Dolomite crystallinity identification method and device, storage medium and electronic equipment

Abstract

The present application relates to the technical field of exploration, and particularly relates to a dolomite crystallization degree identification method and device, a storage medium and an electronic device, the method comprising: obtaining preset quantity characteristics and preset qualitative characteristics of dolomite of a target reservoir; identifying the crystallization degree of the dolomite according to a preset crystallization degree identification template and the preset quantity characteristics and the preset qualitative characteristics; and the crystallization degree of rock slices containing dolomite crystals can be identified quickly, at low cost and in large batches.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of exploration, in particular to a dolomite crystallization degree identification method and device, a storage medium and an electronic device. BACKGROUND

[0002] Carbonate reservoirs are an important oil and gas reservoir in the world today, and dolomite is more likely to develop high-quality reservoirs than limestone, so the dolomitization degree determines the quality of dolomite reservoirs to some extent. The dolomite crystallization degree generally represents the dolomitization degree, so studying the dolomite crystallization degree is a fundamental and important part of oil and gas exploration and development.

[0003] However, the existing methods for judging the dolomite crystallization degree basically rely on geochemical test analysis, such as dolomite X-ray diffraction order experiment, and methods for indirectly judging the dolomitization degree and the dolomite crystallization degree by testing the Mg and Ca element content of the mineral, including X-ray diffraction energy spectrum analysis and major element analysis. The existing technologies have the following technical problems: (1) high cost; (2) long cycle; (3) some experiments have high requirements for laboratory precision, and it is difficult to quickly and massively test the crystallization degree. At the same time, the sample may be contaminated by other minerals. In carbonate rock formations, both early terrigenous clastics and later diagenesis may cause other substances containing Mg and Ca elements in the sample, resulting in a significant reduction in experimental accuracy. Of course, the in-situ testing method that has emerged in recent years can solve this problem, and the testing accuracy can reach tens of microns, which can meet the element analysis of most samples, but it further increases the experimental cost and the requirement for laboratory precision, so it is difficult to realize low-cost mass sample testing today.

[0004] There is an urgent need in the art for a solution to judge the dolomite crystallization degree in a low-cost and large batch manner. SUMMARY

[0005] The present application provides a dolomite crystallization degree identification method, device, storage medium and electronic device, which solves the technical problem that it is difficult to judge the dolomite crystallization degree in a low-cost and large batch manner in some technical solutions.

[0006] In a first aspect, the present application provides a dolomite crystallization degree identification method, which comprises:

[0007] S10, obtaining a preset quantity feature and a preset qualitative feature of dolomite in a target reservoir;

[0008] S20, identifying the crystallization degree of the dolomite according to a preset crystallization degree identification template, and the preset quantity feature and the preset qualitative feature;

[0009] The preset quantitative features include the number of straight edges, the length of the longest edge, and the crystallization degree parameter, and the preset qualitative features include the distribution of the straight edges.

[0010] In some embodiments, the dolomite of the target reservoir includes rock slices ground from a rock sample including dolomite obtained by coring.

[0011] In some embodiments, the preset quantitative features of the dolomite of the target reservoir are obtained, including:

[0012] S11, classifying the dolomite crystals according to the mineralogical features of the dolomite;

[0013] S12, obtaining the number of straight edges and the length of the longest edge of each type of dolomite crystal under different fields of view of a microscope;

[0014] S13, calculating the average number of straight edges and the average length of the longest edge of the different types of dolomite crystals;

[0015] S14, obtaining the crystallization degree parameter of the different types of dolomite crystals based on the average number of straight edges and the average length of the longest edge.

[0016] In some embodiments, the crystallization degree parameter of the different types of dolomite crystals is obtained based on the average number of straight edges and the average length of the longest edge, including:

[0017] calculating the ratio of the average length of the longest edge to the average number of straight edges to obtain the crystallization degree parameter of the different types of dolomite crystals.

[0018] In some embodiments, the crystallization degree of the dolomite is identified according to the preset crystallization degree identification template and the preset quantitative features and the preset qualitative features, including:

[0019] S21, if the number of straight edges is less than the number of straight edge threshold, the crystallization degree parameter is greater than the first crystallization degree parameter threshold, and the proportion of straight edges is greater than the first proportion of straight edge threshold, the crystallization degree is the first grade.

[0020] In some embodiments, the crystallization degree of the dolomite is identified according to the preset crystallization degree identification template and the preset quantitative features and the preset qualitative features, including:

[0021] S22, if the number of straight edges is greater than the number of straight edge threshold, the length of the longest edge is greater than the length of the longest edge threshold, the crystallization degree parameter is less than or equal to the first crystallization degree parameter threshold and greater than or equal to the second crystallization degree parameter threshold, and the proportion of straight edges is less than or equal to the first proportion of straight edge threshold and greater than the second proportion of straight edge threshold, the crystallization degree is the second grade.

[0022] In some embodiments, the preset crystallization degree identification template, the preset quantitative feature and the preset qualitative feature are used to identify the crystallization degree of the dolomite, including:

[0023] S23, if the number of straight edges is greater than the number of straight edge threshold, the length of the longest edge is less than the length of the longest edge threshold, the crystallization degree parameter is less than the second crystallization degree parameter threshold, and the straight edge proportion is less than the second straight edge proportion threshold, the crystallization degree is the third grade.

[0024] In a second aspect, the present application provides a dolomite crystallization degree identification device, comprising:

[0025] The parameter acquisition module 100 is configured to acquire the preset quantitative feature and the preset qualitative feature of the dolomite in the target reservoir.

[0026] The crystallization degree judgment module 200 is configured to identify the crystallization degree of the dolomite according to the preset crystallization degree identification template, the preset quantitative feature and the preset qualitative feature.

[0027] The preset quantitative feature includes the number of straight edges, the length of the longest edge and the crystallization degree parameter, the preset qualitative feature includes the distribution of the straight edges, and the preset crystallization degree identification template includes the preset quantitative feature and the preset qualitative feature corresponding to different crystallization degrees.

[0028] In a third aspect, the present application provides a computer readable storage medium, and the computer readable storage medium stores a computer program. When the computer program is executed by one or more processors, the method for identifying the crystallization degree of dolomite according to the first aspect is implemented.

[0029] In a fourth aspect, the present application provides an electronic device, which comprises a memory and one or more processors. The memory stores a computer program, and when the computer program is executed by the one or more processors, the method for identifying the crystallization degree of dolomite according to the first aspect is implemented.

[0030] The method for identifying the crystallization degree of dolomite, the device, the storage medium and the electronic device provided by the present application can quickly, low-cost and large-batch identify the crystallization degree of rock slices containing dolomite crystals by acquiring the preset quantitative feature and the preset qualitative feature of the dolomite in the target reservoir, and identifying the crystallization degree of the dolomite according to the preset crystallization degree identification template, the preset quantitative feature and the preset qualitative feature. BRIEF DESCRIPTION OF DRAWINGS

[0031] In the following, the present application will be described in more detail based on embodiments and with reference to the accompanying drawings:

[0032] Figure 1 FIG. 1 is a schematic diagram of a method for identifying the crystallization degree of dolomite according to an embodiment of the present application;

[0033] Figures 2(a) to 2(d) A diagram showing the result of identifying the quantitative characteristics of different dolomite minerals in an embodiment of the present application;

[0034] Figure 3 A diagram showing the verification of the crystallization degree in an embodiment of the present application;

[0035] Figure 4 A diagram showing a dolomite crystallization degree identification device in an embodiment of the present application.

[0036] In the drawings, the same components are designated by the same reference numerals, and the drawings are not drawn to scale. DETAILED DESCRIPTION

[0037] In order to enable those skilled in the art to better understand the present application and how the present application applies technical means to solve technical problems and achieve corresponding technical effects, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. The embodiments of the present application and each feature in the embodiments can be combined with each other without conflict, and the formed technical solutions are all within the protection scope of the present application. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor should be within the protection scope of the present application.

[0038] It should be noted that the terms "first", "second", and the like in the specification and claims of the present application and the above-described drawings are used to distinguish similar objects, and do not necessarily indicate a specific order or a chronological sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product, or device that includes a series of steps or units does not necessarily have to be limited to only those steps or units clearly listed, but can include other steps or units that are not clearly listed or inherent to these processes, methods, products, or devices.

[0039] It should be noted that the steps shown in the flowchart of the drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described herein can be executed in an order different from that shown herein.

[0040] Carbonate reservoir is an important oil and gas reservoir in the world today, and dolomite is more likely to develop high-quality reservoir than limestone, so the dolomitization degree determines the quality of dolomite reservoir to some extent. The crystallization degree of dolomite generally represents the dolomitization degree, so studying the crystallization degree of dolomite is a basic and important part in the process of oil and gas exploration and development.

[0041] However, the existing judgment method of dolomite crystallization degree basically depends on geochemical test analysis, such as dolomite X-diffraction order experiment, and the method of indirectly judging dolomitization degree and dolomite crystallization degree by testing Mg and Ca element content of mineral, including X-diffraction energy spectrum analysis and major element analysis.

[0042] The existing technology has the following technical problems:

[0043] (1) high cost; (2) long cycle; (3) part of the experiment has higher requirements for the precision of the laboratory, and it is difficult to quickly and massively test the crystallization degree. At the same time, the sample may be contaminated by other minerals. In carbonate rock stratum, whether it is early terrigenous clastic or later diagenesis, there may be other substances containing Mg and Ca elements in the sample, which may greatly reduce the accuracy of the experiment. Of course, the in-situ testing method rising in recent years can solve this problem, and the testing accuracy can reach tens of microns, which can meet the element analysis of most samples, but it further increases the experimental cost and the requirement for the precision of the laboratory, so it is difficult to realize low-cost mass sample testing at present.

[0044] The technical field urgently needs a scheme to judge the crystallization degree of dolomite in a low-cost and large-batch manner.

[0045] Example One

[0046] Figure 1 A dolomite crystallization degree identification method for an embodiment of the application is shown in FIG. 1. Figure 1 As shown in FIG. 1, the embodiment provides a dolomite crystallization degree identification method, which comprises the following steps:

[0047] S10, obtaining preset quantitative features and preset qualitative features of dolomite in a target reservoir;

[0048] S20, identifying the crystallization degree of dolomite according to a preset crystallization degree identification template, and the preset quantitative features and the preset qualitative features;

[0049] The preset quantitative features include the number of straight edges, the length of the longest edge, and the crystallization degree parameter, the preset qualitative features include the distribution of straight edges, and the preset crystallization degree identification template includes preset quantitative features and preset qualitative features corresponding to different crystallization degrees.

[0050] Because the precursor minerals (aragonite, calcite) in the process of dolomitization, the crystal will gradually grow to the complete rhombohedron, which shows as rhombus with straight edges under microscope. Therefore, the crystallization degree of the dolomite can be determined by observing the number of straight edges and the length of the longest edge of the mineral in the ordinary (cast) thin section, and then the dolomitization degree of the sample can be analyzed, and finally the prediction of high-quality reservoirs can be realized.

[0051] The method provided by the embodiment can quickly and low-costly identify the crystallization degree of dolomite in large batches, and then analyze the dolomitization degree of the sample, and finally realize the prediction of high-quality reservoirs.

[0052] Example Two

[0053] On the basis of the above-mentioned embodiments, the embodiment describes the acquisition of the preset crystallization degree identification template.

[0054] In some embodiments, the dolomite of the target reservoir includes a rock thin section obtained by thin section grinding on a rock sample including dolomite obtained by coring.

[0055] In some embodiments, the preset quantitative characteristics of the dolomite of the target reservoir include:

[0056] S11, classifying the dolomite crystals according to the mineralogical characteristics of the dolomite;

[0057] S12, obtaining the number of straight edges and the length of the longest edge of each type of dolomite crystal under different fields of view of a microscope;

[0058] S13, calculating the average number of straight edges and the average length of the longest edge of different types of dolomite crystals;

[0059] S14, obtaining the crystallization degree parameter of different types of dolomite crystals based on the average number of straight edges and the average length of the longest edge.

[0060] In some embodiments, the obtaining of the crystallization degree parameter of different types of dolomite crystals based on the average number of straight edges and the average length of the longest edge includes:

[0061] calculating the ratio of the average length of the longest edge to the average number of straight edges to obtain the crystallization degree parameter of different types of dolomite crystals.

[0062] In one implementation, the method includes the following steps:

[0063] Step (1), the different crystallization degrees of dolomite in the rock thin section sample are classified according to the mineralogical characteristics of dolomite, such as the crystal self-forming degree and the crystal size.

[0064] Step (2), the same type of dolomite in the same rock thin section sample has multiple mineral crystals with different sizes, and the linear edges of different types of dolomite are described under the microscope, wherein a plurality of crystals in multiple fields of view are described for each sample, and the number n of linear edges of, for example, 10 crystals is counted.

[0065] Step (3), the longest edges of different types of dolomite under different fields of view are described under the microscope, and the longest edge length a of the longest edge of each crystal with the measured number of linear edges is measured. FIG. 2 is a schematic diagram of the identification of the quantitative characteristics of different dolomite minerals in the embodiment. As shown in the figure, the linear edges and the longest edges of the dolomite minerals in the dolomite rock sample with different crystallization degrees are identified under the microscope in the embodiment. Figures 2(a) to 2(d)

[0066] Step (4), the average number of linear edges of different types of dolomite in each sample is calculated as follows: and the average longest edge length a of different types of dolomite in each sample is calculated as follows:

[0067] Step (5), the crystallization degree parameter CD of dolomite is represented by the following expression:

[0068]

[0069] The crystallization degree parameter CD of different types of dolomite in the sample is calculated by using the above expression, wherein the higher the CD value, the higher the crystallization degree of the dolomite in the sample.

[0070] Step (6), the dolomite parameter CD of multiple rock thin section samples is calculated, and the X-ray diffraction dolomite order degree data of the rock thin section sample is used for comparison. The results show that there is a strong correlation between the two, indicating that the parameter CD indeed has the meaning of representing the crystallization degree of dolomite.

[0071] ​Dolomite as a common carbonate mineral, formula is CaMg(CO3)2, belongs to the trigonal system, three complete cleavage can be seen, often rhombohedron. As precursor mineral aragonite or calcite (CaCO3) in the process of dolomitization, under the microscope mineral generally tend to edge flat rhombus, the ratio of calcium magnesium ions in the mineral tends to 1:1, magnesium ions into the lattice replacement of calcium ions position and metasomatism, ultimately as the calcium magnesium ion layer uniform distribution. In the process of dolomitization of calcite (aragonite) - calcite, the intermediate crystal state relative to stoichiometric dolomite is disordered, so the dolomite X-ray diffraction order degree can be used to reflect the degree of dolomitization.

[0072] Figure 3 The figure for verifying the crystallization degree in the embodiment of the application. As shown in Figure 3 , different sample identifies the characteristic data of multiple crystals, and the X-ray diffraction dolomite order degree data is used for correction, and the result shows that there is strong correlation, and finally the effect of dolomite crystallization degree characterization is good.

[0073] Step (7), establishing the identification template of the dolomite crystallization degree under the microscope. The petrographic characteristics of dolomite described in steps (2), (3), (4) and (5) are as follows:

[0074] The number of straight edges n <9, CD >3.5, there is no concave edge, and the dolomite crystallization degree is good, which is regarded as the first grade;

[0075] The number of straight edges n >9, the longest edge length a >30 μm, CD is between 1.6 and 3.5, there are a small amount of concave edges and part of curved edges, and the dolomite crystallization degree is general, which is regarded as the second grade;

[0076] The number of straight edges n >9, the longest edge length a <30 μm, CD <1.6, there are a large number of concave edges, and only a small amount of straight edges, and the dolomite crystallization degree is poor, which is regarded as the third grade.

[0077] Based on the above described petrographic characteristics of dolomite, the dolomite crystallization degree identification template shown in Table 1 is established.

[0078] Table 1

[0079]

[0080] The embodiment can be used as a method for preliminarily identifying the dolomite crystallization degree, and is particularly suitable for a small amount of thin section data, a small amount of experimental samples, and samples that cannot be subjected to a large number of experiments or geochemical experiments.

[0081] Dolomite reservoir research has always been the top priority of carbonate reservoir research in the oil and gas industry in China and the world. Studies have shown that the higher the dolomitization degree of the formation, the higher the possibility of developing high-quality reservoirs and forming large-scale oil and gas reservoirs. This is inevitably linked to the nature of dolomite and calcite. Dolomite is harder than calcite. Whether it is dissolution or faulting, dolomite as the framework is more likely to preserve primary and secondary reservoir space. However, previous methods of judging dolomitization degree are demanding and expensive. Therefore, this example uses rock thin sections, which are the most easily obtained in geological research and oil and gas exploration, as samples for analysis to qualitatively and semi-quantitatively determine the crystallization degree of dolomite, thereby reflecting the dolomitization degree of the sample, and ultimately providing a theoretical basis for predicting the distribution of high-quality reservoirs.

[0082] The present example is a method for determining the crystallization degree of dolomite, which has a wide range of applications and can be used as an important means for identifying the crystallization degree of dolomite in dolomite with limited sample quantity, or as a petrographic auxiliary method for geochemical experiments. First, select the common dolomite mineral crystals in the thin section, and use a microscope to identify the number of straight edges and the average length of the longest edge. Generally, identify about 10 minerals per sample, calculate the average number of straight edges and the average length of the longest edge Calculate the crystallization degree of dolomite The CD value can represent the crystallization degree of dolomite in the dolomite sample.

[0083] Example Three

[0084] On the basis of the above examples, the present example combines Table 1 to explain the process of identifying the crystallization degree of dolomite according to the preset crystallization degree identification template and the preset quantitative characteristics and preset qualitative characteristics. In this example, the crystallization degree is divided into a first grade, a second grade, and a third grade, corresponding to good, general, and poor in Table 1, respectively.

[0085] In some embodiments, the crystallization degree of dolomite is identified according to the preset crystallization degree identification template and the preset quantitative characteristics and preset qualitative characteristics, including:

[0086] S21, if the number of straight edges is less than the number of straight edge thresholds, the crystallization degree parameter is greater than the first crystallization degree parameter threshold, and the straight edge ratio is greater than the first straight edge ratio threshold, the crystallization degree is the first grade.

[0087] In some embodiments, the crystallization degree of dolomite is identified according to the preset crystallization degree identification template and the preset quantitative characteristics and preset qualitative characteristics, including:

[0088] S22, if the number of straight edges is greater than the number of straight edge threshold, the length of the longest edge is greater than the length of the longest edge threshold, the crystallinity parameter is less than or equal to the first crystallinity parameter threshold and greater than or equal to the second crystallinity parameter threshold, and the straight edge ratio is less than or equal to the first straight edge ratio threshold and greater than the second straight edge ratio threshold, the crystallinity degree is the second grade.

[0089] In some embodiments, according to the preset crystallinity identification template, the preset quantitative feature and the preset qualitative feature, the crystallinity degree of dolomite is identified, including:

[0090] S23, if the number of straight edges is greater than the number of straight edge threshold, the length of the longest edge is less than the length of the longest edge threshold, the crystallinity parameter is less than the second crystallinity parameter threshold, and the straight edge ratio is less than the second straight edge ratio threshold, the crystallinity degree is the third grade.

[0091] Taking Table 1 as an example, the number of straight edge threshold is 9, the first crystallinity parameter threshold is 3.5, the length of the longest edge threshold is 30, the second crystallinity parameter threshold is 1.6, and the first straight edge ratio threshold and the second straight edge ratio threshold can be set according to actual conditions to determine whether the straight edge ratio is small (for example, a small part of all edges are straight edges), moderate or large (for example, most of all edges are straight edges). The proportion threshold of the number of concave edges can also be set according to actual conditions. It can be understood that the specific values of the thresholds in the present embodiment are not limited.

[0092] In the present embodiment, the crystallinity degree of dolomite is identified based on the crystallinity identification template and the preset quantitative feature and the preset qualitative feature established in the above embodiment, which can quickly and low-costly identify the crystallinity degree of rock thin sections including dolomite crystals in large batches.

[0093] The technology proposed in the present embodiment can be applied to ancient dolomite reservoir areas, and has a wide range of applications: it can be used as an important means for identifying the crystallinity degree of dolomite based on a limited number of dolomite samples, or as a petrographic auxiliary method for geochemical experiments to analyze the dolomitization degree of a large number of samples with developed dolomite in the reservoir.

[0094] Example Four

[0095] Figure 4 A dolomite crystallinity identification method according to an embodiment of the present application is shown in FIG. 1. Figure 4 As shown in the above embodiment, the present embodiment provides a dolomite crystallinity identification device, which includes:

[0096] The parameter acquisition module 100 is configured to acquire the preset quantitative feature and the preset qualitative feature of the dolomite in the target reservoir.

[0097] The crystallization degree judgment module 200 is configured to identify the crystallization degree of the dolomite according to a preset crystallization degree identification template, preset quantitative features and preset qualitative features.

[0098] The preset quantitative features include the number of straight edges, the longest edge length and the crystallization degree parameter, the preset qualitative features include the distribution of the straight edges, and the preset crystallization degree identification template includes preset quantitative features and preset qualitative features corresponding to different crystallization degrees.

[0099] In some embodiments, the device also implements the following scheme:

[0100] S10, obtaining preset quantitative features and preset qualitative features of dolomite in a target reservoir;

[0101] S20, identifying the crystallization degree of the dolomite according to a preset crystallization degree identification template, preset quantitative features and preset qualitative features;

[0102] The preset quantitative features include the number of straight edges, the longest edge length and the crystallization degree parameter, the preset qualitative features include the distribution of the straight edges, and the preset crystallization degree identification template includes preset quantitative features and preset qualitative features corresponding to different crystallization degrees.

[0103] In some embodiments, the dolomite in the target reservoir includes a rock slice obtained by thin sectioning a rock sample including dolomite obtained by coring.

[0104] In some embodiments, the preset quantitative features of the dolomite in the target reservoir include:

[0105] S11, classifying dolomite crystals according to mineralogical features of the dolomite;

[0106] S12, obtaining the number of straight edges and the longest edge length of each type of dolomite crystal under different fields of view of a microscope;

[0107] S13, calculating the average number of straight edges and the average longest edge length of different types of dolomite crystals;

[0108] S14, calculating the crystallization degree parameter of different types of dolomite crystals based on the average number of straight edges and the average longest edge length.

[0109] In some embodiments, the calculation of the crystallization degree parameter of different types of dolomite crystals based on the average number of straight edges and the average longest edge length includes:

[0110] calculating the ratio of the average longest edge length to the average number of straight edges to obtain the crystallization degree parameter of different types of dolomite crystals.

[0111] In some embodiments, the crystallinity degree of dolomite is identified according to a preset crystallinity degree identification template, and preset quantitative features and preset qualitative features, and the method comprises:

[0112] S21, if the number of straight edges is less than the number of straight edge threshold, the crystallinity degree parameter is greater than the first crystallinity degree parameter threshold, and the straight edge proportion is greater than the first straight edge proportion threshold, the crystallinity degree is the first level.

[0113] In some embodiments, the crystallinity degree of dolomite is identified according to a preset crystallinity degree identification template, and preset quantitative features and preset qualitative features, and the method comprises:

[0114] S22, if the number of straight edges is greater than the number of straight edge threshold, the longest edge length is greater than the longest edge length threshold, the crystallinity degree parameter is less than or equal to the first crystallinity degree parameter threshold and greater than or equal to the second crystallinity degree parameter threshold, and the straight edge proportion is less than or equal to the first straight edge proportion threshold and greater than the second straight edge proportion threshold, the crystallinity degree is the second level.

[0115] In some embodiments, the crystallinity degree of dolomite is identified according to a preset crystallinity degree identification template, and preset quantitative features and preset qualitative features, and the method comprises:

[0116] S23, if the number of straight edges is greater than the number of straight edge threshold, the longest edge length is less than the longest edge length threshold, the crystallinity degree parameter is less than the second crystallinity degree parameter threshold, and the straight edge proportion is less than the second straight edge proportion threshold, the crystallinity degree is the third level.

[0117] Example Five

[0118] On the basis of the above-mentioned embodiments, the present embodiment provides a computer readable storage medium having a computer program stored thereon, and the computer program is executed by a processor to implement the method of the above-mentioned embodiments.

[0119] The storage medium can be a flash memory, a hard disk, a multimedia card, a card-type memory (such as an SD or DX memory, etc.), a random access memory (RAM), a static random access memory (SRAM), a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), a programmable read-only memory (PROM), a magnetic memory, a magnetic disk, an optical disk, a server, an App application market, etc.

[0120] In some embodiments, the method implemented by the present embodiment comprises:

[0121] S10, obtaining preset quantitative features and preset qualitative features of dolomite of a target reservoir;

[0122] S20, identifying the crystallization degree of the dolomite according to the preset crystallization degree identification template, and the preset quantitative feature and the preset qualitative feature.

[0123] The preset quantitative feature includes the number of straight edges, the longest edge length, and the crystallization degree parameter, the preset qualitative feature includes the distribution of the straight edges, and the preset crystallization degree identification template includes the preset quantitative feature and the preset qualitative feature corresponding to different crystallization degrees.

[0124] In some embodiments, the dolomite of the target reservoir includes obtaining a rock thin section by thin section grinding on a rock sample including the dolomite obtained by coring.

[0125] In some embodiments, the preset quantitative feature of the dolomite of the target reservoir includes:

[0126] S11, classifying the dolomite crystals according to the mineralogical features of the dolomite;

[0127] S12, obtaining the number of straight edges and the longest edge length of each type of dolomite crystal under different fields of view of a microscope;

[0128] S13, calculating the average number of straight edges and the average longest edge length of different types of dolomite crystals;

[0129] S14, calculating the crystallization degree parameter of different types of dolomite crystals based on the average number of straight edges and the average longest edge length.

[0130] In some embodiments, the calculation of the crystallization degree parameter of different types of dolomite crystals based on the average number of straight edges and the average longest edge length includes:

[0131] calculating the ratio of the average longest edge length to the average number of straight edges to obtain the crystallization degree parameter of different types of dolomite crystals.

[0132] In some embodiments, the identification of the crystallization degree of the dolomite according to the preset crystallization degree identification template, and the preset quantitative feature and the preset qualitative feature includes:

[0133] S21, if the number of straight edges is less than the number of straight edges threshold, the crystallization degree parameter is greater than the first crystallization degree parameter threshold, and the proportion of straight edges is greater than the first proportion of straight edges threshold, the crystallization degree is the first grade.

[0134] In some embodiments, the identification of the crystallization degree of the dolomite according to the preset crystallization degree identification template, and the preset quantitative feature and the preset qualitative feature includes:

[0135] S22, if the number of straight edges is greater than the number of straight edge threshold, the length of the longest edge is greater than the length of the longest edge threshold, the crystallinity degree parameter is less than or equal to the first crystallinity degree parameter threshold and greater than or equal to the second crystallinity degree parameter threshold, and the straight edge proportion is less than or equal to the first straight edge proportion threshold and greater than the second straight edge proportion threshold, the crystallinity degree is the second grade.

[0136] In some embodiments, according to the preset crystallinity identification template, the preset quantitative feature and the preset qualitative feature, the crystallinity degree of the dolomite is identified, including:

[0137] S23, if the number of straight edges is greater than the number of straight edge threshold, the length of the longest edge is less than the length of the longest edge threshold, the crystallinity degree parameter is less than the second crystallinity degree parameter threshold, and the straight edge proportion is less than the second straight edge proportion threshold, the crystallinity degree is the third grade.

[0138] Example Six

[0139] On the basis of the above-mentioned embodiments, the present embodiment provides an electronic device, including a processor and a memory, the memory has a computer program stored thereon, and the processor implements the method of the above-mentioned embodiments when executing the computer program.

[0140] The processor can be an Application Specific Integrated Circuit (ASIC), a Digital Signal Processor (DSP), a Digital Signal Processing Device (DSPD), a Programmable Logic Device (PLD), a Field Programmable Gate Array (FPGA), a controller, a microcontroller, a microprocessor or other electronic elements, which is used to execute the method in the above-mentioned embodiments.

[0141] The memory can be implemented by any type of volatile or nonvolatile storage devices or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk or optical disk.

[0142] In some embodiments, the method implemented by the present embodiment comprises:

[0143] S10, obtaining preset quantitative features and preset qualitative features of dolomite in a target reservoir;

[0144] S20, identifying the crystallization degree of dolomite according to a preset crystallization degree identification template, the preset quantitative features and the preset qualitative features;

[0145] The preset quantitative features include the number of straight edges, the length of the longest edge and the crystallization degree parameter, the preset qualitative features include the distribution of straight edges, and the preset crystallization degree identification template includes preset quantitative features and preset qualitative features corresponding to different crystallization degrees.

[0146] In some embodiments, the dolomite in the target reservoir includes rock slices obtained by thin sectioning a rock sample including dolomite obtained by coring.

[0147] In some embodiments, obtaining the preset quantitative features of dolomite in the target reservoir comprises:

[0148] S11, classifying dolomite crystals according to the mineralogical features of dolomite;

[0149] S12, obtaining the number of straight edges and the length of the longest edge of each type of dolomite crystal under different fields of view of a microscope;

[0150] S13, calculating the average number of straight edges and the average length of the longest edge of different types of dolomite crystals;

[0151] S14, obtaining the crystallization degree parameter of different types of dolomite crystals based on the average number of straight edges and the average length of the longest edge.

[0152] In some embodiments, the crystallization degree parameter of different types of dolomite crystals is calculated based on the average value of the number of straight edges and the average value of the length of the longest edge, including:

[0153] The ratio of the average value of the length of the longest edge to the average value of the number of straight edges is calculated to obtain the crystallization degree parameter of different types of dolomite crystals.

[0154] In some embodiments, the crystallization degree of dolomite is identified according to a preset crystallization degree identification template, a preset quantitative feature and a preset qualitative feature, including:

[0155] S21, if the number of straight edges is less than the number of straight edge threshold, the crystallization degree parameter is greater than the first crystallization degree parameter threshold, and the proportion of straight edges is greater than the first proportion of straight edge threshold, the crystallization degree is the first grade.

[0156] In some embodiments, the crystallization degree of dolomite is identified according to a preset crystallization degree identification template, a preset quantitative feature and a preset qualitative feature, including:

[0157] S22, if the number of straight edges is greater than the number of straight edge threshold, the length of the longest edge is greater than the length of the longest edge threshold, the crystallization degree parameter is less than or equal to the first crystallization degree parameter threshold and greater than or equal to the second crystallization degree parameter threshold, and the proportion of straight edges is less than or equal to the first proportion of straight edge threshold and greater than the second proportion of straight edge threshold, the crystallization degree is the second grade.

[0158] In some embodiments, the crystallization degree of dolomite is identified according to a preset crystallization degree identification template, a preset quantitative feature and a preset qualitative feature, including:

[0159] S23, if the number of straight edges is greater than the number of straight edge threshold, the length of the longest edge is less than the length of the longest edge threshold, the crystallization degree parameter is less than the second crystallization degree parameter threshold, and the proportion of straight edges is less than the second proportion of straight edge threshold, the crystallization degree is the third grade.

[0160] Example Seven

[0161] On the basis of the above-mentioned embodiments, an application example is provided herein.

[0162] The above-mentioned embodiments of the present application have been well applied in the isopachous dolomite reservoir of Lower Palaeozoic in Ordos Basin. The above-mentioned embodiments of the present application can quickly and massively identify the crystallization degree of dolomite, accurately analyze the dolomitization degree of reservoir, and help to find the favorable reservoir development area. The above-mentioned embodiments of the present application have been well applied in Daniudi and Fuxian blocks in Ordos Basin.

[0163] The Ordovician thick dolomite reservoir in Sichuan Oilfield is difficult to analyze the dolomitization degree of the carbonate reservoir in the area in a large amount and systematically because the number of cores taken in some drilling is limited, and the reservoir prediction and subsequent oil and gas exploration in the area with a small number of samples are restricted.

[0164] Therefore, the dolomite crystallization degree identification template is used in the research process, a small amount of coring is used for ordinary (cast body) thin section grinding, a large amount of rapid identification of the petrographic characteristics of dolomite crystals is carried out under a microscope, the dolomite crystallization degree in the area is accurately identified by using the final point result, the dolomitization degree of different regions is analyzed, and finally the development region and horizon of high-quality dolomite are determined, thereby guiding the subsequent exploration and development.

[0165] In the embodiments provided in the present application, it should be understood that the disclosed devices and methods can also be implemented by other manners. The device embodiments described above are only schematic, for example, the flowcharts and block diagrams in the drawings show the possible implementation architectures, functions and operations of the devices, methods and computer program products according to the embodiments of the present application. In this regard, each block in the flowcharts or block diagrams can represent a module, a program segment or a part of code, which contains one or more executable instructions for implementing the specified logic function. It should also be noted that, in some alternative implementation manners, the functions noted in the blocks can also occur in different orders from those noted in the drawings. For example, two consecutive blocks can actually be executed substantially in parallel, and sometimes they can be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and the combination of blocks in the block diagrams and / or flowcharts, can be implemented by a special hardware-based system for executing the specified functions or actions, or can be implemented by a combination of special hardware and computer instructions.

[0166] It should be noted that in the present application, the terms "comprising", "including" or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or other elements inherent to such a process, method, article or device. Without more limitations, the element limited by the statement "including a" does not exclude the presence of another identical element in the process, method, article or device including the element.

[0167] Although the embodiments of the present application have been disclosed with reference to the above embodiments, the above embodiments are merely used to facilitate understanding of the present application and are not used to limit the present application. Any person skilled in the art, without departing from the spirit and scope of the present application, can make any modification and change in the form and details of the embodiments, but the patent protection scope of the present application should be subject to the scope defined by the appended claims.

Claims

1. A method for identifying the degree of crystallinity of dolomite, characterized by, The method comprises: S10, obtaining preset quantitative characteristics and preset qualitative characteristics of dolomite in a target reservoir; S20, identifying a crystallization degree of dolomite according to a preset crystallization degree identification template, the preset quantitative characteristics and the preset qualitative characteristics; The preset quantitative characteristics comprise a number of straight edges, a longest edge length and a crystallization degree parameter, the preset qualitative characteristics comprise a distribution of straight edges, and the preset crystallization degree identification template comprises preset quantitative characteristics and preset qualitative characteristics corresponding to different crystallization degrees; The preset quantitative characteristics of dolomite in the target reservoir are obtained by: S11, classifying dolomite crystals according to mineralogical characteristics of the dolomite; S12, obtaining a number of straight edges and a longest edge length of each type of dolomite crystal under different fields of view of a microscope; S13, calculating an average value of the number of straight edges and an average value of the longest edge length of different types of dolomite crystals; S14, calculating a ratio of the average value of the longest edge length to the average value of the number of straight edges to obtain a crystallization degree parameter of different types of dolomite crystals.

2. The method of claim 1, wherein, The dolomite in the target reservoir comprises rock slices obtained by grinding rock samples containing dolomite obtained by coring.

3. The method of claim 1, wherein, The crystallization degree of dolomite is identified according to the preset crystallization degree identification template, the preset quantitative characteristics and the preset qualitative characteristics, comprising: S21, if the number of straight edges is less than a number of straight edges threshold value, the crystallization degree parameter is greater than a first crystallization degree parameter threshold value, and the proportion of straight edges is greater than a first proportion of straight edges threshold value, the crystallization degree is a first grade.

4. The method of claim 1, wherein, The crystallization degree of dolomite is identified according to the preset crystallization degree identification template, the preset quantitative characteristics and the preset qualitative characteristics, comprising: S22, if the number of straight edges is greater than a number of straight edges threshold value, the longest edge length is greater than a longest edge length threshold value, the crystallization degree parameter is less than or equal to a first crystallization degree parameter threshold value and greater than or equal to a second crystallization degree parameter threshold value, and the proportion of straight edges is less than or equal to a first proportion of straight edges threshold value and greater than a second proportion of straight edges threshold value, the crystallization degree is a second grade.

5. The method of claim 1, wherein, The crystallization degree of dolomite is identified according to the preset crystallization degree identification template, the preset quantitative characteristics and the preset qualitative characteristics, comprising: S23, if the number of straight edges is greater than a number of straight edges threshold value, the longest edge length is less than a longest edge length threshold value, the crystallization degree parameter is less than a second crystallization degree parameter threshold value, and the proportion of straight edges is less than a second proportion of straight edges threshold value, the crystallization degree is a third grade.

6. A dolomite crystallinity identification device, characterized by, Comprise: A parameter acquisition module 100 is configured to obtain preset quantitative characteristics and preset qualitative characteristics of dolomite in a target reservoir; A crystallization degree judgment module 200 is configured to identify a crystallization degree of dolomite according to a preset crystallization degree identification template, the preset quantitative characteristics and the preset qualitative characteristics; The preset quantitative characteristics comprise a number of straight edges, a longest edge length and a crystallization degree parameter, the preset qualitative characteristics comprise a distribution of straight edges, and the preset crystallization degree identification template comprises preset quantitative characteristics and preset qualitative characteristics corresponding to different crystallization degrees; The preset quantitative characteristics of dolomite in the target reservoir are obtained by: S11, classifying dolomite crystals according to mineralogical characteristics of dolomite; S12, obtaining the number of straight edges and the length of the longest edge of each type of dolomite crystal under different fields of view of a microscope; S13, calculating the average number of straight edges and the average length of the longest edge of different types of dolomite crystals; S14, calculating the ratio of the average length of the longest edge to the average number of straight edges to obtain a crystallization degree parameter of different types of dolomite crystals.

7. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program, and the computer program is executed by one or more processors to implement the dolomite crystallization degree identification method in any one of claims 1 to 5.

8. An electronic device, comprising: The computer readable storage medium stores a computer program, and the computer program is executed by one or more processors to implement the dolomite crystallization degree identification method in any one of claims 1 to 5.

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