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

Abstract

The application discloses a stratum vertical thickness rule analysis method and device, electronic equipment and a storage medium. The method comprises the following steps: dividing a target stratum into multiple unit strata according to lithology data in logging data and stratum thickness of each unit stratum; determining target thickness change information according to 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 strata, determining candidate thickness change information of the candidate strata according to stratum thickness of each unit stratum corresponding to the candidate strata from bottom to top, and determining a candidate power spectrum of the candidate strata according to the candidate thickness change information; determining a target probability value according to the target power spectrum and the candidate power spectrum, and reflecting whether stratum thickness change of the target stratum is a periodic change rule according to the target probability value. The scheme effectively identifies and distinguishes the periodicity of the vertical stratum thickness change.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of sedimentary geology, and particularly relates to a stratum vertical thickness regularity analysis method and device, an electronic device and a storage medium. BACKGROUND

[0002] Sedimentary rocks often have a "cyclicity" in the vertical direction, that is, the stratum has a repeated, identifiable, upward trend of lithology change or thickness change. The vertical stratum thickness change records important information of the water environment and basin evolution during deposition, but the definition and explanation of the "cyclicity" of the sedimentary stratum thickness are often mainly qualitative analysis, and thus are relatively subjective and have considerable uncertainty. The understanding and explanation of the vertical change rule of the lithology are to meet the assumptions of sequence stratigraphy, and ignore the objective rule of the stratum thickness change, which brings difficulties and uncertainty to the construction of the basin sedimentary stratum framework, the comparison of the strata of different wells and the examination of the existing geological knowledge. SUMMARY

[0003] The present application provides a stratum vertical thickness regularity analysis method and device, an electronic device and a storage medium, to effectively identify and distinguish the periodicity of the vertical stratum thickness change.

[0004] According to an aspect of the present application, a stratum vertical thickness regularity analysis method is provided, which comprises:

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

[0006] 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;

[0007] 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 stratum;

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

[0009] 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 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.

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

[0011] a formation thickness determining module configured to obtain well logging data of a target formation, divide the target formation into a plurality of unit formations according to lithology data in the well logging data, and determine a formation thickness of each of the unit formations;

[0012] a first power spectrum determining module configured to determine target thickness variation information according to the formation thicknesses of each of the unit formations 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 formation determining module configured to determine a first preset number of candidate formations, the candidate formations being obtained by exchanging positions of a second preset number of unit formations with different lithologies in the target formation;

[0014] a second power spectrum determining module configured to determine candidate thickness variation information of the candidate formations according to the formation thicknesses of each of the unit formations corresponding to the candidate formations from bottom to top, and determine a candidate power spectrum of the candidate formations according to the candidate thickness variation information;

[0015] an analyzing module configured to determine a target probability value according to the target power spectrum and the candidate power spectrum, and reflect whether the formation thickness variation of the target formation is a periodic variation regularity according to the target probability value, the target probability value being used to describe a probability of the target power spectrum coinciding with all the candidate power spectra.

[0016] According to another aspect of the present application, there is provided an electronic device, 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 executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to execute the method for analyzing a vertical thickness regularity of a formation according to any one of the embodiments of the present application.

[0020] According to another aspect of the present application, there is provided a computer readable storage medium storing computer instructions for enabling a processor to execute the method for analyzing a vertical thickness regularity of a formation according to any one of the embodiments of the present application when executed by the processor.

[0021] The technical scheme of the embodiment of the present application obtains the well logging data of the target formation, divides the target formation into multiple unit formations according to the lithology data in the well logging data, and determines the formation thickness of each unit formation; the present application takes the well logging lithology data as the starting point, overcomes the problems of large amount of gamma curve data, not directly reflecting the lithology, and needing preprocessing and correction; then the target thickness variation information is determined according to the formation thickness of each unit formation corresponding to the target formation from bottom to top, and the target power spectrum of the target formation is determined according to the target thickness variation information; a first preset number of candidate formations are determined; the candidate formations are obtained by exchanging the positions of the second preset number of unit formations with different lithologies in the target formation; the candidate thickness variation information of the candidate formation is determined according to the formation thickness of each unit formation corresponding to the candidate formation from bottom to top, and the candidate power spectrum of the candidate formation is determined according to the candidate thickness variation information; that is, the present application calculates the power spectrum of the disturbed formation again, constructs a probability density function, and compares it with the original target formation without disturbance, which can completely exclude the contingency; further, the target probability value is determined according to the target power spectrum and the candidate power spectrum, and whether the formation thickness variation of the target formation is a periodic variation rule is reflected 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 spectrums, that is, the present application is flexible in use, simple in principle, easy to understand, objective, reproducible and easy to understand, and can quickly and effectively identify and distinguish the periodicity of the vertical formation thickness variation.

[0022] It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present application, nor is it used to limit the scope of the present application. Other features of the present application will become apparent from the following description. BRIEF DESCRIPTION OF DRAWINGS

[0023] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiment description. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creating any creative labor.

[0024] Figure 1 is a flow chart of a formation vertical thickness rule analysis method according to an embodiment of the present application;

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

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

[0027] Figure 4is a probability density function corresponding to a power spectrum of a target formation and a candidate formation according to an embodiment of the present application;

[0028] Figure 5 is a diagram of a target probability value according to an embodiment of the present application;

[0029] Figure 6 is a diagram of a well layer section in a reference area analyzed by a formation vertical thickness regularity analysis method according to an embodiment of the present application;

[0030] Figure 7 is a structural diagram of a formation vertical thickness regularity analysis device according to an embodiment of the present application;

[0031] Figure 8 is a structural diagram of an electronic device for implementing the formation vertical thickness regularity analysis method according to an embodiment of the present application. DETAILED DESCRIPTION

[0032] In order to make the personnel in the art better understand the present application, the technical solutions in the embodiments of the present application will be described clearly and completely in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all the other embodiments obtained by the personnel in the art without creative labor should belong to the scope of protection of the present application.

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

[0034] Embodiment one

[0035] Figure 1A flowchart of a stratum vertical thickness regularity analysis method provided by an embodiment of the present application, the embodiment can be applied to the case of analyzing the stratum vertical thickness regularity, the method can be executed by a stratum vertical thickness regularity analysis device, the stratum vertical thickness regularity analysis device can be realized in the form of hardware and / or software, and the stratum vertical thickness regularity analysis device can be configured in any electronic device with network communication function. As shown in Figure 1 The stratum vertical thickness regularity analysis method of the present application comprises the following steps:

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

[0037] All unit strata constitute the target stratum, each unit stratum corresponds to one lithology, and the lithology data includes the particle size of rock particles in the stratum. The lithology data is mainly controlled by the particle size of rock particles and reflects the characteristics of the sedimentary environment. Logging data is various information collected and recorded in real time during wellbore drilling in the process of oil and gas exploration and development, which is crucial for understanding the underground geological conditions, evaluating the potential of oil and gas resources, and guiding drilling operations. The present application takes logging lithology data as the starting point, which can overcome the problems of large amount of gamma curve data, not directly reflecting lithology, and the need for preprocessing and correction.

[0038] Specifically, the target stratum is a stratum with a preset stratum thickness, and the lithology of the stratum with a certain thickness in the target stratum is consistent. The stratum corresponding to this thickness is a unit stratum. Therefore, by obtaining the logging data of the target stratum and analyzing the lithology data in the logging data, the target stratum can be divided into multiple unit strata from bottom to top, and the stratum thickness of the unit stratum can be accurately determined according to the logging data corresponding to the unit stratum.

[0039] S120, determining target thickness variation information according to the stratum thickness of each unit stratum corresponding to the target stratum from bottom to top, and determining the 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 sequential arrangement of the stratum thickness of each unit stratum of the target stratum from bottom to top. For example, taking Figure 2 the target stratum as an example, Figure 3 is Figure 2 a schematic diagram of the target thickness variation information corresponding to the target stratum, as shown in Figure 4 the black curve in Figure 3 is the target power spectrum of the target stratum obtained after information processing in

[0041] Correspondingly, the target thickness variation information is determined according to the thicknesses of the unit strata corresponding to the target stratum from bottom to top, including: converting the thicknesses of the unit strata corresponding to the target stratum from bottom to top into a target one-dimensional array, and taking 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 subject to a standard normal distribution.

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

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

[0044] Specifically, the power spectrum analysis of the target stratum is determined individually, and the vertical thickness rule of the target stratum has occasional nature. Therefore, the second preset number of unit strata with different lithology are selected from the target stratum, and the operation of selecting the second preset number of unit strata with different lithology for the first preset number of times and the operation of exchanging the positions of the second preset number of unit strata with different lithology in the target stratum are performed, so as to obtain the first preset number of candidate strata, and ensure the diversity of data.

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

[0046] Specifically, the thicknesses of the unit strata corresponding to the candidate stratum from bottom to top are converted into a candidate one-dimensional array, and the candidate one-dimensional array is taken as the candidate thickness variation information of the candidate stratum. The candidate one-dimensional array can be a one-dimensional random number matrix subject to a standard normal distribution. One-dimensional fast Fourier transform is performed on the candidate thickness variation information to obtain candidate Fourier transform information, and the square of the modulus of the candidate Fourier transform information is taken as the candidate power spectrum of the candidate stratum.

[0047] S150, a target probability value is determined according to the target power spectrum and the candidate power spectrum, and whether the thickness variation of the target stratum is a periodic variation rule is reflected according to the target probability value; the target probability value is used to describe the probability of coincidence of the target power spectrum and all candidate power spectra.

[0048] The target probability value can be understood as the significance in statistics, i.e., the significance between the target stratum and the candidate stratum.

[0049] Specifically, a Monte Carlo method is used to process all candidate power spectra to construct a probability density function. This probability density function reflects the probability of different candidate power spectra appearing among all candidate power spectra. The target probability value is determined based on the target power spectrum and the probability density function; that is, the target probability value is reflected by the degree of overlap between the target power spectrum and the probability density function. For example, using... Figure 2 Based on the target strata, a first preset number of candidate strata are obtained by performing a first preset number of position exchanges on a second preset number of unit strata with different lithologies within the target strata. Then, based on the stratigraphic thickness of each unit stratum corresponding to the candidate strata from bottom to top, candidate thickness variation information is determined. Based on this candidate thickness variation information, candidate power spectra are determined. Furthermore, a Monte Carlo method is used to process all candidate power spectra to construct probability density functions, such as... Figure 4 The red and yellow regions shown represent probability density functions.

[0050] Optionally, determining the target probability value based on 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 degree of overlap is a first preset value, then the target probability value for the corresponding formation thickness in the target power spectrum is the first preset value; if the degree of overlap is a second preset value, then the target probability value for the corresponding formation thickness in the target power spectrum is the second preset value. The first preset value can be 0, and the second preset value can be 1.

[0051] The overlap can be understood as the target power exceeding a preset value of the reference power indicated by the probability density function at the corresponding formation thickness. The preset value can be the maximum power value indicated by the probability density function. Figure 4 For example, taking stratum 5 as an example, the target power of the target stratum is 16. If the reference power indicated by stratum 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, indicating that the target power corresponding to each stratum thickness in the target power spectrum does not coincide with the probability density function, and the overlap is 0. Taking stratum 10 as an example, the target power of the target stratum is 0, and the reference power is 10, indicating that the target power corresponding to each stratum thickness in the target power spectrum coincides with the probability density function, and the overlap is 1. By analyzing the overlap between the power corresponding to each unit stratum in the power spectrum of the target stratum and the probability density function, the target probability value of each unit stratum in the target stratum can be obtained, such as... Figure 5 As shown.

[0052] Further, whether the change of the formation thickness of the target formation is a periodic change rule 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 of the formation thickness of the target formation is a periodic change rule; and when the target probability value is a second preset value, it is determined that the change of the formation thickness of the target formation is not a periodic change rule.

[0053] As shown in FIG. 2, assuming that the target formation is composed of 18 identical anticlinoriums, each of which contains five small units (n = 5), and the formation thickness of each unit is 0.25, 0.5, 1, 2 and 4 meters, respectively, and increases in turn upwards. Figure 3 As shown in FIG. 3, the power spectrum result shows that the power of the target formation is the strongest when the number of layers is equal to 5, and significantly exceeds the power corresponding to the probability density function of the random formation, which well reflects the periodicity (n = 5) of the anticlinoriums in the target formation in the change of thickness. Figure 4 As shown in FIG. 4, the change of the P value with different periods (frequencies) further proves this point. Figure 5

[0054] Further, the formation vertical thickness rule analysis method of the present application is applied to a certain layer section in a reference area, as shown in FIG. 5, the selected layer section is located in the same structure of two different wells, and significant differences are also found: layer section one shows weak periodicity (n = 2) in the number of layers 16-40 (FIG. 6A), while layer section two shows a strong peak (n = 5) in the number of layers = 5 (FIG. 6B). Figure 6 Figure 6 This proves that the formation vertical thickness rule analysis method of the present application also has good distinguishability and applicability on real formations, i.e., the formation vertical thickness rule analysis method of the present application can effectively distinguish the periodicity and difference in the change of formation thickness between the two. This is of great significance for clarifying how the formation with periodic characteristics is controlled by potential factors, and further understanding the inheritance, periodicity and difference in the spatial distribution of the sedimentary system. Figure 6

[0055] ​​​The technical scheme of the embodiment of the present application obtains the logging data of a target formation, divides the target formation into multiple unit formations according to the lithology data in the logging data, and determines the formation thickness of each unit formation; the present application takes the logging lithology data as a starting point, and overcomes the problems of large amount of gamma curve data, no direct reflection of lithology, and the need for preprocessing and correction; then, the target thickness variation information is determined according to the formation thickness of each unit formation corresponding to the target formation from bottom to top, and the target power spectrum of the target formation is determined according to the target thickness variation information; a first preset number of candidate formations are determined; the candidate formations are obtained by exchanging the positions of a second preset number of unit formations with different lithologies in the target formation; the candidate thickness variation information of the candidate formation is determined according to the formation thickness of each unit formation corresponding to the candidate formation from bottom to top, and the candidate power spectrum of the candidate formation is determined according to the candidate thickness variation information; that is, the present application calculates the power spectrum of the disturbed formation again, constructs a probability density function, and compares it with the original target formation that has not been disturbed, which can completely rule out contingency; further, the target probability value is determined according to the target power spectrum and the candidate power spectrum, and whether the formation thickness variation of the target formation is a periodic variation rule is reflected according to the target probability value; the target probability value is used to describe the probability of the coincidence of the target power spectrum and all candidate power spectra, that is, the present application is flexible in use, simple in principle, easy to understand, objective, reproducible and easy to understand, and can quickly and effectively identify and distinguish the periodicity of the vertical formation thickness variation.

[0056] Embodiment two

[0057] Figure 7 A structural schematic diagram of a formation vertical thickness rule analysis device provided by the embodiment of the present application, the embodiment can be applicable to the case of analyzing the formation vertical thickness rule, the formation vertical thickness rule analysis device can be realized in the form of hardware and / or software, and the formation vertical thickness rule analysis device can be configured in any electronic device with network communication function. Figure 3 As shown in the figure, the formation vertical thickness rule analysis device of the present application comprises:

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

[0059] The first power spectrum determination module 220 is configured 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 the target power spectrum of the target formation according to the target thickness variation information;

[0060] The candidate formation determining module 230 is configured to determine a first preset number of candidate formations by exchanging positions of a second preset number of unit formations with different lithologies in the target formation.

[0061] The second power spectrum determining module 240 is configured to determine candidate thickness variation information of the candidate formation according to formation thicknesses of each unit formation corresponding to the candidate formation from bottom to top, and determine a candidate power spectrum of the candidate formation according to the candidate thickness variation information.

[0062] The analysis module 250 is configured to determine a target probability value according to the target power spectrum and the candidate power spectrum, and reflect whether the formation thickness variation of the target formation is a periodic variation rule according to the target probability value. The target probability value is used to describe a probability of coincidence of the target power spectrum and all the candidate power spectra.

[0063] Optionally, in the technical solution of the above embodiment, the first power spectrum determining module comprises a target thickness variation information determining unit, which is configured to convert formation thicknesses of each unit formation corresponding to the target formation from bottom to top into a target one-dimensional array, and take the target one-dimensional array as target thickness variation information of the target formation.

[0064] Optionally, in the technical solution of the above embodiment, the first power spectrum determining module comprises a target power spectrum determining unit, which is configured to perform one-dimensional fast Fourier transformation on the target thickness variation information to obtain target Fourier transformation information, and take a square of a modulus of the target Fourier transformation information as the target power spectrum of the target formation.

[0065] Optionally, in the technical solution of the above embodiment, the analysis module comprises a probability density function constructing unit and a target probability value determining unit. The probability density function constructing unit is configured to process all the candidate power spectra in a Monte Carlo manner to construct a probability density function, and the probability density function is used to reflect probabilities of different candidate power spectra in all the candidate power spectra. The target probability value determining unit is configured to determine a target probability value according to the target power spectrum and the probability density function.

[0066] Optionally, in the technical solution of the above embodiment, the target probability value determining unit is further configured to determine a coincidence degree of a target power corresponding to each formation thickness in the target power spectrum and the probability density function, and if the coincidence degree is a first preset value, the target probability value of the corresponding formation thickness in the target power spectrum is a first preset value, and if the coincidence degree is a second preset value, the target probability value of the corresponding formation thickness in the target power spectrum is a second preset value.

[0067] Optionally, based on the technical solution of the above-mentioned embodiment, the analysis module comprises a periodic variation rule analysis unit, which is configured to determine that the formation thickness variation of the target formation is a periodic variation rule when the target probability value is a first preset value, and determine that the formation thickness variation of the target formation is not a periodic variation rule when the target probability value is a second preset value.

[0068] Optionally, based on the technical solution of the above-mentioned embodiment, the second power spectrum determination module is configured to convert the formation thicknesses of each unit formation corresponding to the candidate formation from bottom to top into a candidate one-dimensional array, and take the candidate one-dimensional array as the candidate thickness variation information of the candidate formation. The one-dimensional fast Fourier transform is performed on the candidate thickness variation information to obtain candidate Fourier transform information, and the square of the modulus of the candidate Fourier transform information is taken as the candidate power spectrum of the candidate formation.

[0069] The formation vertical thickness rule analysis device provided by the embodiment of the present application can perform the formation vertical thickness rule analysis method provided by any embodiment of the present application, and has the corresponding function modules and beneficial effects of the execution method.

[0070] Embodiment three

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

[0072] Figure 8 A structural schematic diagram of an electronic device that can be used to implement the formation vertical thickness rule analysis method of the embodiments of the present application is shown. The electronic device is intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular telephones, 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 meant to be examples only, and are not intended to limit the implementations of the present application described and / or claimed in this document.

[0073] As Figure 8As shown, the electronic device 10 includes at least one processor 11, and a memory, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., communicatively connected to the at least one processor 11, where the memory stores a computer program executable by the at least one processor. The processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or loaded into the random access memory (RAM) 13 from the storage unit 18. 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] Various 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, a speaker, etc., a storage unit 18, such as a magnetic 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 can be various general and / or special-purpose 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-purpose 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 performs various methods and processes described above, such as the formation vertical thickness regularity analysis method.

[0076] In some embodiments, the formation vertical thickness regularity analysis method can be implemented as a computer program tangibly embodied in a computer readable storage medium, such as the storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed onto 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 formation vertical thickness regularity analysis method described above can be performed. Alternatively, in other embodiments, the processor 11 can be configured to perform the formation vertical thickness regularity analysis method by any other appropriate means, such as by means of firmware.

[0077] The various embodiments of the systems and techniques described above can be implemented in digital electronic circuitry, integrated circuitry, a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), a system on a chip (SOC), a complex programmable logic device (CPLD), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include implementation in one or more computer programs that are executable and / or interpretable on a programmable system including at least one programmable processor, which can be special or general purpose, coupled to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device.

[0078] Computer programs used to implement the processes of the application can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer program

[0079] In the context of the present application, a computer-readable storage medium can be a tangible medium that can contain or store computer programs for use by or in connection with an instruction execution system, apparatus, or device. Computer-readable storage media can include, but are not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium can be a machine-readable signal medium. More specific examples of the machine-readable storage medium will include one or more lines of a program of instructions in a transitory signal, a portable computer diskette, 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 disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0080] To provide for interaction with a user, the systems and techniques described here can 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 a trackball) by which the user can provide input to the electronic device. Other kinds of devices can be used to provide for interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form, including acoustic, speech, or tactile input.

[0081] The systems and techniques described here can be implemented in a computing system that includes a back end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front end component (e.g., a user computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back end, middleware, or front end components. The components of the system can 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] The computing system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. A server can 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 large management difficulty and weak business scalability in traditional physical host and VPS service.

[0083] It should be understood that the various forms of flow shown above can be re-ordered, added to, or deleted from without departing from the scope of the present disclosure. For example, the steps recited in the present disclosure can be executed in parallel, executed in sequence, or executed in a different order, as long as the desired results of the present disclosure are achieved, and the present disclosure is not limited herein.

[0084] The specific embodiments described above are not intended to be limiting, and persons skilled in the art will appreciate that various modifications, combinations, sub-combinations and alternatives can be made to the specific embodiments without departing from the spirit and principles of the disclosure. Accordingly, the disclosure is not limited to the specific embodiments described above, but only by the scope of the appended claims.

Claims

1. A method for analyzing the vertical thickness regularity of strata, characterized in that, The method includes: Obtain logging data of the target formation, divide the target formation into multiple unit formations based on the lithological data in the logging data, and determine the formation thickness of each unit formation; The target thickness variation information is determined based on the thickness of each unit stratum corresponding to the target stratum from bottom to top, and the target power spectrum of the target stratum is determined based on the target thickness variation information; A first preset number of candidate strata are determined; the candidate strata are obtained by exchanging the positions of a second preset number of unit strata with different lithologies in the target strata. Based on the stratigraphic thickness of each unit stratigraphic unit corresponding to the candidate stratigraphic unit from bottom to top, the candidate thickness variation information of the candidate stratigraphic unit is determined, and the candidate power spectrum of the candidate stratigraphic unit is determined based on the candidate thickness variation information; A target probability value is determined based on the target power spectrum and the candidate power spectra. The target probability value reflects whether the variation in the formation thickness of the target formation follows a periodic variation pattern. The target probability value is used to describe the probability that the target power spectrum coincides with all the candidate power spectra.

2. The method according to claim 1, characterized in that, The target thickness variation information is determined based on the stratigraphic thickness of each unit stratigraphic unit corresponding to the target stratigraphic unit from bottom to top, including: The thickness of each unit stratum corresponding to the target stratum from bottom to top is converted into a target one-dimensional array, and the target one-dimensional array is used as the target thickness change information of the target stratum.

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

4. The method according to claim 1, characterized in that, Determining the target probability value based on the target power spectrum and the candidate power spectrum includes: A probability density function is constructed by processing all the candidate power spectra using the Monte Carlo method. 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 is determined based on the target power spectrum and the probability density function.

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

6. The method according to claim 5, characterized in that, The target probability value reflects whether the variation in the formation thickness of the target stratum follows a periodic pattern, including: When the target probability value is a first preset value, the formation thickness of the target stratum is determined to be a periodic variation. When the target probability value is the second preset value, it is determined that the change in the formation thickness of the target formation is not a periodic change.

7. The method according to claim 1, characterized in that, Based on the stratigraphic thickness of each unit stratigraphic unit corresponding to the candidate stratigraphic unit from bottom to top, candidate thickness variation information of the candidate stratigraphic unit is determined, and candidate power spectrum of the candidate stratigraphic unit is determined based on the candidate thickness variation information, including: The thickness of each unit stratum corresponding to the candidate strata from bottom to top is converted into a candidate one-dimensional array, and the candidate one-dimensional array is used as the candidate thickness variation information of the candidate strata. The candidate thickness variation information is subjected to a one-dimensional fast Fourier transform to obtain candidate Fourier transform information, and the square of the modulus of the candidate Fourier transform information is used as the candidate power spectrum of the candidate stratum.

8. A device for analyzing the vertical thickness regularity of strata, characterized in that, The device includes: The formation thickness determination module is used to acquire well logging data of the target formation, divide the target formation into multiple unit formations based on the lithological data in the well logging data, and determine the formation thickness of each unit formation. The first power spectrum determination module is used to determine the target thickness variation information based on the thickness of each unit stratum corresponding to the target stratum from bottom to top, and to determine the target power spectrum of the target stratum based on the target thickness variation information. The candidate stratigraphic determination module is used to determine a first preset number of candidate stratigraphic layers; the candidate stratigraphic layers are obtained by exchanging the positions of a second preset number of unit stratigraphic layers with different lithologies in the target stratigraphic layer. The second power spectrum determination module is used to determine the candidate thickness variation information of the candidate strata based on the stratum thickness of each unit stratum corresponding to the candidate strata from bottom to top, and to determine the candidate power spectrum of the candidate strata based on the candidate thickness variation information. The analysis module is used to determine a target probability value based on the target power spectrum and the candidate power spectra. The target probability value reflects whether the change in the formation thickness of the target formation is a periodic change. 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 includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the formation vertical thickness regularity analysis method according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the method for analyzing the vertical thickness regularity of strata as described in any one of claims 1-7.

Images