Biological disturbance-based quantitative sedimentary rock classification evaluation method and system

Abstract

The invention belongs to the technical field of sedimentary geology research, and discloses a quantitative sedimentary rock classification evaluation method and system based on biological disturbance. The method comprises the following steps: acquiring a high-resolution image of a unit area of a field outcrop or core sample; identifying a relics fossil or a biological disturbance area in the high-resolution image, and obtaining a biological disturbance quantity percentage of the high-resolution image by using a unit grid method; identifying the belonging number of the relics fossils in the high-resolution image; measuring to obtain the diving hole diameter of each relics fossil, and obtaining the diving hole diameter of the maximum relics fossil; obtaining the natural layer thickness of the field outcrop or rock core sample and the average particle size of the surrounding rock; calculating to obtain a biological disturbance coefficient; and based on the biological disturbance coefficient of the field outcrop or rock core sample, evaluating to obtain a classification evaluation result of the sedimentary rock. When a researcher performs classification evaluation on the same or similar sedimentary rock samples, a relatively consistent result can be obtained, and the repeatability and comparability of evaluation are enhanced.

Description

Technical Field

[0001] This invention belongs to the field of sedimentary geology research technology and relates to a quantitative sedimentary rock classification and evaluation method and system based on bio-disturbance. Background Technology

[0002] Bioturbation refers to the intense agitation of sediments by organisms, which significantly alters the physical and chemical properties of the sediments. Bioturbation is widespread in various sedimentary environments, including marine, lacustrine, riverine, and terrestrial environments, and has a profound impact on sediment diagenesis, pore structure, and reservoir performance. The main forms of bioturbation include, but are not limited to: 1. Burrowing: Tubular structures formed by organisms digging in sediments, such as double cup tracks and serpentine tracks. 2. Footprints: Traces left by organisms walking on the sediment surface. 3. Movement tracks: Traces formed by organisms agitating sediments during movement. These trace structures not only record the presence and activity of organisms but also reflect the physical and chemical conditions of the sedimentary environment. Oil and gas exploration practice shows that bioturbation has a significant impact on the reservoir performance of clastic and carbonate reservoirs. Specifically, it manifests as: 1. Enhanced heterogeneity: Bioturbation disrupts the original bedding and structure of sediments, resulting in strong heterogeneity in the reservoir both laterally and vertically. This heterogeneity poses greater challenges to oil and gas exploration and development. 2. Changes in Porosity and Permeability: Bioturbation can alter the particle sorting and size distribution of sediments, thereby affecting reservoir porosity and permeability. For example, some biological burrowing activities may mix fine-grained materials (such as clay and organic matter) into the burrow filler and lining, reducing the porosity and permeability of local areas; while other biological activities may remove fine-grained materials from the burrow, increasing porosity and permeability. Objectively evaluating the sedimentary environment and reservoir performance of this type of reservoir is a key geological problem that urgently needs to be solved. Identifying the main controlling factors of reservoir development will provide support for the prediction and evaluation of favorable reservoir zones.

[0003] Currently, there is no separate petrological nomenclature scheme or related evaluation method for bioturbation. Only qualitative bioturbation indices (Reaneck, 1963; Knaust, 2012) or trace texture indices (Bottjer & Droser, 1991) based on field outcrop observations exist. These are highly subjective and subject to human intervention, making accurate nomenclature impossible and thus affecting the assessment of the strength of bioturbation's impact on reservoir properties. Traditional bioturbation indices or trace texture indices are mainly based on the proportion of disturbance or damage to sediments by trace-forming organisms, and are subjectively divided into 6 levels of bioturbation indices and 5 levels of trace texture indices. Moreover, these indices are not linked to specific petrological classifications and corresponding reservoir evaluation indicators. Summary of the Invention

[0004] The purpose of this invention is to solve the technical problem that there is no separate petrological nomenclature scheme and related evaluation method for bio-disturbance in the existing technology, and to provide a quantitative sedimentary rock classification and evaluation method and system based on bio-disturbance.

[0005] To achieve the above objectives, the present invention employs the following technical solution:

[0006] In a first aspect, the present invention provides a quantitative sedimentary rock classification and evaluation method based on bio-disturbance, comprising:

[0007] Acquire high-resolution images per unit area of ​​field outcrops or core samples;

[0008] Identify trace fossils or areas of biological disturbance in the high-resolution image, and use the unit grid method to obtain the percentage of biological disturbance in the high-resolution image;

[0009] The number of genera of trace fossils in the high-resolution image was identified; the burrow diameter of each trace fossil was measured, and the burrow diameter of the largest trace fossil was obtained.

[0010] Obtain the natural layer thickness and average grain size of the surrounding rock from the field outcrops or core samples;

[0011] The biodisturbance coefficient of the field outcrop or core sample is calculated based on the percentage of biodisturbance, the number of genera of trace fossils, the burrow diameter of the largest trace fossil, the natural layer thickness, and the average grain size of the surrounding rock.

[0012] Based on the biodisturbance coefficient of the field outcrops or core samples, the classification evaluation results of sedimentary rocks are obtained.

[0013] Further improvements are made in the following aspects:

[0014] The biodisturbance coefficient of the field outcrop or core sample, calculated based on the percentage of biodisturbance, the number of genera of trace fossils, the burrow diameter of the largest trace fossil, the natural layer thickness, and the average grain size of the surrounding rock, is specifically as follows:

[0015] Biodisturbance coefficient = (Percentage of biodisturbance * Number of genera of trace fossils * Maximum diameter of trace burrows) / (Average grain size of surrounding rock * Thickness of natural layer).

[0016] Based on the biodisturbance coefficient of the aforementioned field outcrops or core samples, the classification and evaluation results of sedimentary rocks specifically include:

[0017] When the biodisturbance coefficient is 0, the sedimentary rock is named undisturbed rock; when the biodisturbance coefficient is between 0 and 10, the sedimentary rock is named weakly biodisturbed rock; when the biodisturbance coefficient is between 10 and 40, the sedimentary rock is named poorly biodisturbed rock; when the biodisturbance coefficient is between 40 and 60, the sedimentary rock is named moderately biodisturbed rock; when the biodisturbance coefficient is between 60 and 90, the sedimentary rock is named highly biodisturbed rock; when the biodisturbance coefficient is greater than 90, the sedimentary rock is named strongly biodisturbed rock.

[0018] The highly biodisturbed rocks and strongly biodisturbed rocks are excellent biodisturbed reservoirs.

[0019] The high-resolution image is processed for contrast and brightness before identifying trace fossils or areas of biological disturbance in the image.

[0020] The burrow diameter is in mm, with the value rounded to one decimal place; the natural layer thickness is in m; the average grain size of the surrounding rock is in mm; no unit conversion is performed on the values ​​of the parameters when calculating the bio-disturbance coefficient.

[0021] The grid size of the unit grid method is proportional to the size of the field outcrop or core sample.

[0022] Secondly, the present invention provides a quantitative sedimentary rock classification and evaluation system based on bio-disturbance, comprising:

[0023] The image acquisition module is used to acquire high-resolution images per unit area of ​​field outcrops or core samples;

[0024] A bio-disturbance identification module is used to identify trace fossils or bio-disturbance areas in the high-resolution image and to obtain the percentage of bio-disturbance in the high-resolution image using the unit grid method.

[0025] The trace fossil identification module is used to identify the number of genera of trace fossils in the high-resolution image; measure the burrow diameter of each trace fossil, and obtain the burrow diameter of the largest trace fossil;

[0026] The natural layer thickness acquisition module is used to acquire the natural layer thickness and the average grain size of the surrounding rock of the field outcrop or core sample.

[0027] The biodisturbance coefficient calculation module is used to calculate the biodisturbance coefficient of the field outcrop or core sample based on the percentage of biodisturbance, the number of genera of trace fossils, the burrow diameter of the largest trace fossil, the natural layer thickness, and the average grain size of the surrounding rock.

[0028] The sedimentary rock classification and evaluation module uses the bio-disturbance coefficient based on the field outcrops or core samples to evaluate the classification and evaluation results of sedimentary rocks.

[0029] Thirdly, the present invention provides an electronic device including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the above-described quantitative sedimentary rock classification and evaluation method based on bio-disturbance.

[0030] Fourthly, the present invention provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the above-described quantitative sedimentary rock classification and evaluation method based on bio-disturbance.

[0031] Compared with the prior art, the present invention has the following beneficial effects:

[0032] This invention discloses a quantitative classification and evaluation method for sedimentary rocks based on bioturbation. Through high-resolution image analysis technology, it can accurately identify and quantify bioturbation phenomena in sedimentary rocks, including the distribution, quantity, and characteristics of trace fossils (such as burrow diameter), as well as key parameters such as the percentage of bioturbation. Compared with traditional manual observation and description, this method significantly improves the accuracy and objectivity of classification and evaluation, reducing errors caused by subjective judgment. Furthermore, this invention introduces multiple quantitative indicators, such as the percentage of bioturbation, the number of genera of trace fossils, the diameter of the largest trace fossil burrow, the natural layer thickness, and the average grain size of the surrounding rock, and calculates the bioturbation coefficient based on these indicators, thereby achieving a comprehensive and quantitative evaluation of the bioturbation characteristics of sedimentary rocks. This quantitative evaluation method provides a more scientific and systematic basis for the classification and research of sedimentary rocks. Utilizing modern image processing and data analysis technologies, large amounts of high-resolution image data can be processed quickly and efficiently, automatically identifying and extracting key information, greatly shortening the time cycle for sedimentary rock classification and evaluation, and improving evaluation efficiency. Because this method relies on explicit quantitative indicators and standardized calculation procedures, different researchers can obtain relatively consistent results when classifying and evaluating the same or similar sedimentary rock samples, thus enhancing the repeatability and comparability of the evaluation.

[0033] Furthermore, quantitative formulas can accurately determine bio-disturbance coefficients, allowing researchers to quickly identify rock nomenclatures based on bio-disturbance intensity, thus improving work efficiency. Measurements of several conventional petrological parameters can be performed quantitatively without the need for corresponding geochemical or geophysical methods, significantly reducing the instability caused by modifications to geochemical or geophysical parameters. Detailed classification standards and keyword descriptions enable the establishment of corresponding bio-disturbance reservoir evaluation systems, allowing for more precise reservoir evaluation. Attached Figure Description

[0034] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0035] Figure 1 This is a flowchart of a quantitative sedimentary rock classification and evaluation method based on bio-disturbance in this invention;

[0036] Figure 2 This is a flowchart illustrating the quantitative sedimentary rock classification and evaluation method based on bio-disturbance in an embodiment of the present invention.

[0037] Figure 3 This is a block diagram of a quantitative sedimentary rock classification and evaluation system based on bio-disturbance in this invention;

[0038] Figure 4 This is a block diagram of the electronic device in this invention. Detailed Implementation

[0039] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0040] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0041] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0042] The present invention will now be described in further detail with reference to the accompanying drawings:

[0043] See Figure 1 This invention discloses a quantitative sedimentary rock classification and evaluation method based on bio-disturbance, comprising:

[0044] S1, acquire high-resolution images per unit area of ​​field outcrops or core samples;

[0045] S2, identify trace fossils or areas of biological disturbance in the high-resolution image, and use the unit grid method to obtain the percentage of biological disturbance in the high-resolution image;

[0046] S3, identify the number of genera of trace fossils in the high-resolution image; measure the burrow diameter of each trace fossil, and obtain the burrow diameter of the largest trace fossil;

[0047] S4, obtain the natural layer thickness and average grain size of the surrounding rock of the field outcrop or core sample;

[0048] S5. The biodisturbance coefficient of the field outcrop or core sample is calculated based on the percentage of biodisturbance, the number of genera of trace fossils, the burrow diameter of the largest trace fossil, the thickness of the natural layer, and the average grain size of the surrounding rock.

[0049] S6. Based on the biodisturbance coefficient of the field outcrops or core samples, the classification evaluation results of sedimentary rocks are obtained.

[0050] This invention discloses a quantitative classification and evaluation method for sedimentary rocks based on bioturbation. Through high-resolution image analysis technology, it can accurately identify and quantify bioturbation phenomena in sedimentary rocks, including the distribution, quantity, and characteristics of trace fossils (such as burrow diameter), as well as key parameters such as the percentage of bioturbation. Compared with traditional manual observation and description, this method significantly improves the accuracy and objectivity of classification and evaluation, reducing errors caused by subjective judgment. Furthermore, this invention introduces multiple quantitative indicators, such as the percentage of bioturbation, the number of genera of trace fossils, the diameter of the largest trace fossil burrow, the natural layer thickness, and the average grain size of the surrounding rock, and calculates the bioturbation coefficient based on these indicators, thereby achieving a comprehensive and quantitative evaluation of the bioturbation characteristics of sedimentary rocks. This quantitative evaluation method provides a more scientific and systematic basis for the classification and research of sedimentary rocks. Utilizing modern image processing and data analysis technologies, large amounts of high-resolution image data can be processed quickly and efficiently, automatically identifying and extracting key information, greatly shortening the time cycle for sedimentary rock classification and evaluation, and improving evaluation efficiency. Because this method relies on explicit quantitative indicators and standardized calculation procedures, different researchers can obtain relatively consistent results when classifying and evaluating the same or similar sedimentary rock samples, enhancing the repeatability and comparability of the evaluation. Furthermore, the quantitative formula allows for precise determination of the bioturbation coefficient, enabling researchers to quickly identify the rock nomenclature based on the intensity of bioturbation, thus improving work efficiency. Measurements of several conventional petrological parameters can be performed quantitatively without the need for corresponding geochemical or geophysical methods, significantly reducing the instability caused by modifying geochemical or geophysical parameters. Detailed classification criteria and keyword descriptions allow for the establishment of a corresponding reservoir evaluation system based on bioturbation, enabling more precise reservoir evaluation. The application of synonyms greatly improves the matching rate between the nomenclature and reservoir evaluation of different rock types with the same bioturbation type.

[0051] See Figure 2 The present invention will be further described below with reference to specific embodiments:

[0052] Example 1

[0053] Step 1: Obtain high-resolution images per unit area of ​​field outcrops or core samples.

[0054] First, when observing field outcrops or core samples, select representative outcrops or cores that preserve fossils or signs of bioturbation. Then, use a high-resolution camera or scanner to photograph or scan the outcrops or cores with obvious bioturbation to obtain clear, detailed, high-resolution images per unit area. These high-resolution images should contain sufficient detail to accurately identify trace fossils and bioturbation phenomena later. Specifically, "unit area" refers to outcrops with a unit area of ​​10cm*10cm, 15cm*15cm, 20cm*20cm, 25cm*25cm, etc., or cores with a unit area of ​​7.5cm*75cm.

[0055] Step 2: Identify the trace fossils or areas of biological disturbance in the high-resolution image, and use the unit grid method to obtain the percentage of biological disturbance in the high-resolution image, denoted as value A.

[0056] The acquired high-resolution images are imported into image processing software such as Photoshop for contrast and brightness adjustments. Enhancing image contrast and brightness makes fossil remains or biological disturbances stand out more, facilitating subsequent identification and measurement. Contrast adjustment: Increases the difference between different brightness areas in the image, making details clearer. Brightness adjustment: Improves the distribution of light and dark areas in the image, ensuring moderate overall brightness and avoiding loss of detail due to excessive darkness or brightness. Image noise reduction: If there is significant noise or interference in the image, noise reduction processing is required to improve image quality. Noise reduction processing can remove random noise from the image while preserving useful detail information.

[0057] The steps of the unit grid method are as follows:

[0058] Grid division: Divide the image into unit grids of a certain size (e.g., 2mm*2mm or 2cm*2cm, or as needed) to ensure that the grid covers the entire high-resolution image area. The grid size of the unit grid method is proportional to the size of the field outcrop or core sample.

[0059] Statistical analysis of biodisturbance areas: Count the area or number of biodisturbance areas within each grid (select the statistical method according to specific circumstances). Biodisturbance areas include various traces and structures formed by biological activities (such as digging, burrowing, foraging, etc.), exhibiting morphological diversity, including burrows and traces of various shapes such as straight lines, curves, nets, and spirals.

[0060] Calculate the percentage: Add up the areas or numbers of biologically disturbed regions in all grids, then divide by the area of ​​the entire image region or the total number of grids to obtain the percentage of biological disturbance. This percentage reflects the density and distribution of biological disturbance in the image.

[0061] In addition to the unit grid method, specialized image processing or geological analysis software can be used to identify and quantitatively analyze biodisturbance areas in rock images. These software programs typically offer a variety of identification algorithms and tools, enabling more accurate extraction and measurement of biodisturbance features.

[0062] Step 3: Identify the number of genera of trace fossils in the high-resolution image, denoted as value B; measure the burrow diameter of each trace fossil, and obtain the burrow diameter of the largest trace fossil, denoted as value C;

[0063] The number of genera of trace fossils is recorded in Arabic numerals, such as 1, 2, 4, etc.; the maximum diameter of the burrow is recorded in millimeters (mm), with one decimal place, such as 2.1mm, 4.5mm. No unit conversion is performed on the parameters when calculating the bioturbation coefficient. Table 1 shows the number of genera of trace fossils.

[0064] Table 1

[0065]

[0066]

[0067] Step four: Obtain the natural layer thickness of the field outcrop or core sample, in meters (m), denoted as D. Natural layer thickness refers to the thickness of a certain layer (or stratum) in the rock, which is formed naturally during the geological history of the rock. Observe and measure the average grain size of the surrounding rock using a polarizing microscope, in millimeters (mm), denoted as E.

[0068] Polarizing microscopy: A polarizing microscope is an important instrument for studying the optical properties of thin crystal sections and is widely used for identifying the composition and microstructure of rocks and minerals. It utilizes the polarization properties of light to more clearly display the microstructure and mineral composition of rocks. When observing rock thin sections, researchers can place the section on the microscope stage and, by adjusting the microscope's focal length and polarizing device, observe information such as the size, shape, arrangement, and contact relationships between minerals.

[0069] Measuring the average grain size of the surrounding rock: The surrounding rock refers to the rock surrounding the target rock. The grain size of the surrounding rock is an important parameter reflecting its genesis, sedimentary environment, and other information. The average grain size of the surrounding rock is generally measured by selecting a certain number of grains (e.g., tens to hundreds) under a microscope, then measuring the grain size of each grain using the microscope's scale or measurement software, and finally calculating the average of these grain sizes. This average value reflects the grain size distribution characteristics of the surrounding rock, thus providing important evidence for geological interpretation. Table 2 shows the data on natural layer thickness and the average grain size of the surrounding rock.

[0070] Table 2

[0071]

[0072] Step 5: Calculate the biodisturbance coefficient of the field outcrop or core sample based on the percentage of biodisturbance, the number of genera of trace fossils, the burrow diameter of the largest trace fossil, the natural layer thickness, and the average grain size of the surrounding rock. The core principle is that the biodisturbance coefficient per unit area is directly proportional to the percentage of biodisturbance, the number of genera of trace fossils, and the maximum burrow diameter, and inversely proportional to the average grain size of the surrounding rock and the natural layer thickness. Specifically:

[0073] Biodisturbance coefficient = (Percentage of biodisturbance * Number of genera of trace fossils * Maximum diameter of trace burrows) / (Average grain size of surrounding rock * Thickness of natural layer).

[0074] It can also be expressed as: (S is the biological disturbance coefficient)

[0075] S = (value A * value B * value C) / (value D * value E).

[0076] Step six involves evaluating the classification results of sedimentary rocks based on the biodisturbance coefficients of the field outcrops or core samples. Specifically:

[0077] When the biodisturbance coefficient S is 0, the sedimentary rock is named undisturbed rock; when the biodisturbance coefficient S is between 0 and 10, the sedimentary rock is named weakly biodisturbed rock; when the biodisturbance coefficient S is between 10 and 40, the sedimentary rock is named poorly biodisturbed rock; when the biodisturbance coefficient S is between 40 and 60, the sedimentary rock is named moderately biodisturbed rock; when the biodisturbance coefficient S is between 60 and 90, the sedimentary rock is named highly biodisturbed rock; and when the biodisturbance coefficient S > 90, the sedimentary rock is named strongly biodisturbed rock. The highly biodisturbed and strongly biodisturbed rocks are excellent biodisturbed reservoirs.

[0078] Example 2

[0079] The steps in the quantitative sedimentary rock classification and evaluation method based on bio-disturbance disclosed in this invention can also be manually operated, as follows:

[0080] Step 1: Open a new file. After opening Adobe Illustrator, click the "File" tab and select "New". Choose the size of the new document, name the new document, set the document's "width" and "height", and choose whether to measure in inches, pixels, pica, dots, millimeters, or centimeters.

[0081] Step 2: Click "File" in the upper left corner, then click "Open" to insert a high-resolution image per unit area of ​​the saved field outcrop or core sample.

[0082] Step 3: Click the "Rectangular Grid Tool" option on the left, left-click on a blank area of ​​the canvas to bring up the "Grid Tool Options", set the grid parameters as needed (grid width, height, number of vertical dividing lines and horizontal dividing lines, which can be directly used as the image scale), click OK, and the grid is successfully drawn.

[0083] Step four: Arrange the high-resolution image and grid neatly and adjust them to the appropriate positions.

[0084] Step 5: Click the "Eyedropper Tool" in the left toolbar to fill the entire grid with white for later processing.

[0085] Step 6: Adjust the grid transparency so that the background image can be seen before applying color in real time. Click "Opacity" in the toolbar above to select an opacity of 0%-100%.

[0086] Step 7: Click the "Live Color Tool" in the left toolbar, click in the grid to activate the shape, then select the creature relic or creature disturbance shape, and finally select the corresponding color to fill it.

[0087] Step 8: After completing the drawing, save and export the image with the fill color, and name it "Image 1".

[0088] Step 9: Open "Image 1" in Photoshop, click "Select" in the toolbar, select the "Color Range" option, enter the Color Range, click the color swatch you want to view the proportion of, and then click OK.

[0089] Step 10: Return to the Photoshop toolbar, select "Image", then select "Analysis", then select "Record Measurements", and click "Record Measurements" to record or export data such as area and perimeter (referred to as Data 1).

[0090] Step 11: Calculate the area ratio of different colors in "Image 1" in "Data 1" in Excel, and define the area ratio of colors marked as biological disturbance or biological remains as the percentage of biological disturbance (value A).

[0091] Step 12: Identify the number of genera of trace fossils in the high-resolution image and record it as value B. Find the largest diameter of trace fossil burrows per unit area by measuring the diameter of the burrows and record it as value C.

[0092] Step 13: Measure the natural thickness of the rock layers in the field and in the core, and record it as the value D. Observe the thin sections of the rock at the corresponding layer using a polarizing microscope, measure the average grain size of the surrounding rock, and record it as the value E.

[0093] Step fourteen: Input the values ​​A, B, C, D and E into the biological disturbance coefficient calculation formula as follows: S = (value A * value B * value C) / (value D * value E). Record the result as S.

[0094] Step 15: Rocks with a result S of 0 are named as non-biologically disturbed rocks; rocks with a result S between 0 and 10 are named as weakly biologically disturbed rocks; rocks with a result S between 10 and 40 are named as poorly biologically disturbed rocks; rocks with a result S between 40 and 60 are named as moderately biologically disturbed rocks; rocks with a result S between 60 and 90 are named as highly biologically disturbed rocks; and rocks with a result S > 90 are named as strongly biologically disturbed rocks.

[0095] After all calculations are completed, a classification method is used to identify reservoirs with a bio-disturbance coefficient S > 60 as excellent indicators of bio-disturbance reservoirs for customers to choose from.

[0096] See Figure 3 This invention discloses a quantitative sedimentary rock classification and evaluation system based on bio-disturbance, comprising:

[0097] The image acquisition module is used to acquire high-resolution images per unit area of ​​field outcrops or core samples;

[0098] A bio-disturbance identification module is used to identify trace fossils or bio-disturbance areas in the high-resolution image and to obtain the percentage of bio-disturbance in the high-resolution image using the unit grid method.

[0099] The trace fossil identification module is used to identify the number of genera of trace fossils in the high-resolution image; measure the burrow diameter of each trace fossil, and obtain the burrow diameter of the largest trace fossil;

[0100] The natural layer thickness acquisition module is used to acquire the natural layer thickness and the average grain size of the surrounding rock of the field outcrop or core sample.

[0101] The biodisturbance coefficient calculation module is used to calculate the biodisturbance coefficient of the field outcrop or core sample based on the percentage of biodisturbance, the number of genera of trace fossils, the burrow diameter of the largest trace fossil, the natural layer thickness, and the average grain size of the surrounding rock.

[0102] The sedimentary rock classification and evaluation module is used to assess the classification and evaluation results of sedimentary rocks based on the biodisturbance coefficient of the field outcrops or core samples.

[0103] See Figure 4A third objective of this invention is to provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the quantitative sedimentary rock classification and evaluation method based on bio-disturbance.

[0104] The quantitative sedimentary rock classification and evaluation method based on bio-disturbance includes the following steps:

[0105] Acquire high-resolution images per unit area of ​​field outcrops or core samples;

[0106] Identify trace fossils or areas of biological disturbance in the high-resolution image, and use the unit grid method to obtain the percentage of biological disturbance in the high-resolution image;

[0107] The number of genera of trace fossils in the high-resolution image was identified; the burrow diameter of each trace fossil was measured, and the burrow diameter of the largest trace fossil was obtained.

[0108] Obtain the natural layer thickness and average grain size of the surrounding rock from the field outcrops or core samples;

[0109] The biodisturbance coefficient of the field outcrop or core sample is calculated based on the percentage of biodisturbance, the number of genera of trace fossils, the burrow diameter of the largest trace fossil, the natural layer thickness, and the average grain size of the surrounding rock.

[0110] Based on the biodisturbance coefficient of the field outcrops or core samples, the classification evaluation results of sedimentary rocks are obtained.

[0111] A fourth objective of this invention is to provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the quantitative sedimentary rock classification and evaluation method based on bio-disturbance.

[0112] The quantitative sedimentary rock classification and evaluation method based on bio-disturbance includes the following steps:

[0113] Acquire high-resolution images per unit area of ​​field outcrops or core samples;

[0114] Identify trace fossils or areas of biological disturbance in the high-resolution image, and use the unit grid method to obtain the percentage of biological disturbance in the high-resolution image;

[0115] The number of genera of trace fossils in the high-resolution image was identified; the burrow diameter of each trace fossil was measured, and the burrow diameter of the largest trace fossil was obtained.

[0116] Obtain the natural layer thickness and average grain size of the surrounding rock from the field outcrops or core samples;

[0117] The biodisturbance coefficient of the field outcrop or core sample is calculated based on the percentage of biodisturbance, the number of genera of trace fossils, the burrow diameter of the largest trace fossil, the natural layer thickness, and the average grain size of the surrounding rock.

[0118] Based on the biodisturbance coefficient of the field outcrops or core samples, the classification evaluation results of sedimentary rocks are obtained.

[0119] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0120] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0121] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0122] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0123] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A quantitative classification and evaluation method for sedimentary rocks based on bio-disturbance, characterized in that, include: Acquire high-resolution images per unit area of ​​field outcrops or core samples; Identify trace fossils or areas of biological disturbance in the high-resolution image, and use the unit grid method to obtain the percentage of biological disturbance in the high-resolution image; The number of genera of trace fossils in the high-resolution image was identified; the burrow diameter of each trace fossil was measured, and the burrow diameter of the largest trace fossil was obtained. Obtain the natural layer thickness and average grain size of the surrounding rock from the field outcrops or core samples; The biodisturbance coefficient of the field outcrop or core sample is calculated based on the percentage of biodisturbance, the number of genera of trace fossils, the burrow diameter of the largest trace fossil, the natural layer thickness, and the average grain size of the surrounding rock. Based on the biodisturbance coefficient of the field outcrops or core samples, the classification evaluation results of sedimentary rocks are obtained.

2. The quantitative sedimentary rock classification and evaluation method based on bio-disturbance according to claim 1, characterized in that, The biodisturbance coefficient of the field outcrop or core sample, calculated based on the percentage of biodisturbance, the number of genera of trace fossils, the burrow diameter of the largest trace fossil, the natural layer thickness, and the average grain size of the surrounding rock, is specifically as follows: Biodisturbance coefficient = (Percentage of biodisturbance * Number of genera of trace fossils * Maximum diameter of trace burrows) / (Average grain size of surrounding rock * Thickness of natural layer).

3. The quantitative sedimentary rock classification and evaluation method based on bio-disturbance according to claim 2, characterized in that, Based on the biodisturbance coefficient of the aforementioned field outcrops or core samples, the classification and evaluation results of sedimentary rocks specifically include: When the biodisturbance coefficient is 0, the sedimentary rock is named undisturbed rock; when the biodisturbance coefficient is between 0 and 10, the sedimentary rock is named weakly biodisturbed rock; when the biodisturbance coefficient is between 10 and 40, the sedimentary rock is named poorly biodisturbed rock; when the biodisturbance coefficient is between 40 and 60, the sedimentary rock is named moderately biodisturbed rock; when the biodisturbance coefficient is between 60 and 90, the sedimentary rock is named highly biodisturbed rock; when the biodisturbance coefficient is greater than 90, the sedimentary rock is named strongly biodisturbed rock.

4. The quantitative sedimentary rock classification and evaluation method based on bio-disturbance according to claim 3, characterized in that, The highly biodisturbed rocks and strongly biodisturbed rocks are excellent biodisturbed reservoirs.

5. The quantitative sedimentary rock classification and evaluation method based on bio-disturbance according to claim 1, characterized in that, The high-resolution image is processed for contrast and brightness before identifying trace fossils or areas of biological disturbance in the image.

6. The quantitative sedimentary rock classification and evaluation method based on bio-disturbance according to claim 1, characterized in that, The diameter of the burrow is in mm, and the value is rounded to one decimal place. The unit for the natural layer thickness is m; the unit for the average grain size of the surrounding rock is mm; no unit conversion is performed on the values ​​of the parameters when calculating the bio-disturbance coefficient.

7. The quantitative sedimentary rock classification and evaluation method based on bio-disturbance according to claim 1, characterized in that, The grid size of the unit grid method is proportional to the size of the field outcrop or core sample.

8. A quantitative sedimentary rock classification and evaluation system based on bio-disturbance, characterized in that, include: The image acquisition module is used to acquire high-resolution images per unit area of ​​field outcrops or core samples; A bio-disturbance identification module is used to identify trace fossils or bio-disturbance areas in the high-resolution image and to obtain the percentage of bio-disturbance in the high-resolution image using the unit grid method. The trace fossil identification module is used to identify the number of genera of trace fossils in the high-resolution image; measure the burrow diameter of each trace fossil, and obtain the burrow diameter of the largest trace fossil; The natural layer thickness acquisition module is used to acquire the natural layer thickness and the average grain size of the surrounding rock of the field outcrop or core sample. The biodisturbance coefficient calculation module is used to calculate the biodisturbance coefficient of the field outcrop or core sample based on the percentage of biodisturbance, the number of genera of trace fossils, the burrow diameter of the largest trace fossil, the natural layer thickness, and the average grain size of the surrounding rock. The sedimentary rock classification and evaluation module uses the bio-disturbance coefficient based on the field outcrops or core samples to evaluate the classification and evaluation results of sedimentary rocks.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the steps of the quantitative sedimentary rock classification and evaluation method based on bio-disturbance as described in any one of claims 1-7.

10. A computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the quantitative sedimentary rock classification and evaluation method based on bio-disturbance as described in any one of claims 1-7.

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