Stratum vertical thickness rule analysis method and device, electronic equipment and storage medium

Abstract

The invention discloses a stratum vertical thickness rule analysis method and device, electronic equipment and a storage medium. The method comprises the steps that a target stratum is divided into a plurality of unit stratums and the stratum thickness of each unit stratum according to lithology data in logging data; determining target thickness change information according to the stratum thickness of each unit stratum corresponding to the target stratum from bottom to top, and determining a target power spectrum of the target stratum according to the target thickness change information; determining a first preset number of candidate stratums, determining candidate thickness change information of the candidate stratums according to the stratum thickness of each unit stratum corresponding to the candidate stratums from bottom to top, and determining candidate power spectrums of the candidate stratums according to the candidate thickness change information; and determining a target probability value according to the target power spectrum and the candidate power spectrum, and reflecting whether the stratum thickness change of the target stratum is a periodic change rule or not according to the target probability value. According to the scheme, the periodicity of vertical stratum thickness change is effectively identified and distinguished.

Description

Technical Field

[0001] The invention relates to the technical field of sedimentary geology, and in particular to a method, device, electronic equipment and storage medium for analyzing vertical thickness rules of strata. Background Art

[0002] Sedimentary rocks often have "cyclical" characteristics in the vertical direction, that is, the strata have a repetitive, identifiable, upward trend in lithology or thickness. The vertical variation of stratum thickness records important information about the water environment and basin evolution during deposition, but the definition and interpretation of the "cyclical" nature of sedimentary stratum thickness are often based on qualitative analysis, which is relatively subjective and has considerable uncertainty. The understanding and interpretation of the law of vertical lithology variation is to conform to the assumptions of sequence stratigraphy, ignoring the objective law of stratum thickness variation, which brings difficulties and uncertainties to the construction of the basin sedimentary stratigraphic framework, the comparison of strata from different wells, and the verification of existing geological knowledge. Summary of the invention

[0003] The present invention provides a method, device, electronic equipment and storage medium for analyzing the vertical thickness law of formations, so as to effectively identify and distinguish the periodicity of vertical formation thickness changes.

[0004] According to one aspect of the present invention, a method for analyzing vertical thickness regularity of a stratum is provided, the method comprising:

[0005] Obtaining logging data of a target stratum, dividing the target stratum into a plurality of unit strata according to lithology data in the logging data, and determining the stratum thickness of each unit stratum;

[0006] Determine target thickness variation information according to the formation thickness of each unit formation corresponding to the target formation from bottom to top, and determine the target power spectrum of the target formation according to the target thickness variation information;

[0007] Determine a first preset number of candidate strata; the candidate strata are obtained by exchanging positions of a second preset number of unit strata with different lithologies in the target strata;

[0008] Determine candidate thickness variation information of the candidate stratum according to the stratum thickness of each of the unit strata corresponding to the candidate stratum from bottom to top, and determine a candidate power spectrum of the candidate stratum according to the candidate thickness variation information;

[0009] A target probability value is determined according to the target power spectrum and the candidate power spectrum, and the target probability value reflects whether the change in the thickness of the target stratum is a periodic change law; the target probability value is used to describe the probability of the target power spectrum overlapping with all the candidate power spectra.

[0010] According to another aspect of the present invention, a device for analyzing vertical thickness regularity of formations is provided, the device comprising:

[0011] A formation thickness determination module is used to obtain logging data of a target formation, divide the target formation into a plurality of unit formations according to lithology data in the logging data, and determine the formation thickness of each unit formation;

[0012] A first power spectrum determination module is used to determine target thickness variation information according to the formation thickness of each unit formation corresponding to the target formation from bottom to top, and determine a target power spectrum of the target formation according to the target thickness variation information;

[0013] A candidate stratum determination module is used to determine a first preset number of candidate strata; the candidate strata are obtained by exchanging the positions of a second preset number of unit strata with different lithologies in the target stratum;

[0014] A second power spectrum determination module is used to determine candidate thickness variation information of the candidate stratum according to the stratum thickness of each of the unit strata corresponding to the candidate stratum from bottom to top, and determine a candidate power spectrum of the candidate stratum according to the candidate thickness variation information;

[0015] An analysis module is used to determine a target probability value based on the target power spectrum and the candidate power spectrum, and to reflect whether the change in the thickness of the target formation follows a periodic variation pattern based on the target probability value; the target probability value is used to describe the probability that the target power spectrum coincides with all the candidate power spectra.

[0016] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0017] at least one processor; and

[0018] a memory communicatively connected to the at least one processor; wherein,

[0019] The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the method for analyzing the vertical thickness law of the formation described in any embodiment of the present invention.

[0020] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the method for analyzing the vertical thickness regularity of formations described in any embodiment of the present invention when executed.

[0021] The technical solution of the embodiment of the present invention obtains logging data of the target stratum, divides the target stratum into multiple unit strata according to the lithology data in the logging data, and determines the stratum thickness of each unit stratum; the present invention takes the logging lithology data as the starting point, overcomes the problem that the gamma curve data is large in amount, does not directly reflect the lithology, and requires preprocessing and correction; then determines the target thickness change information according to the stratum thickness of each unit stratum corresponding to the target stratum from bottom to top, and determines the target power spectrum of the target stratum according to the target thickness change information; determines a first preset number of candidate strata; the candidate strata are obtained by exchanging the positions of a second preset number of unit strata with different lithologies in the target stratum; and determines the target power spectrum of the target stratum according to the target thickness change information. The stratum thickness determines the candidate thickness change information of the candidate stratum, and determines the candidate power spectrum of the candidate stratum according to the candidate thickness change information; that is, the present invention recalculates the power spectrum of the disrupted stratum, and constructs a probability density function, and compares it with the original undisrupted target stratum, which can completely eliminate contingency; further determines the target probability value according to the target power spectrum and the candidate power spectrum, and reflects whether the stratum thickness change of the target stratum is a periodic change law according to the target probability value; the target probability value is used to describe the probability of the target power spectrum coinciding with all the candidate power spectra, that is, the present invention is flexible in use, the principle is simple and easy to use, the result is objective, reproducible and easy to understand, and can quickly and effectively identify and distinguish the periodicity of vertical stratum thickness changes.

[0022] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0024] Figure 1 is a flow chart of a method for analyzing vertical thickness rules of formations provided according to an embodiment of the present invention;

[0025] Figure 2 is a schematic diagram of an example of a target formation applicable to an embodiment of the present invention;

[0026] Figure 3 is a schematic diagram of an example of target thickness variation information applicable to an embodiment of the present invention;

[0027] Figure 4is a power spectrum of a target stratum applicable to an embodiment of the present invention and a probability density function corresponding to a candidate stratum;

[0028] Figure 5 is a schematic diagram of target probability values ​​applicable according to an embodiment of the present invention;

[0029] Figure 6 It is a schematic diagram after analyzing a certain well layer section in a reference area using a formation vertical thickness law analysis method applicable to an embodiment of the present invention;

[0030] Figure 7 It is a schematic structural diagram of a device for analyzing vertical thickness regularity of a stratum provided according to an embodiment of the present invention;

[0031] Figure 8 It is a schematic diagram of the structure of an electronic device for implementing the method for analyzing vertical thickness regularity of formations according to an embodiment of the present invention. DETAILED DESCRIPTION

[0032] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0033] It should be noted that the terms "target", "candidate", "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0034] Embodiment 1

[0035] Figure 1The present invention provides a flowchart of a method for analyzing the vertical thickness law of a stratum. This embodiment is applicable to the case of analyzing the vertical thickness law of a stratum. The method can be executed by a device for analyzing the vertical thickness law of a stratum. The device for analyzing the vertical thickness law of a stratum can be implemented in the form of hardware and / or software. The device for analyzing the vertical thickness law of a stratum can be configured in any electronic device with a network communication function. Figure 1 As shown, the method for analyzing the vertical thickness law of formations of the present invention includes:

[0036] S110, acquiring logging data of a target stratum, dividing the target stratum into a plurality of unit strata according to lithology data in the logging data, and determining the stratum thickness of each unit stratum.

[0037] Among them, all unit formations constitute the target formation, each unit formation corresponds to a lithology, and the lithology data includes the particle size of rock particles in the formation. Lithology data is mainly controlled by the particle size of rock particles and reflects the characteristics of the sedimentary environment. Mud logging data is a variety of information collected and recorded in real time during the wellbore drilling process in the process of oil and gas exploration and development. It is very important for understanding underground geological conditions, evaluating the potential of oil and gas resources, and guiding drilling operations. The present invention takes logging lithology data as the starting point, which can overcome the problems of large gamma curve data volume, not directly reflecting lithology, and requiring preprocessing and correction.

[0038] Specifically, the target formation is a formation with a preset formation thickness. The lithology of the formations with a certain thickness in the target formation is consistent, and the formation corresponding to the thickness is a unit formation. Therefore, the logging data of the target formation is obtained, and the lithology data in the logging data is analyzed, so that the target formation can be divided into multiple unit formations from bottom to top, and the formation thickness of the unit formation can be accurately determined based on the logging data corresponding to the unit formation.

[0039] S120, determining target thickness variation information according to the thickness of each unit stratum corresponding to the target stratum from bottom to top, and determining a target power spectrum of the target stratum according to the target thickness variation information.

[0040] The target thickness variation information is used to describe the numerical information of the thickness of each unit layer of the target layer arranged in order from bottom to top. Figure 2 Taking the target stratum as an example, Figure 3 yes Figure 2 Schematic diagram of target thickness change information corresponding to the target formation, such as Figure 4 The black curve shown is Figure 3 The target power spectrum of the target formation obtained after information processing.

[0041] Accordingly, the target thickness variation information is determined according to the stratum thickness of each unit stratum corresponding to the target stratum from bottom to top, including: converting the stratum thickness of each unit stratum corresponding to the target stratum from bottom to top into a target one-dimensional array, and using the target one-dimensional array as the target thickness variation information of the target stratum. The target one-dimensional array can be a one-dimensional random number matrix that obeys a standard normal distribution.

[0042] Further, the target power spectrum of the target formation is determined according to the target thickness change information, including: performing a one-dimensional fast Fourier transform on the target thickness change information to obtain target Fourier change information, and taking the square of the modulus of the target Fourier change information as the target power spectrum of the target formation.

[0043] S130, determining a first preset number of candidate strata; the candidate strata are obtained by exchanging the positions of a second preset number of unit strata with different lithologies in the target strata.

[0044] Specifically, there is randomness in the vertical thickness law of the power spectrum analysis of the target stratum determined separately. Therefore, a second preset number of unit strata with different lithologies are selected from the target stratum, and the operation of selecting the second preset number of unit strata with different lithologies is performed for the first preset number of times, and the operation of exchanging the positions of the second preset number of unit strata with different lithologies in the target stratum is performed, so as to obtain the first preset number of candidate strata, thereby ensuring data diversity.

[0045] S140, determining candidate thickness variation information of the candidate stratum according to the stratum thicknesses of each unit stratum corresponding to the candidate stratum from bottom to top, and determining a candidate power spectrum of the candidate stratum according to the candidate thickness variation information.

[0046] Specifically, the stratum thickness of each unit stratum corresponding to the candidate stratum from bottom to top is converted into a candidate one-dimensional array, and the candidate one-dimensional array is used as the candidate thickness change information of the candidate stratum, wherein the candidate one-dimensional array can be a one-dimensional random number matrix obeying a standard normal distribution. A one-dimensional fast Fourier transform is performed on the candidate thickness change information to obtain the candidate Fourier change information, and the square of the modulus of the candidate Fourier change information is used as the candidate power spectrum of the candidate stratum.

[0047] S150, determining a target probability value according to the target power spectrum and the candidate power spectra, and reflecting whether the change in the thickness of the target stratum is a periodic change law according to the target probability value; the target probability value is used to describe the probability of the target power spectrum coinciding with all candidate power spectra.

[0048] The target probability value can be understood as statistical significance, that is, the significance between the target stratum and the candidate stratum.

[0049] Specifically, all candidate power spectra are processed by Monte Carlo method to construct probability density functions, which are used to reflect the probability of different candidate power spectra appearing in all candidate power spectra; the target probability value is determined according to the target power spectrum and the probability density function, that is, the target probability value is reflected according to the overlap between the target power spectrum and the probability density function. Figure 2 Based on the target stratum, a first preset number of candidate strata are obtained by exchanging the positions of a second preset number of unit strata with different lithologies in the target stratum for a first preset number of times, thereby determining candidate thickness change information of the candidate strata according to the stratum thickness of each unit stratum corresponding to the candidate stratum from bottom to top, and determining a candidate power spectrum of the candidate stratum according to the candidate thickness change information, and further processing all candidate power spectra using the Monte Carlo method to construct a probability density function, such as Figure 4 The red and yellow areas shown are probability density functions.

[0050] Optionally, determining the target probability value according to the target power spectrum and the probability density function includes: determining the overlap between the target power corresponding to each stratum thickness in the target power spectrum and the probability density function; if the overlap is a first preset value, the target probability value of the stratum thickness corresponding to the target power spectrum is the first preset value; if the overlap is a second preset value, the target probability value of the stratum thickness corresponding to the target power spectrum is the second preset value. The first preset value may be 0, and the second preset value may be 1.

[0051] The coincidence degree can be understood as the target power exceeding the preset value of the reference power indicated in the probability density function at the corresponding formation thickness. The preset value can be the maximum power indicated in the probability density function. Figure 4 For example, taking layer 5 as an example, the target power of the target layer is 16. If the reference power indicated by layer 5 in the probability density function is the maximum power indicated in the probability density function, then the reference power is 10. 16 is greater than 10, which means that the target power corresponding to each layer thickness in the target power spectrum does not coincide with the probability density function, and the coincidence degree is 0; taking layer 10 as an example, the target power of the target layer is 0, and the reference power is 10, which means that the target power corresponding to each layer thickness in the target power spectrum coincides with the probability density function, and the coincidence degree is 1. By analyzing the coincidence degree between the power corresponding to each unit layer in the power spectrum of the target layer and the probability density function, the target probability value of each unit layer in the target layer can be obtained, such as Figure 5 shown.

[0052] Furthermore, whether the change in the formation thickness of the target formation is a periodic change pattern is reflected according to the target probability value, including: when the target probability value is a first preset value, it is determined that the change in the formation thickness of the target formation is a periodic change pattern; when the target probability value is a second preset value, it is determined that the change in the formation thickness of the target formation is not a periodic change pattern.

[0053] For example, Figure 3 As shown in FIG. 1 , if the target stratum is composed of 18 identical anticycles, each anticycle contains five small units (n=5), and the stratum thickness of the unit stratum is 0.25, 0.5, 1, 2 and 4 meters, increasing upwards. Figure 4 As shown in Figure 1, the power spectrum results show that the target stratum has the strongest power when the number of layers is equal to 5, and significantly exceeds the power corresponding to the probability density function of the random stratum, which well reflects the periodicity of the anti-cycle in the thickness change of the target stratum (n=5). Figure 5 This was further confirmed by the changes in P values ​​with different cycles (frequencies).

[0054] The vertical thickness law analysis method of the present invention is further applied to a certain layer section in the reference area, such as Figure 6 As shown in Figure 2, significant differences were also found in the selected intervals located in two wells in the same structure: interval 1 showed weak periodicity in layers 16 to 40 ( Figure 6 A), while the second layer has a strong peak near layer number = 5 ( Figure 6 Figure B). This proves that the vertical thickness law analysis method of the present invention also has good discrimination and applicability in real strata, that is, the vertical thickness law analysis method of the present invention can effectively distinguish the periodicity and difference in the thickness changes of the two. This is of great significance for clarifying how strata with periodic characteristics are controlled by potential factors, and further understanding the inheritance, periodicity and difference of the spatial distribution of sedimentary systems.

[0055] The technical solution of the embodiment of the present invention obtains logging data of the target stratum, divides the target stratum into multiple unit strata according to the lithology data in the logging data, and determines the stratum thickness of each unit stratum; the present invention takes the logging lithology data as the starting point, overcomes the problem that the gamma curve data is large in amount, does not directly reflect the lithology, and requires preprocessing and correction; then determines the target thickness change information according to the stratum thickness of each unit stratum corresponding to the target stratum from bottom to top, and determines the target power spectrum of the target stratum according to the target thickness change information; determines a first preset number of candidate strata; the candidate strata are obtained by exchanging the positions of a second preset number of unit strata with different lithologies in the target stratum; and determines the target power spectrum of the target stratum according to the target thickness change information. The stratum thickness determines the candidate thickness change information of the candidate stratum, and determines the candidate power spectrum of the candidate stratum according to the candidate thickness change information; that is, the present invention recalculates the power spectrum of the disrupted stratum, and constructs a probability density function, and compares it with the original undisrupted target stratum, which can completely eliminate contingency; further determines the target probability value according to the target power spectrum and the candidate power spectrum, and reflects whether the stratum thickness change of the target stratum is a periodic change law according to the target probability value; the target probability value is used to describe the probability of the target power spectrum coinciding with all the candidate power spectra, that is, the present invention is flexible in use, the principle is simple and easy to use, the result is objective, reproducible and easy to understand, and can quickly and effectively identify and distinguish the periodicity of vertical stratum thickness changes.

[0056] Embodiment 2

[0057] Figure 7 The schematic diagram of the structure of a device for analyzing the vertical thickness law of a stratum provided in an embodiment of the present invention is applicable to the case of analyzing the vertical thickness law of a stratum. The device for analyzing the vertical thickness law of a stratum can be implemented in the form of hardware and / or software. The device for analyzing the vertical thickness law of a stratum can be configured in any electronic device with a network communication function. Figure 3 As shown, the stratum vertical thickness regularity analysis device of the present invention comprises:

[0058] The formation thickness determination module 210 is used to obtain logging data of the target formation, divide the target formation into a plurality of unit formations according to the lithology data in the logging data, and determine the formation thickness of each unit formation;

[0059] A first power spectrum determination module 220 is used to determine target thickness variation information according to the formation thickness of each unit formation corresponding to the target formation from bottom to top, and determine a target power spectrum of the target formation according to the target thickness variation information;

[0060] A candidate stratum determination module 230 is used to determine a first preset number of candidate strata; the candidate strata are obtained by exchanging the positions of a second preset number of unit strata with different lithologies in the target stratum;

[0061] A second power spectrum determination module 240 is used to determine candidate thickness variation information of the candidate stratum according to the stratum thickness of each of the unit strata corresponding to the candidate stratum from bottom to top, and determine a candidate power spectrum of the candidate stratum according to the candidate thickness variation information;

[0062] The analysis module 250 is used to determine a target probability value based on the target power spectrum and the candidate power spectrum, and reflect whether the change in the thickness of the target formation follows a periodic variation pattern based on the target probability value; the target probability value is used to describe the probability that the target power spectrum coincides with all the candidate power spectra.

[0063] In the technology of the above embodiment, optionally, the first power spectrum determination module includes a target thickness change information determination unit, which is used to convert the formation thickness of each unit formation corresponding to the target formation from bottom to top into a target one-dimensional array, and use the target one-dimensional array as the target thickness change information of the target formation.

[0064] In the technology of the above embodiment, optionally, the first power spectrum determination module includes a target power spectrum determination unit, which is used to perform a one-dimensional fast Fourier transform on the target thickness change information to obtain target Fourier change information, and take the square of the modulus of the target Fourier change information as the target power spectrum of the target formation.

[0065] In the technology of the above-mentioned embodiment, optionally, the analysis module includes a probability density function construction unit and a target probability value determination unit; the probability density function construction unit is used to process all the candidate power spectra using the Monte Carlo method to construct a probability density function, and the probability density function is used to reflect the probability of different candidate power spectra appearing in all the candidate power spectra; the target probability value determination unit is used to determine the target probability value based on the target power spectrum and the probability density function.

[0066] In the technology of the above embodiment, optionally, the target probability value determination unit is also used to: determine the degree of overlap between the target power corresponding to each formation thickness in the target power spectrum and the probability density function; if the degree of overlap is a first preset value, the target probability value of the corresponding formation thickness in the target power spectrum is the first preset value; if the degree of overlap is a second preset value, the target probability value of the corresponding formation thickness in the target power spectrum is the second preset value.

[0067] In the technology of the above embodiment, optionally, the analysis module includes a periodic change law analysis unit, which is used to determine that the change in the formation thickness of the target formation is a periodic change law when the target probability value is a first preset value; and to determine that the change in the formation thickness of the target formation is not a periodic change law when the target probability value is a second preset value.

[0068] In the technology of the above embodiment, optionally, the second power spectrum determination module is used to convert the stratum thickness of each unit stratum corresponding to the candidate stratum from bottom to top into a candidate one-dimensional array, and use the candidate one-dimensional array as the candidate thickness change information of the candidate stratum. Perform a one-dimensional fast Fourier transform on the candidate thickness change information to obtain candidate Fourier change information, and take the square of the modulus of the candidate Fourier change information as the candidate power spectrum of the candidate stratum.

[0069] The device for analyzing the regularity of vertical thickness of formations provided in the embodiment of the present invention can execute the method for analyzing the regularity of vertical thickness of formations provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0070] Embodiment 3

[0071] According to an embodiment of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium and a computer program product.

[0072] Figure 8 The structural schematic diagram of the electronic device that can be used to implement the vertical thickness law analysis method of the formation of the embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workbenches, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are only examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0073] like Figure 8As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0074] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0075] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as a method for analyzing the vertical thickness law of a formation.

[0076] In some embodiments, the method for analyzing the regularity of vertical thickness of formations may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the method for analyzing the regularity of vertical thickness of formations described above may be executed. Alternatively, in other embodiments, the processor 11 may be configured to execute the method for analyzing the regularity of vertical thickness of formations by any other appropriate means (e.g., by means of firmware).

[0077] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0078] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0079] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0080] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0081] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0082] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0083] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0084] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for analyzing the vertical thickness regularity of a stratum, characterized in that: The method comprises: Obtaining logging data of a target stratum, dividing the target stratum into a plurality of unit strata according to lithology data in the logging data, and determining the stratum thickness of each unit stratum; Determine target thickness variation information according to the formation thickness of each unit formation corresponding to the target formation from bottom to top, and determine the target power spectrum of the target formation according to the target thickness variation information; Determine a first preset number of candidate strata; the candidate strata are obtained by exchanging positions of a second preset number of unit strata with different lithologies in the target strata; Determine candidate thickness variation information of the candidate stratum according to the stratum thickness of each of the unit strata corresponding to the candidate stratum from bottom to top, and determine a candidate power spectrum of the candidate stratum according to the candidate thickness variation information; A target probability value is determined according to the target power spectrum and the candidate power spectrum, and the target probability value reflects whether the change in the thickness of the target stratum is a periodic change law; the target probability value is used to describe the probability of the target power spectrum overlapping with all the candidate power spectra.

2. The method according to claim 1, characterized in that: Determining target thickness change information according to the formation thickness of each unit formation corresponding to the target formation from bottom to top includes: The stratum thicknesses of the unit strata corresponding to the target stratum from bottom to top are converted into a target one-dimensional array, and the target one-dimensional array is used as the target thickness variation information of the target stratum.

3. The method according to claim 1 or 2, characterized in that: Determining a target power spectrum of a target formation according to the target thickness change information includes: A one-dimensional fast Fourier transform is performed on the target thickness change information to obtain target Fourier change information, and the square of the modulus of the target Fourier change information is used as the target power spectrum of the target formation.

4. The method according to claim 1, characterized in that: Determining a target probability value according to the target power spectrum and the candidate power spectrum includes: Processing all the candidate power spectra using a Monte Carlo method to construct a probability density function, wherein the probability density function is used to reflect the probability of different candidate power spectra appearing in all the candidate power spectra; A target probability value is determined according to the target power spectrum and the probability density function.

5. The method according to claim 4, characterized in that Determining a target probability value according to the target power spectrum and the probability density function includes: Determining the degree of overlap between the target power corresponding to each formation thickness in the target power spectrum and the probability density function; If the coincidence degree is the first preset value, the target probability value of the corresponding formation thickness in the target power spectrum is the first preset value; If the coincidence degree is the second preset value, the target probability value of the corresponding formation thickness in the target power spectrum is the second preset value.

6. The method according to claim 5, characterized in that Reflecting whether the change in the thickness of the target stratum is a periodic change rule according to the target probability value includes: When the target probability value is the first preset value, it is determined that the change in the thickness of the target stratum is a periodic change rule; When the target probability value is the second preset value, it is determined that the change in the thickness of the target stratum is not a periodic change rule.

7. The method according to claim 1, characterized in that Determining candidate thickness variation information of the candidate stratum according to the stratum thickness of each of the unit strata corresponding to the candidate stratum from bottom to top, and determining a candidate power spectrum of the candidate stratum according to the candidate thickness variation information, including: Converting the stratum thickness of each of the unit strata corresponding to the candidate strata from bottom to top into a candidate one-dimensional array, and using the candidate one-dimensional array as candidate thickness change information of the candidate strata; A one-dimensional fast Fourier transform is performed on the candidate thickness change information to obtain candidate Fourier change information, and the square of the modulus of the candidate Fourier change information is used as the candidate power spectrum of the candidate formation.

8. A device for analyzing vertical thickness regularity of formations, characterized in that: The device comprises: A formation thickness determination module is used to obtain logging data of a target formation, divide the target formation into a plurality of unit formations according to lithology data in the logging data, and determine the formation thickness of each unit formation; A first power spectrum determination module is used to determine target thickness variation information according to the formation thickness of each unit formation corresponding to the target formation from bottom to top, and determine a target power spectrum of the target formation according to the target thickness variation information; A candidate stratum determination module is used to determine a first preset number of candidate strata; the candidate strata are obtained by exchanging the positions of a second preset number of unit strata with different lithologies in the target stratum; A second power spectrum determination module is used to determine candidate thickness variation information of the candidate stratum according to the stratum thickness of each of the unit strata corresponding to the candidate stratum from bottom to top, and determine a candidate power spectrum of the candidate stratum according to the candidate thickness variation information; An analysis module is used to determine a target probability value based on the target power spectrum and the candidate power spectrum, and to reflect whether the change in the thickness of the target stratum follows a periodic variation pattern based on the target probability value; the target probability value is used to describe the probability that the target power spectrum coincides with all the candidate power spectra.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the method for analyzing vertical thickness regularity of formations as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the method for analyzing vertical thickness regularity of formations according to any one of claims 1 to 7 when executed.

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