characterize and identify invalid circulation within a reservoir layer, predicting the timing of invalid circulation formation within the actual displacement unit. This method can provide a reference for use in other research fields related to the invalid circulation phenomenon.

[0041] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or understood by practicing the present invention. The purposes and other advantages of the present invention are realized and obtained by the structures particularly pointed out in the description, claims and drawings.

[0042] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0044] Figure 1 1 is a flow chart of a method for identifying invalid cycles within a layer based on a reservoir displacement unit provided by an embodiment of the present invention;

[0045] Figure 2 Schematic diagram of a five-point method mainstream river channel mechanism model provided by an embodiment of the present invention;

[0046] Figure 3 This is a conceptual plan view of a one-injection-one-production displacement unit provided by an embodiment of the present invention;

[0047] Figure 4 This is a schematic diagram of a streamline model of a displacement unit on a mainstream line provided by an embodiment of the present invention;

[0048] Figure 5a This is a schematic diagram of the S111 sublayer displacement unit before division provided by an embodiment of the present invention;

[0049] Figure 5b This is a schematic diagram of the S111 sublayer displacement unit divided according to an embodiment of the present invention;

[0050] Figure 6 1 is a schematic structural diagram of an intra-layer invalid circulation identification device based on an oil reservoir displacement unit provided by an embodiment of the present invention;

[0051] Figure 7 It is a structural diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0052] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0053] Exemplary embodiments will be described in detail herein, examples of which are illustrated in the accompanying drawings. In the following description, when referring to the drawings, like numbers in different figures represent like or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all possible embodiments consistent with the present invention. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present invention, as detailed in the appended claims.

[0054] Old oilfields in certain regions have entered a period of extremely high water cuts. Some have reached a comprehensive water cut approaching 96%, entering the late stage of extremely high water cut, while others have exceeded 97%, just one percentage point away from the technical water cut threshold for oilfield abandonment. Despite this, approximately 60% of remaining reserves remain unproduced. The primary reason is that injected water forms a severely inefficient and ineffective cycle along the dominant seepage pathways, suppressing the production potential of low-permeability and upper layers, where residual oil is still abundant. Consequently, their proportion of total oil production is decreasing. Considering economic factors, it can be argued that ineffective circulation can determine the survival of an oilfield, making the precise identification and control of ineffective water circulation a crucial issue in oilfield development.

[0055] The issue of ineffective injection water circulation was raised a decade ago, and numerous research results have been achieved. However, this research remains far from meeting actual production needs. Some reservoirs, due to their inherent geological characteristics, are more susceptible to ineffective injection water circulation. Given the significant harm caused by ineffective water circulation, controlling ineffective injection water circulation will undoubtedly become a crucial strategic measure in the later stages of oilfield development. Research has shown that two key characteristics of oilfields entering the extremely high water-cut period are increasing ineffective circulation and a growing proportion of residual oil within the layer. Therefore, managing ineffective circulation within interwell zones and recovering the residual oil within these zones will become the primary focus of future development adjustments. As most mature oilfields enter the high-water-cut period and ineffective circulation continues to worsen, it is necessary to conduct in-depth research into the specific timing of ineffective water circulation during oilfield development, analyze the factors that may influence its occurrence, identify the key controlling factors for avoiding it, and implement appropriate control measures in a timely manner.

[0056] The reservoir displacement unit is the most basic unit for the occurrence of invalid cycles. The study of reservoir displacement units is the starting point for invalid cycle research. To accurately identify and manage invalid cycles, it is necessary to analyze and accurately grasp the main controlling factors of invalid cycles within the reservoir displacement unit, including geology, development dynamics, well patterns, and measures. Characterizing invalid cycles within the reservoir layer is crucial for accurately determining when invalid cycles form within the reservoir displacement unit.

[0057] Currently, research on factors affecting invalid circulation within a displacement unit has only provided qualitative analysis, but has been unable to quantitatively characterize and identify invalid circulation within the reservoir, failing to meet the inventors' expectations. The inventors, through further research and development, have developed the present invention.

[0058] Example 1

[0059] The present invention aims to solve the problem that the existing technology cannot quantitatively characterize and identify the invalid circulation in the reservoir layer. Based on the reservoir displacement unit, the invention analyzes the influence of various influencing factors on the timing of invalid circulation, and proposes a method for identifying invalid circulation in the layer based on the reservoir displacement unit. Figure 1 Shown, including:

[0060] S101. Use multi-factor and multi-level orthogonal experiments to determine the degree of influence of various geological and development factors on the timing of the occurrence of invalid cycles within the reservoir displacement unit;

[0061] Based on displacement unit seepage theory and reservoir numerical simulation principles, this study quantitatively characterizes the timing of void cycle formation within a reservoir displacement unit, taking into account both geological and development factors. A multi-factor, multi-level orthogonal experiment is used to determine the degree to which each factor influences the timing of void cycle occurrence.

[0062] S102. Establishing a prediction model for the occurrence of invalid cycles based on the degree of influence of various geological factors and development factors on the occurrence of invalid cycles in the reservoir displacement unit;

[0063] After determining the order and degree of influence of various influencing factors, namely the aforementioned geological and development factors, on the timing of the occurrence of invalid water circulation, a regression was performed on the orthogonal test data to develop the aforementioned invalid water circulation prediction model. This invalid water circulation prediction model was used to determine whether invalid water circulation occurred in each actual displacement unit during detailed oilfield research.

[0064] S103, determining a predicted value of the recovery degree of an actual displacement unit based on the invalid cycle occurrence timing prediction model, and determining an actual value of the recovery degree of the actual displacement unit using a black oil model;

[0065] Taking the actual displacement unit as the object, the numerical values ​​of the geological factors and development factors of the actual displacement unit are input into the invalid cycle occurrence timing prediction model to calculate the predicted value of the recovery degree. The numerical values ​​of the geological factors and development factors of the actual displacement unit are then input into the black oil model to obtain the actual value of the recovery degree of the actual displacement unit.

[0066] S104: Determine an invalid cycle identification result according to the predicted value of the recovery degree and the actual value of the recovery degree.

[0067] Compare the predicted recovery value with the actual recovery value to determine whether invalid circulation occurs in the reservoir displacement unit.

[0068] The present invention belongs to the technical field of oil and gas field development, and specifically relates to a method for identifying invalid circulation within a layer based on an oil reservoir displacement unit. The method utilizes a multi-factor and multi-level orthogonal test to determine the degree of influence of various geological factors and development factors on the timing of invalid water circulation, and can quantitatively characterize the degree of influence of various geological factors and development factors on the timing of invalid circulation. According to the degree of influence of various geological factors and development factors on the timing of invalid circulation, a prediction model for the timing of invalid circulation is regressed. Then, based on the invalid circulation timing prediction model, a predicted value of the recovery degree of an actual displacement unit is determined, and an actual value of the recovery degree of the actual displacement unit is determined through a black oil model. According to the predicted recovery degree value and the actual recovery degree value, an invalid circulation identification result is determined, and the invalid circulation within the oil reservoir layer can be quantitatively characterized and identified, and the timing of the formation of the invalid circulation within the actual displacement unit is predicted, so as to provide use and reference for other research fields related to the invalid circulation phenomenon.

[0069] In an optional embodiment, the multi-factor multi-level orthogonal test described in step S101 above is used to determine the degree of influence of various geological factors and development factors on the timing of occurrence of invalid cycles in the reservoir displacement unit, including:

[0070] S1011. Establish multiple orthogonal test plans based on the selected combinations of geological factors and development factors at different levels;

[0071] In order to study the influence of various geological factors and development factors on the timing of invalid circulation formation in the displacement unit, the present invention selects multiple representative levels for each geological factor and development factor according to the actual reservoir attribute parameter range for experimental analysis, establishes corresponding orthogonal test schemes according to the combination of geological factors and development factors at different levels, and obtains an orthogonal test factor level table. In the present invention, three geological factors including permeability difference, permeability variation coefficient and porosity, and three development factors including injection-production well spacing, injection intensity, and well network type are comprehensively screened and analyzed to quantitatively characterize the timing of invalid circulation formation in the reservoir displacement unit. Multiple representative levels are selected for permeability difference, permeability variation coefficient, porosity, injection intensity, injection-production well spacing and well network type respectively for experimental analysis, and corresponding orthogonal test schemes are established for each selected level of permeability difference, permeability variation coefficient, porosity, injection intensity, injection-production well spacing and well network type combination. Taking five representative levels of permeability difference, permeability variation coefficient, porosity, injection intensity, injection-production well spacing and well pattern type as an example, the six factors and five levels L25 (56 ) Orthogonal experiment schemes were conducted using the orthogonal experiment factor level table. For each well pattern type, each level of the permeability differential, permeability variation coefficient, porosity, injection intensity, and injection-production well spacing combination within that well pattern type constituted an orthogonal experiment scheme, totaling 25 orthogonal experiment schemes.

[0072]

[0073] Table 1

[0074] S1012. Based on actual formation data, establish orthogonal test mechanism models corresponding to the respective orthogonal test schemes through a black oil model;

[0075] For each orthogonal test scheme, a corresponding orthogonal test mechanism model is established. The orthogonal test scheme of the present invention adopts the orthogonal test factor level table as shown in Table 1, and uses the numerical simulation software Eclipse to perform numerical simulation. The orthogonal test of the present invention only considers oil-water two-phase flow. Therefore, the orthogonal test mechanism model uses the black oil model, assuming that the seepage in the reservoir is isothermal seepage. According to the principles of mass conservation and material balance, the black oil model divides the reservoir into multiple grid units. Within each grid unit, discretization calculations are performed according to time and space, and a numerical method is used to solve a group of partial differential equations to simulate the behavior of the fluid in the reservoir. For details, please refer to the description in Eclipse. Using the numerical simulation software Eclipse, we interpolated interwell porosity and permeability using the Kriging interpolation method based on actual formation data such as crude oil density, formation crude oil viscosity, initial formation pressure, crude oil saturation pressure, crude oil volume coefficient, formation porosity, permeability, and oil saturation. We also ensured that the permeability range and permeability coefficient of variation for each grid after interpolation matched those designed in the orthogonal experimental scheme. For example, if the permeability gradient in a block is 600 mD, with a maximum and minimum permeability of 800 mD and 200 mD, respectively, the permeability range selected for the orthogonal experimental mechanism model would be 200-800 mD.

[0076] Taking an injection-production unit in a three-dimensional five-point well pattern of oil-water two-phase as an example, the main steps of characterizing the orthogonal experimental mechanism model are explained. The black oil model grid cell number is 25×25×5, the horizontal grid step size is 10m, and the vertical grid step size is 2m. The formation parameters of the black oil model are then set based on actual formation data, such as the crude oil density of 0.88g / cm 3 , the formation crude oil viscosity is 10.3cp, the original formation pressure is 16.39MPa, the original saturation pressure is 13.89MPa, and the crude oil volume coefficient is 1.118. Finally, the permeability difference, permeability variation coefficient, porosity, injection intensity and injection-production well spacing of the black oil model are set to obtain the corresponding orthogonal test mechanism model. Figure 2 As shown in Figure 1, the orthogonal test mechanism model of the main stream channel of the five-point method is established. According to the parameters in the orthogonal test design table in Table 1, and based on the actual formation data, the orthogonal test mechanism models of the remaining orthogonal test schemes are established in turn.

[0077] S1013, performing numerical simulation using the orthogonal test mechanism model until an invalid cycle occurs in the reservoir displacement unit, thereby obtaining orthogonal test data;

[0078] For each orthogonal test scheme, numerical simulation is performed using the orthogonal test mechanism model corresponding to the orthogonal test scheme. When an invalid cycle occurs in the reservoir displacement unit, the simulation is stopped, and the recovery rate at the time of the invalid cycle is obtained to obtain the above-mentioned orthogonal test data. In oil field development, the water content at which an oil well or oil field loses its economic value is called the limit water content. When the water content in the reservoir displacement unit reaches the preset limit water content, it is considered that an invalid cycle has occurred in the reservoir displacement unit. Numerical simulation is performed using the orthogonal test mechanism model, and the water content in the reservoir displacement unit is obtained in real time until the water content in the reservoir displacement unit reaches the preset limit water content. The occurrence of an invalid cycle in the reservoir displacement unit is determined, and the simulation is stopped. The recovery rate at the time of the invalid cycle is obtained to obtain the orthogonal test data. A water content of 98% is usually used as the limit water content. In the orthogonal test design of the present invention, a water content of 98% is intended to be used as the limit when an invalid cycle occurs in the reservoir displacement unit.

[0079] Based on the principles of reservoir numerical simulation, various orthogonal experimental schemes were simulated. Each orthogonal experimental mechanism model was set to halt well production when the water cut reached a preset limit of 98% for a void cycle. Simultaneously, the degree of recovery for each orthogonal experimental scheme was calculated. The degree of recovery, a metric describing the percentage of a reservoir's cumulative recovered geological reserves, can be used to determine the reservoir's development level based on the degree of recovery at the time of void cycle formation, thereby predicting the timing of void cycle formation within a displacement unit. Therefore, using the degree of recovery as the ultimate development evaluation metric, the degree of recovery for each orthogonal experimental scheme was calculated. The influence of various influencing factors on the degree of recovery was then used to evaluate the impact of each factor on the timing of void cycle occurrence.

[0080] S1014. Analyze the orthogonal test data corresponding to different orthogonal test schemes using a range analysis method to determine the degree of influence of various geological factors and development factors on the timing of occurrence of invalid cycles in the reservoir displacement unit.

[0081] By synthesizing the orthogonal test data under each orthogonal test scheme, the orthogonal test scheme result analysis table shown in Table 2 was obtained. The elements in Table 2 are the recovery degrees under each orthogonal test scheme. By analyzing the recovery degrees of 25 orthogonal test schemes with six influencing factors, the range analysis method was selected to perform dimensionless processing on the orthogonal test results to determine the weight of each influencing factor. Finally, the influence degree of the six influencing factors of invalid circulation was obtained. The influence degree of each influencing factor on the timing of invalid circulation formation is from large to small: well network type > permeability range > injection intensity > injection-production well spacing > permeability variation coefficient > porosity. Based on the direct analysis and range analysis of the orthogonal test data, the present invention obtains the primary and secondary order and influence degree of various influencing factors on the invalid circulation of injected water.

[0082]

[0083] Table 2

[0084] In an optional embodiment, the method of establishing a prediction model for the occurrence of an invalid cycle according to the influence of various geological factors and development factors on the occurrence of an invalid cycle in the reservoir displacement unit in S102 includes:

[0085] S1021. If the well network type has the greatest impact on the timing of invalid cycle occurrence, then for each well network type, a regression analysis is performed on the orthogonal test data corresponding to all permeability differences, permeability variation coefficients, porosity, injection intensity and injection-production well spacing combinations under the well network type to obtain the corresponding invalid cycle occurrence timing prediction model.

[0086] Well pattern type has the greatest impact on the timing of the occurrence of a void cycle. Therefore, a corresponding void cycle occurrence prediction model was established for each well pattern type. Specifically, for each well pattern type, a regression simulation method was used to analyze the orthogonal experimental data corresponding to all orthogonal experimental schemes for that well pattern type, and a multivariate linear regression model was established using SPSS software. By running SPSS software, enter or open the orthogonal experimental data table (Table 2), select Analyze → Regression → Linear. The Linear Regression dialog box will appear. Select the dependent variable (i.e., recovery level) in Dependent, and the independent variables (i.e., permeability differential, permeability coefficient of variation, porosity, injection intensity, and injection-production well spacing) in Independents. Click OK to calculate the coefficients of each parameter in the void cycle occurrence prediction model and obtain the correlation coefficient of the regression equation. The correlation coefficient reflects the closeness of the correlation between recovery level and each influencing factor and is used to measure the fit of the void cycle occurrence prediction model to the observed data. The closer the correlation coefficient is to 1, the higher the accuracy of the void cycle occurrence prediction model.

[0087] Based on the degree of influence of each influencing factor on the timing of invalid cycle formation determined by differential analysis, the present invention uses a regression curve to regress a mathematical model between the five influencing factors including permeability differential, permeability variation coefficient, porosity, injection intensity, and injection-production well spacing and the production degree R when invalid cycle is formed, that is, the above-mentioned invalid cycle occurrence timing prediction model.

[0088] In an optional embodiment, the predicted value of the recovery degree of the actual displacement unit is determined by the following invalid cycle occurrence timing prediction model:

[0089]

[0090] Among them, R is the predicted value of recovery degree, X1 is the permeability difference, X2 is the permeability variation coefficient, X3 is the porosity, X4 is the injection intensity, X5 is the injection-production well spacing, A, B1, B2, B3, B4, B5, C1, C2, C3, and C4 are all model parameters. These parameters are obtained by regression using SPSS software. For details, please refer to the description of S1021 above.

[0091] Taking the five-point method as an example, the prediction model for the occurrence of invalid cycles is as follows:

[0092]

[0093] Among them, R is the predicted value of recovery degree, X1 is the permeability difference, X2 is the permeability variation coefficient, X3 is the porosity, X4 is the injection intensity, and X5 is the injection-production well spacing.

[0094] In an optional embodiment, the step S104 of determining the invalid cycle identification result according to the predicted recovery degree value and the actual recovery degree value includes:

[0095] Determining whether the actual value of the recovery degree is greater than or equal to the predicted value of the recovery degree;

[0096] If so, an invalid cycle occurs in the actual displacement unit in the reservoir layer; if not, an invalid cycle does not occur in the actual displacement unit in the reservoir layer.

[0097] When the well pattern type of the displacement unit is known, the corresponding recovery degree prediction value is calculated using the invalid cycle occurrence timing prediction model corresponding to the displacement unit, and compared with the actual recovery degree value obtained by the black oil model to determine whether there is invalid water circulation.

[0098] In a specific embodiment, the actual reservoir displacement unit is selected, and the selected reservoir displacement unit refers to Figure 3 As shown, Figure 3 The five parameters required for the displacement unit of the reservoir, namely permeability difference, permeability variation coefficient, porosity, injection intensity, and injection-production well spacing, are substituted into the invalid cycle occurrence timing prediction model of Equation 2 to calculate the predicted value b of the recovery degree when the invalid cycle is formed, and the black oil model (refer to Figure 4 The actual recovery value a of the reservoir displacement unit is obtained by using the predicted recovery value b (as shown). This is then compared with the actual recovery value a. When the actual recovery value a is greater than or equal to the predicted recovery value b, it is considered that an ineffective cycle has occurred in the reservoir displacement unit within the reservoir layer. The applicable ranges of the parameters in Equation 2 above, namely permeability differential, permeability coefficient of variation, porosity, injection intensity, and injection-production well spacing, are consistent with the parameter ranges used in orthogonal experimental design. Taking the permeability differential as an example, the applicable range of the permeability differential in Equation 2 is 5-25, which is consistent with the permeability parameter range in Table 1. Figure 4 This is a schematic diagram of the streamline model of the displacement unit on the mainstream line. Figure 3 and Figure 4 The color change in the middle represents the oil saturation. Figure 3 and Figure 4 The saturation of the middle displacement unit is the oil saturation corresponding to the formation of an invalid cycle in the displacement unit.

[0099] To more clearly illustrate the intralayer invalid circulation identification method based on reservoir displacement units provided by an embodiment of the present invention, the intralayer invalid circulation identification method based on reservoir displacement units is applied to the S111 sublayer of the M reservoir in a period of extremely high water cut to identify whether invalid water circulation occurs in the S111 sublayer of the M reservoir. The method includes the following steps:

[0100] S201. Based on the established reservoir numerical model, such as the black oil model, the streamline field map of the S111 layer is derived and the displacement units are divided. The displacement unit is the part of the reservoir controlled by the injection and production wells that is affected by the injected water and displaced, that is, the area where the injection and production flow occurs under the production pressure difference, that is, Figure 5a The area enclosed by the flow lines from the point source to the point confluence. The changes in the pressure field of the injection and production wells are described by numerical simulation of the reservoir. The displacement units are divided according to the range of the flow lines between the injection and production wells. Figure 5b As shown, this is a schematic diagram of the S111 sublayer after it is divided into displacement units.

[0101] S202: Select a displacement unit and calculate the actual value a of the recovery degree of the displacement unit using a black oil model.

[0102] S203: Statistically analyze the five influencing factors of the selected displacement unit (permeability extreme difference, permeability variation coefficient, porosity, injection intensity, and injection-production well spacing), and substitute the value of each statistical influencing factor into the regression invalid cycle occurrence timing prediction model (Formula 2) for calculation, thereby obtaining the predicted value b of the recovery degree when the displacement unit forms an invalid cycle.

[0103] S204: Compare the actual recovery value a with the predicted recovery value b. If the actual recovery value a is greater than or equal to the predicted recovery value b, it is considered that invalid water circulation has occurred within the displacement unit. By comparing the prediction results of the invalid circulation occurrence prediction model with the numerical simulation results of the black oil model when the water cut of the displacement unit reaches 98%, it is possible to accurately determine whether invalid circulation exists within the displacement unit along the main flow line of the injection and production well.

[0104] Example 2

[0105] Based on the same inventive concept, the embodiment of the present invention also provides an intra-layer invalid cycle identification device based on the reservoir displacement unit, referring to Figure 6 Shown, including:

[0106] The influence degree determination module 301 is used to determine the influence degree of each geological factor and development factor on the occurrence timing of invalid cycle in the reservoir displacement unit by using a multi-factor and multi-level orthogonal test;

[0107] The model building module 302 is used to build a prediction model for the occurrence of invalid cycles based on the degree of influence of various geological factors and development factors on the occurrence of invalid cycles in the reservoir displacement unit;

[0108] A prediction module 303 is configured to determine a predicted value of the recovery degree of an actual displacement unit based on the invalid cycle occurrence timing prediction model, and determine an actual value of the recovery degree of the actual displacement unit using a black oil model;

[0109] The identification result determination module 304 is configured to determine an invalid cycle identification result based on the predicted recovery degree value and the actual recovery degree value.

[0110] The implementation principle and technical effects of the electronic device provided by the embodiment of the present invention are similar to those of any of the aforementioned method embodiments and will not be repeated here.

[0111] Example 3

[0112] An embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon. When the program is executed by a processor, the method for identifying invalid cycles within a layer based on reservoir displacement units as described in the aforementioned method embodiment is implemented.

[0113] The computer-readable storage medium may be included in the device / apparatus described in the above embodiments, or may exist independently and not be incorporated into the device / apparatus. The computer-readable storage medium carries one or more programs, which, when executed, implement the method according to the embodiment of the present invention.

[0114] According to an embodiment of the present invention, a computer-readable storage medium may be a non-volatile computer-readable storage medium, such as, but not limited to, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0115] Example 4

[0116] An embodiment of the present invention provides an electronic device, referring to Figure 7 As shown, it includes a processor 111, a communication interface 112, a memory 113 and a communication bus 114, wherein the processor 111, the communication interface 112 and the memory 113 communicate with each other through the communication bus 114.

[0117] Memory 113, for storing computer programs;

[0118] The processor 111 is configured to implement the invalid cycle identification method within a layer based on reservoir displacement units as described in the aforementioned method embodiment when executing the program stored in the memory 113 .

[0119] The implementation principle and technical effects of the electronic device provided by the embodiment of the present invention are similar to those of any of the aforementioned method embodiments and will not be repeated here.

[0120] The memory 113 can be an electronic memory such as a flash memory, an EEPROM (Electrically Erasable Programmable Read-Only Memory), an EPROM, a hard disk, or a ROM. The memory 113 has storage space for program code for executing any of the method steps described above. For example, the storage space for program code can include individual program codes for implementing each of the steps in the method described above. These program codes can be read from or written to one or more computer program products. These computer program products include program code carriers such as a hard disk, a compact disc (CD), a memory card, or a floppy disk. Such computer program products are typically portable or fixed storage units. The storage unit can have storage segments or storage space arranged similarly to the memory 113 in the electronic device described above. The program code can be compressed, for example, in a suitable form. Typically, the storage unit includes a program for executing the method steps according to an embodiment of the present invention, i.e., code that can be read by, for example, the processor 111, and when executed by the electronic device, causes the electronic device to execute the various steps in the method described above.

[0121] Example 5

[0122] An embodiment of the present invention provides a computer program product, comprising a computer program, which, when executed by a processor, implements the steps of the method for identifying invalid cycles within a layer based on reservoir displacement units as described in the aforementioned method embodiment.

[0123] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments. It should be noted that, in the absence of conflict, the embodiments of the present invention and the features in the embodiments can be combined with each other. The present invention is not limited to any single aspect, nor to any single embodiment, nor to any combination and / or permutation of these aspects and / or embodiments. Each aspect and / or embodiment of the present invention can be used alone or in combination with one or more other aspects and / or other embodiments.

[0124] Finally, it should be noted that the above-described embodiments are only specific implementation methods of the present invention, which are used to illustrate the technical solutions of the present invention, rather than to limit them. The scope of protection of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the above-described embodiments, those skilled in the art should understand that any person skilled in the art can modify or easily conceive of changes to the technical solutions described in the above-described embodiments within the technical scope disclosed by the present invention, or replace some of the technical features therein with equivalents. Such modifications, changes, or replacements do not deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the scope of protection of the present invention. Therefore, the scope of protection of the present invention shall be subject to the scope of protection of the claims.

Claims

1. A method for identifying invalid cycles within a layer based on reservoir displacement units, characterized in that: include: Using multi-factor and multi-level orthogonal experiments, we determined the influence of various geological and development factors on the occurrence of invalid cycles within the reservoir displacement unit. According to the influence of various geological factors and development factors on the occurrence of invalid cycle in the reservoir displacement unit, a prediction model for the occurrence of invalid cycle is established; Determining a predicted value of the recovery degree of an actual displacement unit based on the invalid cycle occurrence timing prediction model, and determining an actual value of the recovery degree of the actual displacement unit through a black oil model; An invalid cycle identification result is determined according to the predicted value of the recovery degree and the actual value of the recovery degree.

2. The method for identifying invalid cycles within a layer based on reservoir displacement units according to claim 1, characterized in that: The multi-factor and multi-level orthogonal test is used to determine the influence of various geological factors and development factors on the timing of the occurrence of invalid cycles in the reservoir displacement unit, including: Establish multiple orthogonal test plans based on the selected combinations of geological factors and development factors at different levels; Based on actual formation data, orthogonal test mechanism models corresponding to each of the orthogonal test schemes are established through the black oil model; Performing numerical simulation using the orthogonal test mechanism model until an invalid cycle occurs in the reservoir displacement unit, thereby obtaining orthogonal test data; The orthogonal test data corresponding to different orthogonal test schemes are analyzed using the range analysis method to determine the degree of influence of various geological factors and development factors on the timing of occurrence of invalid cycles in the reservoir displacement unit.

3. The method for identifying invalid cycles within a layer based on reservoir displacement units according to claim 2, characterized in that: The geological factors include permeability gradient, permeability variation coefficient and porosity, and the development factors include injection intensity, injection-production well spacing and well pattern type; According to the combination of geological factors and development factors at different levels, multiple orthogonal test schemes are established, including: Multiple orthogonal test schemes were established based on the selected combinations of different levels of permeability difference, permeability variation coefficient, porosity, injection intensity, injection-production well spacing and well pattern type.

4. The method for identifying invalid cycles within a layer based on reservoir displacement units according to claim 2, characterized in that: The orthogonal test mechanism model is used to perform numerical simulation until an invalid cycle occurs in the reservoir displacement unit to obtain orthogonal test data, including: The orthogonal test mechanism model is used to perform numerical simulation until the water content in the reservoir displacement unit reaches the preset limit water content, and invalid circulation is determined in the reservoir displacement unit to obtain orthogonal test data.

5. The method for identifying invalid cycles within a layer based on reservoir displacement units according to claim 3, characterized in that: According to the influence of various geological factors and development factors on the invalid cycle occurrence timing in the reservoir displacement unit, a invalid cycle occurrence timing prediction model is established, which includes: If the well network type has the greatest impact on the timing of invalid cycle occurrence, then for each well network type, a regression analysis is performed on the orthogonal experimental data corresponding to all permeability differences, permeability variation coefficients, porosity, injection intensity and injection-production well spacing combinations under the well network type to obtain the corresponding invalid cycle occurrence timing prediction model.

6. The method for identifying invalid cycles within a layer based on reservoir displacement units according to claim 3, characterized in that: The predicted value of the recovery degree of the actual displacement unit is determined by the invalid cycle occurrence timing prediction model as follows: R=A-B1X1-B2X2-B3X3+B4X4-B5X5+C1X1 2 +C2X2 2 +C3X3 2 -C4X4 2 Among them, R is the predicted value of recovery degree, X1 is the permeability difference, X2 is the permeability variation coefficient, X3 is the porosity, X4 is the injection intensity, X5 is the injection-production well spacing, and A, B1, B2, B3, B4, B5, C1, C2, C3, and C4 are all model parameters.

7. The method for identifying invalid cycles within a layer based on reservoir displacement units according to claim 1, characterized in that: Determining an invalid cycle identification result according to the predicted value of the recovery degree and the actual value of the recovery degree includes: Determining whether the actual value of the recovery degree is greater than or equal to the predicted value of the recovery degree; If so, an ineffective cycle occurs within the actual displacement unit within the reservoir; If not, no invalid circulation occurs in the actual displacement unit in the reservoir.

8. A device for identifying invalid cycles within a layer based on a reservoir displacement unit, characterized in that: include: The influence degree determination module is used to determine the influence degree of various geological factors and development factors on the timing of invalid cycle occurrence in the reservoir displacement unit by using multi-factor and multi-level orthogonal experiments; The model building module is used to establish a prediction model for the occurrence of invalid cycles based on the degree of influence of various geological factors and development factors on the occurrence of invalid cycles in the reservoir displacement unit; A prediction module, configured to determine a predicted value of the recovery degree of an actual displacement unit based on the invalid cycle occurrence timing prediction model, and determine an actual value of the recovery degree of the actual displacement unit through a black oil model; The recognition result determination module is used to determine the invalid cycle recognition result according to the recovery degree prediction value and the recovery degree actual value.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method for identifying invalid cycles within a layer based on a reservoir displacement unit as described in any one of claims 1 to 7 is implemented.

10. An electronic device, characterized in that: The processor, the communication interface, the memory and the communication bus are connected to each other via the communication bus. Memory for storing computer programs; The processor is configured to implement the method for identifying invalid cycles within a layer based on a reservoir displacement unit as described in any one of claims 1 to 7 when executing the program stored in the memory.

11. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method for identifying invalid cycles within a layer based on a reservoir displacement unit are implemented as described in any one of claims 1 to 7.

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