A method and device for identifying the laminar structure of fine-grained sedimentary rocks

Abstract

The embodiment of this specification provides a method and device for identifying the lamination structure of fine-grained sedimentary rocks. The method first realizes the identification and division of the lamination combination characteristics of fine-grained sedimentary rocks based on core data and thin section data, then establishes lamination structure charts of different scales based on conventional logging data and imaging logging images, then realizes the extraction of millimeter-scale lamination structure characteristics based on the imaging logging slicing technology, and finally realizes the identification and evaluation of the single-well multi-scale lamination structure characteristics of fine-grained sedimentary rocks through core data, thin section data, conventional logging data, imaging logging images and sliced images, so as to improve the accuracy of the identification of the lamination structure of fine-grained sedimentary rocks.

Description

Technical Field

[0001] The embodiments of this specification relate to the technical field of oil and gas exploration, and particularly to a method and device for identifying the lamination structure of fine-grained sedimentary rocks. Background Art

[0002] With the continuous deepening of the exploration and development of tight oil and gas and shale oil and gas, fine-grained sedimentary rocks are becoming the focus and hot spot of sedimentology research because they contain rich oil and gas resources. At present, the research degree of fine-grained sedimentary rocks is relatively low, and it is urgent to carry out typical dissection and industrial application research to promote the development of the discipline and better guide oil and gas exploration and development.

[0003] Since for fine-grained sedimentary rocks that serve as tight oil and gas, shale oil and gas reservoirs and source rocks, the development of laminations determines the enrichment and high production of tight oil and gas and shale oil and gas, therefore, the identification of the lamination structure of fine-grained sedimentary rocks has important guiding significance for oil and gas exploration and development. At present, due to the lack of core and thin-section data, the lamination structure of fine-grained sedimentary rocks is usually identified by means of conventional logging.

[0004] However, due to its longitudinal resolution limitation, conventional logging is difficult to pick up the characteristics of lamination structures at the micron to centimeter scale, and it is thus very difficult to finely identify and evaluate multi-scale lamination structures. Summary of the Invention

[0005] The purpose of the embodiments of this specification is to provide a method and device for identifying the lamination structure of fine-grained sedimentary rocks, so as to improve the accuracy of identifying the lamination structure of fine-grained sedimentary rocks and achieve the fine identification and evaluation of multi-scale lamination structures.

[0006] To solve the above problems, a method for identifying the lamination structure of fine-grained sedimentary rocks is established. The method includes: dividing the lamination structure types of fine-grained sedimentary rocks according to the lamination development situation of fine-grained sedimentary rocks; wherein, the lamination development situation of the fine-grained sedimentary rocks is obtained based on the core data and thin-section data of the target well section; making the fine-grained sedimentary rocks of different lamination structure types correspond to the imaging logging images of the target well section, and determining the response characteristics of the fine-grained sedimentary rocks of different lamination structure types on the imaging logging images; and identifying the longitudinal lamination structure types of the target well section according to the response characteristics of the fine-grained sedimentary rocks of different lamination structure types on the imaging logging images.

[0007] To solve the above problems, an apparatus for identifying the lamination structure of fine-grained sedimentary rocks is further provided in an embodiment of this specification. The apparatus includes: a division module configured to divide the lamination structure types of fine-grained sedimentary rocks according to the lamination development of fine-grained sedimentary rocks, where the lamination development of the fine-grained sedimentary rocks is obtained based on the core data and thin-section data of a target well section; a determination module configured to match fine-grained sedimentary rocks of different lamination structure types with the imaging logging images of the target well section to determine the response characteristics of fine-grained sedimentary rocks of different lamination structure types on the imaging logging images; and an identification module configured to identify the longitudinal lamination structure type of the target well section according to the response characteristics of fine-grained sedimentary rocks of different lamination structure types on the imaging logging images.

[0008] As can be seen from the technical solutions provided in the embodiments of this specification above, in the embodiments of this specification, the lamination structure types of fine-grained sedimentary rocks can be divided according to the lamination development of fine-grained sedimentary rocks, where the lamination development of the fine-grained sedimentary rocks is obtained based on the core data and thin-section data of a target well section; match fine-grained sedimentary rocks of different lamination structure types with the imaging logging images of the target well section to determine the response characteristics of fine-grained sedimentary rocks of different lamination structure types on the imaging logging images; and identify the longitudinal lamination structure type of the target well section according to the response characteristics of fine-grained sedimentary rocks of different lamination structure types on the imaging logging images, so as to improve the accuracy of identifying the lamination structure of fine-grained sedimentary rocks and achieve fine identification and evaluation of multi-scale lamination structure types. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] To more clearly illustrate the technical solutions in the embodiments of this specification or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings described below are only some embodiments recorded in this specification. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0010] Figure 1 It is a flowchart of a method for identifying the lamination structure of fine-grained sedimentary rocks in an embodiment of this specification;

[0011] Figure 2a It is a schematic diagram of a core with a laminated lamination structure type in an embodiment of this specification;

[0012] Figure 2b It is a schematic diagram of a core with a layered lamination structure type in an embodiment of this specification;

[0013] Figure 2c It is a schematic diagram of a core with a massive lamination structure type in an embodiment of this specification;

[0014] Figure 3This is a plate of different types of laminar structures under conventional logging - imaging logging - core - thin section in the embodiments of this specification;

[0015] Figure 4 This is a schematic diagram of the response characteristics of different - scale laminar types on the slice image in the embodiments of this specification;

[0016] Figure 5 This is a plate of different types of laminar structures under high - resolution imaging logging slice images - core - thin section in the embodiments of this specification;

[0017] Figure 6 This is a schematic diagram of slicing processing of imaging logging images in the embodiments of this specification;

[0018] Figure 7 This is a schematic diagram for identifying and dividing the single - well longitudinal multi - scale laminar structure by conventional logging + imaging logging + slicing + image core + thin section in the embodiments of this specification;

[0019] Figure 8 This is the result of continuous identification and division of the longitudinal laminations in Well A in the embodiments of this specification;

[0020] Figure 9 This is a schematic diagram of the functional structure of a device for identifying the laminar structure of fine - grained sedimentary rocks in the embodiments of this specification. Detailed implementation manners

[0021] Next, the technical solutions in the embodiments of this specification will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of this specification. Obviously, the described embodiments are only a part of the embodiments of this specification, rather than all of the embodiments. Based on the embodiments in this specification, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of this specification.

[0022] Fine - grained sedimentary rocks refer to sedimentary rocks with the content of particles smaller than 0.0625mm being greater than 50%, including siltstone, claystone, carbonate rocks (limestone, dolomite) and their transitional rocks, etc. They are widely distributed, accounting for about two - thirds of the entire sedimentary rocks; compared with other sedimentary rocks, the sedimentation and diagenesis of fine - grained sedimentary rocks are relatively complex, and the fine - grained sedimentary rock reservoirs are characterized by being dense, having low porosity and low permeability, and having a small scale of reservoir spaces.

[0023] Since for fine-grained sedimentary rocks that serve as tight oil and gas, shale oil and gas reservoirs and source rocks, the development of laminations determines the enrichment and high production of tight oil and gas, shale oil and gas, therefore, the identification of the lamination structure of fine-grained sedimentary rocks is of great guiding significance for oil and gas exploration and development. Currently, due to the scarcity of core and thin-section data, the lamination structure of fine-grained sedimentary rocks is usually identified by means of conventional logging. However, due to its longitudinal resolution limitation, conventional logging is difficult to pick up the characteristics of lamination structures at the micron to centimeter scale, making it difficult to finely identify and evaluate multi-scale lamination structures.

[0024] Considering that if the identification and division of the lamination combination characteristics of fine-grained sedimentary rocks are achieved based on core data and thin-section data, and then different-scale (centimeter-decimeter-meter scale) lamination structure charts are established based on conventional logging and imaging logging; the characteristics of millimeter-scale lamination structures are extracted based on imaging logging slicing technology; and finally, the multi-scale lamination structure characteristics of fine-grained sedimentary rocks in a single well are picked up and characterized through cores, thin sections, conventional, imaging logging, and sliced images, so as to conduct logging identification and single-well lamination structure evaluation of the multi-scale lamination structure of fine-grained sedimentary rocks, it is expected to solve the problem in the prior art that it is difficult to pick up the characteristics of lamination structures at the micron scale, thus making it difficult to finely identify and evaluate multi-scale lamination structures, improve the accuracy of the identification of the lamination structure of fine-grained sedimentary rocks, and achieve fine identification and evaluation of multi-scale lamination structures longitudinally in a single well.

[0025] Please refer to Figure 1 This description provides an embodiment of a method for identifying the lamination structure of fine-grained sedimentary rocks. In the embodiment of this specification, the main body executing the method for identifying the lamination structure of fine-grained sedimentary rocks can be an electronic device with logical operation functions, and the electronic device can be a server. The server can be an electronic device with a certain computing and processing capacity. It can have a network communication unit, a processor, a memory, etc. Of course, the server is not limited to the above-mentioned electronic device with a certain entity, and it can also be software running on the above-mentioned electronic device. The server can also be a distributed server, which can be a system in which multiple processors, memories, network communication modules, etc. operate in coordination. Or, the server can also be a server cluster formed by several servers. The method can include the following steps.

[0026] S110: Divide the lamination structure types of fine-grained sedimentary rocks according to the lamination development situation of the fine-grained sedimentary rocks; wherein, the lamination development situation of the fine-grained sedimentary rocks is obtained based on the core data and thin-section data of the target well section.

[0027] In the embodiments of this specification, the core data can be obtained by using a ring core bit and other coring tools to take cylindrical rock samples from a borehole for analysis according to the requirements of exploration and development work or engineering. By analyzing the core data, the sedimentary characteristics of the reservoir and the law of water flooding in the oil layer can be understood, providing a scientific basis for understanding and mastering the water system characteristics of the oil layer at different development stages, studying the distribution law of remaining oil, formulating an oilfield development plan, and conducting feasibility studies on infill adjustment and tertiary oil recovery.

[0028] In the embodiments of this specification, the thin section data mainly focuses on observing and studying the structure, texture, mineral composition and their symbiotic combination of rocks, studying the metamorphism and alteration phenomena of minerals, determining the names of rocks and minerals, comparing strata and rocks, etc., and also includes determining the occurrence form, crystal form, grain size, content and structural texture and other characteristics of the main minerals in the rocks.

[0029] In some embodiments, core data and thin section data of different depth intervals in the target well section can be obtained. By observing the development of fine-grained sedimentary laminations through these core data and thin section data, and the structural types of fine-grained sedimentary laminations can be divided according to the development of fine-grained sedimentary laminations. Specifically, when obtaining the core data and thin section data of different depth intervals in the target well section, the structural types of fine-grained sedimentary laminations can be divided through the following steps.

[0030] S111: Divide the lamination development intervals according to the development characteristics of centimeter-decimeter-scale laminations of fine-grained sedimentary rocks observed from the core data.

[0031] S112: Observe the development characteristics of millimeter-scale laminations of fine-grained sedimentary rocks according to the thin section data of the lamination development intervals to identify the vertical stacking relationship of the main components of the laminations;

[0032] S113: Divide the structural types of fine-grained sedimentary laminations according to the vertical stacking relationship of the main components of the laminations.

[0033] In some embodiments, the lamination development characteristics can be used to characterize the development of fine-grained sedimentary laminations. For example, they can be different characteristics such as the density of lamination development, the individual thickness of laminations, and the main components during the development process of laminations.

[0034] In some embodiments, the centimeter-decimeter-scale lamination development characteristics can be obtained by visually observing the core data, counting the total number of laminations developed in the dense lamination development sections, the main mineral components and other characteristics, and using corresponding tools such as rulers to statistically analyze the thickness of the lamination development sections and the thickness characteristics of individual laminations. The lamination development intervals can be divided through the centimeter-decimeter-scale lamination development characteristics.

[0035] In some embodiments, the millimeter-scale lamination development characteristics can be obtained by observing and identifying thin-section data under a microscope, so as to identify the vertical stacking relationship of the main components of the lamination, and then the lamination structure types of fine-grained sedimentary rocks can be divided according to the vertical stacking relationship of the main components of the lamination. The lamination structure types may include laminated (binary lamination, ternary lamination, and multi-component lamination), layered, and massive.

[0036] In a specific scenario example, take the identification of the lamination structure of the fine-grained sedimentary rocks in the Lucaogou Formation of Well A in a certain place as an example. Based on core observation and microscopic observation of cast thin sections, the lamination development characteristics of the fine-grained sedimentary rocks in the Lucaogou Formation are determined, and the lamination structure types of the fine-grained sedimentary rocks are divided according to the lamination development situation: the lamination with a thickness less than 1 cm is divided into laminated, as Figure 2a shown; the lamination with a thickness between 1 cm and 10 cm is divided into layered, as Figure 2b shown; if the lamination is not developed and the thickness is greater than 10 cm by naked-eye observation, it is divided into massive, as Figure 2c shown.

[0037] S120: Correlate the fine-grained sedimentary rocks of different lamination structure types with the imaging logging images of the target well section, and determine the response characteristics of the fine-grained sedimentary rocks of different lamination structure types on the imaging logging images.

[0038] In some embodiments, through the core positioning technology, the cores of the fine-grained sedimentary rocks of different lamination structure types can be correlated with the imaging logging images of the target well section, so as to determine the response characteristics of the fine-grained sedimentary rocks of different lamination structure types on the imaging logging images. Specifically, after dividing the lamination structure types in S110, the original depth of the core in the formation can be determined according to the core data, and the core at the same depth can be correlated with the imaging logging image, so that the response of the core on the imaging logging image can be observed. The response characteristics are the lamination structure characteristics that characterize the lamination structure type, and the lamination structure characteristics are unique structural characteristics formed during the development of the lamination and affected by the sedimentary environment. For example, if the original depth of the core in the formation is 2,542 meters and the lamination type of the core is laminated, then the characteristics shown at the depth of 2,542 meters in the imaging logging image are the response characteristics of the laminated fine-grained sedimentary rocks on the imaging logging image.

[0039] In a specific scenario example, still taking the identification of the lamination structure of fine-grained sedimentary rocks in Well A in a certain place as an example. Determining the response characteristics of fine-grained sedimentary rocks with different lamination structure types on the imaging logging image can be regarded as a calibration process. After dividing the lamination structure types of fine-grained sedimentary rocks through core data and thin section data, the lamination structure types can be scaled onto the imaging logging image, and different types of lamination structure diagrams such as imaging logging-core-thin section can be established to reveal the millimeter-level - centimeter-level - decimeter-level - meter-level lamination structure characteristics of fine-grained sedimentary rocks, such as Figure 3 as shown, from Figure 3 it can be seen that the response characteristics of fine-grained sedimentary rocks with different lamination structure types on the imaging logging image are different.

[0040] In some embodiments, to meet the identification requirements of different scale lamination structure types, the method may further include corresponding fine-grained sedimentary rocks with different lamination structure types to the conventional logging data of the target well section, and determining the response characteristics of fine-grained sedimentary rocks with different lamination structure types on the conventional logging data. Specifically, through the core positioning technology, fine-grained sedimentary rocks with different lamination structure types can be corresponding to the conventional logging data of the target well section, and the response characteristics of fine-grained sedimentary rocks with different lamination structure types on the conventional logging data can be determined. Specifically, after dividing the lamination structure types in S110, the original depth of the core in the formation can be determined according to the core data, and the core with the same depth can be corresponding to the conventional logging data, so that the response of the core on the conventional logging data can be observed. Among them, the so-called conventional logging data mainly refers to the logging data obtained by the logging methods that are measured in the exploration wells logging, evaluation wells logging, and development wells logging projects in the current oil and gas exploration and development, that is, the three lithology curves of natural gamma, spontaneous potential, and well diameter, the three resistivity curves of shallow, medium, and deep, and the three porosity curves of acoustic wave, neutron, and density. In the case of complex formations, the dipmeter and natural gamma energy spectrum are added, which are also the basic logging information relied on by logging geology research. The conventional logging data used in the embodiments of this specification may include one or more of the above.

[0041] In a specific scenario example, still taking the identification of the lamination structure of fine-grained sedimentary rocks in Well A in a certain place as an example. After dividing the lamination structure types of fine-grained sedimentary rocks through core data and thin section data, the lamination structure types can be scaled onto the imaging logging image, and the lamination structure types can be scaled onto the conventional logging data, and different types of lamination structure diagrams such as conventional logging-imaging logging-core-thin section can be established to reveal the millimeter-level - centimeter-level - decimeter-level - meter-level lamination structure characteristics of fine-grained sedimentary rocks, such as Figure 3 as shown.

[0042] In some embodiments, to improve the recognition accuracy of the laminated structure type, millimeter-scale laminated structure features can be obtained based on the imaging logging slice technology. Specifically, the imaging logging images of the target well section can be sliced to obtain high-resolution (millimeter-scale) slice images of the target well section; the longitudinal laminated structure type of the target well section can be recognized according to the high-resolution slice images of the target well section and the response characteristics of fine-grained sedimentary rocks of different laminated structure types on the high-resolution slice images.

[0043] In some embodiments, the response characteristics of fine-grained sedimentary rocks of different laminated structure types on the high-resolution slice images include: when the laminated structure type is laminated, the response characteristic on the high-resolution slice image is that the light and dark alternating laminae change at the millimeter scale; when the laminated structure type is layered, the response characteristic on the high-resolution slice image is that the light and dark alternating laminae change at the centimeter scale; when the laminated structure type is massive, the response characteristic on the high-resolution slice image is that the light and dark alternating laminae change at the decimeter or meter scale. Specifically, as Figure 4 shown, by slicing the imaging logging images of the target well section, the response characteristics can be divided into three levels and 4 sub-categories, millimeter scale, centimeter scale (thin-bedded), centimeter scale (thick-bedded), and decimeter-meter scale (massive). Using the slice images can improve the resolution of the imaging logging images and the accuracy of laminated structure recognition.

[0044] In a specific scenario example, still taking the recognition of the laminated structure of the fine-grained sedimentary rocks in the Lucaogou Formation of Well A in a certain place as an example. After dividing the laminated structure type of the fine-grained sedimentary rocks through core data and thin-section data, the laminated structure type can be calibrated to the high-resolution slice images, and different types of laminated structure diagrams such as high-resolution slice image-core-thin section can be established to reveal the millimeter-scale laminated structure characteristics of the fine-grained sedimentary rocks, as Figure 5 shown.

[0045] S130: Recognize the longitudinal laminated structure type of the target well section according to the response characteristics of the fine-grained sedimentary rocks of different laminated structure types on the imaging logging image.

[0046] Specifically, after determining the response characteristics of the fine-grained sedimentary rocks of different laminated structure types on the imaging logging image, the layers at different depths of the imaging logging image can be recognized, and based on the response characteristics of the fine-grained sedimentary rocks of different laminated structure types on the imaging logging image, the recognition of the longitudinal laminated structure type of the target well section can be achieved.

[0047] In some embodiments, to improve the recognition accuracy, the imaging logging images of the target well section may also be sliced to obtain high-resolution sliced images of the target well section; the longitudinal laminar structure type of the target well section is recognized according to the high-resolution sliced images of the target well section and the response characteristics of fine-grained sedimentary rocks of different laminar structure types on the high-resolution sliced images.

[0048] Specifically, as Figure 6 shown, the imaging logging images corresponding to the layers at different depths of the imaging logging images of the target well section may be sliced to obtain high-resolution sliced images, and then the longitudinal laminar structure type of the target well section is recognized according to the response characteristics of fine-grained sedimentary rocks of different laminar structure types on the high-resolution sliced images. Among them, Figure 6 the first to the third images in the figure are static image, dynamic enhanced image, and imaging logging dynamic sliced image respectively.

[0049] In some embodiments, to meet the recognition requirements of different-scale laminar structure types, the laminar structure type may also be recognized by combining conventional logging data. Specifically, the method may further include recognizing the longitudinal laminar structure type of the target well section according to the imaging logging images of the target well section, the conventional logging data of the target well section, the response characteristics of fine-grained sedimentary rocks of different laminar structure types on the imaging logging images, and the response characteristics of fine-grained sedimentary rocks of different laminar structure types on the conventional logging data.

[0050] In a specific scenario example, still taking the recognition of the laminar structure of the fine-grained sedimentary rocks in the Lucaogou Formation of Well A in a certain place as an example. The process of recognizing the laminar structure type by combining conventional logging data is as Figure 7 shown. Combining conventional logging data can achieve the recognition of meter-scale laminations; combining imaging logging images can achieve the recognition of centimeter-decimeter-scale laminations; combining high-resolution sliced images can achieve the recognition of millimeter-decimeter-scale laminations; combining core data can achieve the recognition of millimeter-centimeter-scale laminations; combining thin section data can achieve the recognition of micron-millimeter-scale laminations, progressing layer by layer from macro to micro, with the recognition resolution gradually increasing and corresponding one by one. By calibrating with core and thin sections, clarifying the response characteristics of the laminar structure on the imaging logging and high-resolution sliced images is of great significance for the evaluation of the laminar structure of un-cored wells. Figure 8 is the result of the continuous recognition and division of the longitudinal laminations of Well A.

[0051] As can be seen from the technical solutions provided in the embodiments of this specification above, in the embodiments of this specification, the fine-grained sedimentary rock lamina structure types can be divided according to the lamina development of the fine-grained sedimentary rock; wherein, the lamina development of the fine-grained sedimentary rock is obtained based on the core data and thin section data of the target well section; the fine-grained sedimentary rocks of different lamina structure types are corresponded to the imaging logging images of the target well section to determine the response characteristics of the fine-grained sedimentary rocks of different lamina structure types on the imaging logging images; the longitudinal lamina structure types of the target well section are identified according to the response characteristics of the fine-grained sedimentary rocks of different lamina structure types on the imaging logging images, thereby improving the accuracy of the identification of the fine-grained sedimentary rock lamina structure, compensating for the defect of insufficient coring, and realizing the fine identification and evaluation of multi-scale lamina structure types.

[0052] Figure 9 FIG. is a schematic functional structure diagram of an information acquisition device according to an embodiment of this specification. The device may specifically include the following structural modules.

[0053] A division module 910 is configured to divide the fine-grained sedimentary rock lamina structure types according to the lamina development of the fine-grained sedimentary rock; wherein, the lamina development of the fine-grained sedimentary rock is obtained based on the core data and thin section data of the target well section;

[0054] A determination module 920 is configured to correspond the fine-grained sedimentary rocks of different lamina structure types to the imaging logging images of the target well section to determine the response characteristics of the fine-grained sedimentary rocks of different lamina structure types on the imaging logging images;

[0055] An identification module 930 is configured to identify the longitudinal lamina structure types of the target well section according to the response characteristics of the fine-grained sedimentary rocks of different lamina structure types on the imaging logging images.

[0056] In some embodiments, the corresponding the fine-grained sedimentary rocks of different lamina structure types to the imaging logging images to determine the response characteristics of the fine-grained sedimentary rocks of different lamina structure types on the imaging logging images includes: slicing the imaging logging images of the layers where the fine-grained sedimentary rocks of different lamina structure types are located in the imaging logging images to obtain high-resolution slice images; determining the response characteristics of the fine-grained sedimentary rocks of different lamina structure types on the high-resolution slice images.

[0057] In some embodiments, the identifying the longitudinal lamina structure types of the target well section according to the response characteristics of the fine-grained sedimentary rocks of different lamina structure types on the imaging logging images includes: slicing the imaging logging images of the target well section to obtain high-resolution slice images of the target well section; identifying the longitudinal lamina structure types of the target well section according to the high-resolution slice images of the target well section and the response characteristics of the fine-grained sedimentary rocks of different lamina structure types on the high-resolution slice images.

[0058] It should be noted that each embodiment in this specification is described in a progressive manner. For the same or similar parts among the embodiments, reference can be made to each other. Each embodiment focuses on the differences from other embodiments. In particular, for the apparatus embodiments and equipment embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiments.

[0059] After reading this specification document, those skilled in the art can, without creative work, think of making any combinations of some or all of the embodiments listed in this specification, and these combinations are also within the scope of disclosure and protection of this specification.

[0060] In the 1990s, improvements to a technology could be clearly distinguished as either hardware improvements (e.g., improvements to circuit structures such as diodes, transistors, switches, etc.) or software improvements (improvements to method flows). However, with the development of technology, many method flow improvements today can be regarded as direct improvements to hardware circuit structures. Almost all designers obtain the corresponding hardware circuit structure by programming the improved method flow into the hardware circuit. Therefore, it cannot be said that an improvement to a method flow cannot be implemented using a hardware entity module. For example, a Programmable Logic Device (PLD) (such as a Field Programmable Gate Array (FPGA)) is an integrated circuit whose logic function is determined by the user programming the device. Designers can program themselves to "integrate" a digital system onto a single PLD, without having to ask a chip manufacturer to design and fabricate a dedicated integrated circuit chip. Moreover, nowadays, instead of manually fabricating integrated circuit chips, this programming is mostly implemented using "logic compiler" software, which is similar to the software compilers used in program development and writing. The original code before compilation also has to be written in a specific programming language, which is called a Hardware Description Language (HDL), and there is not just one type of HDL, but many types, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, RHDL (Ruby Hardware Description Language), etc. Currently, the most commonly used are VHDL (Very-High-Speed Integrated Circuit Hardware Description Language) and Verilog. Those skilled in the art should also be aware that by simply performing a little logical programming on the method flow using the above-mentioned several hardware description languages and programming it into an integrated circuit, it is easy to obtain a hardware circuit that implements the logical method flow.

[0061] The systems, devices, modules or units illustrated in the above embodiments can be specifically implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, the computer can be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device or a combination of any of these devices.

[0062] From the description of the above embodiments, those skilled in the art can clearly understand that this specification can be implemented by means of software plus a necessary general hardware platform. Based on such an understanding, the technical solutions of this specification, in essence or the part that contributes to the prior art, can be embodied in the form of a software product, which can be stored in a storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., including several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in various embodiments or some parts of the embodiments of this specification.

[0063] The various embodiments in this specification are described in a progressive manner. For the same or similar parts between the various embodiments, reference can be made to each other. Each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0064] This specification can be used in numerous general or special computer system environments or configurations. For example: personal computers, server computers, handheld or portable devices, tablet-type devices, multi-processor systems, microprocessor-based systems, set-top boxes, programmable consumer electronic devices, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, and so on.

[0065] This specification can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. This specification can also be practiced in a distributed computing environment, where tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media including storage devices.

[0066] Although this specification is described by way of examples, those of ordinary skill in the art will recognize that the specification has many modifications and variations without departing from the spirit of the specification. It is intended that the appended claims cover these modifications and variations without departing from the spirit of the specification.

Claims

1. A method for identifying laminar structure of fine-grained sedimentary rocks, characterized in that: The method comprises: Classifying the lamination structure types of fine-grained sedimentary rocks according to the lamination development of the fine-grained sedimentary rocks; wherein the lamination development of the fine-grained sedimentary rocks is obtained based on core data and thin section data of the target well section; Corresponding fine-grained sedimentary rocks of different laminae structural types to imaging logging images of target well sections, determining the response characteristics of fine-grained sedimentary rocks of different laminae structural types on the imaging logging images, calibrating the laminae structural types onto the imaging logging images, and establishing imaging logging-core-thin section maps of different laminae structural types; Identify the longitudinal lamination structure type of the target well section according to the response characteristics of the fine-grained sedimentary rocks of different lamination structure types on the imaging logging image; Gradually scale the laminar structure types onto high-resolution slice images, and establish a high-resolution slice image-core-thin section plate with different types of laminar structures. Based on the different types of laminar structure plates of the high-resolution slice image-core-thin section, the longitudinal laminar structure type of the well section to be identified is identified according to the response characteristics of the fine-grained sedimentary rocks of different laminar structure types on the imaging logging image; the identification process includes sequentially performing the following identification methods: Combined with conventional logging data, it can identify meter-scale laminations; Combined with imaging logging images, centimeter-decimeter level lamination identification can be achieved; Millimeter-to-decimeter-level laminae recognition is achieved by combining high-resolution slice images; the high-resolution slice images are obtained by slicing the imaging logging images; Combined with core data, millimeter-centimeter level lamination identification can be achieved; Combined with thin section data, micron-millimeter level lamination identification can be achieved.

2. The method according to claim 1, characterized in that The identifying of the longitudinal lamination structure type of the well section to be identified based on the response characteristics of the fine-grained sedimentary rocks of different lamination structure types on the imaging logging image comprises: Slice the imaging logging image of the target well section to obtain a high-resolution slice image of the target well section; The vertical lamination structure type of the target well section is identified based on the high-resolution slice image of the target well section and the response characteristics of fine-grained sedimentary rocks with different lamination structure types on the high-resolution slice image.

3. The method according to claim 1, characterized in that The laminar structure types include laminar, layered and massive.

4. The method according to claim 1, wherein The response characteristics of fine-grained sedimentary rocks with different laminar structure types on high-resolution slice images include: In the case where the laminar structure type is laminar, the response feature on the high-resolution slice image is that the light and dark laminae vary at the millimeter level; When the laminar structure type is layered, the response feature on the high-resolution slice image is that the light and dark laminae vary at the centimeter level; In the case where the laminar structure type is blocky, the response feature on the high-resolution slice image is that the light and dark laminae vary at the decimeter or meter level.

5. The method according to claim 1, wherein The classification of fine-grained sedimentary rock laminae structure types according to the laminae development of fine-grained sedimentary rocks includes: According to the centimeter-decimeter-scale lamination characteristics of fine-grained sedimentary rocks observed from core data, lamination development intervals were divided; Based on the thin section data of the laminae development interval, the millimeter-scale laminae development characteristics of fine-grained sedimentary rocks are observed to identify the vertical superposition relationship of the main components of the laminae; The laminar structural types of fine-grained sedimentary rocks are divided according to the vertical superposition relationship of the main components of the laminae.

6. The method according to claim 1, characterized in that The method further comprises: Corresponding fine-grained sedimentary rocks of different laminar structural types to conventional logging data of a target well section, and determining response characteristics of fine-grained sedimentary rocks of different laminar structural types on the conventional logging data; Accordingly, the longitudinal lamination structure type of the target well section is identified based on the imaging logging image of the target well section, the conventional logging data of the target well section, the response characteristics of fine-grained sedimentary rocks with different lamination structure types on the imaging logging image, and the response characteristics of fine-grained sedimentary rocks with different lamination structure types on the conventional logging data.

7. A device for identifying laminar structure of fine-grained sedimentary rocks, characterized in that: The device comprises: A classification module is used to classify the laminar structure types of fine-grained sedimentary rocks based on the development of fine-grained sedimentary rock laminae observed from core data and thin section data of the target well section; a determination module for aligning fine-grained sedimentary rocks of different laminae structural types with imaging logging images of target well sections, determining response characteristics of fine-grained sedimentary rocks of different laminae structural types on the imaging logging images, calibrating the laminae structural types onto the imaging logging images, and establishing imaging logging-core-thin section maps of different laminae structural types; The identification module is used to identify the longitudinal lamination structure type of the well section to be identified based on the different types of lamination structure plates of the high-resolution slice image, core, and thin section, according to the response characteristics of the fine-grained sedimentary rocks of the different lamination structure types on the imaging logging image. The identification process includes sequentially executing the following identification methods: Combined with conventional logging data, it can identify meter-scale laminations; Combined with imaging logging images, centimeter-decimeter level lamination identification can be achieved; Millimeter-to-decimeter-level laminae recognition is achieved by combining high-resolution slice images; the high-resolution slice images are obtained by slicing the imaging logging images; Combined with core data, millimeter-centimeter level lamination identification can be achieved; Combined with thin section data to achieve micron-millimeter level lamination identification; The device is also used to: mark the laminar structure type on the high-resolution slice image, and establish a laminar structure plate of different types of the high-resolution slice image-core-thin slice.

8. The device according to claim 7, characterized in that The step of making the fine-grained sedimentary rocks of different laminar structural types correspond to the imaging logging image and determining the response characteristics of the fine-grained sedimentary rocks of different laminar structural types on the imaging logging image includes: Slicing the imaging logging image of the interval where the fine-grained sedimentary rock of different laminar structure types is located in the imaging logging image to obtain a high-resolution slice image; Determine the response characteristics of fine-grained sedimentary rocks with different laminar structural types on high-resolution slice images.

9. The device according to claim 8, characterized in that The identifying of the longitudinal lamination structure type of the well section to be identified based on the response characteristics of the fine-grained sedimentary rocks of different lamination structure types on the imaging logging image comprises: Slice the imaging logging image of the target well section to obtain a high-resolution slice image of the target well section; The vertical lamination structure type of the target well section is identified based on the high-resolution slice image of the target well section and the response characteristics of fine-grained sedimentary rocks with different lamination structure types on the high-resolution slice image.

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