CN114280686A

CN114280686A - Method and equipment for analyzing physical properties of core of carbonate reservoir

Info

Publication number: CN114280686A
Application number: CN202011032179.0A
Authority: CN
Inventors: 夏茂龙; 杨雨; 文龙; 罗冰; 王文之; 罗文军; 陈文�; 曾乙洋
Original assignee: Petrochina Co Ltd
Current assignee: Petrochina Co Ltd
Priority date: 2020-09-27
Filing date: 2020-09-27
Publication date: 2022-04-05
Anticipated expiration: 2040-09-27
Also published as: CN114280686B

Abstract

The application discloses a method and equipment for analyzing physical properties of a core of a carbonate reservoir, and belongs to the field of natural gas exploration. According to the method, the carbonate reservoir is divided into multiple types with different reservoir space sizes according to the size of the reservoir space (hole) in the carbonate reservoir, and each type is further divided into multiple small types with different heterogeneity change degrees according to the heterogeneity change degree of the hole distribution in the carbonate reservoir, so that the classification mode of the carbonate reservoir is more refined. On the basis, physical property analysis is respectively carried out on each small type according to the development degree of the core hole, so that the characteristic of heterogeneity of various carbonate rock reservoirs is fully considered, and the accuracy of a physical property analysis result is improved.

Description

Method and equipment for analyzing physical properties of core of carbonate reservoir

Technical Field

The application relates to the field of natural gas exploration, in particular to a method and equipment for analyzing physical properties of a core of a carbonate reservoir.

Background

Carbonate reservoir formation is mainly controlled by two aspects of reef facies deposition and erosion. The storage space of the carbonate reservoir has various types, and various types of pores such as inter-granular pores, inter-granular solution pores and intra-granular pores in the reservoir and solution cavities with different scales, namely holes for short, are developed in the reservoir. Due to the non-uniform distribution of holes with different sizes or the non-uniform distribution of the holes combined with the holes, the heterogeneity of the carbonate reservoir is caused, so that the heterogeneity of different carbonate reservoirs has different characteristics.

The existing core physical property analysis technology does not fully consider the heterogeneity characteristic of the carbonate reservoir, and the accuracy of physical property analysis of the carbonate reservoir is influenced.

Disclosure of Invention

The embodiment of the application provides a method and equipment for analyzing the physical properties of a core of a carbonate reservoir, which can improve the accuracy of physical property analysis of the carbonate reservoir, and the technical scheme is as follows:

in one aspect, a method for analyzing core properties of a carbonate reservoir is provided, the method comprising:

respectively detecting the storage spaces of multiple carbonate rock reservoirs to obtain first data, wherein the first data represents the size of each hole in the carbonate rock reservoirs;

according to the first data, carrying out storage space type identification on the multiple types of carbonate rock reservoirs to obtain multiple types, wherein each type in the multiple types comprises the carbonate rock reservoirs with the same storage space type, and the storage space types are divided according to the size of the hole;

respectively detecting the multiple classes to obtain second data of each class, wherein the second data represents the heterogeneity variation degree of pore distribution in the carbonate reservoir;

according to the second data, conducting heterogeneity type identification on the multiple carbonate rock reservoirs to obtain multiple subclasses included by each class, wherein each subclass of the multiple subclasses includes carbonate rock reservoirs with the same heterogeneity type, and the heterogeneity types are divided according to the heterogeneity change degree;

respectively detecting the subclasses to obtain third data of each subclass, wherein the third data represents the development degree of core holes of the carbonate reservoir;

and according to the third data, performing physical property analysis on the subclasses respectively to obtain a physical property analysis result.

Optionally, the first data includes a diameter of each hole in the carbonate reservoir, the reservoir space type includes a pore, a small cavern and a large cavern, the diameter of the pore is smaller than a diameter threshold, the diameter of the small cavern is smaller than a core diameter, the diameter of the large cavern is larger than the core diameter, the multiple classes include a pore type reservoir, a small cavern type reservoir and a multiple-type cavern type reservoir, and reservoir space type identification is performed on the multiple-type carbonate reservoir according to the first data to obtain multiple classes, including:

identifying a first carbonate reservoir as the porous reservoir in response to each reservoir space in the first carbonate reservoir being a pore, the first carbonate reservoir being a type of carbonate reservoir included in the plurality of types of carbonate reservoirs;

identifying a second carbonate reservoir as the small cavern type reservoir in response to a reservoir space in the second carbonate reservoir comprising pores and small caverns, the second carbonate reservoir being a type of carbonate reservoir comprised by the plurality of types of carbonate reservoirs;

identifying a third carbonate reservoir as the multi-type cavernous reservoir in response to a reservoir space in the third carbonate reservoir comprising pores, small-scale caverns, and large-scale caverns, the third carbonate reservoir being a type of carbonate reservoir included in the multi-type carbonate reservoir.

Optionally, the second data includes a heterogeneity variation scale of pore distribution in the carbonate reservoir, the pore type reservoir includes sub-classes of pore graded reservoir, pore mutant reservoir, or pore spot type reservoir, and the heterogeneous type identification is performed on the multiple classes according to the second data to obtain multiple sub-classes included in each class, including:

identifying a fourth carbonate reservoir as the pore graded reservoir in response to a scale of heterogeneity change of the fourth carbonate reservoir being greater than a scale threshold and a gradual heterogeneity change, the fourth carbonate reservoir belonging to the class of pore-type reservoirs;

identifying a fifth carbonate reservoir as the pore mutant reservoir in response to a magnitude of heterogeneity change of the fifth carbonate reservoir being greater than a scale threshold and a sudden change in heterogeneity, the fifth carbonate reservoir belonging to the class of pore type reservoirs;

in response to a heterogeneity change scale of a sixth carbonate reservoir being less than a scale threshold, identifying the sixth carbonate reservoir as the pore-speck reservoir, the category to which the sixth carbonate reservoir belongs being the pore-speck reservoir.

Optionally, the performing, according to the third data, physical property analysis on each of the plurality of subclasses includes:

according to the third data, identifying the development type of the pore gradual change type reservoir to obtain the development class, the medium development class and the under development class of the pore gradual change type reservoir, and respectively analyzing the small core sample property of the development class, the medium development class and the under development class of the pore gradual change type reservoir;

according to the third data, identifying the development type of the pore mutation type reservoir to obtain a relatively developed type and an under-developed type included by the pore mutation type reservoir, and respectively analyzing the relatively developed type and the under-developed type included by the pore mutation type reservoir;

and carrying out full-diameter core physical property analysis on the pore spot type reservoir.

Optionally, the subclasses included in the small karst cave type reservoir are small karst cave tapered reservoirs or small karst cave mutant reservoirs, and the heterogeneous type recognition is performed on the multiple classes according to the second data to obtain multiple subclasses included in each class, where the subclasses include:

identifying a seventh carbonate reservoir as the small cavern graded reservoir in response to gradual changes in heterogeneity of the seventh carbonate reservoir, the seventh carbonate reservoir belonging to the class of small cavern-type reservoirs;

identifying an eighth carbonate reservoir as the small cavern mutant reservoir in response to an abrupt change in heterogeneity of the eighth carbonate reservoir, the eighth carbonate reservoir belonging to the class of small cavern type reservoirs.

according to the third data, identifying the development type of the small karst cave gradient reservoir to obtain a relatively development type, a medium development type and an under-development type which are included in the small karst cave gradient reservoir, and respectively analyzing the physical properties of the full-diameter core of the relatively development type, the medium development type and the under-development type which are included in the small karst cave gradient reservoir;

and identifying the development type of the small karst cave mutant reservoir according to the third data to obtain the relatively developed and under-developed types included by the small karst cave mutant reservoir, and respectively performing full-diameter core physical property analysis on the relatively developed and under-developed types included by the small karst cave mutant reservoir.

Optionally, the multiple types of cavern type reservoirs include a multiple types of cavern graded reservoirs and a multiple types of cavern mutant reservoirs, and the heterogeneous type identification is performed on the multiple classes according to the second data to obtain multiple subclasses included in each class, where the identification includes:

identifying a ninth carbonate reservoir as the multi-type karst cave graded reservoir in response to a gradual change in heterogeneity of the ninth carbonate reservoir, the ninth carbonate reservoir belonging to the class of the multi-type karst cave graded reservoir;

identifying a tenth carbonate reservoir as the multi-type karst cave mutant reservoir in response to a sudden change in heterogeneity of the tenth carbonate reservoir, the tenth carbonate reservoir belonging to the class of the multi-type karst cave reservoir.

according to the third data, identifying development types of the multi-type karst cave gradient reservoir to obtain a relatively development type, a medium development type and an under-development type which are included in the multi-type karst cave gradient reservoir, and respectively analyzing the physical properties of the full-diameter core of the relatively development type, the medium development type and the under-development type which are included in the multi-type karst cave gradient reservoir;

and identifying development types of the multiple types of karst cave mutant reservoirs according to the third data to obtain relatively developed and under-developed types included by the multiple types of karst cave mutant reservoirs, and respectively performing full-diameter core physical property analysis on the relatively developed and under-developed types included by the multiple types of karst cave mutant reservoirs.

In another aspect, an apparatus for analyzing core properties of a carbonate reservoir is provided, the apparatus comprising:

the detection module is used for respectively detecting multiple carbonate reservoirs to obtain first data, and the first data represent the size of each hole in the carbonate reservoirs;

the storage space type identification module is used for identifying the types of the multiple types of carbonate rock reservoirs according to the first data to obtain multiple types, each type of the multiple types comprises the carbonate rock reservoirs with the same storage space type, and the storage space types are divided according to the sizes of the holes;

the detection module is further used for respectively detecting the multiple classes to obtain second data of each class, and the second data represent the heterogeneous variation degree of pore distribution in the carbonate reservoir;

the heterogeneity type identification module is used for carrying out heterogeneity type identification on the multiple classes according to the second data to obtain multiple subclasses included in each class, each subclass in the multiple subclasses includes carbonate rock reservoirs with the same heterogeneity type, and the heterogeneity types are divided according to the heterogeneity change degree;

the detection module is further used for respectively detecting the subclasses to obtain third data of each subclass, and the third data represents the development degree of a core hole of the carbonate reservoir;

and the physical property analysis module is used for respectively carrying out physical property analysis on the subclasses according to the third data to obtain a physical property analysis result.

Optionally, the first data includes a diameter of each reservoir space in the carbonate reservoir, the reservoir space types include pores, small-sized caverns, and large-sized caverns, the diameters of the pores are smaller than a diameter threshold, the diameters of the small-sized caverns are smaller than a core diameter, the diameters of the large-sized caverns are larger than a core diameter, the plurality of classes include pore type reservoirs, small-sized cavern type reservoirs, and multi-type cavern type reservoirs, and the reservoir space type identification module is configured to identify a first carbonate reservoir as a pore type reservoir in response to each reservoir space in the first carbonate reservoir being a pore, the first carbonate reservoir being a class of carbonate reservoirs included in the multi-type carbonate reservoir; identifying a second carbonate reservoir as the small cavern type reservoir in response to a reservoir space in the second carbonate reservoir comprising pores and small caverns, the second carbonate reservoir being a type of carbonate reservoir included in the plurality of types of carbonate reservoirs; identifying a third carbonate reservoir as the multiple-type cavernous reservoir in response to a reservoir space in the third carbonate reservoir comprising pores, small-scale caverns, and large-scale caverns, the third carbonate reservoir being a type of carbonate reservoir that the multiple-type carbonate reservoir comprises.

Optionally, the second data includes a heterogeneity variation scale of pore distribution in the carbonate reservoir, the pore type reservoir including a subclass of pore graded reservoir, pore mutant reservoir, or pore speckled reservoir, the heterogeneity type identification module to identify a fourth carbonate reservoir as the pore graded reservoir in response to a heterogeneity variation scale of the fourth carbonate reservoir being greater than a scale threshold and a heterogeneity gradient, the fourth carbonate reservoir belonging to the subclass of the pore type reservoir; identifying a fifth carbonate reservoir as the pore mutant reservoir in response to a magnitude of heterogeneity change of the fifth carbonate reservoir being greater than a scale threshold and a sudden change in heterogeneity, the fifth carbonate reservoir belonging to the class of pore type reservoirs; in response to a heterogeneity change scale of a sixth carbonate reservoir being less than a scale threshold, identifying the sixth carbonate reservoir as the pore-speck reservoir, the category to which the sixth carbonate reservoir belongs being the pore-speck reservoir.

Optionally, the physical property analysis module is configured to perform development type identification on the pore graded reservoir according to the third data to obtain a development class, a medium development class, and an underdeveloped class included in the pore graded reservoir, and perform small core sample physical property analysis on the development class, the medium development class, and the underdeveloped class included in the pore graded reservoir respectively; according to the third data, identifying the development type of the pore mutation type reservoir to obtain a relatively developed type and an under-developed type included by the pore mutation type reservoir, and respectively analyzing the relatively developed type and the under-developed type included by the pore mutation type reservoir; and carrying out full-diameter core physical property analysis on the pore spot type reservoir.

Optionally, the small karst cave type reservoir comprises a subclass of small karst cave graded reservoirs or small karst cave mutant reservoirs, and the heterogeneity type identification module is configured to identify a seventh carbonate reservoir as a small karst cave graded reservoir in response to gradual heterogeneity change of the seventh carbonate reservoir, where the subclass to which the seventh carbonate reservoir belongs is the small karst cave type reservoir; identifying an eighth carbonate reservoir as the small cavern mutant reservoir in response to an abrupt change in heterogeneity of the eighth carbonate reservoir, the eighth carbonate reservoir belonging to the class of small cavern type reservoirs.

Optionally, the physical property analysis module is configured to perform development type identification on the small karst cave graded reservoir according to the third data to obtain a relatively-developed class, a medium-developed class and an under-developed class included in the small karst cave graded reservoir, and perform full-diameter core physical property analysis on the relatively-developed class, the medium-developed class and the under-developed class included in the small karst cave graded reservoir respectively; and identifying the development type of the small karst cave mutant reservoir according to the third data to obtain the relatively developed and under-developed types included by the small karst cave mutant reservoir, and respectively performing full-diameter core physical property analysis on the relatively developed and under-developed types included by the small karst cave mutant reservoir.

Optionally, the multi-type karst cave type reservoir comprises a multi-type karst cave graded reservoir and a multi-type karst cave mutant reservoir, and the heterogeneity type identification module is configured to identify a ninth carbonate reservoir as the multi-type karst cave graded reservoir in response to a gradual heterogeneity change of the ninth carbonate reservoir, where the category to which the ninth carbonate reservoir belongs is the multi-type karst cave type reservoir; identifying a tenth carbonate reservoir as the multi-type karst cave mutant reservoir in response to a sudden change in heterogeneity of the tenth carbonate reservoir, the tenth carbonate reservoir belonging to the class of the multi-type karst cave reservoir.

Optionally, the physical property analysis module is configured to perform development type identification on the multiple types of karst cave gradient reservoirs according to the third data, obtain a relatively-developed class, a medium-developed class and an under-developed class that are included in the multiple types of karst cave gradient reservoirs, and perform full-diameter core physical property analysis on the relatively-developed class, the medium-developed class and the under-developed class that are included in the multiple types of karst cave gradient reservoirs respectively; and identifying development types of the multiple types of karst cave mutant reservoirs according to the third data to obtain relatively developed and under-developed types included by the multiple types of karst cave mutant reservoirs, and respectively performing full-diameter core physical property analysis on the relatively developed and under-developed types included by the multiple types of karst cave mutant reservoirs.

In another aspect, an electronic device is provided that includes one or more processors and one or more memories having at least one program code stored therein that is loaded and executed by the one or more processors to implement the above-described method for core properties analysis of carbonate reservoirs.

In another aspect, a computer-readable storage medium having at least one program code stored therein is provided, the at least one program code being loaded and executed by a processor to implement the above-described method for core properties analysis of a carbonate reservoir.

In another aspect, a computer program product or computer program is provided, the computer program product or computer program comprising computer instructions stored in a computer readable storage medium. The processor of the electronic device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the electronic device executes the method for analyzing the core physical property of the carbonate reservoir.

The beneficial effects brought by the technical scheme provided by the embodiment of the application at least comprise:

according to the method provided by the embodiment, the carbonate reservoir is divided into a plurality of types of reservoirs with different reservoir space sizes according to the size of the reservoir space in the carbonate reservoir, and each type of the plurality of types is further divided into a plurality of small types with different heterogeneity change degrees according to the heterogeneity change degree of pore distribution in the carbonate reservoir, so that the classification mode of the carbonate reservoir is more refined. On the basis, physical property analysis is respectively carried out on each of the further divided subclasses according to the development degree of the core hole, so that carbonate rock reservoirs with different hole sizes and different heterogeneity change degrees can utilize different physical property analysis modes. Therefore, the method fully considers the characteristics of multi-scale reservoir space and heterogeneity of carbonate reservoir development, selects a targeted physical property analysis technology, and improves the accuracy of a physical property analysis result.

Drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.

Fig. 1 is a flowchart of a method for analyzing core properties of a carbonate reservoir according to an embodiment of the present disclosure;

FIG. 2 is a schematic diagram illustrating pore, small hole and large hole classifications of a carbonate reservoir for core physical property analysis according to an embodiment of the present disclosure;

fig. 3 is a schematic diagram of a heterogeneous cavernous carbonate reservoir classification scheme provided by an embodiment of the present application;

fig. 4 is a schematic structural diagram of a core physical property analysis device for a carbonate reservoir according to an embodiment of the present disclosure;

fig. 5 is a schematic structural diagram of a terminal according to an embodiment of the present application;

fig. 6 is a schematic structural diagram of a server according to an embodiment of the present application.

Detailed Description

To make the objects, technical solutions and advantages of the present application more clear, embodiments of the present application will be described in further detail below with reference to the accompanying drawings.

The heterogeneity of the carbonate rock reservoir has important influence on the comprehensive and accurate evaluation of the physical property characteristics of the reservoir. Carbonate reservoir formation is mainly controlled by two aspects of reef facies deposition and erosion. The reservoir space types of the reservoir layer are various, and various types of pores such as interparticle pores, interparticle dissolution pores and intraparticle pores and the like and dissolution holes with different scales are developed. The non-uniform distribution of different scale caverns and pores or the non-uniform distribution combined with pores causes the heterogeneity of the reservoir and controls different characteristics of the heterogeneity.

The carbonate reservoir core physical property analysis method comprises a full-diameter core physical property analysis method and a small core sample physical property analysis method. The full-diameter core physical property analysis can better reflect the physical property characteristics of the strong heterogeneous hole type carbonate rock reservoir compared with a small core sample.

However, a core physical property analysis technical method aiming at a hole type carbonate reservoir scientific system with different characteristics is not formed at present, so that the comprehensive and accurate evaluation of the physical properties of a strong heterogeneous carbonate reservoir is restricted, and the determination of reserve calculation parameters and the accuracy of reserve calculation are influenced.

In the embodiment of the application, aiming at the difficult problem of testing physical property analysis of the strong heterogeneous cavernous carbonate reservoir, different scales of karst caves and pores of the carbonate reservoir are analyzed through distribution characteristics of the karst caves and the pores of the carbonate reservoir, the karst caves and the pores of the carbonate reservoir are classified according to the heterogeneous characteristics of the size and the distribution of the reservoir space, an experimental method and a sample selection technology aiming at physical property analysis of different types of carbonate reservoirs are established, and a core physical property analysis technical method aiming at a scientific system of the strong heterogeneous cavernous carbonate reservoir is formed.

Specifically, the carbonate reservoirs are divided into seven types according to different sizes of karst caves and pores of the carbonate reservoirs and the heterogeneous characteristics of the size and distribution of reservoir spaces, the applicability of physical property analysis of small core samples and full-diameter core samples is analyzed according to the characteristics of the seven types of reservoirs, a method for selecting targeted small core samples or full-diameter core experimental analysis methods and experimental samples is formed, the adaptability of the experimental methods and the representativeness of the samples are improved, the purpose of comprehensively and accurately testing the physical properties of the core is achieved, and the requirement for describing the oil and gas reservoirs is met.

The seven types of the carbonate reservoir are respectively a pore graded reservoir, a pore mutant reservoir, a pore spot reservoir, a small karst cave graded reservoir, a small karst cave mutant reservoir, a multi-type karst cave graded reservoir and a multi-type karst cave mutant reservoir. In one exemplary embodiment, carbonate reservoirs are first classified into three major categories, namely pore type reservoirs, small karst cave type reservoirs, and multi-type karst cave type reservoirs; then, each category is divided into a plurality of sub categories, such as a pore type reservoir is divided into a pore graded reservoir, a pore mutant reservoir and a pore spot type reservoir, a small karst cave type reservoir is divided into a small karst cave graded reservoir and a small karst cave mutant reservoir, and a multi-type karst cave type reservoir is divided into a multi-type karst cave graded reservoir and a multi-type karst cave mutant reservoir.

It should be noted that, optionally, the carbonate reservoirs are divided into seven types, in other embodiments, the reservoir space type of large karst cave is not identified, the carbonate reservoirs are firstly divided into two types, namely a pore type reservoir and a small karst cave type reservoir, the pore type reservoir is divided into a pore graded reservoir, a pore mutant reservoir and a pore spot type reservoir, and the small karst cave type reservoir is divided into a small karst cave graded reservoir and a small karst cave mutant reservoir, so that the carbonate reservoirs are divided into five types. The five types of carbonate reservoirs are respectively a pore graded reservoir, a pore mutant reservoir, a pore spot reservoir, a small karst cave graded reservoir and a small karst cave mutant reservoir.

The method for analyzing the core physical properties of the rock reservoir provided in the embodiments of the present application is specifically described below.

Fig. 1 is a flowchart of a method for analyzing core physical properties of a rock reservoir according to an embodiment of the present disclosure. Referring to fig. 1, the method includes:

s101, the electronic equipment respectively detects the multiple carbonate rock reservoirs to obtain first data.

The first data represents the size of each hole in the carbonate reservoir. For example, the first data includes a diameter of each hole in each type of carbonate reservoir in a plurality of types of carbonate reservoirs.

S102, the electronic equipment identifies the types of the storage spaces of the carbonate rock reservoirs according to the first data to obtain multiple types.

Wherein each of the plurality of classes comprises carbonate reservoirs of a same reservoir space type, the reservoir space types being divided according to a size of the hole.

In some embodiments, the reservoir space types include pores, small-scale caverns, and large-scale caverns. The diameter of the pore is smaller than the diameter threshold, the diameter of the small karst cave is smaller than the diameter of the core, and the diameter of the large karst cave is larger than the diameter of the core. For example, the diameter threshold is 2 millimeters (mm). In other words, the cavern with the diameter less than 2mm is used as a pore, the cavern with the diameter less than the diameter of the core is used as a small cavern, and the cavern with the diameter greater than the diameter of the core is used as a large cavern. In some embodiments, the reservoir space types include pores and small caverns.

In some embodiments, the plurality of classes includes pore type reservoirs, small cavern type reservoirs, and multi-type cavern type reservoirs. Each reservoir space of the porous reservoir distribution is a pore. A porous reservoir is also known as a p-type reservoir. The reservoir space of the small cavern type reservoir distribution includes pores and small caverns. The small-scale karst cave type reservoir is also called f type reservoir. The storage space distributed by the multi-type karst cave type reservoir comprises not only large karst caves, but also pores and small karst caves. The multi-type karst cave reservoir is also called a c-type reservoir. In other embodiments, the plurality of classes includes pore type reservoirs and small cavern type reservoirs.

In the following, taking the process of classifying the first carbonate reservoir, the second carbonate reservoir and the third carbonate reservoir as an example, how to classify the carbonate reservoirs into three categories (i.e., the carbonate reservoirs are classified into a p-type reservoir, a f-type reservoir and a c-type reservoir) is illustrated. The first carbonate reservoir, the second carbonate reservoir and the third carbonate reservoir are all carbonate reservoirs of one type included in multiple carbonate reservoirs. For example, the process of classifying multiple types of carbonate reservoirs includes the following steps one through three:

step one, the electronic device compares the diameter of each reservoir space in the first carbonate reservoir with a diameter threshold, and if the diameter of each reservoir space in the first carbonate reservoir is smaller than the diameter threshold, the electronic device determines that each reservoir space in the first carbonate reservoir is a pore. The electronic device would then identify the first carbonate reservoir as a porous reservoir in response to each reservoir space in the first carbonate reservoir being a pore.

For example, according to the size of a storage space in a pore type reservoir, a p type reservoir is divided, the p type reservoir is a pore type reservoir, and the pore diameter of the p type reservoir is less than 2 mm. For example, referring to fig. 2, fig. 2 is a schematic diagram of the classification of pores, small holes and large holes of a carbonate reservoir for core physical analysis, and the reservoir with the pore diameter less than 2mm is classified into a p-type reservoir. Where 2mm is illustrative of the diameter threshold, any of the p-type reservoirs is illustrative of the first carbonate reservoir.

And step two, the electronic equipment compares the diameter of each storage space in the second carbonate reservoir with the diameter of the core, if the diameter of the storage space in the second carbonate reservoir is smaller than the diameter threshold, the electronic equipment determines the development pore of the second carbonate reservoir, and if the diameter of the storage space in the second carbonate reservoir is smaller than the diameter of the core, the electronic equipment determines the development small karst cave of the second carbonate reservoir. The electronic device would then identify the second carbonate reservoir as a small cavern type reservoir in response to the reservoir space in the second carbonate reservoir including pores and small caverns.

For example, according to the size of a hole in a hole type reservoir, f type reservoirs are divided, the f type reservoirs are small karst cave type reservoirs, and the karst cave diameter of the f type reservoirs is larger than a diameter threshold value or smaller than the core diameter. The f-type reservoir can also develop pores (the diameter of the pores is less than 2mm), and the pores are divided into the f-type reservoirs when developing or not developing. For example, referring to fig. 2, reservoirs with pore diameters greater than 2mm and less than the core diameter D are classified as f-type reservoirs. Where 2mm is an illustration of the diameter threshold and any of the f-type reservoirs is an illustration of the second carbonate reservoir.

And step three, the electronic equipment compares the diameter of each storage space in the third carbonate reservoir with the core diameter, and in response to the fact that the storage spaces in the third carbonate reservoir comprise pores, small karst caves and large karst caves, the electronic equipment identifies the third carbonate reservoir as a multi-type karst cave reservoir.

For example, according to the size of a reservoir space in the reservoir, a type c reservoir is divided, and the type c reservoir is a multi-type karst cave reservoir. The storage space of the c-type reservoir not only develops large karst caves (i.e. the karst caves with the diameter larger than that of the core) but also develops small karst caves and pores, the large karst caves are mostly distributed dispersedly, and the core is broken and broken at the development position of the large karst caves. For example, referring to fig. 2, reservoirs with pore diameters larger than the core diameter D are classified as c-type reservoirs. Wherein any of the class c reservoirs is illustrative of a third carbonate reservoir.

Analysis shows that for physical property analysis of the full-diameter core, when the diameter of the karst cave is larger than that of the core, the core is usually broken and broken, and a proper sample cannot be obtained, and when the diameter of the karst cave is smaller than that of the core, the proper sample can be selected. Therefore, in this embodiment, by defining the cavern larger than the core diameter as a large cavern and defining the cavern smaller than the core diameter as a small cavern, physical property analysis is performed on a multi-type cavern-type reservoir with the large cavern, the small cavern, and the pore and a small cavern-type reservoir with the small cavern and the pore, respectively, so as to facilitate screening of suitable samples.

It should be noted that the carbonate reservoir may be optionally classified as a type c reservoir. In other embodiments, the first through second steps are performed without performing the third step, thereby classifying the carbonate reservoirs into two broad categories (i.e., carbonate reservoirs into a category p reservoir and a category f reservoir)

S103, the electronic equipment detects the multiple classes respectively to obtain second data of each class.

Wherein the second data is indicative of a degree of heterogeneity of pore distribution in the carbonate reservoir. For example, the second data includes a measure of heterogeneity variation of pore distribution in the carbonate reservoir and a heterogeneity variation of pore distribution in the carbonate reservoir.

And S104, the electronic equipment performs heterogeneity type identification on the multiple classes according to the second data to obtain multiple subclasses included in each class.

Each subclass of the subclasses comprises carbonate reservoirs with the same heterogeneity type, and the heterogeneity types are divided according to the heterogeneity change degree. For example, the plurality of sub-categories include a p1 category reservoir, a p2 category reservoir, a p3 category reservoir, a f1 category reservoir, a f2 category reservoir, a c1 category reservoir, and a c2 category reservoir. Among them, the reservoir of p1 type is also called a pore graded reservoir, the reservoir of p2 type is also called a pore mutant reservoir, and the reservoir of p3 type is also called a pore spot reservoir. The reservoir of p1 class and the reservoir of p2 class are obtained by dividing the reservoir of p class according to the variation degree of heterogeneity. The f1 reservoir is also called a small karst cave graded reservoir, and the f2 reservoir is also called a small karst cave mutant reservoir. The f1 reservoir and the f2 reservoir are obtained by dividing the f reservoir according to the variation degree of the heterogeneity. The c1 reservoir is also called a multi-type karst cave graded reservoir, and the c2 reservoir is also called a multi-type karst cave mutant reservoir. The reservoir of the c1 class and the reservoir of the c2 class are obtained by dividing the reservoir of the c class according to the variation degree of the heterogeneity.

In the following, taking the process of classifying the fourth carbonate reservoir, the fifth carbonate reservoir and the sixth carbonate reservoir as an example, how to further classify the pore type reservoirs into three categories: pore graded reservoirs, pore mutated reservoirs or pore-patchy reservoirs (i.e. further classification of p-type reservoirs into p1 type reservoirs, p2 type reservoirs and p3 type reservoirs) are specified. The fourth carbonate reservoir, the fifth carbonate reservoir and the sixth carbonate reservoir are all carbonate reservoirs of the same type, and the fourth carbonate reservoir, the fifth carbonate reservoir and the sixth carbonate reservoir belong to the same type, namely porous reservoirs. For example, the process of classifying a pore type reservoir includes the following steps one to three:

step one, the electronic equipment compares the heterogeneity variation scale of a fourth carbonate reservoir with a scale threshold value, and analyzes the heterogeneity variation of the fourth carbonate reservoir; in response to the heterogeneity change scale of the fourth carbonate reservoir being greater than the scale threshold and the heterogeneity changing gradually, the electronic device identifies the fourth carbonate reservoir as a pore graded reservoir. Wherein the dimension threshold is, for example, 10 cm.

Step two, the electronic equipment compares the heterogeneity variation scale of the fifth carbonate reservoir with a scale threshold value, and analyzes the heterogeneity variation of the fifth carbonate reservoir; in response to the heterogeneity change scale of the fifth carbonate reservoir being greater than the scale threshold and the heterogeneity changing abruptly, the electronic device identifies the fifth carbonate reservoir as a pore mutant reservoir.

Step three, the electronic equipment compares the heterogeneity variation scale of the sixth carbonate reservoir with a scale threshold; in response to the heterogeneity change scale of the sixth carbonate reservoir being less than the scale threshold, the electronics identify the sixth carbonate reservoir as a pore-blob-type reservoir.

For example, referring to fig. 3, P-type pore type reservoirs are further divided into P1, P2 and P3 according to the variation degree of heterogeneity of pore distribution, and those with heterogeneity of large scale (greater than 10cm) gradually change are divided into P1, which are called pore graded reservoirs; the heterogeneous is a p2 type with large scale (more than 10cm) sudden change and is called a pore mutation type reservoir, the heterogeneous is a p3 type with small scale (less than 10cm) change, and the pore development section of the core is distributed in a core in a spot shape in a region less than 10cm and is called a pore spot type reservoir.

The size of the heterogeneous variation scale is divided into a boundary of 10cm, mainly because the length of a full-diameter core analysis sample is generally 10cm, and when the heterogeneous is small-scale less than 10cm, the whole influence of the heterogeneity on physical properties can be comprehensively reflected by full-diameter physical property analysis; the small core sample is affected by the heterogeneity, can only represent local parts of the core, and cannot reflect the overall physical properties.

In the following, taking the process of classifying the seventh carbonate reservoir and the eighth carbonate reservoir as an example, how to further classify the small cavern type reservoirs into two types: small karst cave graded reservoirs and small karst cave mutant reservoirs (i.e. further dividing the f type reservoirs into f1 type reservoirs and f2 type reservoirs) are specified. The seventh carbonate reservoir and the eighth carbonate reservoir are both carbonate reservoirs of the same type, and the seventh carbonate reservoir and the eighth carbonate reservoir belong to the same type, namely small karst cave reservoirs. For example, the process of classifying a small vug reservoir includes the following steps a to B.

And step A, responding to gradual change of the heterogeneity of the seventh carbonate reservoir, identifying the seventh carbonate reservoir as a small karst cave gradual change reservoir by the electronic equipment, wherein the seventh carbonate reservoir belongs to the small karst cave reservoir.

And step B, responding to the sudden change of the heterogeneity of the eighth carbonate reservoir, identifying the eighth carbonate reservoir as a small karst cave mutation type reservoir by the electronic equipment, wherein the category to which the eighth carbonate reservoir belongs is a small karst cave type reservoir.

For example, referring to fig. 3, the f-type small cavern type reservoirs are further classified into f1 types and f2 types according to the degree of heterogeneity variation of the cavern distribution. Specifically, heterogeneous in the f types is gradually changed and is classified into f1 types, which are called small karst cave gradient reservoirs; heterogeneous in the f type is suddenly changed and is classified into f2 type, which is called a small karst cave mutant reservoir.

Next, taking the process of classifying the ninth carbonate reservoir and the tenth carbonate reservoir as an example, how to further classify the multi-type cavern reservoir into two types, i.e., a multi-type cavern graded reservoir and a multi-type cavern mutated reservoir (i.e., further classifying the c-type reservoir into a c1 type reservoir and a c2 type reservoir), will be specifically described. The ninth carbonate reservoir and the tenth carbonate reservoir are both carbonate reservoirs of one type, and the ninth carbonate reservoir and the tenth carbonate reservoir belong to the types of the various karst cave reservoirs. For example, the process of classifying the multi-type vuggy reservoir includes the following steps (1) to (2).

Analyzing the heterogeneity variation of a ninth carbonate reservoir by electronic equipment; in response to the gradual change in heterogeneity of the ninth carbonate reservoir, the electronic device identifies the ninth carbonate reservoir as a multi-type karst cave graded reservoir, the category to which the ninth carbonate reservoir belongs being a multi-type karst cave reservoir.

Analyzing the heterogeneity variation of a tenth carbonate reservoir by the electronic equipment; in response to a sudden change in heterogeneity of the tenth carbonate reservoir, the electronic device identifies the tenth carbonate reservoir as a multi-type karst cave mutant reservoir, the tenth carbonate reservoir belonging to the class being the multi-type karst cave reservoir.

For example, referring to fig. 3, the c-type multi-type cavern-type reservoir is further classified into c1 type and c2 type according to the degree of heterogeneity variation of the multi-type cavern distribution. Heterogeneous gradual change in the c types is classified into c1 types, which are called multi-type karst cave gradual change type reservoirs; heterogeneous sudden changes in the c types are classified into c2 types, and the reservoirs are called multi-type karst cave mutant reservoirs.

The above describes how to classify carbonate reservoirs into seven types according to the heterogeneous characteristics of reservoir space size and distribution, and the following further describes how to perform physical property analysis on the seven types of carbonate reservoirs respectively according to the characteristics of the seven types of reservoirs. A targeted small core sample or full-diameter core experimental analysis method selection and an experimental sample selection method are formed through the following steps. It should be noted that the following steps may also be used in the case of dividing carbonate reservoirs into five types.

S105, the electronic equipment respectively detects the subclasses to obtain third data of each subclass, and the third data represent the development degree of the core hole of the carbonate reservoir.

And S106, the electronic equipment analyzes the physical properties of the subclasses according to the third data to obtain physical property analysis results.

Exemplarily, step S106 includes the following steps (1) to (7).

In the process of analyzing the pore gradual change type reservoir, the electronic equipment identifies the development type of the pore gradual change type reservoir according to the third data to obtain the development type, the medium development type and the under development type of the pore gradual change type reservoir, and respectively analyzes the physical properties of the small core sample of the development type, the medium development type and the under development type of the pore gradual change type reservoir.

For example, for a p1 pore graded reservoir, the development degree of the pore of the core is observed and described, the core is divided into three types of development, medium development and under development according to the development degree of the pore, the change cycle of the development degree of the pore is divided according to the development degree, medium development, under development, medium development and under development, core segments with the development degrees of the medium development, the medium development and the under development are respectively and uniformly selected from small core samples for physical property analysis, and the sampling density is 4 samples per meter. If the length is 0.75m longer than the development segment, 3 samples are taken; medium is more than 0.5m, 2 samples are taken; the length of the underdeveloped segment was 0.25m, and 1 sample was taken.

The physical property characteristics of the pore graded reservoir can be better reflected by the physical property analysis of the small core sample, so that the full-diameter core physical property analysis with longer experimental period and higher cost does not need to be carried out on the pore graded reservoir, and the time and the economic cost for the core physical property analysis are saved.

And (2) the electronic equipment identifies the development type of the pore mutation type reservoir according to the third data to obtain the relatively development type and the under development type of the pore mutation type reservoir, and respectively analyzes the physical properties of the small core sample of the relatively development type and the under development type of the pore mutation type reservoir.

For example, referring to fig. 3, for a p2 type pore mutation reservoir, the pore development degree of a core is observed and described, the core is divided into a relatively developed type and an under developed type according to the pore development degree, the change cycle of the pore development degree is divided according to the relatively developed type, the under developed type, the relatively developed type and the under developed type, small core samples are uniformly selected for physical property analysis of the cores with the relatively developed type and the under developed type, and the sampling density is about 4 samples per meter.

And (3) carrying out full-diameter core physical property analysis on the pore spot type reservoir by the electronic equipment.

For example, referring to fig. 3, for a p3 pore-pattern reservoir, a full-diameter core sample is uniformly selected from the core for physical analysis, and the sampling density is 4 samples per meter.

Because the physical property analysis of the small core sample is influenced by the pore spot block distribution of the core, only the local physical property characteristics of the core can be reflected, and the physical property analysis of the full-diameter core can more accurately reflect the overall physical property characteristics of the pore spot reservoir core, the method is favorable for improving the accuracy of the physical property analysis of the pore spot reservoir core by adopting the full-diameter core physical property analysis mode.

And (4) the electronic equipment identifies the development type of the small karst cave gradient reservoir according to the third data to obtain a relatively development type, a medium development type and an under development type which are included in the small karst cave gradient reservoir, and respectively analyzes the physical properties of the full-diameter core of the relatively development type, the medium development type and the under development type which are included in the small karst cave gradient reservoir.

For example, referring to fig. 3, for an f1 small karst cave graded reservoir, the development degree of a core hole is observed and described, the core is divided into three types, namely a relatively-developed type, a medium-developed type and an under-developed type according to the development degree of the hole, the change cycle of the development degree of the hole is divided according to the relatively-developed type, the medium-developed type, the under-developed type, the medium-developed type, the relatively-developed type and the under-developed type, rock cores with the development degrees of the relatively-developed type, the medium-developed type and the under-developed type are respectively and uniformly selected from full-diameter core samples for analysis, and the sampling density is 4 samples per meter.

The physical property characteristics of the karst cave reservoir stratum cannot be comprehensively reflected by the physical property analysis of the small core sample, and the physical property characteristics of the karst cave reservoir stratum can be accurately reflected by the physical property analysis of the full-diameter core, so that the accuracy of the physical property analysis of the karst cave reservoir stratum is improved by adopting the full-diameter core physical property analysis mode.

And (5) the electronic equipment identifies the development type of the small karst cave mutant reservoir according to the third data to obtain the relatively developed and under-developed types included in the small karst cave mutant reservoir, and respectively performs full-diameter core physical property analysis on the relatively developed and under-developed types included in the small karst cave mutant reservoir.

For example, referring to fig. 3, for an f2 small karst cave mutation reservoir, the development degree of a core hole is observed and described, the core is divided into a relatively developed type and an under-developed type according to the development degree of the hole, the change of the development degree of the hole is divided into a gyrus according to the relatively developed type, the under-developed type, the relatively developed type and the under-developed type, full-diameter core samples are uniformly selected for the core with the relatively developed type and the under-developed type respectively, and the physical property analysis is performed, wherein the sampling density is about 4 samples per meter.

And (6) the electronic equipment identifies the development types of the multi-type karst cave gradient reservoir according to the third data to obtain a relatively development type, a medium development type and an under-development type which are included in the multi-type karst cave gradient reservoir, and respectively performs full-diameter core physical property analysis on the relatively development type, the medium development type and the under-development type which are included in the multi-type karst cave gradient reservoir.

For example, referring to fig. 3, for a c1 multi-type karst cave graded reservoir, the development degree of the core hole is observed and described, the whole section of the core that does not develop in the large cave is divided into three types, i.e. a relatively-developing type, a medium-developing type and a sub-developing type according to the development degree of the hole (most of the large karst caves are distributed dispersedly, and the core is often broken and broken at the development position of the large karst cave, so the physical property of the large karst cave cannot reflect the physical property of the large cave, the physical property of the large karst cave part needs to be obtained by combining the core observation and description with the conventional and imaging logging comprehensive analysis, the physical property analysis technology of the large karst cave is difficult to measure the physical property of the large karst cave at present), the variation of the development degree is divided into a cycle according to relatively-medium development type, under development type, medium development type and under development type, the core samples with the whole diameter are respectively and uniformly selected for physical property analysis, the sampling density was 4 samples per meter.

And (7) the electronic equipment identifies the development types of the multi-type karst cave mutant reservoir according to the third data to obtain the relatively development and under development types included in the multi-type karst cave mutant reservoir, and respectively performs full-diameter core physical property analysis on the relatively development and under development types included in the multi-type karst cave mutant reservoir.

For example, referring to fig. 3, for a c2 multi-type karst cave mutant reservoir, the development degree of the core hole is observed and described, the whole section of the core with a big hole but not developed is divided into a relatively developed type and an under developed type according to the development degree of the hole, the change cycle of the development degree of the hole is divided according to the relatively developed type, the under developed type, the relatively developed type and the under developed type, the full-diameter core samples are uniformly selected for physical property analysis of the cores with the relatively developed type and the under developed type respectively, and the sampling density is about 4 samples per meter.

In the method provided by the embodiment, the carbonate reservoir is divided into multiple types with different hole sizes according to the size of each hole in the carbonate reservoir, and each type is further divided into multiple small types with different heterogeneity change degrees according to the heterogeneity change degree of the hole distribution in the carbonate reservoir, so that the classification mode of the carbonate reservoir is more refined. On the basis, physical property analysis is respectively carried out on each small type according to the development degree of the core hole, so that the characteristic of heterogeneity of various carbonate rock reservoirs is fully considered, and the accuracy of a physical property analysis result is improved.

Furthermore, the embodiment establishes a carbonate rock reservoir core physical property analysis experiment method and a sample selection technology aiming at different reservoir space types and distribution characteristics, improves the adaptability of the experiment method and the representativeness of the sample, forms a core physical property analysis technical method aiming at the heterogeneous porous carbonate rock reservoir science, achieves the aim of accurately testing the core physical property of the heterogeneous carbonate rock reservoir, improves the comprehensive and accurate evaluation of the strong heterogeneous carbonate rock reservoir physical property, and improves the accuracy of the determination of reserve calculation parameters and the reserve calculation. The analysis effect is considered, and convenience and economy of the experimental method are combined, so that the analysis accuracy is improved, and the method has the characteristics of high efficiency and low cost.

The above examples will be described in further detail below by taking physical property analysis of a core of a MX13 well longwanggio group as an example. The physical property analysis of the core of the MX13 Jinglongwanggao group specifically comprises the following steps of one to three.

Observing a core of the MX13 Jinglongwanggao group, analyzing heterogeneous characteristics of different-scale karst caves and pores of the core according to the size and distribution of a reservoir space, and obtaining the knowledge that the core of the MX13 Jinglongwanggao group is mainly small karst caves and pores and the heterogeneous change of the pores is gradual. The well core was defined as a small cavern graded reservoir of type f1 according to the seven types of taxonomy for carbonate reservoirs.

And step two, dividing the rock cores of the MX13 well Longwanggao group into three types of relatively-developed, medium-developed and under-developed according to the development degree of the holes, dividing the change cycle of the development degree of the holes according to the relatively-medium development, under-developed, medium-developed, relatively-developed and under-developed states, and uniformly selecting full-diameter rock core samples from the rock cores of the relatively-developed, medium-developed and under-developed states respectively, wherein the sampling densities of the rock cores of the three types of the hole development degrees are 4 samples per meter.

And step three, analyzing the physical properties of the full-diameter core of the selected MX13 well Longwangtao group, and accurately and comprehensively reflecting the physical properties of the coring section of the MX13 well Longwangtao group according to the porosity and the permeability obtained by analysis.

The application of the physical property analysis result includes various scenes. In some embodiments, the electronic device stores the physical property analysis results onto a blockchain. For example, the electronic device packs the physical property analysis results into blocks, and adds blocks including the physical property analysis results to a block chain. In some embodiments, the electronic device transmits the physical property analysis result to a server over a network. In some embodiments, the electronic device displays the physical property analysis result in a screen. For example, the electronic device visually displays the physical property analysis result. In some embodiments, the electronic device writes the physical property analysis result into a file and outputs the file.

Fig. 4 is a schematic structural diagram of a core physical property analysis device for a carbonate reservoir according to an embodiment of the present application. Referring to fig. 4, the apparatus includes:

the detection module 401 is configured to detect multiple carbonate reservoirs respectively to obtain first data, where the first data represents a size of each hole in the carbonate reservoirs;

a storage space type identification module 402, configured to perform storage space type identification on multiple types of carbonate reservoirs according to the first data to obtain multiple types, where each of the multiple types includes a carbonate reservoir of the same storage space type, and the storage space types are divided according to the size of the hole;

the detection module 401 is further configured to detect the multiple classes respectively to obtain second data of each class, where the second data represents a degree of heterogeneity change of pore distribution in the carbonate reservoir;

the heterogeneity type identification module 403 is configured to perform heterogeneity type identification on the multiple classes according to the second data to obtain multiple subclasses included in each class, where each subclass of the multiple subclasses includes carbonate reservoirs of the same heterogeneity type, and the heterogeneity types are divided according to a heterogeneity change degree;

the detection module 401 is further configured to detect the multiple subclasses respectively to obtain third data of each subclass, where the third data represents a rock core hole development degree of the carbonate reservoir;

and a property analysis module 404 for performing property analysis on each of the plurality of subclasses based on the third data to obtain a property analysis result.

Optionally, the first data includes a diameter of each hole in the carbonate reservoir, the reservoir space types include pores, small-sized caverns, and large-sized caverns, the diameter of the pores is smaller than a diameter threshold, the diameter of the small-sized caverns is smaller than a core diameter, the diameter of the large-sized caverns is larger than the core diameter, the plurality of classes include pore type reservoirs, small-sized cavern type reservoirs, and multiple-type cavern type reservoirs, and the reservoir space type identification module 402 is configured to identify the first carbonate reservoir as a pore type reservoir in response to each reservoir space in the first carbonate reservoir being a pore, the first carbonate reservoir being a class of carbonate reservoirs included in the multiple-type carbonate reservoir; identifying a second carbonate reservoir as a small cavern type reservoir in response to a reservoir space in the second carbonate reservoir including pores and small caverns, the second carbonate reservoir being a type of carbonate reservoir included in a plurality of types of carbonate reservoirs; in response to a reservoir space in the third carbonate reservoir including pores, small-scale caverns, and large-scale caverns, identifying the third carbonate reservoir as a multi-type cavern-type reservoir, the third carbonate reservoir being a type of carbonate reservoir included in the multi-type carbonate reservoir.

Optionally, the second data includes a heterogeneity variation scale of pore distribution in the carbonate reservoir, the pore type reservoir includes subclasses of a pore graded reservoir, a pore mutant reservoir, or a pore spot type reservoir, and the heterogeneity type identification module 403 is configured to identify the fourth carbonate reservoir as a pore graded reservoir in response to the heterogeneity variation scale of the fourth carbonate reservoir being greater than a scale threshold and the heterogeneity being gradually changed, and the class to which the fourth carbonate reservoir belongs is the pore type reservoir; in response to the fact that the heterogeneity variation scale of the fifth carbonate reservoir is larger than the scale threshold value and the heterogeneity suddenly changes, identifying the fifth carbonate reservoir as a pore mutation type reservoir, wherein the category to which the fifth carbonate reservoir belongs is a pore type reservoir; and in response to the heterogeneity variation scale of the sixth carbonate reservoir being smaller than the scale threshold, identifying the sixth carbonate reservoir as a pore-speck reservoir, wherein the category to which the sixth carbonate reservoir belongs is a pore-speck reservoir.

Optionally, the physical property analysis module 404 is configured to perform development type identification on the pore graded reservoir according to the third data to obtain a development class, a medium development class, and an under development class included in the pore graded reservoir, and perform small core sample physical property analysis on the development class, the medium development class, and the under development class included in the pore graded reservoir respectively; according to the third data, identifying the development type of the pore mutation type reservoir to obtain a relatively developed type and an under developed type included by the pore mutation type reservoir, and respectively analyzing the physical properties of the small core sample of the relatively developed type and the under developed type included by the pore mutation type reservoir; and (4) carrying out full-diameter core physical property analysis on the pore spot type reservoir.

Optionally, the small karst cave type reservoir includes a subclass of small karst cave graded reservoirs or small karst cave mutant reservoirs, and the heterogeneity type identification module 403 is configured to identify a seventh carbonate reservoir as a small karst cave graded reservoir in response to gradual change in heterogeneity of the seventh carbonate reservoir, where the subclass to which the seventh carbonate reservoir belongs is a small karst cave type reservoir; in response to a sudden change in heterogeneity of the eighth carbonate reservoir, identifying the eighth carbonate reservoir as a small karst cave mutant reservoir, the eighth carbonate reservoir belonging to the class of small karst cave type reservoirs.

Optionally, the physical property analysis module 404 is configured to perform development type identification on the small karst cave graded reservoir according to the third data to obtain a relatively-developed type, a medium-developed type, and an under-developed type included in the small karst cave graded reservoir, and perform full-diameter core physical property analysis on the relatively-developed type, the medium-developed type, and the under-developed type included in the small karst cave graded reservoir, respectively; and identifying the development type of the small karst cave mutant reservoir according to the third data to obtain the relatively developed and under-developed types included by the small karst cave mutant reservoir, and respectively performing full-diameter core physical property analysis on the relatively developed and under-developed types included by the small karst cave mutant reservoir.

Optionally, the multi-type karst cave type reservoir includes a multi-type karst cave graded reservoir and a multi-type karst cave mutant reservoir, and the heterogeneity type identification module 403 is configured to identify the ninth carbonate reservoir as the multi-type karst cave graded reservoir in response to gradual heterogeneity change of the ninth carbonate reservoir, where the ninth carbonate reservoir belongs to the multi-type karst cave type reservoir; in response to a sudden change in heterogeneity of the tenth carbonate reservoir, identifying the tenth carbonate reservoir as a multi-type karst cave mutant reservoir, the tenth carbonate reservoir belonging to the class being the multi-type karst cave reservoir.

Optionally, the physical property analysis module 404 is configured to perform development type identification on the multiple types of karst cave graded reservoirs according to the third data, obtain a relatively-developed class, a medium-developed class and an under-developed class included in the multiple types of karst cave graded reservoirs, and perform full-diameter core physical property analysis on the relatively-developed class, the medium-developed class and the under-developed class included in the multiple types of karst cave graded reservoirs, respectively; and identifying development types of the multi-type karst cave mutant reservoir according to the third data to obtain relatively developed and under-developed types included by the multi-type karst cave mutant reservoir, and respectively performing full-diameter core physical property analysis on the relatively developed and under-developed types included by the multi-type karst cave mutant reservoir.

According to the device provided by the embodiment of the application, the carbonate reservoir is divided into multiple types with different hole sizes according to the size of each hole in the carbonate reservoir, and each type is further divided into multiple small types with different anisotropic change degrees according to the anisotropic change degrees of the pore distribution in the carbonate reservoir, so that the classification mode of the carbonate reservoir is more refined. On the basis, physical property analysis is respectively carried out on each small type according to the development degree of the core hole, so that the characteristic of heterogeneity of various carbonate rock reservoirs is fully considered, and the accuracy of a physical property analysis result is improved.

All the above optional technical solutions may be combined arbitrarily to form optional embodiments of the present application, and are not described herein again.

It should be noted that: when the core physical property analysis device for a carbonate reservoir provided in the above embodiment performs core physical property analysis on the carbonate reservoir, only the division of each function module is illustrated, and in practical application, the function distribution may be completed by different function modules as needed, that is, the internal structure of the core physical property analysis device for a carbonate reservoir may be divided into different function modules to complete all or part of the functions described above. In addition, the core physical property analysis device for the carbonate reservoir and the core physical property analysis method for the carbonate reservoir provided in the above embodiments belong to the same concept, and specific implementation processes thereof are described in the method embodiments and are not described herein again.

The electronic device in the above method embodiment may be implemented as a terminal. For example, fig. 5 shows a block diagram of a terminal 600 according to an exemplary embodiment of the present application. The terminal 600 may be: a smart phone, a tablet computer, an MP3(Moving Picture Experts Group Audio Layer III, motion video Experts compression standard Audio Layer 3) player, an MP4(Moving Picture Experts Group Audio Layer IV, motion video Experts compression standard Audio Layer 4) player, a notebook computer or a desktop computer. The terminal 600 may also be referred to by other names such as user equipment, portable terminal, laptop terminal, desktop terminal, etc.

In general, the terminal 600 includes: one or more processors 601 and one or more memories 602.

The processor 601 may include one or more processing cores, such as a 4-core processor, an 8-core processor, and so on. The processor 601 may be implemented in at least one hardware form of a DSP (Digital Signal Processing), an FPGA (Field-Programmable Gate Array), and a PLA (Programmable Logic Array). The processor 601 may also include a main processor and a coprocessor, where the main processor is a processor for Processing data in an awake state, and is also called a Central Processing Unit (CPU); a coprocessor is a low power processor for processing data in a standby state. In some embodiments, the processor 601 may be integrated with a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content that the display screen needs to display. In some embodiments, processor 601 may also include an AI (Artificial Intelligence) processor for processing computational operations related to machine learning.

The memory 602 may include one or more computer-readable storage media, which may be non-transitory. The memory 602 may also include high-speed random access memory, as well as non-volatile memory, such as one or more magnetic disk storage devices, flash memory storage devices. In some embodiments, a non-transitory computer readable storage medium in memory 602 is used to store at least one program code for execution by processor 601 to implement the method for core property analysis of carbonate reservoirs provided by the method embodiments herein.

In some embodiments, the terminal 600 may further optionally include: a peripheral interface 603 and at least one peripheral. The processor 601, memory 602, and peripheral interface 603 may be connected by buses or signal lines. Various peripheral devices may be connected to the peripheral interface 603 via a bus, signal line, or circuit board. Specifically, the peripheral device includes: at least one of a radio frequency circuit 604, a display 605, a camera assembly 606, an audio circuit 607, a positioning component 608, and a power supply 609.

The peripheral interface 603 may be used to connect at least one peripheral related to I/O (Input/Output) to the processor 601 and the memory 602. In some embodiments, the processor 601, memory 602, and peripheral interface 603 are integrated on the same chip or circuit board; in some other embodiments, any one or two of the processor 601, the memory 602, and the peripheral interface 603 may be implemented on a separate chip or circuit board, which is not limited in this embodiment.

The Radio Frequency circuit 604 is used for receiving and transmitting RF (Radio Frequency) signals, also called electromagnetic signals. The radio frequency circuitry 604 communicates with communication networks and other communication devices via electromagnetic signals. The rf circuit 604 converts an electrical signal into an electromagnetic signal to transmit, or converts a received electromagnetic signal into an electrical signal. Optionally, the radio frequency circuit 604 comprises: an antenna system, an RF transceiver, one or more amplifiers, a tuner, an oscillator, a digital signal processor, a codec chipset, a subscriber identity module card, and so forth. The radio frequency circuitry 604 may communicate with other terminals via at least one wireless communication protocol. The wireless communication protocols include, but are not limited to: the world wide web, metropolitan area networks, intranets, generations of mobile communication networks (2G, 3G, 4G, and 5G), Wireless local area networks, and/or WiFi (Wireless Fidelity) networks. In some embodiments, the rf circuit 604 may further include NFC (Near Field Communication) related circuits, which are not limited in this application.

The display 605 is used to display a UI (User Interface). The UI may include graphics, text, icons, video, and any combination thereof. When the display screen 605 is a touch display screen, the display screen 605 also has the ability to capture touch signals on or over the surface of the display screen 605. The touch signal may be input to the processor 601 as a control signal for processing. At this point, the display 605 may also be used to provide virtual buttons and/or a virtual keyboard, also referred to as soft buttons and/or a soft keyboard. In some embodiments, the display 605 may be one, providing the front panel of the terminal 600; in other embodiments, the display 605 may be at least two, respectively disposed on different surfaces of the terminal 600 or in a folded design; in other embodiments, the display 605 may be a flexible display disposed on a curved surface or a folded surface of the terminal 600. Even more, the display 605 may be arranged in a non-rectangular irregular pattern, i.e., a shaped screen. The Display 605 may be made of LCD (Liquid Crystal Display), OLED (Organic Light-Emitting Diode), and the like.

The camera assembly 606 is used to capture images or video. Optionally, camera assembly 606 includes a front camera and a rear camera. Generally, a front camera is disposed at a front panel of the terminal, and a rear camera is disposed at a rear surface of the terminal. In some embodiments, the number of the rear cameras is at least two, and each rear camera is any one of a main camera, a depth-of-field camera, a wide-angle camera and a telephoto camera, so that the main camera and the depth-of-field camera are fused to realize a background blurring function, and the main camera and the wide-angle camera are fused to realize panoramic shooting and VR (Virtual Reality) shooting functions or other fusion shooting functions. In some embodiments, camera assembly 606 may also include a flash. The flash lamp can be a monochrome temperature flash lamp or a bicolor temperature flash lamp. The double-color-temperature flash lamp is a combination of a warm-light flash lamp and a cold-light flash lamp, and can be used for light compensation at different color temperatures.

Audio circuitry 607 may include a microphone and a speaker. The microphone is used for collecting sound waves of a user and the environment, converting the sound waves into electric signals, and inputting the electric signals to the processor 601 for processing or inputting the electric signals to the radio frequency circuit 604 to realize voice communication. For the purpose of stereo sound collection or noise reduction, a plurality of microphones may be provided at different portions of the terminal 600. The microphone may also be an array microphone or an omni-directional pick-up microphone. The speaker is used to convert electrical signals from the processor 601 or the radio frequency circuit 604 into sound waves. The loudspeaker can be a traditional film loudspeaker or a piezoelectric ceramic loudspeaker. When the speaker is a piezoelectric ceramic speaker, the speaker can be used for purposes such as converting an electric signal into a sound wave audible to a human being, or converting an electric signal into a sound wave inaudible to a human being to measure a distance. In some embodiments, audio circuitry 607 may also include a headphone jack.

The positioning component 608 is used for positioning the current geographic Location of the terminal 600 to implement navigation or LBS (Location Based Service). The Positioning component 608 can be a Positioning component based on the Global Positioning System (GPS) in the united states, the beidou System in china, or the galileo System in russia.

Power supply 609 is used to provide power to the various components in terminal 600. The power supply 609 may be ac, dc, disposable or rechargeable. When the power supply 609 includes a rechargeable battery, the rechargeable battery may be a wired rechargeable battery or a wireless rechargeable battery. The wired rechargeable battery is a battery charged through a wired line, and the wireless rechargeable battery is a battery charged through a wireless coil. The rechargeable battery may also be used to support fast charge technology.

In some embodiments, the terminal 600 also includes one or more sensors 610. The one or more sensors 610 include, but are not limited to: acceleration sensor 611, gyro sensor 612, pressure sensor 613, fingerprint sensor 614, optical sensor 615, and proximity sensor 616.

The acceleration sensor 611 may detect the magnitude of acceleration in three coordinate axes of the coordinate system established with the terminal 600. For example, the acceleration sensor 611 may be used to detect components of the gravitational acceleration in three coordinate axes. The processor 601 may control the display screen 605 to display the user interface in a landscape view or a portrait view according to the gravitational acceleration signal collected by the acceleration sensor 611. The acceleration sensor 611 may also be used for acquisition of motion data of a game or a user.

The gyro sensor 612 may detect a body direction and a rotation angle of the terminal 600, and the gyro sensor 612 and the acceleration sensor 611 may cooperate to acquire a 3D motion of the user on the terminal 600. The processor 601 may implement the following functions according to the data collected by the gyro sensor 612: motion sensing (such as changing the UI according to a user's tilting operation), image stabilization at the time of photographing, game control, and inertial navigation.

Pressure sensors 613 may be disposed on the side bezel of terminal 600 and/or underneath display screen 605. When the pressure sensor 613 is disposed on the side frame of the terminal 600, a user's holding signal of the terminal 600 can be detected, and the processor 601 performs left-right hand recognition or shortcut operation according to the holding signal collected by the pressure sensor 613. When the pressure sensor 613 is disposed at the lower layer of the display screen 605, the processor 601 controls the operability control on the UI interface according to the pressure operation of the user on the display screen 605. The operability control comprises at least one of a button control, a scroll bar control, an icon control and a menu control.

The fingerprint sensor 614 is used for collecting a fingerprint of a user, and the processor 601 identifies the identity of the user according to the fingerprint collected by the fingerprint sensor 614, or the fingerprint sensor 614 identifies the identity of the user according to the collected fingerprint. Upon identifying that the user's identity is a trusted identity, the processor 601 authorizes the user to perform relevant sensitive operations including unlocking the screen, viewing encrypted information, downloading software, paying, and changing settings, etc. The fingerprint sensor 614 may be disposed on the front, back, or side of the terminal 600. When a physical button or vendor Logo is provided on the terminal 600, the fingerprint sensor 614 may be integrated with the physical button or vendor Logo.

The optical sensor 615 is used to collect the ambient light intensity. In one embodiment, processor 601 may control the display brightness of display screen 605 based on the ambient light intensity collected by optical sensor 615. Specifically, when the ambient light intensity is high, the display brightness of the display screen 605 is increased; when the ambient light intensity is low, the display brightness of the display screen 605 is adjusted down. In another embodiment, the processor 601 may also dynamically adjust the shooting parameters of the camera assembly 606 according to the ambient light intensity collected by the optical sensor 615.

A proximity sensor 616, also known as a distance sensor, is typically disposed on the front panel of the terminal 600. The proximity sensor 616 is used to collect the distance between the user and the front surface of the terminal 600. In one embodiment, when proximity sensor 616 detects that the distance between the user and the front face of terminal 600 gradually decreases, processor 601 controls display 605 to switch from the bright screen state to the dark screen state; when the proximity sensor 616 detects that the distance between the user and the front face of the terminal 600 is gradually increased, the processor 601 controls the display 605 to switch from the breath-screen state to the bright-screen state.

Those skilled in the art will appreciate that the configuration shown in fig. 5 is not intended to be limiting of terminal 600 and may include more or fewer components than those shown, or some components may be combined, or a different arrangement of components may be used.

The electronic device in the above method embodiment may be implemented as a server. For example, fig. 6 is a schematic structural diagram of a server 700 provided in this embodiment of the present application, where the server 700 may generate relatively large differences due to different configurations or performances, and may include one or more processors (CPUs) 701 and one or more memories 702, where at least one program code is stored in the memory 702, and is loaded and executed by the processors 701 to implement the method for analyzing core properties of a carbonate reservoir provided in the above-described method embodiments. Of course, the server may also have a wired or wireless network interface, an input/output interface, and other components to facilitate input and output, and the server may also include other components for implementing the functions of the device, which are not described herein again.

In an exemplary embodiment, a computer-readable storage medium, such as a memory including at least one program code, the at least one program code executable by a processor to perform the method of core properties analysis of a carbonate reservoir in the above embodiments is also provided. For example, the computer-readable storage medium may be a Read-Only Memory (ROM), a Random Access Memory (RAM), a Compact Disc Read-Only Memory (CD-ROM), a magnetic tape, a floppy disk, an optical data storage device, and the like.

In an exemplary embodiment, a computer program product is also provided that includes one or more program codes that, when executed by a processor of an electronic device, enable the electronic device to perform the above-described method for core properties analysis of a carbonate reservoir.

The terms "first," "second," and the like in this application are used for distinguishing between similar items and items that have substantially the same function or similar functionality, and it should be understood that "first," "second," and "nth" do not have any logical or temporal dependency or limitation on the number or order of execution. It will be further understood that, although the following description uses the terms first, second, etc. to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another. For example, a first carbonate reservoir may be referred to as a second carbonate reservoir, and similarly, a second carbonate reservoir may be referred to as a first carbonate reservoir, without departing from the scope of the various described examples. The first carbonate reservoir and the second carbonate reservoir may both be carbonate reservoirs, and in some cases, may be separate and distinct carbonate reservoirs.

It is to be understood that the terminology used in the description of the various described examples herein is for the purpose of describing particular examples only and is not intended to be limiting. As used in the description of the various described examples and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.

It should also be understood that the term "and/or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items. The term "and/or" is an associative relationship that describes an associated object, meaning that three relationships may exist, e.g., A and/or B, may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" in the present application generally indicates that the former and latter related objects are in an "or" relationship.

It will be further understood that the terms "Comprises," "Comprising," "inCludes" and/or "inCluding," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.

It is also understood that the term "if" may be interpreted to mean "when" ("where" or "upon") or "in response to a determination" or "in response to a detection". Similarly, the phrase "if it is determined." or "if [ a stated condition or event ] is detected" may be interpreted to mean "upon determining.. or" in response to determining. "or" upon detecting [ a stated condition or event ] or "in response to detecting [ a stated condition or event ]" depending on the context.

It should be understood that, in the various embodiments of the present application, the sequence numbers of the above-mentioned processes do not mean the execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.

It should be understood that determining B from a does not mean determining B from a alone, but may also be determined from a and/or other information.

It will be understood by those skilled in the art that all or part of the steps for implementing the above embodiments may be implemented by hardware, or may be implemented by a program instructing relevant hardware, and the program may be stored in a computer-readable storage medium, and the above-mentioned storage medium may be a read-only memory, a magnetic disk or an optical disk, etc.

The above description is only for the purpose of illustrating the preferred embodiments of the present application and is not intended to limit the present application, but rather, the present application is intended to cover any variations, equivalents, improvements, etc. within the principles of the present application.

Claims

1. A method for analyzing physical properties of a core of a carbonate reservoir, the method comprising:

respectively detecting multiple carbonate reservoirs to obtain first data, wherein the first data represent the size of each hole in the carbonate reservoirs;

according to the second data, conducting heterogeneity type identification on the multiple classes to obtain multiple subclasses included in each class, wherein each subclass in the multiple subclasses includes carbonate rock reservoirs with the same heterogeneity type, and the heterogeneity types are divided according to the heterogeneity change degree;

2. The method of claim 1, wherein the first data comprises a diameter of each hole in a carbonate reservoir, the reservoir space types comprise pores, small-sized caverns and large-sized caverns, the diameters of the pores are smaller than a diameter threshold, the diameters of the small-sized caverns are smaller than a core diameter, the diameters of the large-sized caverns are larger than the core diameter, the multiple classes comprise pore type reservoirs, small-sized cavern type reservoirs and multiple-type cavern type reservoirs, and the reservoir space type identification is performed on the multiple classes of carbonate reservoirs according to the first data to obtain multiple classes, and the reservoir space type identification comprises:

identifying a second carbonate reservoir as the small cavern type reservoir in response to a reservoir space in the second carbonate reservoir comprising pores and small caverns, the second carbonate reservoir being a type of carbonate reservoir included in the plurality of types of carbonate reservoirs;

identifying a third carbonate reservoir as the multiple-type cavernous reservoir in response to a reservoir space in the third carbonate reservoir comprising pores, small-scale caverns, and large-scale caverns, the third carbonate reservoir being a type of carbonate reservoir that the multiple-type carbonate reservoir comprises.

3. The method of claim 2, wherein the second data comprises a heterogeneity variation scale of pore distribution in carbonate reservoirs, the pore type reservoirs comprise subclasses of pore graded type reservoirs, pore mutant type reservoirs or pore speckled type reservoirs, and the heterogeneity type identification of the plurality of classes according to the second data obtains a plurality of subclasses included in each class, and the heterogeneity variation scale comprises:

4. The method of claim 3, wherein said performing a physical property analysis on each of said plurality of subclasses based on said third data comprises:

5. The method of claim 2, wherein the sub-classes included in the small cavern-type reservoir are small cavern graded reservoirs or small cavern mutant reservoirs, and the performing heterogeneity type identification on the plurality of classes according to the second data to obtain a plurality of sub-classes included in each class comprises:

6. The method of claim 5, wherein said performing a physical property analysis on each of said plurality of subclasses based on said third data comprises:

7. The method of claim 2, wherein the multiple types of cavern-type reservoirs comprise a multiple types of cavern graded reservoirs and a multiple types of cavern mutant reservoirs, and the identifying the heterogeneity types of the multiple types according to the second data to obtain multiple subclasses included in each class comprises:

8. The method of claim 7, wherein said performing a physical property analysis on each of said plurality of subclasses based on said third data comprises:

9. The method according to claim 1, wherein after the property analysis is performed on each of the plurality of subclasses according to the third data to obtain property analysis results, the method further comprises at least one of:

storing the physical property analysis result to a block chain;

sending the physical property analysis result to a server;

displaying the physical property analysis result on a screen;

and writing the physical property analysis result into a file, and outputting the file.

10. An electronic device comprising one or more processors and one or more memories having at least one program code stored therein, the at least one program code being loaded and executed by the one or more processors to implement the method of core properties analysis of a carbonate reservoir as claimed in any one of claims 1 to 9.