A method, device, equipment and medium for predicting a distribution range of a magma intrusion body

Abstract

The embodiment of the present application discloses a kind of magmatic intrusive body distribution range prediction method, device, equipment and medium.The method comprises: obtaining the seismic exploration data of exploration target interval;The seismic exploration data includes fault interpretation data, oil and gas well logging data and petroleum seismic data;According to the high body seismic attribute and seismic frequency attribute of exploration target interval determined by the seismic exploration data;According to the high body seismic attribute and seismic frequency attribute, determine the magmatic intrusion characteristic parameter, and according to the magmatic intrusion characteristic parameter, determine the magmatic intrusive body distribution range of exploration target interval.Adopting the technical scheme, the seismic reflection highlight and frequency characteristics of magmatic intrusive body are considered, the magmatic intrusion characteristic parameter closely associated with magmatic intrusive body and seismic reflection characteristics is proposed, the purpose of quantitatively predicting the distribution position of magmatic intrusive body is achieved, and the distribution range of magmatic intrusive body can be directly determined using seismic data.

Description

Technical Field

[0001] The embodiments of the present invention relate to the technical field of oil and gas field exploration and development, and in particular to a method, device, equipment and medium for predicting the distribution range of a magma intrusion. Background Art

[0002] Due to frequent tectonic activities in faulted lake basins, igneous rocks in the basins have intruded into the overlying strata along deep faults and associated secondary faults, and some have intruded into the sandstone and mudstone strata along the weak surfaces of the rock strata in a layered manner. As a result, the coexistence of igneous rocks and clastic rocks in the fault zone is very common. The reflection characteristics formed in seismic observations are similar to those of lake bottom fan lithologies, which are difficult to distinguish. This poses a direct challenge to the exploration of clastic block oil and gas reservoirs, lithologic oil and gas reservoirs, and igneous oil and gas reservoirs.

[0003] Although seismic data currently contain rich information on the reflection of magmatic intrusions, information mining in the use of seismic data is far from enough, and it is difficult to determine from the intuitive understanding of the seismic profile which geological body causes the seismic reflection anomaly, forming an exploration trap. This is one of the reasons for the failure of exploratory wells for lithologic oil and gas reservoirs in eastern my country, and increases the difficulty of exploring lithologic oil and gas reservoirs in lake bottom fans.

[0004] Therefore, how to quickly and effectively identify and predict abnormal bodies formed by igneous rocks is a technical problem that needs to be solved urgently by those skilled in the art. Summary of the Invention

[0005] The embodiments of the present invention provide a method, device, electronic device and storage medium for predicting the distribution range of a magma intrusion, so as to achieve the purpose of directly determining the distribution range of a magma intrusion using seismic data.

[0006] In a first aspect, an embodiment of the present invention provides a method for predicting the distribution range of a magma intrusion, comprising:

[0007] Acquiring seismic exploration data of the target exploration interval; the seismic exploration data includes fault interpretation data, oil and gas well logging data, and petroleum seismic data;

[0008] Determining the seismic attributes and frequency attributes of the highlight body of the exploration target layer segment based on the seismic exploration data;

[0009] The magma intrusion characteristic parameters are determined based on the seismic attributes and seismic frequency attributes of the highlight body, and the distribution range of the magma intrusion body in the exploration target layer is determined based on the magma intrusion characteristic parameters.

[0010] In a second aspect, an embodiment of the present invention further provides a device for predicting the distribution range of a magma intrusion, comprising:

[0011] A seismic exploration data acquisition module is used to acquire seismic exploration data of the exploration target layer; the seismic exploration data includes fault interpretation data, oil and gas well logging data, and petroleum seismic data;

[0012] A seismic attribute information acquisition module, configured to determine the seismic attributes and frequency attributes of the highlight body of the exploration target layer segment based on the seismic exploration data;

[0013] The magma intrusion distribution range determination module is used to determine the magma intrusion characteristic parameters based on the seismic attributes and seismic frequency attributes of the highlight body, and to determine the magma intrusion distribution range of the exploration target layer based on the magma intrusion characteristic parameters.

[0014] In a third aspect, an embodiment of the present invention further provides an electronic device, the electronic device comprising:

[0015] one or more processors;

[0016] a storage device for storing one or more programs;

[0017] When the one or more programs are executed by the one or more processors, the one or more processors implement the method for predicting the distribution range of magma intrusions described in any embodiment of the present invention.

[0018] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method for predicting the distribution range of magma intrusions described in any embodiment of the present invention.

[0019] The embodiments of the present invention provide a method, apparatus, device, and medium for predicting the distribution range of a magma intrusion. The method comprises obtaining seismic exploration data of a target exploration layer; the seismic exploration data includes fault interpretation data, oil and gas well logging data, and petroleum seismic data; determining the seismic attributes and frequency attributes of the highlight body of the target exploration layer based on the seismic exploration data; determining characteristic parameters of the magma intrusion based on the seismic attributes and frequency attributes of the highlight body; and determining the distribution range of the magma intrusion in the target exploration layer based on the characteristic parameters of the magma intrusion. The technical solution of the embodiments of the present invention takes into account the seismic reflection highlight body and frequency characteristics of the magma intrusion, proposes a magma intrusion characteristic parameter that is closely linked to the seismic reflection characteristics of the magma intrusion, reflects the heterogeneous characteristics of the magma intrusion outline and interior, achieves the purpose of quantitatively predicting the distribution location of the magma intrusion, and can directly determine the distribution range of the magma intrusion using seismic data. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Other features, objects, and advantages of the application will become more apparent from the following detailed description when read in connection with the following accompanying drawings. The drawings are merely schematic and are not intended to portray the relative actual size or proportions of the concepts disclosed herein. The figures illustrate preferred embodiments of the application and, together with the written description, serve to explain their principles. Identical reference numerals have been used, where possible, to designate corresponding parts throughout the figures. In the drawings:

[0021] Figure 1 is a flow chart of a method for predicting the distribution range of a magma intrusion body provided in an embodiment of the application;

[0022] Figure 2 is a schematic diagram of the distribution range of a magma intrusion body in the Hailaer Basin provided in an embodiment of the application;

[0023] Figure 3 is a structural schematic diagram of a device for predicting the distribution range of a magma intrusion body provided in an embodiment of the application;

[0024] Figure 4 is a structural schematic diagram of an electronic device provided in an embodiment of the application. DETAILED DESCRIPTION

[0025] The application will be further described below in conjunction with the drawings and embodiments. It can be understood that the specific embodiments described herein are only used to explain the application, but not to limit the application. In addition, it should be noted that, for the convenience of description, only the parts related to the application are shown in the drawings, but not all the structures.

[0026] Before the example embodiments are discussed in more detail, it should be mentioned that some of the example embodiments are described as processes or methods depicted as flow charts. Although the flow charts describe the operations (or steps) as sequential processes, many of the operations (or steps) can be implemented in parallel, concurrently or simultaneously. In addition, the order of the operations can be rearranged. The processes can be terminated when their operations are completed, but can also have additional steps not included in the figures. The processes can correspond to methods, functions, routines, subroutines, subprograms, etc.

[0027] In the technical solutions of the present application, the acquisition, storage, use and processing of data all comply with the relevant provisions of national laws and regulations.

[0028] Figure 1This is a flow chart of a method for predicting the distribution range of a magmatic intrusion, provided in an embodiment of the present invention. This embodiment is applicable to predicting the distribution range of magmatic intrusions in lake-floor fan lithologic oil and gas reservoirs. The method of this embodiment can be executed by a magmatic intrusion distribution range prediction device, which can be implemented using hardware and / or software. The device can be configured in a server for predicting the distribution range of magmatic intrusions. The method specifically includes the following steps:

[0029] S110: Acquire seismic exploration data of the exploration target layer.

[0030] In the embodiment of the present invention, the distribution range of magma intrusions can be directly predicted by using seismic exploration data, which includes but is not limited to fault interpretation data, oil and gas well logging data, and petroleum seismic data.

[0031] S120 , determining the seismic attributes and the seismic frequency attributes of the highlight volume of the exploration target layer segment according to the seismic exploration data.

[0032] Among them, the highlight body seismic attribute can refer to a post-stack seismic data attribute, which is obtained by performing a time-frequency transformation on the post-stack seismic data in a specified frequency range. Specifically, the time domain data is converted to the frequency domain using a short-time window Fourier transform, and is the algebraic difference obtained by subtracting the average amplitude of the spectrum from the peak amplitude of the spectrum in the specified frequency range.

[0033] The seismic frequency attribute may refer to the dominant seismic frequency of a point in the target exploration interval. The seismic frequency attribute may be directly obtained from seismic exploration data. For example, the dominant seismic frequency of point A in the target exploration interval may be directly obtained from petroleum seismic data.

[0034] As an optional but non-limiting implementation, determining the seismic attributes of the highlight volume of the exploration target layer segment based on the seismic exploration data includes but is not limited to steps A1-A2:

[0035] Step A1: determining the seismic amplitude of the exploration target layer at the current frequency and the mean value of the seismic amplitude within a preset frequency range based on the seismic exploration data.

[0036] Step A2: Determine the seismic attributes of the highlight body of the exploration target layer according to the seismic amplitude at the current frequency and the mean seismic amplitude within a preset frequency range.

[0037] The highlight body seismic attribute is obtained by the difference between the seismic amplitude at the current frequency and the average seismic amplitude in the preset frequency range. The seismic amplitude and the average seismic amplitude can be directly obtained from the seismic exploration data. For example, if the seismic amplitude obtained from the seismic exploration data is 1800 and the average seismic amplitude is 1780, the highlight body seismic attribute of the exploration target layer is determined as 20.

[0038] As an optional but non-limiting implementation, the determination of the highlight body seismic attribute of the exploration target layer according to the seismic amplitude at the current frequency and the average seismic amplitude in the preset frequency range includes but is not limited to the following steps B1-B2:

[0039] Step B1: determining the amplitude difference between the seismic amplitude at the current frequency and the average seismic amplitude in the preset frequency range.

[0040] Step B2: taking the amplitude difference as the highlight body seismic attribute of the exploration target layer.

[0041] The amplitude difference between the seismic amplitude at the current frequency and the average seismic amplitude in the preset frequency range is taken as the highlight body seismic attribute of the exploration target layer, and the highlight body seismic attribute is:

[0042] A hlb = |f(x)-A ave |

[0043] wherein A hlb represents the highlight body seismic attribute; f(x) represents the seismic amplitude at the current frequency, x is between the lower limit and the upper limit of the preset frequency range; A ave represents the average seismic amplitude in the preset frequency range. If the average seismic amplitude is regarded as the expected value, the calculation of the highlight body seismic attribute is equivalent to the calculation of the deviation; the highlight body seismic attribute with small deviation represents the corresponding seismic amplitude as normal amplitude, and the highlight body seismic attribute with large deviation represents the corresponding seismic amplitude as abnormal amplitude.

[0044] S130, determining the magma intrusion characteristic parameter according to the highlight body seismic attribute and the seismic frequency attribute, and determining the distribution range of the magma intrusion body in the exploration target layer according to the magma intrusion characteristic parameter.

[0045] The magma intrusion characteristic parameter is determined according to the highlight body seismic attribute and the seismic frequency attribute after the highlight body seismic attribute and the seismic frequency attribute are determined. The magma intrusion body can refer to the high-temperature molten magma in the deep underground rising along the tectonic weak zone and intruding into the stratum to form the magma intrusion body. In the embodiment of the present application, the magma intrusion characteristic parameter is used to represent the amount of magma intruding into the exploration target layer, and the larger the magma intrusion characteristic parameter is, the more magma intruding into the target layer.

[0046] As an optional but non-limiting implementation, the magma intrusion feature parameter is determined according to the highlighted body seismic attribute and the seismic frequency attribute, and the distribution range of the magma intrusion body in the exploration target layer is determined according to the magma intrusion feature parameter, including but not limited to steps C1-C3:

[0047] Step C1: The magma intrusion feature parameter of each point in the target layer is determined according to the highlighted body seismic attribute and the seismic frequency attribute.

[0048] In the embodiment of the present application, the number of magma intruded into the target layer is represented by the magma intrusion feature parameter of a preset number of points in the target layer, so as to determine the distribution range of the magma intrusion body. The magma intrusion feature parameter of each point in the target layer is determined by the highlighted body seismic attribute and the seismic frequency attribute; the magma intrusion feature parameter is represented as:

[0049]

[0050] Wherein, R represents the magma intrusion feature parameter; LN(A hlb ) is obtained by taking the logarithm of the highlighted body seismic attribute; f represents the seismic frequency attribute at the point, that is, the main frequency of the seismic frequency at the point.

[0051] Step C2: Determine the lower limit threshold of the magma intrusion feature parameter of the exploration target layer.

[0052] Wherein, it is known whether the target layer contains a magma intrusion body at each point; by obtaining the first magma intrusion feature parameter at the point containing the magma intrusion body and the second magma intrusion feature parameter at the point not containing the magma intrusion body, a third magma intrusion feature parameter capable of distinguishing whether the magma intrusion body is contained is determined; and the third magma intrusion feature parameter is taken as the lower limit threshold of the magma intrusion feature parameter of the exploration target layer.

[0053] As an optional but non-limiting implementation, the determination of the lower limit threshold of the magma intrusion feature parameter of the exploration target layer includes but is not limited to steps D1-D3:

[0054] Step D1: Determine the first magma intrusion feature parameter of the first point on the exploration target layer; wherein the first point represents a point containing magma.

[0055] Step D2: Determine the second magma intrusion feature parameter of the second point on the exploration target layer; wherein the second point represents a point not containing magma.

[0056] Step D3: Determine the lower limit threshold of the magma intrusion feature parameter of the exploration target layer according to the first magma intrusion feature parameter and the second magma intrusion feature parameter.

[0057] In the embodiment of the present invention, the point containing magma is called the first point, and the point not containing magma is called the second point; the first magma intrusion characteristic parameter at the first point is determined, and the second magma intrusion characteristic parameter at the second point is determined; from the first magma intrusion characteristic parameter and the second magma intrusion characteristic parameter, a third magma intrusion characteristic parameter that can distinguish whether a magma intrusion body is contained is determined, and the third magma intrusion characteristic parameter is used as the lower limit threshold of the magma intrusion characteristic parameter.

[0058] The method of determining a third magma intrusion characteristic parameter that can distinguish whether a magma intrusion body is present includes, but is not limited to, determining the parameter by taking the mean, minimum or maximum value. For example, the smallest magma intrusion characteristic parameter among the first magma intrusion characteristic parameters can be used as the lower limit threshold of the magma intrusion characteristic parameter; the largest magma intrusion characteristic parameter among the second magma intrusion characteristic parameters can also be used as the lower limit threshold of the magma intrusion characteristic parameter; the smallest magma intrusion characteristic parameter among the first magma intrusion characteristic parameters and the largest magma intrusion characteristic parameter among the second magma intrusion characteristic parameters can also be averaged, and the third magma intrusion characteristic parameter obtained by the average is used as the lower limit threshold of the magma intrusion characteristic parameter of the exploration target layer. The method of determining the lower limit threshold of the magma intrusion characteristic parameter can be determined according to actual conditions and is not specifically limited in the embodiments of the present invention.

[0059] Step C3: Determine the distribution range of the magma intrusion body in the exploration target layer according to the magma intrusion characteristic parameters of each point in the target layer and the lower limit threshold of the magma intrusion characteristic parameters.

[0060] Among them, after determining the magma intrusion characteristic parameters and the lower limit threshold of the magma intrusion characteristic parameters at each point in the target layer, the magma intrusion characteristic parameters at each point are compared with the lower limit threshold of the magma intrusion characteristic parameters, and the range of the points where the magma intrusion characteristic parameters are greater than the lower limit threshold of the magma intrusion characteristic parameters is taken as the distribution range of the magma intrusion body in the exploration target layer.

[0061] As an optional but non-limiting implementation, determining the distribution range of the magma intrusion body in the exploration target layer according to the magma intrusion characteristic parameters at each point in the target layer and the lower limit threshold of the magma intrusion characteristic parameters includes but is not limited to steps E1-E3:

[0062] Step E1: Determine the lower limit threshold of the magma intrusion characteristic parameter of the confirmed drilled well in the exploration target layer.

[0063] Step E2: compare the magma intrusion characteristic parameter value of each point in the exploration target layer section with the lower threshold of the magma intrusion characteristic parameter, and determine the distribution range of the target point whose magma intrusion characteristic parameter value is greater than the lower threshold of the magma intrusion characteristic parameter.

[0064] Step E3: determine the distribution range of the magma intrusion body of the exploration target layer section according to the distribution range of the target point.

[0065] Wherein, it is determined whether the magma intrusion characteristic parameter value at each point is greater than the lower threshold of the magma intrusion characteristic parameter, and the point whose value is greater than the preset magma intrusion characteristic parameter is taken as the target point; the distribution range of the target point is obtained, and the distribution range of the magma intrusion body of the exploration target layer section is determined according to the distribution range of the target point.

[0066] In the embodiment of the present application, the lower segment of Tongbomiao Formation in the southern Wuerxun Sag of Hailaer Basin is taken as an example, as shown in the figure, Figure 2 As shown in the figure, large boundary faults are developed in the west and south of the research area, and the faults in the lower segment of Tongbomiao Formation are connected with the basement faults; Figure 2 The distribution of the magma intrusion characteristic R is shown in the figure, and it is found that there are obvious high R value anomalies in the middle and western edge of the work area, and this feature shows that the R anomaly not only has internal differences, but also reflects the characteristics related to the faults, that is, the development of the basement faults is often accompanied by the anomalies; the obvious anomaly in the west of the work area is more related to the development of the large boundary fault in the west. Combined with the results of the igneous rock drilled by the exploration well, it is considered that the position with R index greater than 19 is the position where the magma intrusion body is developed; the position with R index less than 19 is not the position where the magma intrusion body is developed, and the statistical results show that the application effect of the present application conforms to the geological law and is reliable.

[0067] In the embodiment of the present application, a magma intrusion body distribution range prediction method is provided, which comprises the following steps: obtaining seismic exploration data of an exploration target layer section; the seismic exploration data comprises fault interpretation data, oil and gas well logging data and petroleum seismic data; determining highlight body seismic attributes and seismic frequency attributes of the exploration target layer section according to the seismic exploration data; determining a magma intrusion characteristic parameter according to the highlight body seismic attributes and the seismic frequency attributes, and determining the distribution range of the magma intrusion body of the exploration target layer section according to the magma intrusion characteristic parameter. The technical scheme of the embodiment of the present application considers the seismic reflection highlight body and frequency characteristics of the magma intrusion body, proposes a magma intrusion characteristic parameter closely related to the magma intrusion body and the seismic reflection characteristics, reflects the outline and internal heterogeneous characteristics of the magma intrusion body, achieves the purpose of quantitatively predicting the distribution position of the magma intrusion body, and can directly determine the distribution range of the magma intrusion body by using the seismic data.

[0068] Figure 3Fig. 1 is a structural schematic diagram of a magma intrusion body distribution range prediction device provided in an embodiment of the present application. The technical solution of the embodiment can be applied to the case of predicting the distribution range of a magma intrusion body of a lake fan lithologic oil and gas reservoir. The device can be realized by software and / or hardware, and is generally integrated on any electronic device with network communication function, including but not limited to: a server, a computer, a personal digital assistant, and the like. As shown in Fig. 1, the magma intrusion body distribution range prediction device provided in the embodiment can include a seismic exploration data acquisition module 310, a seismic attribute information acquisition module 320, and a magma intrusion body distribution range determination module 330. Wherein, Figure 3

[0069] The seismic exploration data acquisition module 310 is configured to acquire seismic exploration data of a target exploration layer. The seismic exploration data includes fault interpretation data, well logging data, and seismic data.

[0070] The seismic attribute information acquisition module 320 is configured to determine highlight body seismic attributes and seismic frequency attributes of the target exploration layer according to the seismic exploration data.

[0071] The magma intrusion body distribution range determination module 330 is configured to determine a magma intrusion characteristic parameter according to the highlight body seismic attributes and the seismic frequency attributes, and determine a distribution range of a magma intrusion body of the target exploration layer according to the magma intrusion characteristic parameter.

[0072] In the above embodiment, the seismic attribute information acquisition module can be configured to:

[0073] determine a seismic amplitude at a current frequency and a seismic amplitude mean value in a preset frequency range of the target exploration layer according to the seismic exploration data.

[0074] determine the highlight body seismic attributes of the target exploration layer according to the seismic amplitude at the current frequency and the seismic amplitude mean value in the preset frequency range.

[0075] In the above embodiment, the seismic attribute information acquisition module can be configured to:

[0076] determine an amplitude difference value between the seismic amplitude at the current frequency and the seismic amplitude mean value in the preset frequency range.

[0077] take the amplitude difference value as the highlight body seismic attributes of the target exploration layer.

[0078] In the above embodiment, the magma intrusion body distribution range determination module can be configured to:

[0079] ​Determine the magma intrusion characteristic parameter of each point in the target layer section according to the highlighted seismic attribute and the seismic frequency attribute;

[0080] Determine the lower limit threshold of the magma intrusion characteristic parameter of the exploration target layer section;

[0081] Determine the distribution range of the magma intrusion body of the exploration target layer section according to the magma intrusion characteristic parameter of each point in the target layer section and the lower limit threshold of the magma intrusion characteristic parameter.

[0082] On the basis of the above-mentioned embodiments, optionally, the magma intrusion body distribution range determination module is specifically used for:

[0083] Determine the lower limit threshold of the magma intrusion characteristic parameter of the determined drilling in the exploration target layer section;

[0084] Compare the magma intrusion characteristic parameter value of each point in the exploration target layer section with the lower limit threshold of the magma intrusion characteristic parameter, and determine the distribution range of the target point whose magma intrusion characteristic parameter value is greater than the lower limit threshold of the magma intrusion characteristic parameter;

[0085] Determine the distribution range of the magma intrusion body of the exploration target layer section according to the distribution range of the target point.

[0086] The magma intrusion body distribution range prediction device provided in the embodiments of the present application can execute the magma intrusion body distribution range prediction method provided in any of the embodiments of the present application, has the corresponding functions and beneficial effects of executing the magma intrusion body distribution range prediction method, and the detailed process is referred to the related operations of the magma intrusion body distribution range prediction method in the foregoing embodiments.

[0087] Figure 4 is a structural schematic diagram of an electronic device provided in the embodiments of the present application. The electronic device 10 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.

[0088] As Figure 4As 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., connected to the at least one processor 11 in communication. The memory stores computer programs executable by the at least one processor 11, and the processor 11 can perform various appropriate actions and processes according to the computer programs stored in the read-only memory (ROM) 12 or loaded from the storage unit 18 into 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.

[0089] 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.

[0090] The processor 11 can be various general and / or special-purpose processing components having 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 magma intrusion distribution range prediction method.

[0091] In some embodiments, the magma intrusion distribution range prediction 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 magma intrusion distribution range prediction method described above can be performed. Alternatively, in other embodiments, the processor 11 can be configured to perform the magma intrusion distribution range prediction method by any other appropriate means, such as by means of firmware.

[0092] 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 load 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.

[0093] 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, when executed, can cause instructions defined in the flow charts and / or block diagrams to be implemented. The computer program can be executed entirely on a machine, partially on a machine, partially on a machine as a standalone software package and partially on a remote machine or entirely on a remote machine or server.

[0094] 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 systems, apparatus, or devices, 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 electrical connections, portable computer disks, hard disk drives, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or Flash memory), optical fibers, portable compact disc read-only memories (CD-ROMs), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0095] 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.

[0096] 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.

[0097] 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.

[0098] 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.

[0099] 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 predicting the distribution range of magma intrusions, characterized in that: The method comprises: Acquiring seismic exploration data of the target exploration interval; the seismic exploration data includes fault interpretation data, oil and gas well logging data, and petroleum seismic data; Determining the seismic attributes and frequency attributes of the highlight body of the exploration target layer segment based on the seismic exploration data; Determining magma intrusion characteristic parameters based on the seismic attributes and seismic frequency attributes of the highlight body, and determining the distribution range of the magma intrusion body in the exploration target layer based on the magma intrusion characteristic parameters; The determining of the magma intrusion characteristic parameters based on the seismic attributes and seismic frequency attributes of the highlight body, and the determining of the distribution range of the magma intrusion body in the exploration target layer based on the magma intrusion characteristic parameters, include: Determine the magma intrusion characteristic parameters of each point in the target layer based on the seismic attributes and seismic frequency attributes of the highlight body; determine the lower limit threshold of the magma intrusion characteristic parameters of the exploration target layer; determine the distribution range of the magma intrusion body in the exploration target layer based on the magma intrusion characteristic parameters of each point in the target layer and the lower limit threshold of the magma intrusion characteristic parameters; the magma intrusion characteristic parameters are characterized by: Among them, R represents the characteristic parameters of magma intrusion; LN(A hlb ) is obtained by taking the logarithm of the seismic attributes of the highlight body, A hlb represents the earthquake attributes of the highlighted body; f represents the earthquake frequency attribute at the point, that is, the main frequency of the earthquake at the point.

2. The method according to claim 1, characterized in that Determining the seismic attributes of the highlight body of the exploration target layer segment based on the seismic exploration data includes: Determining the seismic amplitude at the current frequency of the exploration target layer segment and the mean seismic amplitude within a preset frequency range based on the seismic exploration data; The seismic attributes of the highlight body of the exploration target layer are determined based on the seismic amplitude at the current frequency and the average seismic amplitude within a preset frequency range.

3. The method according to claim 2, characterized in that Determining the seismic attributes of the highlight body of the exploration target layer segment based on the seismic amplitude at the current frequency and the mean seismic amplitude within a preset frequency range includes: Determining an amplitude difference between the seismic amplitude at the current frequency and an average seismic amplitude within a preset frequency range; The amplitude difference is used as the seismic attribute of the highlight body of the exploration target layer.

4. The method according to claim 1, wherein Determining the distribution range of the magma intrusion body in the exploration target layer section based on the magma intrusion characteristic parameters at each point in the target layer section and the lower limit threshold of the magma intrusion characteristic parameters includes: Determine the lower limit threshold of the magma intrusion characteristic parameters of the confirmed drilled wells in the exploration target interval; Compare the magma intrusion characteristic parameter value of each point in the exploration target layer with the lower limit threshold of the magma intrusion characteristic parameter, and determine the distribution range of the target points where the magma intrusion characteristic parameter value is greater than the lower limit threshold of the magma intrusion characteristic parameter; The distribution range of the magma intrusion body in the exploration target layer section is determined based on the distribution range of the target points.

5. A device for predicting the distribution range of magma intrusions, characterized in that: The device comprises: A seismic exploration data acquisition module is used to acquire seismic exploration data of the exploration target layer; the seismic exploration data includes fault interpretation data, oil and gas well logging data, and petroleum seismic data; A seismic attribute information acquisition module, configured to determine the seismic attributes and frequency attributes of the highlight body of the exploration target layer segment based on the seismic exploration data; a magma intrusion distribution range determination module, configured to determine magma intrusion characteristic parameters based on the seismic attributes and seismic frequency attributes of the highlight body, and determine the distribution range of the magma intrusion body in the exploration target layer based on the magma intrusion characteristic parameters; Among them, the module for determining the distribution range of magma intrusion is specifically used to: Determine the magma intrusion characteristic parameters of each point in the target layer based on the seismic attributes and seismic frequency attributes of the highlight body; determine the lower limit threshold of the magma intrusion characteristic parameters of the exploration target layer; determine the distribution range of the magma intrusion body in the exploration target layer based on the magma intrusion characteristic parameters of each point in the target layer and the lower limit threshold of the magma intrusion characteristic parameters; the magma intrusion characteristic parameters are characterized by: Among them, R represents the characteristic parameters of magma intrusion; LN(A hlb ) is obtained by taking the logarithm of the seismic attributes of the highlight body, A hlb represents the earthquake attributes of the highlighted body; f represents the earthquake frequency attribute at the point, that is, the main frequency of the earthquake at the point.

6. The device according to claim 5, characterized in that The earthquake attribute information acquisition module is specifically used to: Determining the seismic amplitude at the current frequency of the exploration target layer segment and the mean seismic amplitude within a preset frequency range based on the seismic exploration data; The seismic attributes of the highlight body of the exploration target layer are determined based on the seismic amplitude at the current frequency and the average seismic amplitude within a preset frequency range.

7. The device according to claim 6, characterized in that The earthquake attribute information acquisition module is specifically used to: Determining an amplitude difference between the seismic amplitude at the current frequency and an average seismic amplitude within a preset frequency range; The amplitude difference is used as the seismic attribute of the highlight body of the exploration target layer.

8. An electronic device, characterized in that: include: one or more processors; a storage device for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the method for predicting the distribution range of magma intrusions as described in any one of claims 1-4.

9. A storage medium containing computer-executable instructions, characterized in that: When executed by a computer processor, the computer executable instructions are used to execute the method for predicting the distribution range of magma intrusions as described in any one of claims 1 to 4.

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