A complex reservoir conductive mechanism analysis method, system, device, medium and program
By identifying the single pore type of complex reservoirs and constructing a three-dimensional core model, the resistivity relationship of the core was calculated, which solved the problem of low efficiency in the analysis of conductivity mechanisms in complex reservoirs and achieved higher accuracy.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- CHINA PETROCHEMICAL CORP
- Filing Date
- 2024-12-10
- Publication Date
- 2026-06-12
Smart Images
Figure CN122193308A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of conductivity mechanism analysis technology, and in particular to a method, system, device, medium and program for analyzing the conductivity mechanism of complex reservoirs. Background Technology
[0002] In oilfield exploration and development, accurately assessing the pore structure characteristics of reservoirs and their impact on resistivity is crucial. Complex reservoirs, especially carbonate reservoirs, exhibit exceptionally complex pore structures due to their diverse pore types and sizes spanning multiple orders of magnitude. This results in pronounced non-Arche characteristics in reservoir electrical properties, limiting the application of traditional evaluation models such as the Archie formula. More refined methods are needed to assess reservoir resistivity.
[0003] In complex reservoirs (low-porosity and low-permeability sandstone, tight sandstone reservoirs, and carbonate reservoirs with well-developed multi-porous media), low-porosity and low-permeability sandstone reservoirs and tight sandstone reservoirs are characterized by low porosity and low permeability, well-developed matrix and dissolution pores, complex pore structures, and strong heterogeneity, all of which contribute to the non-Arch phenomenon. The complex pore structure is the main cause of this phenomenon. The rock pore structure mainly includes the geometry, size, distribution, and interconnection of pores and throats. Existing research, through nuclear magnetic resonance, rock electrical experiments, porosimetry, mercury intrusion porosimetry, and thin section experiments on carbonate samples from the Middle Triassic Leikoupo Formation, combined with digital image analysis to quantitatively analyze pore structure characteristics, has found that porosity is an important factor affecting resistivity, but not the only one. The size and number of pores, and the complexity of the pore network, have a much greater impact on resistivity than throat size. These complex factors have varying degrees of influence on the resistivity of shale reservoirs. Therefore, improving the accuracy of reservoir conductivity mechanism research has become an urgent problem to be solved. Summary of the Invention
[0004] This application provides a method, system, device, medium, and program for analyzing the conductivity mechanism of complex reservoirs, in order to solve the problem of poor efficiency in analyzing the conductivity mechanism of complex reservoirs.
[0005] In a first aspect, this application provides a method for analyzing the conductivity mechanism of complex reservoirs, including:
[0006] Acquire reservoir data and identify individual pore types within the reservoir data;
[0007] Construct a three-dimensional core model corresponding to the single pore type, and calculate the core resistivity corresponding to the single pore type and multiple pores based on the three-dimensional core model;
[0008] Calculate the core resistivity relationship between the single core pore type and the multiple pore types based on the core resistivity;
[0009] Construct a pore throat model for the single pore type, and calculate the quantitative relationship of the pore structure parameters of the single pore type based on the pore throat model;
[0010] The quantitative relationship of multiple parameters of the core resistivity of the multi-pore structure is calculated based on the core resistivity relationship and the quantitative relationship of the pore structure parameters.
[0011] In some embodiments, identifying a single pore type in the reservoir data includes:
[0012] The reservoir data is classified to obtain different categories of category data;
[0013] Extract the data features of each data item in the aforementioned categories;
[0014] Identify the single pore type in the reservoir data based on the data characteristics.
[0015] In some embodiments, constructing the three-dimensional core model corresponding to the single pore type includes:
[0016] Obtain the core CT scan image corresponding to the reservoir data, and perform image filtering on the core CT scan image to obtain the filtered scan image;
[0017] The filtered scan image is segmented according to the single pore type to obtain pore scan images corresponding to different pore types;
[0018] The pore scanning image is reconstructed in three dimensions to obtain a three-dimensional core model corresponding to the single pore type.
[0019] In some embodiments, calculating the core resistivity corresponding to the single pore type and multiple pore types based on the three-dimensional core model includes:
[0020] By nesting the three-dimensional core models corresponding to the single pore type, a multi-pore three-dimensional core model is obtained.
[0021] The three-dimensional core model and the multi-pore three-dimensional core model are discretized to obtain discretized units.
[0022] Finite element analysis is performed on the discretized unit to obtain the core resistivity corresponding to the single pore type and the multiple pores.
[0023] In some embodiments, calculating the core resistivity relationship between the single core pore type and the multiple pore types based on the core resistivity includes:
[0024] A series-parallel conductivity model was used to analyze the resistivity of the core corresponding to the single pore type to obtain the series-parallel conductivity form of the multiple pores.
[0025] The theoretical core resistivity of the multi-pore structure is derived based on the series-parallel conduction configuration.
[0026] The core resistivity relationship between the multiple pore types and the single core pore type is determined based on the theoretical core resistivity and the core resistivity corresponding to the multiple pores.
[0027] In some embodiments, the step of calculating the quantitative relationship of multiple parameters of the core resistivity based on the core resistivity relationship includes:
[0028] The pore correlation and series-parallel relationship of the multiple pores are determined based on the core resistivity relationship;
[0029] The resistivity of the fully saturated formation water in the core with multiple pores is calculated based on the pore correlation, the series-parallel relationship, and the parameter quantitative relationship.
[0030] The quantitative relationship of multiple parameters of the core resistivity of the multi-pore core was constructed based on the resistivity of the fully saturated formation water in the core.
[0031] Secondly, this application provides a device for analyzing the conductivity mechanism of complex reservoirs, comprising:
[0032] A single pore type identification module is used to acquire reservoir data and identify the single pore type in the reservoir data;
[0033] The core resistivity calculation module is used to construct a three-dimensional core model corresponding to the single pore type, and calculate the core resistivity corresponding to the single pore type and multiple pores based on the three-dimensional core model.
[0034] The core resistivity relationship analysis module is used to calculate the core resistivity relationship between the single core pore type and the multiple pore types based on the core resistivity.
[0035] The pore structure parameter quantitative relationship calculation module is used to construct a pore throat cavity model of the single pore type and calculate the quantitative relationship of the pore structure parameters of the single pore type based on the pore throat cavity model.
[0036] The multi-parameter quantitative relationship calculation module is used to calculate the multi-parameter quantitative relationship of the core resistivity based on the core resistivity relationship and the pore structure parameter quantitative relationship.
[0037] Thirdly, this application provides a computer device including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the method described above.
[0038] Fourthly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method described in the above aspects.
[0039] Fifthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the methods described above.
[0040] This application provides a method, system, equipment, medium, and program for analyzing the conductivity mechanism of complex reservoirs. By identifying single pore types in reservoir data, the pore type of the core can be determined, and a three-dimensional digital core model of the single pore type in the reservoir data can be simulated. Based on the three-dimensional core model, the core resistivity corresponding to the single pore type is calculated. A pore throat model of the single pore type is constructed, and the quantitative relationship of pore structure parameters of the single pore type can be calculated based on the pore throat model and the core resistivity. The core resistivity relationship between multiple pores and single core pore types can be determined, and the series and parallel conduction forms between different pore types can be determined, providing a basis for subsequent calculation of multiple parameter quantitative relationships. Through the multiple parameter quantitative relationship of core resistivity of multiple pores, a quantitative relationship between the resistivity of fully water-bearing rocks and pore type and pore structure parameters can be established, thereby characterizing the degree of influence of reservoir resistivity on pore type and pore structure parameters, effectively improving the accuracy of reservoir conductivity mechanism research. Attached Figure Description
[0041] The present application will be described in more detail below based on embodiments and with reference to the accompanying drawings:
[0042] Figure 1 A flowchart illustrating a method for analyzing the conductivity mechanism of complex reservoirs, provided for an embodiment of this application;
[0043] Figure 2 A schematic diagram of the structure of the pharyngeal cavity model provided in the embodiments of this application.
[0044] Figure 3 A functional module diagram of a complex reservoir conductivity mechanism analysis device provided in this application embodiment;
[0045] Figure 4 This is a schematic diagram of the electronic device used in an embodiment of the present application to analyze the conductivity mechanism of complex reservoirs.
[0046] In the accompanying drawings, the same parts are referred to by the same reference numerals, and the drawings are not drawn to scale. Detailed Implementation
[0047] To enable those skilled in the art to better understand the technical solutions of this application, and to fully understand and implement the process of how this application uses technical means to solve technical problems and achieve corresponding technical effects, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, not all of them. The embodiments of this application and the various features within them can be combined with each other without conflict, and the resulting technical solutions are all within the protection scope of this application. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of this application.
[0048] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.
[0049] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.
[0050] This application provides a method for analyzing the conductivity mechanism of complex reservoirs. The execution entity of this method includes, but is not limited to, at least one of the following electronic devices that can be configured to execute the system provided in this application: a server, a terminal, etc. In other words, the method for analyzing the conductivity mechanism of complex reservoirs can be executed by software or hardware installed on a terminal device or a server device. The server includes, but is not limited to, a single server, a server cluster, a cloud server, or a cloud server cluster. The server can be an independent server or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDNs), and big data and artificial intelligence platforms.
[0051] Example 1
[0052] Figure 1 A flowchart illustrating a method for analyzing the conductivity mechanism of complex reservoirs provided in this application embodiment is shown below. Figure 1 As shown, the method for analyzing the conductivity mechanism of complex reservoirs includes:
[0053] S1. Obtain reservoir data and identify the single pore type in the reservoir data.
[0054] In one embodiment, reservoir data includes core images, geological data, and well logging data from rock samples obtained during geological exploration and oil and gas development. Core images refer to images of physical cross-sections of underground rocks obtained through drilling, which can intuitively display the rock's lithology, composition, structure, porosity, permeability, and other parameters. Geological data refers to original geological data, results geological data, and physical geological data such as rock cores and various specimens in the form of text, charts, and audio-visual materials generated during geological work. Well logging data is obtained by using various logging instruments manufactured using physical principles such as electricity, magnetism, sound, heat, and nuclear physics to measure the physical properties of underground rock formations and information on oil and gas-bearing and water-bearing layers within the well.
[0055] Furthermore, a single pore type refers to a pore structure in a rock that has only one specific size or shape. This can be a single pore developed from matrix pores and dissolution pores, as well as a single pore from fractures, such as intergranular dissolution pores, intercrystalline dissolution pores, caverns, dissolution pores, dissolution fissures, etc.
[0056] In one embodiment, identifying a single pore type in the reservoir data includes:
[0057] The reservoir data is classified to obtain different categories of category data;
[0058] Extract the data features of each data item in the aforementioned categories;
[0059] Identify the single pore type in the reservoir data based on the data characteristics.
[0060] In one embodiment, reservoir data is classified into core images, geological data, and well logging data according to the category of reservoir data. Then, the single pore type in the reservoir data is identified by the characteristics of different data. For example, image features are extracted from core images to identify dissolution cavities. Well logging response characteristics in well logging data are analyzed using a pre-constructed complex pore medium model to identify the single pore type in the well logging data.
[0061] In detail, by identifying the single pore type in the reservoir data, the pore type of the core can be determined, and then a three-dimensional digital core model of the single pore type in the reservoir data can be simulated.
[0062] S2. Construct a three-dimensional core model corresponding to the single pore type, and calculate the core resistivity corresponding to the single pore type and multiple pores based on the three-dimensional core model.
[0063] In one embodiment, a three-dimensional core model is a technique that depicts the microstructure of a rock core in the form of images or data. It enables detailed characterization of the rock's microstructure at the pore scale, thereby achieving microscale characterization of the core and quantitatively studying the influence of various microscopic factors on the physical properties of the rock.
[0064] In one embodiment, constructing the three-dimensional core model corresponding to the single pore type includes:
[0065] Obtain the core CT scan image corresponding to the reservoir data, and perform image filtering on the core CT scan image to obtain the filtered scan image;
[0066] The filtered scan image is segmented according to the single pore type to obtain pore scan images corresponding to different pore types;
[0067] The pore scanning image is reconstructed in three dimensions to obtain a three-dimensional core model corresponding to the single pore type.
[0068] In one embodiment, an X-ray CT scanner is used to scan a core sample to obtain X-ray CT scan images, which can acquire three-dimensional grayscale images of the core. Since the density differences of different components lead to different X-ray absorption coefficients, the core's framework and pore space can be distinguished. Therefore, an appropriate threshold can be used to segment the filtered scan images to differentiate the pore scan images corresponding to different pore types.
[0069] Furthermore, the core CT scan images can be filtered to eliminate noise, for example, by median filtering. And computer software (such as Avizo software) can be used to accurately reconstruct the pore scan images in three dimensions to build a three-dimensional digital core model.
[0070] In one embodiment, multiple porosity refers to the presence of multiple pores of different sizes and types within a reservoir (such as rock, soil, etc.). These pores intertwine to form the complex pore structure within the reservoir.
[0071] In one embodiment, calculating the core resistivity corresponding to the single pore type and multiple pore types based on the three-dimensional core model includes:
[0072] By nesting the three-dimensional core models corresponding to the single pore type, a multi-pore three-dimensional core model is obtained.
[0073] The three-dimensional core model and the multi-pore three-dimensional core model are discretized to obtain discretized units.
[0074] Finite element analysis is performed on the discretized unit to obtain the core resistivity corresponding to the single pore type and the multiple pores.
[0075] In one embodiment, discretizing the three-dimensional core model to obtain discretized elements is the basis for finite element analysis. Transforming the continuous three-dimensional core model into discrete elements can convert the complex three-dimensional structure into a finite number of small elements, simplifying the solution of core resistivity.
[0076] In one embodiment, nesting three-dimensional core models involves combining nested models into a complete three-dimensional digital core. This can be achieved by assigning different values to models of different components and then combining them through addition or multiplication operations. For example, in the matrix pore model, the values for pores and skeleton are set to 0 and 1, respectively, while in the dissolution cavity pore model, the values for pores and skeleton are set to 2 and 1, respectively.
[0077] Among them, the finite element analysis of the three-dimensional core model can be performed using preset finite element software to obtain the core resistivity corresponding to a single pore type, i.e., multiple pores.
[0078] In one embodiment, core resistivity is closely related to factors such as porosity, water saturation, and mineral composition of the rocks in the reservoir. It can be used to estimate reservoir characteristics and fluid properties, and to describe the strength of the rocks' electrical conductivity. Core resistivity measurement is of great significance in fields such as petroleum and geological exploration.
[0079] S3. Calculate the core resistivity relationship between the single core pore type and the multiple pore types based on the core resistivity.
[0080] In one embodiment, the core resistivity relationship describes the conductive connection between individual pores that make up a multi-pore structure. For example, if the multi-pore structure includes cracks and dissolution cavities, then the core resistivity relationship between cracks and dissolution cavities is analyzed.
[0081] In one embodiment, calculating the core resistivity relationship between the single core pore type and the multiple pore types based on the core resistivity includes:
[0082] A series-parallel conductivity model was used to analyze the resistivity of the core corresponding to the single pore type to obtain the series-parallel conductivity form of the multiple pores.
[0083] The theoretical core resistivity of the multi-pore structure is derived based on the series-parallel conduction configuration.
[0084] The core resistivity relationship between the multiple pore types and the single core pore type is determined based on the theoretical core resistivity and the core resistivity corresponding to the multiple pores.
[0085] In one embodiment, the core resistivity can be obtained by performing finite element analysis on a multi-pore three-dimensional core model obtained by nesting a three-dimensional core model of a single pore type.
[0086] In one embodiment, the series-parallel conduction form describes the conduction form between different phases (such as solid skeleton, pore fluid, etc.) in the reservoir medium, including the conduction form between different gap types, such as series, parallel, series-parallel, etc.
[0087] Furthermore, the series-parallel conductivity model theory is a theory used to describe the interaction between the conductivity of different phases (such as solid skeletons, pore fluids, etc.) in porous media, and to describe the results of different pore types under different conductivity forms.
[0088] Furthermore, the theoretical resistivity of the three-dimensional core model with multiple pores under different series and parallel conduction modes is derived using the series and parallel conduction model theory. For example, the resistivity of different pores in series and the resistivity in parallel. The theoretical resistivity is compared with the resistivity of finite element analysis to determine the core resistivity relationship between different pore types in multiple pores, i.e., the series and parallel conduction modes.
[0089] In one embodiment, the series and parallel conduction patterns between different pore types can be determined by the core resistivity relationship, which in turn allows for the analysis of the relationship between the resistivity of multi-pore cores and the resistivity of a single pore type, providing a basis for subsequent quantitative calculations of multiple parameters.
[0090] S4. Construct a pore throat model for the single pore type, and calculate the quantitative relationship of pore structure parameters for the single pore type based on the pore throat model and the core resistivity.
[0091] In one embodiment, the pore-throat model is a model used to describe the pore structure of porous media, simplifying the pore structure in rocks as a combination of pores and pore throats. In this model, enlarged spaces are defined as pores, while relatively narrow channels are defined as pore throats. This model typically uses spheres to represent pores and cylinders to represent pore throats. The pore-throat model simplifies the pore structure, decomposing it into a large number of regular pores and pore throats, thus forming a network of pores and pore throats.
[0092] In one embodiment, constructing the pore throat model of the single pore type includes:
[0093] The single pore type is divided into pore types to obtain the pore type classification;
[0094] Calculate the pore throat parameters corresponding to the pore type classification;
[0095] Based on the pore throat parameters, construct the pore throat model corresponding to the pore type classification.
[0096] In one embodiment, the rock physical volume model for the pore-throat cavity includes two parts: the throat and the pore body. For matrix pores and dissolution cavities, the radii of the throat and the pore body are different, while the pores of the fracture have similar radii to the throat. It is also assumed that the cross-sectional areas of the pore body, the throat, and the pore-throat cavity have the same shape. Therefore, the cross-sectional areas of the pore body, the throat, and the pore-throat cavity are proportional to their radii.
[0097] In one embodiment, the pore throat parameters can be calculated using the maximum sphere method. For example, for any point in the three-dimensional digital model corresponding to the pore type, find the maximum inscribed sphere with that point as the center. After removing redundant spheres, obtain the set of all non-redundant inscribed spheres describing the pore space. Define the radius of the inscribed sphere with the largest local radius as the pore radius and the radius of the inscribed sphere with the smallest local radius as the pore throat radius.
[0098] like Figure 2 As shown, Figure 2 In the figure, (a) represents the pore throat model of matrix pores and dissolution pores, and (b) represents the pore throat model corresponding to the crack. Where Awt is the cross-sectional area of the throat, Awp is the cross-sectional area of the pore body, Lwt is the throat length, Lwp is the pore body length, A is the cross-sectional area of the pore throat model, and L is the pore throat length.
[0099] In one embodiment, by constructing a pore-throat model, the relationship between the core resistivity and pore structure parameters of a single pore type can be derived based on the assumption that the pores and throats conduct electricity in series.
[0100] In one embodiment, using a pore-throat model of a single pore type, and based on the assumption that the pores and throats are connected in series for conductivity, a quantitative relationship between the resistivity of a single pore type and the pore structure parameters can be derived.
[0101] For example, in a pore-throat model completely saturated with formation water and its equivalent conductivity model, the total resistance of one throat is r. wt :
[0102]
[0103] Where, r wt For the laryngeal cavity model, R is the laryngeal resistance. w For the resistivity of formation water, A wt L is the cross-sectional area of the throat. wt This refers to the length of the larynx.
[0104] The resistance r0 of the entire laryngeal cavity is equal to the resistance r of the laryngeal passage. wt With pore volume resistance r wp sum:
[0105]
[0106] Where r0 represents the pore-laryngeal resistance of the pore-laryngeal model, r wt The laryngeal resistance, r, represents the laryngeal cavity resistance in the foramen laryngeal model. wp R represents the volume resistance of the pores. w L represents the resistivity of formation water. wp A represents the length of the pore volume. wp A represents the cross-sectional area of the porous volume. wt L is the cross-sectional area of the throat. wt Ks represents the length of the larynx, and Rad represents the preset shape factor. wp Rad represents the pore volume radius. wt Indicates the radius of the throat.
[0107] Based on the definition of pores, the porosity of each pore can be calculated using the following formula:
[0108]
[0109] Where φ represents porosity, A and L represent the cross-sectional area and length of the rock physical volume model containing the pore throat cavity, respectively, and τ wp The tortuosity of the porous body, i.e., the pore length L wp The ratio of τ to the length L of the larynx model wtψ represents the tortuosity of the larynx. wp The cross-sectional area A of the porous body wp The ratio of ψ to the cross-sectional area A of the rock physical volume model wt The cross-sectional area A of the larynx wp The ratio of the cross-sectional area A of the rock physical volume model to the given cross-sectional area, Ks represents the preset shape factor, Rad wp Rad represents the pore volume radius. wt Rad represents the throat radius. wm This indicates the radius of the larynx.
[0110] In detail, core resistivity can be expressed as the resistivity of developed rocks. Based on the above, the quantitative relationship between different single pore types and pore structure parameters can be calculated, such as completely water-bearing rocks and completely water-bearing dissolution cavities, as shown below:
[0111] Resistivity R0 of fully water-bearing rocks and resistivity R of formation water w The quantitative relationships of the pore structure parameters are expressed as follows:
[0112]
[0113] Where R0 represents the resistivity of a completely water-bearing rock, v wp The tortuosity of the porous body, i.e., the pore length L wp The ratio of τ to the length L of the larynx model wt ψ represents the tortuosity of the larynx. wp The cross-sectional area A of the porous body wp The ratio of ψ to the cross-sectional area A of the rock physical volume model wt The cross-sectional area A of the larynx wp The ratio of the cross-sectional area A of the rock physical volume model to the given cross-sectional area, Ks represents the preset shape factor, Rad wp Rad represents the pore volume radius. wt Rad represents the throat radius. wm This indicates the radius of the larynx.
[0114] The quantitative relationships between resistivity R1, porosity φ, and pore structure parameters in fully hydrous matrix pore-developed rocks are expressed as follows:
[0115]
[0116] Among them, R w Rad represents the resistivity of formation water. wbm τ represents the radius of the pore throat in the matrix pore throat model. wbp τ represents the tortuosity of the pore body in the matrix pore throat model. wbtRad represents the tortuosity of the laryngeal passage in the matrix pore pore laryngeal cavity model. wbp Rad represents the pore volume radius of the matrix pores. wbt This indicates the throat radius of the matrix pores.
[0117]
[0118] Among them, Rad wbm τ represents the radius of the pore throat in the matrix pore throat model. wbp τ represents the tortuosity of the pore body in the matrix pore throat model. wbt Rad represents the tortuosity of the laryngeal passage in the matrix pore pore laryngeal cavity model. wbp Rad represents the pore volume radius of the matrix pores. wbt This indicates the throat radius of the matrix pores.
[0119] Furthermore, the quantitative relationships between resistivity R2, porosity φ, and pore structure parameters of rocks with fully developed water-bearing dissolution cavities are expressed as follows:
[0120]
[0121] Among them, R w Rad represents the resistivity of formation water. wvm τ represents the radius of the pore throat in the dissolution pore throat model. wvp τ represents the tortuosity of the pore body in the dissolution cavity throat model. wvt Rad represents the tortuosity of the throat passage in the dissolution cavity throat model. wvp Rad represents the pore volume radius of the dissolution cavity. wvt This indicates the throat radius of the dissolution cavity.
[0122]
[0123] Among them, Rad wvm τ represents the radius of the pore throat in the dissolution pore throat model. wvp τ represents the tortuosity of the pore body in the dissolution cavity throat model. wvt Rad represents the tortuosity of the throat passage in the dissolution cavity throat model. wvp Rad represents the pore volume radius of the dissolution cavity. wvt This indicates the throat radius of the dissolution cavity.
[0124] Furthermore, the quantitative relationships between resistivity R2, porosity φ, and pore structure parameters of fully water-bearing fractured rocks are expressed as follows:
[0125]
[0126] Among them, Rw Rad represents the resistivity of formation water. wfm τ represents the radius of the pore-throat cavity in the pore-throat cavity model of crack development. wfp Rad represents the tortuosity of the pore body in the fracture development pore throat model. wfp The radius of the pore body indicating the development of cracks.
[0127]
[0128] Among them, Rad wfm τ represents the radius of the pore-throat cavity in the pore-throat cavity model of crack development. wfp Rad represents the tortuosity of the pore body in the fracture development pore throat model. wfp The radius of the pore body indicating the development of cracks.
[0129] In one embodiment, by calculating the quantitative relationships between core resistivity and porosity and pore structure parameters for different single pore types, the quantitative relationships of pore structure parameters for a single pore type can be calculated more comprehensively.
[0130] S5. Calculate the quantitative relationship of multiple parameters of the core resistivity based on the core resistivity relationship and the quantitative relationship of the pore structure parameters.
[0131] In one embodiment, the quantitative relationship of multiple parameters is the quantitative relationship between the resistivity of multi-pore core and the pore type and pore structure parameters, which can be derived from the quantitative relationship between the resistivity of a single pore type and the pore structure parameters.
[0132] In one embodiment, the step of calculating the quantitative relationship of multiple parameters of the core resistivity based on the core resistivity relationship includes:
[0133] The pore correlation and series-parallel relationship of the multiple pores are determined based on the core resistivity relationship;
[0134] The resistivity of the fully saturated formation water in the core with multiple pores is calculated based on the pore correlation, the series-parallel relationship, and the parameter quantitative relationship.
[0135] The quantitative relationship of multiple parameters of the core resistivity of the multi-pore core was constructed based on the resistivity of the fully saturated formation water in the core.
[0136] In one embodiment, the pore correlation relationship is that there are several pore types in the multiple pores, for example, two or three types, etc. The multiple pores are connected in series, parallel, series-to-parallel or parallel-to-series conduction forms, etc., to obtain the series-parallel relationship.
[0137] The resistivity of a fully saturated formation water core with multiple pores can be expressed as:
[0138] 1. When two pore types are connected in series for conductivity, the resistivity R of a fully saturated core with formation water is... fnco This can be expressed as the cascade result of the resistivity of pore type I and pore type II:
[0139]
[0140] Among them, R fnco φ represents the resistivity of a fully saturated formation water core. II φ I R represents the porosity of pore type II and pore type I, respectively. II0 R I0 These represent the core resistivity for pore type II and pore type I, respectively.
[0141] 2. When two pore types conduct electricity in parallel, the resistivity R of a fully saturated core with formation water is... fnco This can be expressed as the parallel result of the resistivity of pore type I and pore type II:
[0142]
[0143] Among them, R fnco φ represents the resistivity of a fully saturated formation water core. II φ I R represents the porosity of pore type II and pore type I, respectively. II0 R I0 These represent the core resistivity for pore type II and pore type I, respectively.
[0144] 3. When three pore types are connected in series for conductivity, the resistivity R of a fully saturated core with formation water is... fnco This can be represented as the series result of the resistivity of pore type I, pore type II, and pore type III:
[0145]
[0146] Among them, R fnco φ represents the resistivity of a fully saturated formation water core. I φ II φ III R represents the porosity of the three pore types respectively. I0 R II0 R III0 These represent the core resistivity for pore types I, II, and III, respectively.
[0147] 4. When three pore types conduct electricity in parallel, the resistivity R of a fully saturated core of formation water is... fncoThis can be expressed as the parallel result of the resistivity of pore type I, pore type II, and pore type III:
[0148]
[0149] Among them, R fnco φ represents the resistivity of a fully saturated formation water core. I φ II φ III R represents the porosity of the three pore types respectively. I0 R II0 R III0 These represent the core resistivity for pore types I, II, and III, respectively.
[0150] 5. When two of the three pore types are initially connected in parallel and then connected in series with the third type to conduct electricity, the resistivity R of the core when fully saturated with formation water is... fnco This can be represented as the result of pore type I and pore type II first connected in parallel and then connected in series with pore type III:
[0151]
[0152] Among them, R fnco φ represents the resistivity of a fully saturated formation water core. I φ II φ III R represents the porosity of the three pore types respectively. I0 R II0 R III0 These represent the core resistivity for pore types I, II, and III, respectively.
[0153] 6. When two of the three pore types are connected in series and then connected in parallel with the third type to conduct electricity, the resistivity R of the core when fully saturated with formation water is... fnco This can be represented as the result of pore type I and pore type II first connected in series and then connected in parallel with pore type III:
[0154]
[0155] Among them, R fnco φ represents the resistivity of a fully saturated formation water core. I φ II φ III R represents the porosity of the three pore types respectively. I0 R II0 R III0 These represent the core resistivity for pore types I, II, and III, respectively.
[0156] Furthermore, based on Archie's first formula, a quantitative relationship can be established between the resistivity of multi-porous cores and the pore type and pore structure parameters, resulting in a quantitative relationship of multiple parameters, as shown in the following formula:
[0157]
[0158] Where R0 represents the quantitative relationship of the parameters, R w R represents the resistivity of formation water. fnco This represents the resistivity of the core sample when it is fully saturated with formation water, φ. m_exp This indicates the preset porosity index.
[0159] in, It can represent the formation factors of a reservoir, used to describe the scaling factor between resistivity and pore water resistivity.
[0160] In one embodiment, the quantitative relationship between multiple parameters of the resistivity of multi-pore cores can be used to establish a quantitative relationship between the resistivity of fully water-bearing rocks with multiple pores and pore type and pore structure parameters, thereby characterizing the degree of influence of reservoir resistivity on pore type and pore structure parameters and effectively improving the accuracy of reservoir conductivity mechanism research.
[0161] Example 2
[0162] like Figure 3 The diagram shown is a functional block diagram of a complex reservoir conductivity mechanism analysis device 100 provided for this embodiment.
[0163] The complex reservoir conductivity mechanism analysis device 100 described in this invention can be installed in an electronic device. Depending on the functions implemented, the complex reservoir conductivity mechanism analysis device 100 may include a single pore type identification module 101, a core resistivity calculation module 102, a core resistivity relationship analysis module 103, a pore structure parameter quantitative relationship calculation module 104, and a multi-parameter quantitative relationship calculation module 105. The modules described in this invention can also be referred to as units, which are a series of computer program segments that can be executed by the processor of an electronic device and perform a fixed function, stored in the memory of the electronic device.
[0164] In this embodiment, the functions of each module / unit are as follows:
[0165] The single pore type identification module 101 is used to acquire reservoir data and identify the single pore type in the reservoir data.
[0166] The core resistivity calculation module 102 is used to construct a three-dimensional core model corresponding to the single pore type, and calculate the core resistivity corresponding to the single pore type and multiple pores based on the three-dimensional core model.
[0167] The core resistivity relationship analysis module 103 is used to calculate the core resistivity relationship between the single core pore type and the multiple pores based on the core resistivity.
[0168] The pore structure parameter quantitative relationship calculation module 104 is used to construct a pore throat cavity model of the single pore type and calculate the quantitative relationship of the pore structure parameters of the single pore type based on the pore throat cavity model.
[0169] The multi-parameter quantitative relationship calculation module 105 is used to calculate the multi-parameter quantitative relationship of the core resistivity of the multi-pore based on the core resistivity relationship and the pore structure parameter quantitative relationship.
[0170] Example 3
[0171] Figure 4 This is a schematic diagram of the electronic device used in an embodiment of the present application to analyze the conductivity mechanism of complex reservoirs.
[0172] Based on the above embodiments, this embodiment provides a computer device, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the method described in the above embodiments.
[0173] In some embodiments of this example, a computer-readable storage medium is provided, on which a computer program is stored, characterized in that the computer program, when executed by a processor, implements the steps of the method described in the above embodiments.
[0174] In some embodiments of this example, a computer program product is provided, including a computer program, characterized in that the computer program, when executed by a processor, implements the steps of the method described in the above embodiments.
[0175] The processor may include, but is not limited to, one or more processors or microprocessors. Each processor may be implemented as an Application Specific Integrated Circuit (ASIC), Digital Signal Processor (DSP), Digital Signal Processing Device (DSPD), Programmable Logic Device (PLD), Field Programmable Gate Array (FPGA), controller, microcontroller, microprocessor, or other electronic component, for executing the methods in the above embodiments.
[0176] Computer-readable storage media can be implemented by any type of volatile or non-volatile storage device or a combination thereof, including but not limited to, random access memory (RAM), read-only memory (ROM), flash memory, EPROM memory, EEPROM memory, registers, and computer storage media (e.g., hard disks, floppy disks, solid-state drives, removable disks, CD-ROMs, DVD-ROMs, Blu-ray discs, etc.).
[0177] Computer-readable storage media may also store at least one computer-executable program, such as computer-readable instructions. Computer-readable storage media include, but are not limited to, volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and / or cache memory. Computer-readable storage media may include, for example, read-only memory (ROM), hard disk, flash memory, etc. For example, a non-transitory computer-readable storage medium may be connected to a computing device such as a computer, and then, when the computing device executes the computer-readable instructions stored on the computer-readable storage medium, the various methods described above can be performed.
[0178] In addition, the computer device may include (but is not limited to) a data bus, an input / output (I / O) bus, a display, and input / output devices (e.g., keyboard, mouse, speakers, etc.).
[0179] The processor can communicate with external devices via the communication interface of the I / O bus through wired or wireless networks.
[0180] In one embodiment, the at least one computer-executable instruction may also be compiled into or comprise a software product / computer program product, wherein one or more computer-executable instructions are executed by a processor to perform the steps of the various functions and / or methods in the embodiments described herein.
[0181] In the embodiments provided in this application, it should be understood that the disclosed systems and methods can also be implemented in other ways. The system embodiments described above are merely illustrative. For example, the flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram and / or flowchart, and combinations of blocks in block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.
[0182] It should be noted that, in this application, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element limited by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.
[0183] Although the embodiments disclosed in this application are as described above, the above content is merely for the purpose of facilitating understanding of this application and is not intended to limit this application. Any person skilled in the art to which this application pertains may make any modifications and changes in the form and details of the implementation without departing from the spirit and scope disclosed in this application; however, the scope of patent protection of this application shall still be determined by the scope defined in the appended claims.
Claims
1. A method for analyzing the conductivity mechanism of complex reservoirs, characterized in that, The method includes: Acquire reservoir data and identify individual pore types within the reservoir data; Construct a three-dimensional core model corresponding to the single pore type, and calculate the core resistivity corresponding to the single pore type and multiple pores based on the three-dimensional core model; Calculate the core resistivity relationship between the single core pore type and the multiple pore types based on the core resistivity; Construct a pore throat model for the single pore type, and calculate the quantitative relationship of the pore structure parameters of the single pore type based on the pore throat model; The quantitative relationship of multiple parameters of the core resistivity of the multi-pore structure is calculated based on the core resistivity relationship and the quantitative relationship of the pore structure parameters.
2. The method for analyzing the conductivity mechanism of complex reservoirs according to claim 1, characterized in that, The identification of a single pore type in the reservoir data includes: The reservoir data is classified to obtain different categories of category data; Extract the data features of each data item in the aforementioned categories; Identify the single pore type in the reservoir data based on the data characteristics.
3. The method for analyzing the conductivity mechanism of complex reservoirs according to claim 1, characterized in that, The construction of the three-dimensional core model corresponding to the single pore type includes: Obtain the core CT scan image corresponding to the reservoir data, and perform image filtering on the core CT scan image to obtain the filtered scan image; The filtered scan image is segmented according to the single pore type to obtain pore scan images corresponding to different pore types; The pore scanning image is reconstructed in three dimensions to obtain a three-dimensional core model corresponding to the single pore type.
4. The method for analyzing the conductivity mechanism of complex reservoirs according to claim 1, characterized in that, The calculation of core resistivity corresponding to the single pore type and multiple pore types based on the three-dimensional core model includes: By nesting the three-dimensional core models corresponding to the single pore type, a multi-pore three-dimensional core model is obtained. The three-dimensional core model and the multi-pore three-dimensional core model are discretized to obtain discretized units. Finite element analysis is performed on the discretized unit to obtain the core resistivity corresponding to the single pore type and the multiple pores.
5. The method for analyzing the conductivity mechanism of complex reservoirs according to claim 1, characterized in that, The calculation of the core resistivity relationship between the single core pore type and the multiple pore types based on the core resistivity includes: A series-parallel conductivity model was used to analyze the resistivity of the core corresponding to the single pore type to obtain the series-parallel conductivity form of the multiple pores. The theoretical core resistivity of the multi-pore structure is derived based on the series-parallel conduction configuration. The core resistivity relationship between the multiple pore types and the single core pore type is determined based on the theoretical core resistivity and the core resistivity corresponding to the multiple pores.
6. The method for analyzing the conductivity mechanism of complex reservoirs according to claim 1, characterized in that, The calculation of the multiple parameter quantitative relationship of the core resistivity based on the core resistivity relationship and the quantitative relationship of the pore structure parameters includes: The pore correlation and series-parallel relationship of the multiple pores are determined based on the core resistivity relationship; The resistivity of the fully saturated formation water in the core with multiple pores is calculated based on the pore correlation, the series-parallel relationship, and the parameter quantitative relationship. The quantitative relationship of multiple parameters of the core resistivity of the multi-pore core was constructed based on the resistivity of the fully saturated formation water in the core.
7. A device for analyzing the conductivity mechanism of complex reservoirs, characterized in that, The device includes: A single pore type identification module is used to acquire reservoir data and identify the single pore type in the reservoir data; The core resistivity calculation module is used to construct a three-dimensional core model corresponding to the single pore type, and calculate the core resistivity corresponding to the single pore type and multiple pores based on the three-dimensional core model. The core resistivity relationship analysis module is used to calculate the core resistivity relationship between the single core pore type and the multiple pore types based on the core resistivity. The pore structure parameter quantitative relationship calculation module is used to construct a pore throat cavity model of the single pore type and calculate the quantitative relationship of the pore structure parameters of the single pore type based on the pore throat cavity model. The multi-parameter quantitative relationship calculation module is used to calculate the multi-parameter quantitative relationship of the core resistivity based on the core resistivity relationship and the pore structure parameter quantitative relationship.
8. A computer device, comprising a memory, a processor, and a computer program stored in the memory, characterized in that, The processor executes the computer program to implement the steps of the method according to any one of claims 1 to 6.
9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the steps of the method according to any one of claims 1 to 6.
10. A computer program product, comprising a computer program, characterized in that, When executed by a processor, the computer program implements the steps of the method according to any one of claims 1 to 6.