Volatile oil reservoir depletion exploitation guiding method, device, equipment and medium

Abstract

The invention belongs to the technical field of oilfield development, and particularly discloses a volatile oil reservoir depletion exploitation guiding method, device and equipment and a medium. The method comprises the following steps: determining physical property parameters of fluid in a grid in a depletion exploitation process according to a preset volatile reservoir geologic model; determining a pressure field, a saturation field and a reserve utilization field of the target volatile oil reservoir, and performing grade division to obtain division grades corresponding to the three physical fields; and determining a comprehensive flow field grade of the target volatile oil reservoir based on the respective corresponding division grades, performing flow field evaluation on depletion exploitation of the target volatile oil reservoir, and guiding depletion exploitation of the target volatile oil reservoir based on a flow field evaluation result. By means of the method, the problem that yield increase guidance cannot be conducted on follow-up depletion exploitation of the volatile oil reservoir on the basis of an accurate flow field grading evaluation result can be solved, the accuracy and all factors are considered, and convenient and accurate theoretical guidance is provided for implementation of follow-up yield increase measures of the volatile oil reservoir.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of oilfield development, and particularly relates to a volatile reservoir depletion production guiding method, device, equipment and medium. BACKGROUND

[0002] Related scholars have found that there is a reservoir fluid with high shrinkage characteristics in an ultra-low permeability oilfield, which is quite different from conventional fluids in terms of properties, and this special fluid is called "volatile oil" and the reservoir is also called a volatile reservoir.

[0003] The production method of the volatile reservoir is usually depletion production, and the recovery efficiency of the volatile reservoir is greatly affected by the flow field during production. Compared with conventional reservoirs, the volatile reservoir is more sensitive to changes in reservoir pressure. When the pressure is lower than the bubble point pressure, a large amount of dissolved gas in the crude oil separates, which greatly changes the physical and chemical properties of the crude oil, causing a dramatic change in the flow field, resulting in certain difficulties in adjusting the percolation field of the volatile reservoir, and ultimately affecting the recovery efficiency of the volatile reservoir.

[0004] At present, domestic scholars mainly focus on conventional water drive reservoirs in the study of reservoir flow fields. Related evaluation indicators are directly selected to establish a related evaluation system, but the selected related indicators and the grading process are greatly affected by human factors, resulting in a result that cannot objectively evaluate the flow field of the reservoir; or, using face flux as the only indicator for flow field evaluation. However, the percolation flow field is the result of the coupling of multiple factors, and using only the face flux as an evaluation indicator cannot accurately describe the flow field distribution after the reservoir is produced, ignoring the influence of other factors, and the experimental results cannot truly reflect the actual situation. Foreign scholars often use streamline simulation methods to predict the flow field, but this method is greatly affected by the interaction between geological structures and flow rocks, making it difficult for the final model to converge, and the prediction deviation is large.

[0005] Therefore, the recovery efficiency of the volatile reservoir during production is greatly affected by the flow field, and the accuracy of the flow field grading evaluation after the depletion production of the volatile reservoir is poor at present, and various factors cannot be considered, resulting in the inability to guide the subsequent depletion production of the volatile reservoir based on accurate flow field grading evaluation results. SUMMARY

[0006] The present application aims to provide a volatile reservoir depletion production guiding method, device, equipment and medium to solve the problem that the subsequent depletion production of the volatile reservoir cannot be guided based on accurate flow field grading evaluation results at present.

[0007] In order to achieve the above-mentioned purpose, the present application adopts the following technical solutions:

[0008] The first aspect of the present application provides a volatile oil reservoir depletion production guidance method, comprising:

[0009] determining fluid property parameters in a grid in a depletion process according to a preset volatile oil reservoir geological model;

[0010] determining a pressure field, a saturation field and a reserve producing field of the target volatile oil reservoir according to the fluid property parameters in the grid, respectively performing hierarchical division on the pressure field, the saturation field and the reserve producing field by using a clustering algorithm to obtain respective division levels corresponding to the pressure field, the saturation field and the reserve producing field;

[0011] determining a comprehensive flow field level of the target volatile oil reservoir based on the respective division levels corresponding to the pressure field, the saturation field and the reserve producing field; performing flow field evaluation on the depletion production of the target volatile oil reservoir based on the comprehensive flow field level to obtain a flow field evaluation result;

[0012] guiding the depletion production of the target volatile oil reservoir based on the flow field evaluation result.

[0013] Further, the fluid property parameters in the grid in the depletion process include flow conditions of oil and gas two phases in the grid in the volatile oil reservoir geological model and oil and gas two phase fluid property parameters in each grid;

[0014] The oil and gas two phase fluid property parameters in each grid include relative permeability of oil and gas two phases in each grid, oil and gas viscosity in each grid, oil and gas density in each grid, pressure field change in each grid, thickness of each grid, fluid saturation in each grid, oil saturation in each grid and grid sweep parameter data of each grid.

[0015] Further, the determination of the pressure field, the saturation field and the reserve producing field of the target volatile oil reservoir according to the fluid property parameters in the grid specifically includes:

[0016] calculating the pressure field of the target volatile oil reservoir according to the flow conditions of oil and gas two phases in the grid in the volatile oil reservoir geological model, combining the relative permeability of oil and gas two phases in each grid, the oil and gas viscosity in each grid and the oil and gas density in each grid;

[0017] calculating the saturation field of the target volatile oil reservoir according to the oil and gas viscosity in each grid in the volatile oil reservoir geological model, the pressure field change in each grid and the fluid saturation in each grid;

[0018] According to the thickness of each grid of the volatile oil reservoir geological model, the oil-bearing saturation in the each grid, and the grid sweep parameter data of the each grid, a reserve producing field of the target volatile oil reservoir is calculated.

[0019] Further, before the pressure field, the saturation field and the reserve producing field are respectively classified by using the clustering algorithm, the pressure field, the saturation field and the reserve producing field are respectively normalized by using a membership function, to obtain a normalized pressure field, a normalized saturation field and a normalized reserve producing field.

[0020] Further, the membership function includes a linear membership function or an exponential membership function.

[0021] Further, the comprehensive flow field grade of the target volatile oil reservoir is determined based on the respective classified grades of the pressure field, the saturation field and the reserve producing field, and specifically includes:

[0022] The exploitation potential degree data corresponding to each classified grade is obtained;

[0023] The exploitation potential degree data corresponding to the classified grade of the pressure field, the exploitation potential degree data corresponding to the classified grade of the saturation field and the exploitation potential degree data corresponding to the classified grade of the reserve producing field are multiplied to determine the comprehensive flow field exploitation potential degree data of the pressure field, the saturation field and the reserve producing field;

[0024] The comprehensive flow field exploitation potential degree data is matched with a preset grading standard to determine the comprehensive flow field grade of the target volatile oil reservoir.

[0025] Further, the establishment steps of the pre-set volatile oil reservoir geological model include:

[0026] The target volatile oil reservoir is selected, historical geological data of the target volatile oil reservoir is obtained, and a volatile oil reservoir geological model is established by using the historical geological data of the target volatile oil reservoir.

[0027] In the second aspect of the present application, a volatile oil reservoir depletion production guidance device is provided, which includes:

[0028] A parameter determination module is configured to determine fluid physical property parameters in a grid during the depletion production process according to a pre-set volatile oil reservoir geological model.

[0029] A grade division module is configured to determine a pressure field, a saturation field and a reserve producing field of the target volatile oil reservoir according to fluid property parameters in the grid, and to perform grade division on the pressure field, the saturation field and the reserve producing field respectively by using a clustering algorithm to obtain respective division grades of the pressure field, the saturation field and the reserve producing field.

[0030] An evaluation module is configured to determine a comprehensive flow field grade of the target volatile oil reservoir based on the respective division grades of the pressure field, the saturation field and the reserve producing field, and to perform flow field evaluation on the depletion production of the target volatile oil reservoir based on the comprehensive flow field grade to obtain a flow field evaluation result.

[0031] A production guidance module is configured to guide the depletion production of the target volatile oil reservoir based on the flow field evaluation result.

[0032] In a third aspect, the present application provides an electronic device including a processor and a memory, wherein the processor is configured to execute a computer program stored in the memory to implement the method for guiding the depletion production of the volatile oil reservoir according to any one of the above aspects.

[0033] In a fourth aspect, the present application provides a computer readable storage medium storing at least one instruction, wherein the at least one instruction is executed by a processor to implement the method for guiding the depletion production of the volatile oil reservoir according to any one of the above aspects.

[0034] The present application has the following advantages:

[0035] 1. The present application determines fluid property parameters in the grid during the depletion production according to a preset geological model of the volatile oil reservoir, determines a pressure field, a saturation field and a reserve producing field of the target volatile oil reservoir, performs grade division to obtain respective division grades of the three physical fields, determines a comprehensive flow field grade of the target volatile oil reservoir based on the respective division grades, performs flow field evaluation on the depletion production of the target volatile oil reservoir, and guides the depletion production of the target volatile oil reservoir based on the flow field evaluation result. The present application can solve the problem that the subsequent depletion production of the volatile oil reservoir cannot be guided for production increase based on accurate flow field grading evaluation results, and can realize the accuracy and the compatibility of various factors, thereby providing convenient and accurate theoretical guidance for the implementation of the subsequent production increase measures of the volatile oil reservoir.

[0036] 2、The present application characterizes the flow field of the volatile oil reservoirs in the process of depletion development through the comprehensive effect of three physical fields, and the comprehensive flow field after the depletion development of the volatile oil reservoirs is greatly affected by the above three physical fields, so that the influence of various physical fields on the flow field distribution can be considered, and the single performance of each physical field will be directly fed back to the flow field grade division. BRIEF DESCRIPTION OF DRAWINGS

[0037] The drawings constituting a part of the specification illustrate the present application and, together with the description, serve to explain the principles of the application. In the drawings:

[0038] Figure 1 A flow chart of a volatile oil reservoir depletion development guidance method according to an embodiment of the present application;

[0039] Figure 2 A flow chart of a volatile oil reservoir depletion development guidance method according to an embodiment of the present application;

[0040] Figure 3 A flow chart of a volatile oil reservoir depletion development guidance method according to an embodiment of the present application;

[0041] Figure 4 A flow chart of a volatile oil reservoir depletion development guidance method according to an embodiment of the present application;

[0042] Figure 5 A flow chart of a volatile oil reservoir depletion development guidance method according to an embodiment of the present application;

[0043] Figure 6 A flow chart of a volatile oil reservoir depletion development guidance method according to an embodiment of the present application;

[0044] Figure 7 A flow chart of a volatile oil reservoir depletion development guidance method according to an embodiment of the present application;

[0045] Figure 8 A flow chart of a volatile oil reservoir depletion development guidance method according to an embodiment of the present application;

[0046] Figure 9 A flow chart of a volatile oil reservoir depletion development guidance method according to an embodiment of the present application; DETAILED DESCRIPTION

[0047] In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, clearer and more apparent, below, the technical solutions in the embodiments of the present application will be clearly and completely described with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, rather than all the embodiments. The components of the embodiments of the present application described and shown in the drawings herein can be arranged and designed in various different configurations.

[0048] Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the claimed present application, but only represents selected embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative labor are within the scope of protection of the present application.

[0049] It should be noted that: similar reference numbers and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. At the same time, in the description of the present application, the terms "first", "second" and the like are only used to distinguish the description, and cannot be understood as indicating or implying relative importance.

[0050] It should be noted that: similar reference numbers and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. At the same time, in the description of the present application, the terms "first", "second" and the like are only used to distinguish the description, and cannot be understood as indicating or implying relative importance.

[0051] Some embodiments of the present application will be described in detail below with reference to the drawings. The following embodiments and features in the embodiments can be combined with each other without conflict.

[0052] Embodiment one

[0053] At present, the recovery rate of volatile oil reservoirs in the process of depletion production is greatly affected by the flow field, and the flow field of the volatile oil reservoir after depletion production cannot be effectively predicted, and the accuracy of the grading evaluation of the flow field of the volatile oil reservoir after depletion production is poor, and various factors cannot be considered. Therefore, the present embodiment provides a volatile oil reservoir depletion production guidance scheme, which can avoid the deficiencies in the prior art and establish a set of reasonable, simple and practical method for the flow field of the volatile oil reservoir after depletion production, thereby providing convenient and accurate theoretical guidance for the implementation of subsequent production increase measures of the volatile oil reservoir.

[0054] As shown in Figure 1 , a volatile oil reservoir depletion production guidance method comprises:

[0055] S1: obtaining historical geological data of a target volatile oil reservoir, and establishing a volatile oil reservoir geological model by using the historical geological data.

[0056] In the present embodiment, the establishment of the geological model by using the historical data of the target volatile oil reservoir specifically comprises:

[0057] The target volatile oil reservoir is selected, the historical geological data of the target volatile oil reservoir is obtained, and the volatile oil reservoir geological model is established by using the historical geological data of the target volatile oil reservoir.

[0058] The volatile oil reservoir geological model can be used for the current target volatile oil reservoir. The volatile oil reservoir geological model is discretized by using equal-interval (or unequal-interval) grids in the plane and using grids in the vertical direction to divide the oil and gas reservoir into several geological layers. The volatile oil reservoir geological model reproduces the structural form of the oil reservoir, and lays a foundation for reflecting the plane heterogeneity and interlayer heterogeneity of the reservoir physical properties. The oil and gas two phases in the grid are calculated.

[0059] S2: performing depletion production on the target volatile oil reservoir, and determining the fluid physical property parameters in the grid during the depletion production according to the volatile oil reservoir geological model.

[0060] The fluid physical property parameters in the grid during the depletion production include the flow conditions of the oil and gas two phases in the grid in the volatile oil reservoir geological model and the fluid physical property parameters of the oil and gas two phases in each grid.

[0061] In the present embodiment, after the volatile oil reservoir geological model is established by using the historical geological data of the related target oilfield block, the depletion production is performed by using the volatile oil reservoir geological model, and the fluid physical property parameter conditions of the oil and gas two phases in each grid of the volatile oil reservoir geological model after the depletion production are calculated.

[0062] The oil and gas two-phase fluid property parameters in each grid of the volatile reservoir geological model include: the relative permeability of the oil and gas two-phase in each grid, the oil and gas viscosity in each grid, the oil and gas density in each grid, the change of the pressure field in each grid, the thickness of each grid, the fluid saturation in each grid, the oil saturation in each grid, the grid sweep parameter data of each grid, and the like.

[0063] Specifically, a series of basic parameters such as fluid basic properties, rock basic properties, relative permeability curves and viscosity-temperature curves can be input in the volatile reservoir geological model, and the oil and gas two-phase fluid property parameters in each grid of the volatile reservoir geological model after depletion production are calculated for subsequent calculation.

[0064] S3: determining the pressure field, the saturation field and the reserves producing field of the target volatile reservoir according to the fluid property parameters in the grid, and performing grade division on the pressure field, the saturation field and the reserves producing field respectively according to the grade division rule to obtain the corresponding division grades.

[0065] S31: determining the pressure field, the saturation field and the reserves producing field of the target volatile reservoir according to the fluid property parameters in the grid,

[0066] To realize the purpose of comprehensively evaluating the flow field of the target volatile reservoir, three physical fields are coupled in the embodiment of the present application, which are the pressure field, the saturation field and the reserves producing field;

[0067] Specifically,

[0068] According to the flow condition of the oil and gas two-phase in the grid of the volatile reservoir geological model, the relative permeability of the oil and gas two-phase in each grid, the oil and gas viscosity in each grid and the oil and gas density in each grid are combined to calculate the pressure field of the volatile reservoir geological model to obtain the pressure distribution in each grid.

[0069] According to the oil and gas viscosity in each grid of the volatile reservoir geological model, the change of the pressure field in each grid and the fluid saturation in each grid, the saturation field of the volatile reservoir geological model is calculated to obtain the saturation distribution in each grid.

[0070] According to the thickness of each grid of the volatile reservoir geological model, the oil saturation in each grid, the grid sweep parameter data of each grid, the reserves producing field of the volatile reservoir geological model is calculated to obtain the reserves producing distribution in each grid.

[0071] S32: performing grade division on the pressure field, the saturation field and the reserves producing field respectively according to the grade division rule.

[0072] Specifically, the number of division levels of the pressure field, the saturation field and the reserve producing field should be consistent; therefore, the membership function is used to normalize the pressure field, the saturation field and the reserve producing field respectively to obtain the normalized pressure field, the normalized saturation field and the normalized reserve producing field.

[0073] The normalized pressure field, the normalized saturation field and the normalized reserve producing field are analyzed by using the clustering algorithm respectively to obtain the corresponding division levels.

[0074] Further, in the embodiment, after the pressure field, the saturation field and the reserve producing field of the target volatile reservoir are determined according to the fluid physical property parameters in the grid, the calculated data range is very large, which may be zero to hundreds, and has a certain influence on the subsequent clustering, therefore, the membership function is introduced to normalize the pressure field, the saturation field and the reserve producing field respectively, so that the data range of the three physical fields is between [0, 1], which is convenient for subsequent clustering analysis; the data of the pressure field is the formation pressure or the original formation pressure, the unit is %, between 0 and 1, the saturation field is the oil saturation, the unit is %, between 0 and 1, and the reserve producing field is the cumulative recovery degree, the unit is %, between 0 and 1.

[0075] The membership function can also be called the attribution function or the fuzzy meta function, the function of the membership function is to normalize the selected indexes, process the index data of different orders of magnitude to the range of [0, 1], select the appropriate membership function according to the distribution range of the collected specific data of each index, process the index data with small distribution range by using the linear membership function, and process the data with large distribution range by using the exponential membership function. In the embodiment, since the distribution range of the pressure field is large, the exponential membership function can be selected to normalize the pressure field; and for the saturation field and the reserve producing field with small distribution range, the linear membership function can be selected for normalization.

[0076] Further, after the pressure field, the saturation field and the reserve producing field are normalized, the normalized pressure field, the normalized saturation field and the normalized reserve producing field are analyzed by using the clustering algorithm respectively to obtain the corresponding division levels.

[0077] In this embodiment, when performing the grading, the data of the three physical fields are analyzed by using a clustering algorithm to obtain the grading limits of the three physical fields, and grading is performed according to the grading limits of the three physical fields. In a specific implementation, the MDCA (Maximum Density Clustering Application) algorithm is used to perform the grading of the three physical fields. The MDCA clustering algorithm introduces the idea of density into the division clustering, uses density instead of initial centroid as the basis for investigating the cluster attribution, can automatically determine the number of clusters and find clusters of arbitrary shape. The MDCA clustering algorithm first divides the data set into basic clusters, then uses the idea of agglomerative hierarchical clustering to merge the basic clusters that are close to each other to obtain the final cluster division, and finally processes the remaining points. The MDCA clustering algorithm generally does not retain noise, so it also avoids the situation of discarding a large number of objects due to improper threshold selection. Compared with other algorithms, the MDCA clustering algorithm is not sensitive to noise data and does not depend on the selection of initial data points, and can complete clustering of arbitrary shape.

[0078] In this embodiment, the number of grading of each physical field needs to be determined first, and the number of grading of the physical field should not be too much or too little; too much grading number will make the evaluation of the physical field too complex, increase the calculation amount of the physical field, and the subsequent adjustment of the physical field will also lack pertinence due to too much grading; but too little grading number cannot objectively and effectively evaluate the physical field, and the understanding of the physical field is too shallow. For the grading of the physical field, scholars now commonly divide the physical field into 3-6 levels. The MDCA clustering algorithm is used for iteration, and the corresponding division level of each is calculated after setting the number of grading.

[0079] For example, the MDCA clustering algorithm is used to divide each physical field into four categories, and then the highest utilization degree is defined as the first utilization field, followed by the second utilization field, and so on to obtain the corresponding division level of each physical field.

[0080] In addition, after dividing the grading of each physical field by using the clustering algorithm, the grading limits of each division level after setting the number of grading can also be obtained, that is, the upper limit value and the lower limit value of each physical field division level. Therefore, according to the upper limit value and the lower limit value of each physical field division level, the grading standard can be imported into the volatile oil reservoir geological model after the depletion of the target volatile oil reservoir by using the CMG commonly used numerical simulation software of oil and natural gas, and the physical field map after grading is output, which provides the basis for the distribution of the physical field for the subsequent development adjustment.

[0081] S4: determining a comprehensive flow field grade of the target volatile oil reservoir based on the respective division grades of the pressure field, the saturation field and the reserve producing field; and performing flow field evaluation on the depletion production of the target volatile oil reservoir based on the comprehensive flow field grade to obtain a flow field evaluation result; and guiding the depletion production of the target volatile oil reservoir based on the flow field evaluation result.

[0082] In the embodiment of the present application, the flow field of the depletion production of the target volatile oil reservoir is characterized by the comprehensive effect of the three physical fields. It can be understood that the physicochemical properties of the fluid in each grid of the volatile oil reservoir geological model are different after depletion production, which leads to different three physical fields of each grid. The three physical fields are comprehensively analyzed to determine the flow field grading evaluation standard of the depletion production of the target volatile oil reservoir. The flow field with poor rating has no production value in the subsequent production, which guides the subsequent stimulation operation.

[0083] Specifically, the respective exploitation potential degree data of each division grade is obtained; the exploitation potential degree data of the pressure field corresponding grade, the exploitation potential degree data of the saturation field corresponding grade and the exploitation potential degree data of the reserve producing field corresponding grade are multiplied to determine the comprehensive flow field exploitation potential degree data of the pressure field, the saturation field and the reserve producing field; and the comprehensive flow field exploitation potential degree data is matched with the preset grading standard to determine the comprehensive flow field grade of the target volatile oil reservoir.

[0084] In the embodiment, each grade in the physical field, the saturation field and the reserve producing field is scored to represent the exploitation potential degree data, and then a comprehensive score is determined by comprehensively determining the score of each physical field.

[0085] It can be understood that, since the grade of each physical field is obtained in the foregoing step, the scores of the respective physical field corresponding grades are multiplied to determine the comprehensive flow field grade score, that is, the comprehensive flow field exploitation potential degree data.

[0086] It should be noted that the comprehensive flow field grade level corresponding to each comprehensive flow field exploitation potential degree data is preset, that is, the preset flow field grading standard. When the comprehensive flow field exploitation potential degree data is determined, it is matched with the preset flow field grading standard to determine the comprehensive flow field grade of the target volatile oil reservoir. The flow field of the depletion production of the target volatile oil reservoir is evaluated to guide the corresponding depletion production of the target volatile oil reservoir.

[0087] If the comprehensive flow field grade is high, it represents that the development potential of the position is large and needs to be paid attention to in subsequent development adjustment; if the comprehensive flow field grade is low, it represents that the development potential of the position is poor and does not need to be planned in subsequent development.

[0088] For example, the comprehensive flow field grade of the target volatile oil reservoir is determined by the comprehensive flow field exploitation potential degree data of the pressure field, the saturation field and the reserve producing field. Figure 2The process diagram of the whole target volatile oil reservoir depletion production guidance is shown. The quantitative hierarchical evaluation and characterization of the reconstructed dynamic parameters of the target volatile oil reservoir in the depletion production process are carried out, and a set of hierarchical evaluation method based on non-subjective factor control and coupling of multiple development dynamic factors is established. The historical geological data of the target volatile oil reservoir are used to establish a volatile oil reservoir geological model, and the physical parameters after depletion production are determined;

[0089] Then the pressure distribution, saturation distribution and reservoir producing distribution in the depletion development of the target volatile oil reservoir are calculated through the related formula, the pressure field, saturation field and reserve producing field of the volatile oil reservoir are determined, the data of the three physical fields are normalized by using the membership function, the clustering analysis of the data of the three physical fields is carried out by using the MDCA clustering algorithm, the corresponding grade division limits are determined, and finally the three physical fields are comprehensively analyzed to determine the hierarchical evaluation standard of the flow field of the target volatile oil reservoir in the depletion production. The flow field hierarchical evaluation method of the target volatile oil reservoir in the depletion production is finally formed, which can guide the depletion production of the target volatile oil reservoir.

[0090] The embodiment provides a volatile oil reservoir depletion production guidance method, including: obtaining historical geological data of a target volatile oil reservoir, and establishing a volatile oil reservoir geological model by using the historical geological data; carrying out depletion production on the target volatile oil reservoir by using the volatile oil reservoir geological model, and obtaining grid fluid physical parameters determined by the volatile oil reservoir geological model in the depletion production process; determining a pressure field, a saturation field and a reserve producing field of the target volatile oil reservoir according to the grid fluid physical parameters, and performing grade division on the pressure field, the saturation field and the reserve producing field respectively by using a clustering algorithm to obtain respective corresponding division grades; determining a comprehensive flow field grade of the target volatile oil reservoir based on the respective corresponding division grades of the pressure field, the saturation field and the reserve producing field, and guiding corresponding depletion production of the target volatile oil reservoir based on the comprehensive flow field grade. It can be seen that the three physical fields, i.e. the pressure field, the saturation field and the reserve producing field, are used to characterize the flow field of the target volatile oil reservoir in the depletion development. Since the comprehensive flow field of the target volatile oil reservoir after depletion production is greatly affected by the above three physical fields, the embodiment can take into account the influence of multiple physical fields on the flow field distribution, and the single performance of each physical field can be directly fed back to the flow field grade division. After the three physical fields are divided into grades, the influence of the three physical fields on the flow field after depletion production of the volatile oil reservoir is coupled, the comprehensive flow field grade of the target volatile oil reservoir is determined, and the flow field evaluation of the depletion production of the target volatile oil reservoir is carried out based on the comprehensive flow field grade of the target volatile oil reservoir, so that the guidance of the depletion production of the target volatile oil reservoir is realized.

[0091] Embodiment two

[0092] As Figure 3As shown, a volatile oil reservoir depletion exploitation guidance method comprises:

[0093] S1: Obtain historical geological data of a target volatile oil reservoir, and establish a volatile oil reservoir geological model using the historical geological data.

[0094] In this embodiment, the establishment of the geological model using the historical data of the target volatile oil reservoir specifically comprises:

[0095] A target volatile oil reservoir is selected, and a volatile oil reservoir geological model is established using historical geological data of the target volatile oil reservoir;

[0096] The volatile oil reservoir geological model is discretized by using equidistant (or non-equidistant) grids in the plane and grids in the vertical direction to divide the oil and gas reservoir into several geological layers. The volatile oil reservoir geological model reproduces the structural form of the reservoir, laying a foundation for reflecting the plane heterogeneity and interlayer heterogeneity of reservoir physical properties; and the oil and gas two-phase flow in the grid is calculated.

[0097] S2: Depletion exploitation is performed on the target volatile oil reservoir, and first, second, and third physical parameters in the depletion exploitation process are determined according to the volatile oil reservoir geological model.

[0098] In this embodiment, after the volatile oil reservoir geological model is established using the historical geological data of the target volatile oil reservoir, depletion exploitation is performed using the volatile oil reservoir geological model, and the physical property parameter conditions of the oil and gas two-phase flow in each grid of the volatile oil reservoir geological model after the depletion exploitation are calculated;

[0099] The first, second, and third physical parameters are obtained through the physical property parameter conditions of the oil and gas two-phase flow in the grid, and the first, second, and third physical parameters are parameters for determining the physical field; specifically, the first physical parameter is used to calculate the pressure field of the target volatile oil reservoir, the second physical parameter is used to calculate the saturation field of the target volatile oil reservoir, and the third physical parameter is used to calculate the reserve producing field of the target volatile oil reservoir;

[0100] The first physical parameter includes the relative permeability of the oil and gas two-phase flow in the grid, the oil and gas density in the grid, and the oil and gas viscosity in the grid;

[0101] The second physical parameter includes the oil phase mobility in the grid, the total mobility of the oil and gas two-phase flow in the grid, and the oil saturation in the current grid;

[0102] The third physical parameter includes the grid thickness of the volatile oil reservoir geological model, the oil saturation in the grid, the swept area in the grid, and the porosity.

[0103] S3: determining the pressure field of the target volatile oil reservoir according to the first physical property parameter by using a preset pressure distribution equation, and performing grade division on the pressure field according to a preset grade division rule to obtain a corresponding division grade.

[0104] In this embodiment, after the fluid physical property parameters in the grid of the known volatile oil reservoir geological model are known, the pressure field of the target volatile oil reservoir is calculated according to the oil-gas two-phase flow in the grid of the volatile oil reservoir geological model, in combination with the relative permeability change of the oil-gas two-phase in the grid, the oil-gas density in the grid and the oil-gas viscosity in the grid.

[0105] The preset pressure distribution equation is:

[0106]

[0107] wherein, k ro is the relative permeability of the oil phase in the grid; krg is the relative permeability of the gas phase in the grid; p o is the density of the oil phase in the grid; p g is the density of the gas phase in the grid; m o is the viscosity of the oil phase in the grid; m g is the viscosity of the oil phase in the grid; p is the average pressure of the current target oilfield block; p r is the reference pressure.

[0108] Taking the A block of K oilfield as an example:

[0109]

[0110] wherein, k roij is the relative permeability parameter of the oil phase in the ij grid, with the unit of um 2 ; k rgij is the relative permeability parameter of the gas phase in the ij grid, with the unit of um 2 ; m oij is the viscosity of the oil phase in the ij grid, with the unit of mPa·s; m gij is the viscosity of the gas phase in the ij grid, with the unit of mPa·s; p oij is the density of the oil phase in the ij grid per unit time, with the unit of g / cm 3 ; p gij is the density of the gas phase in the ij grid per unit time, with the unit of g / cm 3 ;

[0111] The pressure distribution in the grid can be obtained from the above equation, and the pressure value in each grid, i.e. the pressure field data, is calculated to obtain the pressure field of the target volatile oil reservoir.

[0112] Further, the pressure field data is normalized by using a preset membership function to obtain normalized pressure field data; since the range of variation of the pressure field data is large, the exponential membership function is used for normalization:

[0113]

[0114] wherein m(p ij ) a is the pressure field data in the ij grid after normalization; m(p ij ) is the pressure field data in the ij grid before normalization; m(p min is the minimum pressure field data; and m(p max ) is the maximum pressure field data.

[0115] According to the pressure distribution in the grid, the distribution of the pressure field is calculated by the CMG software, the normalized pressure field is classified by using the MDCA clustering algorithm, and then the pressure field classification is obtained by using the CMG in combination with the pressure field classification standard, as shown in Figure 4 .

[0116] S4: The saturation field of the target volatile oil reservoir is determined according to the second physical parameter by using a preset saturation equation, and the saturation field is classified according to a preset classification rule to obtain a corresponding classification level.

[0117] In this embodiment, after the fluid physical parameters in the grid of the known volatile oil reservoir geological model are known, the saturation field of the target volatile oil reservoir is calculated according to the oil phase mobility in the grid, the total oil and gas phase mobility in the grid, and the oil saturation change in the grid;

[0118] The preset saturation equation is:

[0119]

[0120] wherein S o is the saturation of the oil phase in the grid; B o is the volume coefficient of the oil phase in the grid; p is the average pressure of the current target oilfield block; λ o is the oil phase mobility in the grid; λ t is the total oil and gas phase mobility in the grid; and c t is the comprehensive compression coefficient of the rock.

[0121] Taking the A block of K oilfield as an example, the saturation field is calculated by using the pressure field data and the known fluid parameters in the grid of the volatile oil reservoir geological model, and the calculation equation of the saturation field is:

[0122]

[0123] Among them, S oij Let λ represent the saturation of the oil phase within the ij grid; oij Let λ be the mobility of the oil phase within the ij grid; tij B represents the total mobility of the oil and gas phases within the ij grid; oij c is the volume factor of the oil phase within the ij grid; tij denoted as the comprehensive rock compression coefficient within the ij grid.

[0124] The above equations can be used to obtain the saturation distribution within the grid, and thus obtain saturation field data and the saturation field of the target volatile oil reservoir.

[0125] Furthermore, the saturation field data is normalized using a preset membership function to obtain a normalized saturation field; a linear membership function is selected for normalization.

[0126]

[0127] In the formula, S represents the saturation field data within the normalized ij grid; ij S represents the saturation field data within the ij grid before normalization; min For the minimum saturation field data; S max This represents the data for the field with the highest saturation.

[0128] Based on the saturation distribution within the grid, the saturation field distribution is calculated using CMG software. The normalized saturation field is then classified using the MDCA clustering algorithm. Combined with the saturation field level classification criteria, the saturation field level classification can be obtained using CMG. Figure 5 As shown.

[0129] S5: Using the preset kinetic field equation, determine the reserve kinetic field of the target volatile oil reservoir based on the third physical property parameter, and classify the reserve kinetic field according to the preset classification rules to obtain the corresponding classification level.

[0130] In this embodiment, the reservoir utilization field is calculated based on the grid thickness, oil saturation variation within the grid, grid sweep area, and porosity of the volatile oil reservoir geological model.

[0131] The presupposed dynamic field equations are:

[0132]

[0133] Among them, E R Used to characterize the degree of reservoir recovery within a grid; A is the planar area of ​​the reservoir within the grid; A s h represents the planar sweep area of ​​the reservoir within the grid; h represents the longitudinal thickness of the reservoir within the grid; h s S represents the longitudinal sweep thickness of the reservoir within the grid;oi is the original oil saturation in the grid; S o is the current oil saturation in the grid.

[0134] Taking the K oilfield A block as an example, under the condition that the grid wave area and various fluid parameters in the volatile reservoir geological model grid are known, the reservoir producing degree is calculated from the saturation change in the grid and the relevant parameters of the volatile reservoir geological model, and the reservoir producing field calculation formula is:

[0135]

[0136] wherein, E Rij is the reservoir producing degree in the ij grid; A ij is the reservoir plane area in the ij grid; A sij is the reservoir plane wave area in the ij grid; h ij is the reservoir vertical thickness in the ij grid; h sij is the reservoir vertical wave thickness in the ij grid; S oi is the original oil saturation in the ij grid; S o is the current oil saturation in the ij grid.

[0137] The reservoir producing distribution in the grid can be obtained from the above equation, and the reservoir producing field data and the reservoir producing field of the target volatile reservoir are obtained.

[0138] Further, the reservoir producing field data is normalized by using a preset membership function to obtain the normalized reservoir producing field; and the subsequent reasonable grading is facilitated.

[0139]

[0140] wherein, is the reservoir producing field data in the ij grid after normalization; E ij is the reservoir producing field data in the ij grid before normalization; E min is the minimum reservoir producing field data; E max is the maximum reservoir producing field data.

[0141] According to the reservoir producing distribution in the grid, the reservoir producing field distribution is calculated by the CMG software, the normalized reservoir producing field is classified by using the MDCA clustering algorithm, and then combined with the reservoir producing field grade division standard, the reservoir producing field grade division situation can be obtained by using the CMG, as shown in Figure 6 .

[0142] S6: determining a comprehensive flow field grade of the target volatile oil reservoir based on the respective division grades of the pressure field, the saturation field and the reserve producing field, and performing flow field evaluation on the depletion production of the target volatile oil reservoir based on the comprehensive flow field grade of the target volatile oil reservoir to obtain a flow field evaluation result;

[0143] guiding the depletion production of the target volatile oil reservoir based on the flow field evaluation result.

[0144] In this embodiment, the pressure field can indicate the pressure distribution in each grid of the target volatile oil reservoir after depletion production, the saturation field can reflect the content of fluid in each grid of the target volatile oil reservoir after depletion production, and the reserve producing field can reflect the crude oil producing situation in each grid of the target volatile oil reservoir after depletion production, through the influence of the three physical fields of the pressure field, the saturation field and the reserve producing field on the flow field evaluation.

[0145] After the distribution diagrams of the pressure field, the saturation field and the reserve producing field are made by using CMG, the flow field of each grid of the target volatile oil reservoir is calculated by assigning scores according to the grade assignment system, and the above three fields are classified into four levels of producing grades in the MDCA clustering algorithm. In the four levels of classification, the first level represents that the producing degree of the physical field is very high, and there is no subsequent research value. If one of the three physical fields is a first-level field, the flow field grade of the grid is a first-level flow field, and there is no subsequent potential tapping value.

[0146] Further, scores are assigned to different producing grades. First, scores are set according to the producing grade types divided by the three physical fields. The first producing grade represents no tapping potential, and the scores of the pressure field, the saturation field and the reserve producing field are all 0. The scores of the second producing grade are all 1, and the producing degree is only next to the first producing grade, and the tapping potential is slightly higher than that of the first producing level. The scores of the third producing grade are all 2, and the producing degree is only next to the second producing grade, and the tapping potential is slightly higher than that of the second producing level. The scores of the fourth producing grade are all 3, and the producing degree is only next to the third producing grade, and the tapping potential is slightly higher than that of the third producing level. Therefore, the comprehensive score = pressure field score × saturation field score × reserve producing field score, and the total producing grade score is 0 when the first producing grade is reached in any field. As shown in Table 1, the grading standard of the comprehensive flow field grade is as follows:

[0147] Table 1 Grading standard of comprehensive flow field grade

[0148] Flow field level Flow field activation level score Flow field level Ⅰ 0 Primary flow field Ⅱ [1,6] Secondary flow field Ⅲ (6,18] Tertiary flow field Ⅳ (18,27] Quaternary flow field

[0149] According to the three physical fields of the pressure field, the saturation field and the reserve producing field in different grids, the final flow field grading situation is obtained, the development potential of the volatile reservoir after depletion production is evaluated, and a theoretical basis is provided for the implementation of the subsequent enhanced oil recovery measures of the whole volatile reservoir. The first grade, the second grade, the third grade and the fourth grade of the flow field represent that the grid has a high degree of development, a higher degree of development, a medium degree of development and a low degree of development in the depletion production process, and the development potential decreases in turn. It can be understood that the part of the first grade flow field represents that the grid has been developed to a great extent in the depletion production process, and almost has no development potential, and does not need to be planned in the subsequent development; the flow field of the fourth grade flow field represents that the grid has almost no development and utilization in the depletion production process, in short, has great subsequent exploitation value.

[0150] As shown in Figure 7 The final flow field grading situation obtained by using the CMG software is shown in the figure, wherein the part with the third grade flow field and concentrated in the target volatile reservoir geological model grid after depletion production of the volatile reservoir has greater development potential, and needs to be paid attention to in the subsequent development adjustment; the part with the first grade flow field and concentrated in the geological model has poor development potential.

[0151] It can be seen that the pressure field, the saturation field and the reserve producing field are respectively graded, and the coupling of the multiple different physical fields in the depletion production of the target volatile reservoir is comprehensively considered; since the comprehensive flow field after the depletion production of the target volatile reservoir is greatly affected by the above three physical fields, the present application can take into account the influence of multiple physical fields on the flow field distribution, and the single performance of each physical field will be directly fed back to the flow field grading.

[0152] In terms of the pressure field, the flow field pressure distribution after the depletion production process of the target volatile reservoir is quantitatively divided, and the pressure zones of different sizes in the flow field are graded;

[0153] In terms of the saturation field, the oil and gas distribution of each grid after the depletion production process of the target volatile reservoir is divided, the key parts for the subsequent stimulation operation are determined, and the saturation of the flow field is graded;

[0154] In terms of the reserve producing field, the reserve producing degree of each grid of the target volatile reservoir geological model after the depletion production is calculated, and the remaining oil in the flow field is graded. After the three physical field standards are determined, the comprehensive influence of the three physical fields on the flow field after the depletion production of the target volatile reservoir is integrated.

[0155] In order for those skilled in the art to better understand the technical solutions of the present embodiment, the specific steps of obtaining the preset pressure field equation will be described:

[0156] Step one: According to the relevant data of the target volatile oil reservoir in the process of depletion, combined with the original formation and fluid physical conditions, the relevant equation is constructed; under the reservoir conditions (lower than the bubble point pressure), oil and gas two-phase flow appears in the formation, and the total mass flow M of the oil and gas two-phase flow is:

[0157]

[0158] Where, ρ o is the oil phase density in the grid; ρ g is the gas phase density in the grid; q o is the oil phase volume flow in the grid; q g is the gas phase volume flow in the grid; and and are brought into the flow mass M, and then the total mass flow M becomes:

[0159]

[0160] In the formula: M is the total mass flow of oil and gas two-phase flow; GOR is the initial oil and gas ratio; B o is the formation coefficient of the oil phase in the grid; B g is the formation coefficient of the gas phase in the grid; μ o is the oil phase viscosity in the grid; k o is the oil phase permeability in the grid; k is the permeability; k ri is the original oil phase relative permeability; k o is the oil phase relative permeability; μ i is the initial viscosity of crude oil; and h is the effective reservoir thickness.

[0161] Step two: According to the material balance equation and combined with the comprehensive compressibility coefficient, the pressure field equation of the target volatile oil reservoir under depletion conditions is constructed. According to the material balance equation:

[0162]

[0163] Where, ρ t = ρ o s o + ρ g s g ; the comprehensive compressibility coefficient Ct is introduced:

[0164] Where, C t is the comprehensive compressibility coefficient of the rock; C o is the compressibility coefficient of the oil phase in the grid; C g is the compressibility coefficient of the gas phase in the grid; s o is the saturation of the oil phase in the grid; and s gSaturation of gas phase in the grid; V is the volume of crude oil under reservoir conditions; ρ is the density of crude oil;

[0165] The material balance equation is transformed as:

[0166]

[0167] Therefore, the function expression of the preset pressure field equation is:

[0168]

[0169] Where, k ro is the relative permeability of oil phase in the grid; k rg is the relative permeability of gas phase in the grid; ρ o is the density of oil phase in the grid; ρ g is the density of gas phase in the grid; μ o is the viscosity of oil phase in the grid; μ g is the viscosity of oil phase in the grid; p is the average pressure of the current target oilfield block; p r is the reference pressure.

[0170] Step three: according to the related data of the target volatile reservoir in the process of depletion recovery, combined with the original formation and fluid physical conditions, the saturation field equation is constructed;

[0171] If the rock skeleton is regarded as a rigid medium, the relationship between pressure and saturation can be derived according to the material balance method, which provides great help for the calculation of saturation field on the basis of pressure field calculation, and the related equation is as follows:

[0172]

[0173] In the formula, V p is the pore volume in the grid; V o is the oil content in the void volume in the grid (low face value); V g is the gas content in the pore volume in the grid; p is the current average pressure; B o is the volume coefficient of oil phase in the grid; B g is the volume coefficient of gas phase in the grid.

[0174] According to the above formula, the oil and gas production under unit pressure drop can be obtained:

[0175]

[0176] Production gas-oil ratio:

[0177]

[0178] In the formula, R p (k) is the production gas-oil ratio; Vo Oil content (low surface value) within the void volume of the grid; V g This refers to the gas content within the pore volume of the grid.

[0179] The production gas-oil ratio consists of two parts:

[0180]

[0181] Combining the above equations, we can obtain:

[0182]

[0183] In the formula, R p For the production gas-oil ratio; k ro k represents the relative permeability of the oil phase within the grid. rg The relative permeability of the gas phase within the grid; μ o The viscosity of the oil phase within the grid; μ g R is the oil phase viscosity within the grid; p is the average pressure of the current target oilfield block; s The dissolved gas-oil ratio of crude oil;

[0184] After sorting and simplification, the relationship between pressure and saturation is obtained as follows:

[0185]

[0186] Among them, c t The overall compressibility coefficient of the rock:

[0187]

[0188] In the formula, R so The dissolved gas-oil ratio;

[0189] If the elasticity of the rock is ignored, the rock elastic compressibility coefficient c in the formula... f This can be ignored. Ignoring the elasticity of the rock, the formula can be simplified to:

[0190]

[0191] Substituting this into the pressure-saturation relationship, we obtain the differential material balance equation for the target volatile oil reservoir:

[0192]

[0193] in: The mass balance equation for two-phase flow of oil and gas is obtained using CMG software to acquire the relative permeability data of the oil and gas phases. The solution is then obtained using the Euler method, where X(p), Y(p), and Z(p) can be obtained from commonly used high-pressure property formulas for the oil and gas phases. tc is the overall compressibility coefficient of the rock. f S is the elastic compressibility coefficient of the rock; o S represents the oil phase saturation within the grid. g λ represents the gas phase saturation within the grid. o λ represents the oil phase mobility within the grid. g This represents the gas phase mobility within the grid.

[0194] Step 4: Based on relevant data from the depletion process of the target volatile oil reservoir, construct the reserve utilization field equations in conjunction with the original formation and fluid properties.

[0195] The thickness and porosity of the target volatile oil reservoir geological model grid were collected, and the parameters such as the swept area, oil saturation, residual oil saturation, and volume factor of each grid in the geological model of the target volatile oil reservoir after exhaustion were statistically analyzed.

[0196] Based on the data from each grid of the volatile oil reservoir geological model after depletion development, the utilization level of reserves in each grid is calculated, and a formula for calculating the recovery level of the reservoir after depletion development within the grid is established:

[0197]

[0198] Among them, E Rij For the oil reservoir recovery degree within grid ij; A ij Let A be the reservoir planar area within grid ij; sij h represents the reservoir's planar sweep area. ij h represents the longitudinal thickness of the reservoir within the ij grid. sij S represents the longitudinal sweep thickness of the reservoir. oi S represents the original oil saturation within the grid. o This represents the current oil saturation level within the grid.

[0199] This embodiment proposes a flow field evaluation method for the depletion development of volatile oil reservoirs, taking Block A of the K oilfield as an example. A geological model is established using data from the target oilfield block to simulate depletion development. Pre-defined pressure distribution equations, saturation equations, and dynamic field equations are used to quantitatively evaluate the three physical fields. Subsequently, the MDCA clustering algorithm is used to normalize and determine the level classification boundaries, thus defining the flow field level classification boundaries. This method can quantitatively describe the flow field distribution and subsequent exploitation potential after reservoir depletion development, providing convenient and accurate theoretical guidance for the implementation of subsequent production enhancement measures for volatile oil reservoirs.

[0200] Example 3

[0201] like Figure 8 As shown, based on the same inventive concept as the above embodiments, the present invention also provides a guidance device for the depletion exploitation of volatile oil reservoirs, comprising:

[0202] The parameter determination module is used to determine the fluid physical property parameters within the grid during the depletion production process based on a preset volatile reservoir geological model.

[0203] The classification module is used to determine the pressure field, saturation field, and reserve utilization field of the target volatile oil reservoir based on the fluid property parameters within the grid, and to classify the pressure field, saturation field, and reserve utilization field into levels using a clustering algorithm to obtain the classification levels corresponding to each of the pressure field, saturation field, and reserve utilization field.

[0204] The evaluation module is used to determine the comprehensive flow field level of the target volatile oil reservoir based on the classification levels corresponding to the pressure field, the saturation field, and the reserve utilization field; and to evaluate the flow field for the depletion exploitation of the target volatile oil reservoir based on the comprehensive flow field level, thereby obtaining the flow field evaluation results.

[0205] The extraction guidance module is used to guide the depletion extraction of the target volatile oil reservoir based on the flow field evaluation results.

[0206] Example 4

[0207] like Figure 9 As shown, the present invention also provides an electronic device 100 for implementing a method for guiding the exploitation of volatile oil reservoirs;

[0208] The electronic device 100 includes a memory 101, at least one processor 102, a computer program 103 stored in the memory 101 and executable on at least one processor 102, and at least one communication bus 104.

[0209] The memory 101 can be used to store computer program 103. The processor 102 implements the steps of the guide method for the depletion exploitation of volatile oil reservoirs in Embodiment 1 by running or executing the computer program stored in the memory 101 and calling the data stored in the memory 101.

[0210] The memory 101 may primarily include a program storage area and a data storage area. The program storage area may store the operating system, application programs required for at least one function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created based on the use of the electronic device 100 (such as audio data), etc. In addition, the memory 101 may include non-volatile memory, such as hard disk, RAM, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one disk storage device, flash memory device, or other non-volatile solid-state storage device.

[0211] At least one processor 102 may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Processor 102 may be a microprocessor or any conventional processor. Processor 102 is the control center of electronic device 100, connecting various parts of electronic device 100 via various interfaces and lines.

[0212] The memory 101 in the electronic device 100 stores multiple instructions to implement a method for guiding the exploitation of volatile oil reservoirs in exhaustion, and the processor 102 can execute multiple instructions to achieve the following:

[0213] The fluid properties parameters within the grid during the depletion extraction process are determined based on the pre-set volatile reservoir geological model;

[0214] The pressure field, saturation field, and reserve utilization field of the target volatile oil reservoir are determined based on the fluid property parameters within the grid. The pressure field, saturation field, and reserve utilization field are then classified into levels using a clustering algorithm to obtain the corresponding classification levels for each of the pressure field, saturation field, and reserve utilization field.

[0215] The comprehensive flow field level of the target volatile oil reservoir is determined based on the classification levels corresponding to the pressure field, the saturation field, and the reserve utilization field; the flow field evaluation of the depletion exploitation of the target volatile oil reservoir is carried out based on the comprehensive flow field level to obtain the flow field evaluation results;

[0216] The flow field evaluation results provide guidance for the depletion exploitation of the target volatile oil reservoir.

[0217] Example 5

[0218] If the modules / units integrated in the electronic device 100 are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, and read-only memory (ROM).

[0219] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0220] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure One One or more processes and / or boxes Figure One A device that provides the functions specified in one or more boxes.

[0221] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure One One or more processes and / or boxes Figure One The function specified in one or more boxes.

[0222] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure One One or more processes and / or boxes Figure One The steps of the function specified in one or more boxes.

[0223] In the description of this specification, references to terms such as "an embodiment," "example," "specific example," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0224] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for guiding the depletion exploitation of volatile oil reservoirs, characterized in that, include: The fluid properties parameters within the grid during the depletion extraction process are determined based on the pre-set volatile reservoir geological model; The pressure field, saturation field, and reserve utilization field of the target volatile oil reservoir are determined based on the fluid property parameters within the grid. The pressure field, saturation field, and reserve utilization field are then classified into levels using a clustering algorithm to obtain the corresponding classification levels for each of the pressure field, saturation field, and reserve utilization field. The comprehensive flow field level of the target volatile oil reservoir is determined based on the classification levels corresponding to the pressure field, the saturation field, and the reserve mobilization field. Based on the comprehensive flow field level, a flow field evaluation is conducted on the depletion exploitation of the target volatile oil reservoir to obtain the flow field evaluation results; The flow field evaluation results provide guidance for the depletion exploitation of the target volatile oil reservoir.

2. The method for guiding the depletion exploitation of volatile oil reservoirs according to claim 1, characterized in that, The fluid properties parameters within the grid during the depletion extraction process include: the flow of oil and gas phases within the grid in the volatile reservoir geological model and the fluid properties parameters of the oil and gas phases within each grid; The fluid properties of the oil and gas phases within each grid include: relative permeability of the oil and gas phases within each grid, oil and gas viscosity within each grid, oil and gas density within each grid, pressure field variation within each grid, thickness of each grid, fluid saturation within each grid, oil saturation within each grid, and grid sweep parameters for each grid.

3. The method for guiding the depletion exploitation of volatile oil reservoirs according to claim 2, characterized in that, The determination of the pressure field, saturation field, and reserve utilization field of the target volatile oil reservoir based on the fluid property parameters within the grid specifically includes: Based on the flow of oil and gas phases within the grid in the geological model of the volatile oil reservoir, and combined with the relative permeability of the oil and gas phases within each grid, the oil and gas viscosity within each grid, and the oil and gas density within each grid, the pressure field of the target volatile oil reservoir is calculated. Based on the oil and gas viscosity in each grid of the geological model of the volatile oil reservoir, the change of pressure field in each grid, and the fluid saturation in each grid, the saturation field of the target volatile oil reservoir is calculated. Based on the thickness of each grid in the geological model of the volatile oil reservoir, the oil saturation within each grid, and the grid sweep efficiency data of each grid, the reserve utilization field of the target volatile oil reservoir is calculated.

4. The method for guiding the depletion exploitation of volatile oil reservoirs according to claim 1, characterized in that, Before using clustering algorithms to classify the pressure field, saturation field, and reserve mobilization field into different levels, the pressure field, saturation field, and reserve mobilization field are normalized using membership functions to obtain normalized pressure field, normalized saturation field, and normalized reserve mobilization field.

5. The method for guiding the depletion exploitation of volatile oil reservoirs according to claim 4, characterized in that, The membership functions include linear membership functions or exponential membership functions.

6. The method for guiding the depletion exploitation of volatile oil reservoirs according to claim 1, characterized in that, The determination of the comprehensive flow field level of the target volatile oil reservoir based on the respective classification levels of the pressure field, the saturation field, and the reservoir utilization field specifically includes: Obtain the mining potential data corresponding to each classification level; Multiply the exploitation potential data corresponding to the pressure field level, the exploitation potential data corresponding to the saturation field level, and the exploitation potential data corresponding to the reserve utilization field level to determine the comprehensive flow field exploitation potential data of the pressure field, the saturation field, and the reserve utilization field. By matching the comprehensive flow field exploitation potential data with the preset flow field classification standard, the comprehensive flow field level of the target volatile oil reservoir is determined.

7. The method for guiding the depletion exploitation of volatile oil reservoirs according to claim 1, characterized in that, The steps for establishing the pre-set geological model of the volatile oil reservoir include: Select the target volatile oil reservoir, obtain the historical geological data of the target volatile oil reservoir, and establish a geological model of the volatile oil reservoir using the historical geological data of the target volatile oil reservoir.

8. A guidance device for the depletion exploitation of volatile oil reservoirs, characterized in that, include: The parameter determination module is used to determine the fluid physical property parameters within the grid during the depletion production process based on a preset volatile reservoir geological model. The classification module is used to determine the pressure field, saturation field, and reserve utilization field of the target volatile oil reservoir based on the fluid property parameters within the grid, and to classify the pressure field, saturation field, and reserve utilization field into levels using a clustering algorithm to obtain the classification levels corresponding to each of the pressure field, saturation field, and reserve utilization field. The evaluation module is used to determine the comprehensive flow field level of the target volatile oil reservoir based on the classification levels corresponding to the pressure field, the saturation field, and the reserve mobilization field. Based on the comprehensive flow field level, a flow field evaluation is conducted on the depletion exploitation of the target volatile oil reservoir to obtain the flow field evaluation results; The extraction guidance module is used to guide the depletion extraction of the target volatile oil reservoir based on the flow field evaluation results.

9. An electronic device, characterized in that, It includes a processor and a memory, the processor being used to execute a computer program stored in the memory to implement a method for guiding the depletion exploitation of a volatile oil reservoir as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores at least one instruction, which, when executed by a processor, implements a method for guiding the depletion exploitation of a volatile oil reservoir as described in any one of claims 1 to 7.

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