Method and apparatus for generating porosity spectra and apparent face porosities based on acoustic imaging images

Abstract

The application discloses a method and device for generating porosity spectrum and apparent face porosity based on acoustic imaging images. The method comprises the following steps: obtaining acoustic imaging images related to formation information according to acoustic signals reflected by a well wall; processing the acoustic imaging images to obtain a porosity spectrum image; distinguishing reservoir background features and secondary pore features of the well in the porosity spectrum image; and calculating apparent face porosity according to the secondary pore features. The method can generate porosity spectrum and quantitatively evaluate apparent face porosity of a well wall by using acoustic imaging images of a well wall, and is simple and easy to implement, and can be rapidly applied.

Description

Technical Field

[0001] This invention relates to the field of acoustic imaging technology, and specifically to a method and apparatus for generating porosity spectrum and visible face ratio based on acoustic imaging images. Background Technology

[0002] Wellbore acoustic imaging logging obtains images of acoustic wave amplitude and propagation time related to formation information by recording the amplitude and propagation time of reflected waves from the wellbore. It is currently widely used in fine reservoir evaluation, particularly for assessing the effectiveness of fractures and pores. However, in recent years, the application of acoustic imaging has stagnated, remaining primarily at the qualitative evaluation level of geological features. Quantitative evaluation relies heavily on resistivity imaging, which significantly hinders the widespread adoption of this instrument.

[0003] For reservoir porosity spectrum evaluation, both domestically and internationally, electrical imaging data has been used for calculation. However, methods for evaluating secondary porosity using well-perimeter acoustic imaging data are relatively rare. In China, Zhang Jie et al. calculated the wave impedance of pixels by combining ultrasonic imaging logging data with formation parameters such as reservoir clay content, thereby calculating the porosity of pixels. Finally, porosity spectra were constructed based on the porosity data to achieve the purpose of reservoir evaluation.

[0004] However, this method requires complex parameters, and some parameters, such as rock skeleton density, skeleton acoustic transit time, and mud wave impedance, cannot be accurately obtained without experimental conditions, making it particularly difficult to implement in the evaluation of complex lithological reservoirs. Summary of the Invention

[0005] In view of the above problems, the present invention is proposed to provide a method and apparatus for generating porosity spectrum and apparent face ratio based on acoustic imaging images to overcome or at least partially solve the above problems.

[0006] According to one aspect of the present invention, a method for generating porosity spectrum and apparent face ratio based on acoustic imaging images is provided, comprising:

[0007] Acoustic imaging images related to formation information are obtained based on the acoustic wave signals reflected from the wellbore during logging.

[0008] The acoustic imaging image is processed to obtain a porosity spectrum image;

[0009] Distinguish between reservoir background features and secondary porosity features in the porosity spectrum image;

[0010] The apparent porosity is calculated based on the secondary porosity characteristics.

[0011] According to another aspect of the present invention, an apparatus for generating porosity spectrum and apparent face ratio based on acoustic imaging images is provided, comprising:

[0012] The acoustic imaging image acquisition module is used to obtain acoustic imaging images related to formation information based on the acoustic wave signals reflected from the wellbore.

[0013] A porosity spectrum image acquisition module is used to process the acoustic imaging image to obtain a porosity spectrum image;

[0014] The feature differentiation module is used to distinguish between the reservoir background features and secondary porosity features of the well logging in the porosity spectrum image;

[0015] The visible porosity calculation module is used to calculate the visible porosity based on the secondary porosity characteristics.

[0016] According to another aspect of the present invention, an electronic device is provided, comprising: a processor, a memory, a communication interface, and a communication bus, wherein the processor, the memory, and the communication interface communicate with each other via the communication bus;

[0017] The memory is used to store at least one executable instruction, which causes the processor to perform the operation corresponding to the method for generating porosity spectrum and apparent face ratio based on acoustic imaging image described in this invention.

[0018] According to another aspect of the present invention, a computer storage medium is provided, the storage medium storing at least one executable instruction, the executable instruction causing a processor to perform operations corresponding to the method of generating porosity spectrum and apparent face ratio based on acoustic imaging image according to the present invention.

[0019] The method and apparatus for generating porosity spectrum and apparent porosity based on acoustic imaging images disclosed in this invention generate porosity spectrum and quantitatively evaluate apparent porosity using acoustic imaging images of the wellbore. This method is simple and easy to implement and can be rapidly promoted and applied.

[0020] The above description is merely an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention and to implement it in accordance with the contents of the specification, and in order to make the above and other objects, features and advantages of the present invention more apparent and understandable, specific embodiments of the present invention are described below. Attached Figure Description

[0021] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings:

[0022] Figure 1A flowchart illustrating a method for generating porosity spectrum and apparent face ratio based on acoustic imaging images according to Embodiment 1 of the present invention is shown.

[0023] Figure 2 A flowchart illustrating a method for generating porosity spectrum and apparent face ratio based on acoustic imaging images according to Embodiment 2 of the present invention is shown.

[0024] Figure 3 This diagram illustrates the natural gamma curve of the preset processing depth segment in a method for generating porosity spectrum and apparent face ratio based on acoustic imaging images according to Embodiment 2 of the present invention.

[0025] Figure 4 This illustrates a pre-processed deep acoustic amplitude image in a method for generating porosity spectrum and apparent face ratio based on acoustic imaging images according to Embodiment 2 of the present invention.

[0026] Figure 5 This diagram illustrates the porosity spectrum corresponding to the amplitude of a preset processing depth in a method for generating porosity spectrum and apparent face ratio based on acoustic imaging images according to Embodiment 2 of the present invention.

[0027] Figure 6 This diagram illustrates the apparent face value corresponding to the amplitude of the preset processing depth in a method for generating porosity spectrum and apparent face value based on acoustic imaging images according to Embodiment 2 of the present invention.

[0028] Figure 7 A flowchart illustrating a method for generating porosity spectrum and apparent face ratio based on acoustic imaging images according to Embodiment 3 of the present invention is shown.

[0029] Figure 8 This illustrates the propagation time image of the preset processing depth in a method for generating porosity spectrum and apparent face ratio based on acoustic imaging images according to Embodiment 3 of the present invention;

[0030] Figure 9 This diagram illustrates the porosity spectrum corresponding to the preset processing depth time in a method for generating porosity spectrum and apparent face ratio based on acoustic imaging images according to Embodiment 3 of the present invention.

[0031] Figure 10 This diagram illustrates the apparent surface area ratio corresponding to the preset processing depth time in a method for generating porosity spectrum and apparent surface area ratio based on acoustic imaging images according to Embodiment 3 of the present invention.

[0032] Figure 11 A schematic diagram of a device for generating porosity spectrum and apparent face ratio based on acoustic imaging images according to Embodiment 4 of the present invention is shown.

[0033] Figure 12 A schematic diagram of the structure of an electronic device according to Embodiment Six of the present invention is shown. Detailed Implementation

[0034] Exemplary embodiments of the invention will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the invention are shown in the drawings, it should be understood that the invention can be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the invention and to fully convey the scope of the invention to those skilled in the art.

[0035] Example 1

[0036] Figure 1 A schematic flowchart of a method for generating porosity spectrum and apparent face ratio based on acoustic imaging images according to Embodiment 1 of the present invention is shown. Figure 1 As shown, the method includes:

[0037] Step S11: Obtain acoustic imaging images related to formation information based on the acoustic wave signals reflected from the wellbore.

[0038] Acoustic imaging images include acoustic amplitude images and / or propagation time images. Specifically, wellbore acoustic imaging logging obtains acoustic amplitude images and propagation time images related to formation information by recording acoustic signals reflected from the wellbore (including the amplitude of the emitted echo and the propagation time).

[0039] Step S12: Process the acoustic imaging image to obtain a porosity spectrum image.

[0040] Specifically, when the acoustic imaging image is a sound wave amplitude image, processing the sound wave amplitude image can yield a porosity spectrum image corresponding to the amplitude. When the acoustic imaging image is a propagation time image, processing the propagation time image can yield a porosity spectrum image corresponding to the propagation time.

[0041] Step S13: Distinguish between reservoir background features and secondary porosity features in the porosity spectrum image.

[0042] The porosity spectrum image includes both reservoir background features and secondary porosity features. If the reservoir has not undergone any secondary changes after formation, such as dissolution, recrystallization, dolomitization, or tectonic stress that produce pores or fractures, then the porosity spectrum image only contains reservoir background features. Conversely, if the reservoir has undergone the aforementioned secondary changes that produce pores or fractures, including dissolution porosity, most intergranular pores, tectonic fractures, interlayer fractures, sub-dissolution fractures, and breccia pores, then the porosity spectrum image contains both reservoir background features and secondary porosity features. In this case, to analyze the pore size or fracture depth caused by secondary changes, it is necessary to distinguish between reservoir background features and secondary porosity features.

[0043] Step S14: Calculate the apparent porosity based on the secondary porosity characteristics.

[0044] Specifically, when the acoustic imaging image is an amplitude image of sound waves, the secondary porosity features corresponding to the amplitude are first identified based on the porosity spectrum image corresponding to the amplitude, and then the apparent porosity is calculated based on the secondary porosity features corresponding to the amplitude. When the acoustic imaging image is a propagation time image, the secondary porosity features corresponding to the time are first identified based on the porosity spectrum image corresponding to the time, and then the apparent porosity is calculated based on the secondary porosity features corresponding to the time.

[0045] Therefore, this embodiment utilizes wellbore acoustic imaging images to generate porosity spectra and quantitatively evaluate the visible porosity of the wellbore. This method is simple, easy to implement, and can be rapidly promoted and applied.

[0046] In an optional embodiment, step S12 specifically includes:

[0047] Based on the preset processing depth of well logging, histogram statistics are performed on the acoustic imaging image according to the propagation characteristics of acoustic waves on the well wall in the preset processing depth according to a preset threshold, and the statistical results are presented in the form of a spectrum to obtain a porosity spectrum image.

[0048] The preset thresholds represent the number of fixed points and the preset step size selected when processing acoustic imaging images of a preset depth range in well logging. The number of fixed points affects the smoothness of the spectral shape, while the step size affects the height of the spectral shape. When the acoustic imaging image is an amplitude image, the number of fixed amplitude points is represented by AMP-samples, the amplitude step size by AMP-step, and AMP-samples*AMP-step > the maximum value of the amplitude range. When the acoustic imaging image is a propagation time image, the number of fixed time points is represented by TT-samples, the time step size by TT-step, and TT-samples*TT-step > the maximum value of the time range.

[0049] Specifically, when the acoustic imaging image is an amplitude image, utilizing the propagation characteristics of sound waves on the well wall, the amplitude image is first statistically analyzed using histograms with a fixed number of points and a preset step size. The results are then displayed in spectral form, thus obtaining the porosity spectral image corresponding to the amplitude. When the acoustic imaging image is a propagation time image, utilizing the propagation characteristics of sound waves on the well wall, the propagation time image is first statistically analyzed using histograms with a fixed number of points and a preset step size. The results are then displayed in spectral form, thus obtaining the porosity spectral image corresponding to the time.

[0050] In an optional embodiment, step S13 specifically includes:

[0051] The cutoff value of reservoir background characteristics based on the preset processing depth of well logging distinguishes reservoir background characteristics from secondary porosity characteristics.

[0052] The cutoff value is set based on the apparent porosity of the dense layer in the preset treatment depth. Specifically, in the absence of experimental data for calibration, the apparent porosity of the dense layer is adjusted to near 0 by adjusting the cutoff value. At this point, the result of the preset treatment depth can be approximately considered as the apparent porosity of the formation.

[0053] In an optional embodiment, step S14 specifically includes:

[0054] Step S141: Search for the number of target depth points in the preset processing depth segment whose target depth is greater than the cutoff value based on the secondary porosity characteristics.

[0055] Step S142: Determine the view surface ratio at the target depth based on the target depth point count and the total number of depth points in the preset processing depth segment.

[0056] Specifically, the target depth point count can be divided by the total number of data points at that depth to obtain the view surface rate at the target depth. Similarly, the view surface rate of each depth point in the preset processing depth segment can be calculated sequentially.

[0057] Example 2

[0058] Figure 2 A schematic flowchart illustrating a method for generating porosity spectrum and apparent face value based on acoustic imaging images according to Embodiment 2 of the present invention is shown. This embodiment is an application scenario where the acoustic imaging image corresponds to a sound wave amplitude image. Figure 2 As shown, the method includes:

[0059] Step S21: Obtain an acoustic amplitude image related to formation information based on the acoustic wave signal reflected from the deep section wellbore by the preset processing of the well logging.

[0060] like Figure 3As shown, this is the natural gamma curve corresponding to the preset processing depth. The acoustic signal reflected from the wellbore wall at this preset processing depth is used to obtain... Figure 4 The image shown is an acoustic amplitude image related to stratigraphic information.

[0061] Step S22: Utilizing the propagation characteristics of sound waves on the well wall, the sound wave amplitude image is statistically analyzed using histograms according to a fixed number of points and step size. The results are then presented in the form of a spectrum to obtain the porosity spectrum image corresponding to the amplitude.

[0062] Taking the UXPL ultrasonic imaging instrument as an example, the preset processing depth amplitude values ​​are mainly between 1000-3000 (where the larger the amplitude value, the denser the lithology and the worse the porosity, and vice versa). With 192 data points per depth, a histogram is plotted on the amplitude data at each depth using a fixed number of points (50) and a step size of 65. This yields a frequency distribution map of the amplitude data in different amplitude ranges. Presenting this map in spectral form provides the desired results. Figure 5 The porosity distribution spectrum corresponding to the amplitude shown.

[0063] Step S23: Select an appropriate reservoir background amplitude cutoff value to distinguish between reservoir background features and secondary porosity features in the porosity spectrum image corresponding to the amplitude.

[0064] Specifically, the target depth points in the porosity spectrum image corresponding to the amplitude, where the target depth is greater than the cutoff value, can be taken as the depth points corresponding to the secondary porosity features; conversely, the remaining depth points can be taken as the depth points corresponding to the reservoir background features.

[0065] Step S24: Divide the number of target depth points by the total number of data points at that depth as the view surface rate at that target depth.

[0066] like Figure 6 As shown, this is the porosity distribution spectrum corresponding to the amplitude of each depth point obtained based on the above example.

[0067] This embodiment generates a porosity spectrum from the acoustic amplitude image using histogram statistics, and selects a reasonable amplitude cutoff value to distinguish between reservoir background features and secondary porosity features, thereby achieving the purpose of calculating the apparent porosity. This method is simple and easy to implement, and can be rapidly promoted and applied.

[0068] Example 3

[0069] Figure 7 A flowchart illustrating a method for generating porosity spectra and apparent face ratios based on acoustic imaging images according to Embodiment 3 of the present invention is shown. This embodiment is an application scenario where the acoustic imaging image corresponds to a propagation time image. Figure 7 As shown, the method includes:

[0070] Step S31: Obtain a propagation time image related to formation information based on the acoustic wave signal reflected from the deep section wellbore by the preset processing of the well logging.

[0071] like Figure 3 As shown, this is the natural gamma curve corresponding to the preset processing depth. The acoustic signal reflected from the wellbore wall at this preset processing depth is used to obtain... Figure 8 The image shown is a propagation time image related to stratigraphic information.

[0072] Step S32: Utilizing the propagation characteristics of sound waves on the well wall, the propagation time image is statistically analyzed using histograms according to a fixed number of points and step size. The results are then presented in the form of a spectrum to obtain the porosity spectrum image corresponding to the time.

[0073] Taking the UXPL ultrasonic imaging instrument as an example, the preset propagation time range for the deep processing segment is 800-1300 microseconds (where a shorter time results in a brighter image, indicating a smoother wellbore; a longer time indicates better development of wellbore fractures and pores). Each depth has 192 data points. Using a fixed number of points (70) and a step size of 20, histograms are plotted on the time data at each depth to obtain the frequency distribution of data across different time intervals. Presenting this graph in spectral form yields the following results: Figure 9 The porosity distribution spectrum corresponding to the time shown is shown.

[0074] Step S33: Select an appropriate reservoir background time cutoff value and distinguish between reservoir background features and secondary porosity features in the porosity spectrum image corresponding to the time.

[0075] Specifically, the target depth points in the porosity spectrum image corresponding to the time can be taken as the depth points corresponding to the secondary porosity features if the target depth is greater than the cutoff value, and conversely, the remaining depth points can be taken as the depth points corresponding to the reservoir background features.

[0076] Step S34: Divide the number of target depth points by the total number of data points at that depth as the view surface rate at that target depth.

[0077] like Figure 10 As shown, this is the porosity distribution spectrum corresponding to the propagation time at each depth point obtained based on the above example.

[0078] This embodiment generates a porosity spectrum from the propagation time image using histogram statistics, and selects a reasonable time cutoff value to distinguish between reservoir background features and secondary porosity features, thereby achieving the purpose of calculating the apparent porosity. This method is simple and easy to implement, and can be rapidly promoted and applied.

[0079] Example 4

[0080] Figure 11A schematic diagram of an apparatus for generating porosity spectra and apparent face ratios based on acoustic imaging images, according to Embodiment 4 of the present invention, is shown. Figure 11 As shown, the device includes: an acoustic imaging image acquisition module 41, a porosity spectrum image acquisition module 42, a feature differentiation module 43, and a visible face rate calculation module 44; wherein,

[0081] The acoustic imaging image acquisition module 41 is used to obtain acoustic imaging images related to formation information based on the acoustic wave signals reflected from the wellbore.

[0082] The porosity spectrum image acquisition module 42 is used to process the acoustic imaging image to obtain the porosity spectrum image;

[0083] The feature differentiation module 43 is used to differentiate between the reservoir background features and secondary porosity features of the well logging in the porosity spectrum image;

[0084] The visible porosity calculation module 44 is used to calculate the visible porosity based on the secondary porosity characteristics.

[0085] Furthermore, the porosity spectrum image acquisition module 42 is specifically used to: based on the preset processing depth of the well logging, perform histogram statistics on the acoustic imaging image according to the propagation characteristics of the sound wave on the well wall in the preset processing depth according to a preset threshold, and display the statistical results in the form of a spectrum to obtain a porosity spectrum image.

[0086] Furthermore, the feature differentiation module 43 is specifically used to: differentiate reservoir background features from secondary porosity features based on the cutoff value of the reservoir background features in the preset processing depth of the well logging.

[0087] Furthermore, the visible porosity calculation module 44 is specifically used to: search for the number of target depth points in the preset processing depth segment whose target depth is greater than the cutoff value based on the secondary porosity features; and determine the visible porosity at the target depth based on the number of target depth points and the total number of depth points in the preset processing depth segment.

[0088] Furthermore, the cutoff value is set according to the apparent surface area ratio of the preset deep dense layer.

[0089] Furthermore, the acoustic imaging image includes an acoustic amplitude image and / or a propagation time image.

[0090] Furthermore, the preset threshold is the fixed number of points and preset step size selected when processing the acoustic imaging image of the preset processing depth of the well logging.

[0091] The apparatus for generating porosity spectrum and visible porosity based on acoustic imaging images described in this embodiment is used to execute the method for generating porosity spectrum and visible porosity based on acoustic imaging images described in Embodiment 1 above. Its working principle and technical effect are similar, and will not be repeated here.

[0092] Example 5

[0093] Embodiment 5 of the present invention provides a non-volatile computer storage medium storing at least one executable instruction that can execute the method for generating porosity spectrum and apparent face value based on acoustic imaging image in any of the above method embodiments.

[0094] Example 6

[0095] Figure 12 A schematic diagram of an electronic device according to Embodiment 8 of the present invention is shown. The specific embodiments of the present invention do not limit the specific implementation of the electronic device.

[0096] like Figure 12 As shown, the electronic device may include: a processor 502, a communications interface 504, a memory 506, and a communications bus 508.

[0097] The processor 502, communication interface 504, and memory 506 communicate with each other via communication bus 508. Communication interface 504 is used to communicate with other network elements such as clients or other servers. The processor 502 executes program 510, specifically performing the relevant steps in the above method embodiments.

[0098] Specifically, program 510 may include program code that includes computer operation instructions.

[0099] Processor 502 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement embodiments of the present invention. The electronic device may include one or more processors of the same type, such as one or more CPUs; or it may include processors of different types, such as one or more CPUs and one or more ASICs.

[0100] Memory 506 is used to store program 510. Memory 506 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0101] Specifically, program 510 can be used to cause processor 502 to execute the method for generating porosity spectrum and apparent face ratio based on acoustic imaging images in any of the above method embodiments.

[0102] The algorithms or displays provided herein are not inherently related to any particular computer, virtual system, or other device. Various general-purpose systems can also be used in conjunction with the teachings herein. The required structure for constructing such systems is apparent from the above description. Furthermore, the embodiments of the present invention are not directed to any particular programming language. It should be understood that the content of the invention described herein can be implemented using various programming languages, and the above description of specific languages ​​is for the purpose of disclosing the best mode of implementation of the invention.

[0103] Numerous specific details are set forth in the specification provided herein. However, it will be understood that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures, and techniques have not been shown in detail so as not to obscure the understanding of this specification.

[0104] Similarly, it should be understood that, in order to simplify the invention and aid in understanding one or more of the various inventive aspects, features of the embodiments of the invention are sometimes grouped together in a single embodiment, figure, or description thereof in the above description of exemplary embodiments of the invention. However, this disclosure should not be construed as reflecting an intention that the claimed invention requires more features than are expressly recited in each claim. Rather, as reflected in the following claims, inventive aspects lie in fewer than all features of a single foregoing disclosed embodiment. Therefore, the claims following the detailed description are hereby expressly incorporated into this detailed description, wherein each claim itself is a separate embodiment of the invention.

[0105] Those skilled in the art will understand that modules in the device of the embodiments can be adaptively changed and placed in one or more devices different from that embodiment. Modules, units, or components in the embodiments can be combined into a single module, unit, or component, and further, they can be divided into multiple sub-modules, sub-units, or sub-components. Except where at least some of such features and / or processes or units are mutually exclusive, any combination can be used to combine all features disclosed in this specification (including the accompanying claims, abstract, and drawings) and all processes or units of any method or device so disclosed. Unless expressly stated otherwise, each feature disclosed in this specification (including the accompanying claims, abstract, and drawings) may be replaced by an alternative feature that serves the same, equivalent, or similar purpose.

[0106] Furthermore, those skilled in the art will understand that although some embodiments herein include certain features included in other embodiments but not others, combinations of features from different embodiments are intended to be within the scope of the invention and form different embodiments. For example, in the following claims, any of the claimed embodiments can be used in any combination.

[0107] The various component embodiments of the present invention can be implemented in hardware, or as software modules running on one or more processors, or a combination thereof. Those skilled in the art will understand that microprocessors or digital signal processors (DSPs) can be used in practice to implement some or all of the functions of some or all of the components according to the embodiments of the present invention. The present invention can also be implemented as a device or apparatus program (e.g., a computer program and computer program product) for performing part or all of the methods described herein. Such programs implementing the present invention can be stored on a computer-readable medium, or can be in the form of one or more signals. Such signals can be downloaded from an Internet website, provided on a carrier signal, or provided in any other form.

[0108] It should be noted that the above embodiments are illustrative of the invention and not restrictive, and that those skilled in the art can devise alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses should not be construed as limiting the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention can be implemented by means of hardware comprising several different elements and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by the same item of hardware. The use of the words first, second, and third, etc., does not indicate any order. These words can be interpreted as names. The steps in the above embodiments, unless otherwise specified, should not be construed as limiting the order of execution.

Claims

1. A method for generating porosity spectrum and apparent face ratio based on acoustic imaging images, characterized in that, include: Acoustic imaging images related to formation information are obtained based on the acoustic wave signals reflected from the wellbore during logging. The acoustic imaging image is processed to obtain a porosity spectrum image; The reservoir background features are distinguished from secondary porosity features based on the cutoff value of the reservoir background features in the preset treatment depth of the well logging; wherein, the cutoff value is set according to the apparent porosity of the tight layer in the preset treatment depth. Based on the secondary porosity features, search for the number of target depth points in the preset processing depth segment whose target depth is greater than the cutoff value; The face density at the target depth is determined based on the target depth point count and the total depth point count in the preset processing depth segment.

2. The method according to claim 1, characterized in that, The process of processing the acoustic imaging image to obtain a porosity spectrum image includes: Based on the preset processing depth of the well logging, the acoustic imaging image is statistically analyzed using a preset threshold according to the propagation characteristics of the acoustic wave on the well wall in the preset processing depth, and the statistical results are presented in the form of a spectrum to obtain a porosity spectrum image.

3. The method according to claim 1 or 2, characterized in that, The acoustic imaging image includes an acoustic amplitude image and / or a propagation time image.

4. The method according to claim 2, characterized in that, The preset threshold is the fixed number of points and preset step size selected when processing the acoustic imaging image of the preset processing depth of the well logging.

5. A device for generating porosity spectrum and apparent face ratio based on acoustic imaging images, characterized in that, include: The acoustic imaging image acquisition module is used to obtain acoustic imaging images related to formation information based on the acoustic wave signals reflected from the wellbore. A porosity spectrum image acquisition module is used to process the acoustic imaging image to obtain a porosity spectrum image; The feature differentiation module is used to distinguish between the reservoir background features and secondary porosity features of the well logging in the porosity spectrum image; The feature differentiation module is specifically used to: differentiate reservoir background features from secondary porosity features based on the cutoff value of the reservoir background features in the preset processing depth of the well logging. The cutoff value is set according to the apparent surface area ratio of the preset deep dense layer. A visible porosity calculation module is used to calculate the visible porosity based on the secondary porosity characteristics. The visible porosity calculation module is specifically used for: searching for the number of target depth points in the preset processing depth segment whose target depth is greater than the cutoff value based on the secondary porosity features; and determining the visible porosity at the target depth based on the number of target depth points and the total number of depth points in the preset processing depth segment.

6. An electronic device, comprising: The processor, memory, communication interface, and communication bus are provided, wherein the processor, memory, and communication interface communicate with each other via the communication bus. The memory is used to store at least one executable instruction that causes the processor to perform the operation corresponding to the method for generating porosity spectrum and apparent face ratio based on acoustic imaging image as described in any one of claims 1-4.

7. A computer storage medium storing at least one executable instruction that causes a processor to perform operations corresponding to the method for generating porosity spectrum and apparent face ratio based on acoustic imaging images as described in any one of claims 1-4.

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