Seismic data filtering processing method and device, computer equipment and storage medium

Abstract

The invention provides a seismic data filtering processing method, and the method comprises the steps: carrying out the denoising processing of an initial signal, and obtaining a noise profile and an initial effective signal profile; determining an effective reflection signal event and noise energy distribution characteristic on the noise profile; according to the effective reflection signal event and noise energy distribution characteristics, determining the spatial attributes of the structural elements; carrying out filtering processing on the noise profile by adopting a preset filtering mode based on the spatial attribute, and separating an effective reflection signal event of the noise profile from noise to obtain an effective signal event; and backfilling the effective signal event to the initial effective signal profile to obtain a de-noised effective signal profile. Effective reflection signals damaged in the denoising process are extracted from a noise profile and backfilled into an effective reflection signal stack profile, weak energy effective reflection signals covered by noise and removed in the denoising process are reduced, and the effective reflection signal stack profile with better amplitude preservation and fidelity is obtained.

Description

Technical Field

[0001] The present invention relates to the technical field of seismic data processing, and in particular to a seismic data filtering processing method, device, computer equipment and storage medium. Background Art

[0002] In the process of seismic exploration data acquisition, due to the influence of surface factors, environmental factors, acquisition factors, etc., the collected data often contains a lot of noise. Acquisition noise suppression has always been one of the key links in the indoor processing of seismic data. Especially when the surface factors are complex surfaces such as deserts or loess plateaus, the signal-to-noise ratio of the obtained seismic data is often very low. The energy of noise in a single-shot record is much greater than the energy of the effective reflection signal. This leads to the removal of some weak energy effective reflection signals masked by noise during the denoising process, but these removed weak effective reflection energies will present a stronger signal-to-noise ratio on the stacked profile. Summary of the invention

[0003] Based on this, it is necessary to provide a seismic data filtering processing method, device, computer equipment and storage medium to address the above technical problems.

[0004] A seismic data filtering processing method, comprising:

[0005] De-noising the initial signal to obtain a noise profile and an initial effective signal profile;

[0006] Determining effective reflection signal event axes and noise energy distribution characteristics on the noise profile;

[0007] Determining the spatial attributes of the structural element according to the effective reflection signal event axis and noise energy distribution characteristics;

[0008] Based on the spatial attribute, the noise profile is filtered by a preset filtering method, and the effective reflection signal event axis of the noise profile is separated from the noise to obtain the effective signal event axis;

[0009] The effective signal event axis is backfilled into the initial effective signal profile to obtain a denoised effective signal profile.

[0010] In one embodiment, the step of determining the effective reflection signal event axis and noise energy distribution characteristics on the noise profile comprises:

[0011] Selecting a time window range on the noise profile according to the effective reflection signal event axis;

[0012] The effective reflection signal event axis and the noise energy distribution characteristics on the noise profile are determined based on the time window range.

[0013] In one of the embodiments, the spatial properties of the structure element include the scale and amplitude of the structure element;

[0014] The step of determining the spatial attribute of the structural element according to the effective reflection signal event axis and noise energy distribution characteristics comprises:

[0015] Determining the scale and amplitude of the structural element of the structural element according to the effective reflection signal event axis and the noise energy distribution characteristics;

[0016] The step of filtering the noise profile using a preset filtering method based on the spatial attribute, separating the effective reflection signal event axis of the noise profile from the noise, and obtaining the effective signal event axis includes:

[0017] Based on the scale and amplitude of the structural element, the noise profile is filtered in a preset filtering manner along the spatial direction, the effective reflection signal event axis of the noise profile is separated from the noise, and the effective signal event axis is obtained.

[0018] In one embodiment, the step of determining the scale and amplitude of the structural element according to the effective reflection signal event axis and the noise energy distribution characteristics comprises:

[0019] Get the scale and amplitude of multiple structural elements;

[0020] According to the effective reflection signal event axis and the noise energy distribution characteristics, a structural element with a scale greater than a preset scale and an amplitude less than a preset amplitude is selected, and the scale and amplitude of the structural element are determined.

[0021] In one embodiment, the step of performing denoising on the initial signal to obtain a noise profile comprises:

[0022] The initial signal is subjected to denoising processing by using a plurality of denoising methods respectively, so as to obtain a plurality of initial noise profiles;

[0023] The noise profile is obtained by superimposing a plurality of the initial noise profiles.

[0024] In one of the embodiments, in the step of denoising the initial signal using multiple denoising methods respectively, the denoising methods include: a denoising method for removing surface waves, a denoising method for removing random noise, and a denoising method for removing linear interference.

[0025] In one of the embodiments, the preset filtering method includes a filtering method based on mathematical morphology.

[0026] A seismic data filtering and processing device, comprising:

[0027] An initial denoising module is used to denoise the initial signal to obtain a noise profile and an initial effective signal profile;

[0028] An effective signal determination module, used to determine the effective reflection signal event axis and noise energy distribution characteristics on the noise profile;

[0029] A spatial attribute determination module, used to determine the spatial attribute of the structural element according to the effective reflection signal event axis and noise energy distribution characteristics;

[0030] A signal-to-noise separation module, configured to filter the noise profile using a preset filtering method based on the spatial attribute, separate the effective reflection signal event axis of the noise profile from the noise, and obtain an effective signal event axis;

[0031] A backfilling module is used to backfill the effective signal event axis into the initial effective signal profile to obtain a denoised effective signal profile.

[0032] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0033] De-noising the initial signal to obtain a noise profile and an initial effective signal profile;

[0034] Determining effective reflection signal event axes and noise energy distribution characteristics on the noise profile;

[0035] Determining the spatial attributes of the structural element according to the effective reflection signal event axis and noise energy distribution characteristics;

[0036] Based on the spatial attribute, the noise profile is filtered by a preset filtering method, and the effective reflection signal event axis of the noise profile is separated from the noise to obtain the effective signal event axis;

[0037] The effective signal event axis is backfilled into the initial effective signal profile to obtain a denoised effective signal profile.

[0038] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the following steps:

[0039] De-noising the initial signal to obtain a noise profile and an initial effective signal profile;

[0040] Determining effective reflection signal event axes and noise energy distribution characteristics on the noise profile;

[0041] Determining the spatial attributes of the structural element according to the effective reflection signal event axis and noise energy distribution characteristics;

[0042] Based on the spatial attribute, the noise profile is filtered by a preset filtering method, and the effective reflection signal event axis of the noise profile is separated from the noise to obtain the effective signal event axis;

[0043] The effective signal event axis is backfilled into the initial effective signal profile to obtain a denoised effective signal profile.

[0044] The above-mentioned seismic data filtering processing method, device, computer equipment and storage medium extract the effective reflection signal damaged in the denoising process from the noise profile and backfill it into the effective reflection signal stacking profile, thereby reducing the weak energy effective reflection signal masked by the noise and removed at the same time in the denoising process, and obtaining a more amplitude-preserving and fidelity-preserving effective reflection signal stacking profile. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 A schematic diagram of a flow chart of a seismic data filtering processing method in one embodiment;

[0046] Figure 2A A schematic diagram of a flow chart of a seismic data filtering processing method in another embodiment;

[0047] Figure 2B A schematic diagram of a flow chart of a method for filtering and processing seismic data in another embodiment;

[0048] Figure 3 is a structural block diagram of a seismic data filtering and processing device in one embodiment;

[0049] Figure 4 is an internal structure diagram of a computer device in one embodiment;

[0050] Figure 5 is a schematic diagram of a noise profile obtained after denoising in one embodiment;

[0051] Figure 6 is a schematic diagram of the influence of structural elements of different scales and amplitudes on filtering results in one embodiment;

[0052] Figure 7 is a schematic diagram of a noise superposition profile obtained after denoising in one embodiment;

[0053] Figure 8 It is a schematic diagram of a noise profile after signal-noise separation using the seismic data filtering processing method of the present application in one embodiment. DETAILED DESCRIPTION

[0054] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0055] Embodiment 1

[0056] In this embodiment, Figure 1 As shown, a method for filtering and processing seismic data is provided, which comprises:

[0057] Step 110, denoising the initial signal to obtain a noise profile and an initial effective signal profile.

[0058] In this embodiment, the initial signal is the initial signal of the collected seismic data, and the initial signal contains effective reflection signals and noise. In this step, the initial signal is subjected to denoising, which can also be called signal-noise separation processing, and is used to separate the effective reflection signal from the noise in the initial signal, so that the noise in the initial signal is removed. After the denoising, a noise profile and an initial effective signal profile with the noise removed can be obtained.

[0059] Step 120: determining the effective reflection signal event axis and noise energy distribution characteristics on the noise profile.

[0060] In this embodiment, the phase axis refers to the line connecting the extreme values ​​(commonly known as peaks or troughs) of the same vibration phase in each channel of the seismic record. In this embodiment, there are still some effective reflection signals of weak energy masked by noise on the noise profile separated by the previous step, and the characteristics of the noise energy distribution of the preset interval of the phase axis with the effective reflection signal are selected. In this embodiment, the selected filtering interval is a preset interval, which can be a certain interval on the noise profile, or an interval selected according to a parameter of the noise profile, for example, an interval selected according to the time range.

[0061] Step 130: Determine the spatial attribute of the structural element according to the effective reflection signal event axis and noise energy distribution characteristics.

[0062] In this embodiment, the spatial attribute is an attribute of the signal distribution in space, such as amplitude, scale, etc. In this embodiment, the spatial attribute of the structural element is determined according to the characteristics of the event axis of the effective reflection signal and the characteristics of the noise energy distribution.

[0063] Step 140: filtering the noise profile using a preset filtering method based on the spatial attribute, separating the effective reflection signal event axis of the noise profile from the noise, and obtaining an effective signal event axis.

[0064] In this embodiment, a preset filtering method is used to filter the noise profile based on the spatial attribute, so as to effectively separate the effective reflection signal from the noise in the noise profile, thereby obtaining an effective signal event axis, which can also be called an effective signal profile. Through this step, the effective reflection signal masked by the noise can be extracted from the noise profile to obtain an effective signal event axis.

[0065] Step 150: backfill the effective signal event axis into the initial effective signal profile to obtain a denoised effective signal profile.

[0066] In this step, the effective signal co-phase axis extracted from the noise profile is backfilled into the initial effective signal profile. The process can be to superimpose the effective signal profile extracted from the noise profile with the initial effective signal profile to obtain a denoised effective signal profile. The denoised effective signal profile is superimposed with the effective reflection signal masked by the noise during the denoising process, thereby well protecting the weak reflection signal damaged in the denoising process and better ensuring the fidelity and amplitude preservation of the data.

[0067] In the above embodiment, the effective reflection signal damaged in the denoising process is extracted from the noise profile and backfilled into the effective reflection signal superposition profile, thereby reducing the weak energy effective reflection signal masked by the noise and removed at the same time in the denoising process, and obtaining a more amplitude-preserving and fidelity-preserving effective reflection signal superposition profile.

[0068] In one embodiment, the step of determining the effective reflection signal event axis and the noise energy distribution characteristics on the noise profile includes: selecting a time window range on the noise profile according to the effective reflection signal event axis; and determining the effective reflection signal event axis and the noise energy distribution characteristics on the noise profile based on the time window range.

[0069] In this embodiment, the time window range may also be referred to as a time window range. Selecting the time window range means selecting a time interval. The time window range is selected based on the effective reflection signal event axis. In this embodiment, the effective reflection signal event axis and noise energy distribution characteristics on the noise profile within the time window range are selected. In this way, part of the effective reflection signal and noise can be selected from the complex noise profile to improve processing efficiency.

[0070] In one embodiment, the step of filtering the noise profile using a preset filtering method based on the spatial attribute, separating the effective reflection signal event axis of the noise profile from the noise, and obtaining the effective signal event axis includes: within a selected time window, filtering the noise profile using a preset filtering method based on the spatial attribute, separating the effective reflection signal event axis of the noise profile from the noise, and obtaining the effective signal event axis.

[0071] In one embodiment, the spatial attributes of the structural element include the scale and amplitude of the structural element; the step of determining the spatial attributes of the structural element according to the effective reflection signal event axis and the noise energy distribution characteristics includes: determining the scale and amplitude of the structural element according to the effective reflection signal event axis and the noise energy distribution characteristics; the step of filtering the noise profile using a preset filtering method based on the spatial attributes, separating the effective reflection signal event axis of the noise profile from the noise, and obtaining the effective signal event axis includes: filtering the noise profile using a preset filtering method along the spatial direction based on the scale and amplitude of the structural element, separating the effective reflection signal event axis of the noise profile from the noise, and obtaining the effective signal event axis.

[0072] It should be understood that the preset filtering method in step 140 includes a filtering method based on mathematical morphology. In this embodiment, the structural element is an indispensable factor of mathematical morphology filtering, and mathematical morphology filtering is a filtering method that uses structural elements and a series of mathematical operations to filter the original signal to obtain a filtered signal. In this method, the amplitude of the structural element should be approximately equal to the amplitude of the event axis of the reflection signal in the profile; the scale of the structural element should be slightly larger than the number of continuous channels of the event axis of the reflection signal in the profile along the spatial direction.

[0073] In one embodiment, the step of determining the scale and amplitude of the structural element of the structural element according to the effective reflection signal event axis and the noise energy distribution characteristics includes: obtaining the scales and amplitudes of multiple structural elements; selecting a structural element whose scale is greater than a preset scale and whose amplitude is less than a preset amplitude according to the effective reflection signal event axis and the noise energy distribution characteristics, and determining the scale and amplitude of the structural element.

[0074] As shown in the figure, Figure 6 The influence of a group of structural elements of different scales and amplitudes on the filtering results is shown in . It can be seen that as the amplitude increases, the filtered signal becomes less and the retained signal becomes more; as the scale increases, the filtered signal becomes more and the retained signal becomes less. Therefore, in order to extract more effective reflection signals and reduce the extraction of noise (reduce the influence of noise), structural elements with larger scales and smaller amplitudes should be selected for signal-noise separation. Therefore, in this embodiment, a structural element with a scale greater than a preset scale and an amplitude less than a preset amplitude is selected, and the scale and amplitude of the structural element are determined as the scale and amplitude of the structural element.

[0075] In one embodiment, the step of denoising the initial signal to obtain the noise profile includes: denoising the initial signal using multiple denoising methods to obtain multiple initial noise profiles; and superimposing the multiple initial noise profiles to obtain the noise profile.

[0076] In this embodiment, the initial signal is denoised using a variety of different denoising methods. After denoising using each denoising method, an initial noise profile is obtained. These initial noise profiles are superimposed to obtain a noise profile. Therefore, the noise profile can also be called a noise superposition profile.

[0077] In one embodiment, the step of denoising the initial signal to obtain the noise profile includes: denoising the initial signal in turn using one of multiple denoising methods to obtain multiple initial noise profiles; and superimposing the multiple initial noise profiles to obtain the noise profile.

[0078] In this embodiment, the initial signal is subjected to denoising processing in turn using various denoising methods. After denoising processing using each denoising method, an initial noise profile is obtained. The noise profile can be obtained by superimposing these initial noise profiles.

[0079] In one embodiment, in the step of denoising the initial signal using a plurality of denoising methods respectively, the denoising methods include: a denoising method for removing surface waves, a denoising method for removing random noise, and a denoising method for removing linear interference.

[0080] In this embodiment, removing the surface wave can also be called eliminating the surface wave, removing the random noise can also be called eliminating the random noise, and removing the linear interference can also be called eliminating the linear interference. It should be understood that the denoising method is not limited to the above three methods, and can also include other existing denoising methods, or denoising methods improved on the basis of the existing denoising methods. Its purpose is to obtain the noise profile and the initial effective signal profile after removing the noise, and then extract the effective reflection signal masked by the noise in the noise profile.

[0081] In one embodiment, the preset filtering method includes a filtering method based on mathematical morphology.

[0082] In this embodiment, mathematical morphology has a good signal-noise separation function, and the operation is only performed in the time domain, avoiding the influence of false frequency and Gibbs effect in conventional transformation. By analyzing the characteristics of the effective reflection signal and noise on the noise superposition profile, different structural elements can be selected to achieve different signal-noise separation effects. When the structural elements are selected reasonably, mathematical morphology filtering can well separate the effective reflection signal event axis from the noise. After signal backfilling, it well protects the weak reflection signal damaged in the denoising process, and better ensures the fidelity and amplitude preservation of the data.

[0083] It should be understood that although Figure 1 The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, Figure 1 At least part of the steps may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0084] Embodiment 2

[0085] In this embodiment, Figure 2A As shown, a method for filtering and processing seismic data is provided, which comprises:

[0086] Step 210, denoising the initial signal to obtain a noise profile and an initial effective signal profile;

[0087] Step 220, selecting a time window range on the noise profile according to the effective reflection signal event axis, and determining the effective reflection signal event axis and the noise energy distribution characteristics on the noise profile based on the time window range;

[0088] Step 230, determining the scale and amplitude of the structural element according to the effective reflection signal event axis and noise energy distribution characteristics;

[0089] Step 240, based on the spatial attribute, performing mathematical morphological filtering on the noise profile along the spatial direction, separating the effective reflection signal event axis of the noise profile from the noise, and obtaining the effective signal event axis;

[0090] Step 250: backfill the effective signal event axis into the initial effective signal profile to obtain a denoised effective signal profile.

[0091] In this embodiment, the effective signal damaged in the denoising process is extracted from the superposition profile of the noise by using the method of mathematical morphology filtering, and is backfilled into the superposition profile of the effective reflection signal, so as to obtain a more amplitude-preserving and fidelity-preserving effective reflection signal superposition profile. Mathematical morphology has a good signal-to-noise separation function, and the operation is only performed in the time domain, avoiding the influence of false frequency and Gibbs effect in conventional transformation. By analyzing the characteristics of the effective reflection signal and noise on the noise superposition profile, different structural elements can be selected to achieve different signal-to-noise separation effects. When the structural elements are reasonably selected, mathematical morphology filtering can well separate the effective reflection signal event axis from the noise. After signal backfilling, the weak reflection signal damaged in the denoising process is well protected, and the fidelity and amplitude preservation of the data are better guaranteed.

[0092] Embodiment 3

[0093] In this embodiment, Figure 2B As shown, a method for filtering and processing seismic data is provided, which comprises:

[0094] Step 101, processing the filtered noise signal to obtain a superposition profile of the noise.

[0095] like Figure 5 As shown in FIG. 1 , the obtained superposition profile after filtering out the noise is shown. From the profile, it can be seen that a part of the effective signal is damaged in the denoising process. This part of the effective signal has a relatively continuous event axis on the noise superposition profile.

[0096] Step 102: determine the time window range from which the event axis of the effective reflection signal needs to be extracted on the noise superposition profile.

[0097] like Figure 5 The part selected by the box shown in is the selected time window. The selected time window should contain the effective reflection signal event axis. Different time windows can be selected for processing according to different signal and noise characteristics.

[0098] Step 103: Determine the scale and amplitude of the structural element in the mathematical morphological filtering according to the characteristics of the effective reflection signal and the noise within the time window.

[0099] The structural element is an indispensable factor in mathematical morphology filtering, which is a filtering method that uses structural elements and a series of mathematical operations to filter the original signal to obtain the filtered signal. In this method, the amplitude of the structural element should be approximately equal to the amplitude of the event axis of the reflected signal in the profile; the scale of the structural element should be slightly larger than the number of continuous channels of the event axis of the reflected signal in the profile along the spatial direction.

[0100] Figure 6The effects of different sets of structural elements of different scales and amplitudes on the filtering results are given. It can be seen that as the amplitude increases, the filtered signal becomes less and the retained signal becomes more; as the scale increases, the filtered signal becomes more and the retained signal becomes less. For the method in this invention, a structural element with a larger scale and smaller amplitude should be selected to separate the signal from the noise.

[0101] Step 104, within the window range determined in step 102, mathematical morphology filtering is performed along the spatial direction on the data within the extraction time window to extract the effective reflection signal event axis on the noise superposition section.

[0102] Step 105, backfill the extracted effective reflections into the denoised stacked profile.

[0103] In this step, the effective reflection signal event axis extracted by mathematical morphology filtering is backfilled into the profile, which effectively protects the weak reflection signal event axis. The result obtained is more fidelity and amplitude-preserving, and also completes the signal protection of the method in the invention.

[0104] Figure 7 and Figure 8 A set of effect demonstrations are given. Figure 7 shows the superimposed profile with the noise filtered out. Figure 8 The noise profile after signal-to-noise separation using the method of the application is shown. It can be seen that after processing using the method of the application, the effective signal reflection that was originally damaged in the denoising process is well extracted.

[0105] In this embodiment, the effective signal damaged in the denoising process is extracted from the superposition profile of the noise by using the method of mathematical morphology filtering, and is backfilled into the superposition profile of the effective reflection signal, so as to obtain a more amplitude-preserving and fidelity-preserving superposition profile of the effective reflection signal. Mathematical morphology has a good signal-to-noise separation function, and the operation is only performed in the time domain, avoiding the influence of false frequency and Gibbs effect in conventional transformation. By analyzing the characteristics of the effective reflection signal and noise on the noise superposition profile, different structural elements can be selected to achieve different signal-to-noise separation effects. When the structural elements are selected reasonably, mathematical morphology filtering can well separate the phase axis of the effective reflection signal from the noise. After signal backfilling, the weak reflection signal damaged in the denoising process is well protected, and the fidelity and amplitude preservation of the data are better guaranteed.

[0106] Embodiment 4

[0107] In this embodiment, Figure 3 As shown, a seismic data filtering processing device is provided, comprising:

[0108] An initial denoising module 310 is used to perform denoising on the initial signal to obtain a noise profile and an initial effective signal profile;

[0109] An effective signal determination module 320, used to determine effective reflected signal event axes and noise energy distribution characteristics on the noise profile;

[0110] A spatial attribute determination module 330, configured to determine the spatial attribute of the structural element according to the effective reflection signal event axis and noise energy distribution characteristics;

[0111] A signal-to-noise separation module 340 is used to filter the noise profile using a preset filtering method based on the spatial attribute, separate the effective reflection signal event axis of the noise profile from the noise, and obtain an effective signal event axis;

[0112] The backfill module 350 is used to backfill the effective signal event axis into the initial effective signal profile to obtain a denoised effective signal profile.

[0113] In one embodiment, the effective signal determination module includes:

[0114] A time window selection unit, used for selecting a time window range according to the effective reflection signal event axis on the noise profile;

[0115] The effective signal determination unit is used to determine the effective reflection signal event axis and the noise energy distribution characteristics on the noise profile based on the time window range.

[0116] In one embodiment, the spatial properties of the structure element include the scale and amplitude of the structure element;

[0117] The spatial attribute determination module is further used to determine the scale and amplitude of the structural element of the structural element according to the effective reflection signal event axis and the noise energy distribution characteristics;

[0118] The signal-to-noise separation module is also used to filter the noise profile in a preset filtering manner along the spatial direction based on the scale and amplitude of the structural element, separate the effective reflection signal event axis of the noise profile from the noise, and obtain the effective signal event axis.

[0119] In one embodiment, the spatial attribute determination module includes:

[0120] A size amplitude acquisition unit, used for acquiring the size and amplitude of multiple structural elements;

[0121] The size amplitude determination unit is used to select a structural element with a scale greater than a preset scale and an amplitude less than a preset amplitude according to the effective reflection signal event axis and the noise energy distribution characteristics, and determine the scale and amplitude of the structural element.

[0122] In one embodiment, the initial denoising module comprises:

[0123] A denoising unit, configured to perform denoising processing on the initial signal using a plurality of denoising methods to obtain a plurality of initial noise profiles;

[0124] The noise superposition unit is used to superimpose a plurality of the initial noise profiles to obtain the noise profile.

[0125] In one embodiment, the denoising method includes: a denoising method for removing surface waves, a denoising method for removing random noise, and a denoising method for removing linear interference.

[0126] In one embodiment, the preset filtering method includes a filtering method based on mathematical morphology.

[0127] The specific definition of the seismic data filtering and processing device can be found in the definition of the seismic data filtering and processing method above, which will not be repeated here. Each unit in the above-mentioned seismic data filtering and processing device can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned units can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory in the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above-mentioned units.

[0128] Embodiment 5

[0129] In this embodiment, a computer device is provided. Its internal structure diagram can be shown as follows: Figure 4As shown. The computer device includes a processor, a memory, a network interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program, and the non-volatile storage medium is deployed with a database, which is used for seismic data, including initial signals, noise profiles, etc. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The network interface of the computer device is used to communicate with other computer devices that deploy application software. When the computer program is executed by the processor, a method for filtering and processing seismic data is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covered on the display screen, or a key, trackball or touchpad set on the computer device housing, or an external keyboard, touchpad or mouse, etc.

[0130] Those skilled in the art will understand that Figure 3 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0131] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0132] De-noising the initial signal to obtain a noise profile and an initial effective signal profile;

[0133] Determining effective reflection signal event axes and noise energy distribution characteristics on the noise profile;

[0134] Determining the spatial attributes of the structural element according to the effective reflection signal event axis and noise energy distribution characteristics;

[0135] Based on the spatial attribute, the noise profile is filtered by a preset filtering method, and the effective reflection signal event axis of the noise profile is separated from the noise to obtain the effective signal event axis;

[0136] The effective signal event axis is backfilled into the initial effective signal profile to obtain a denoised effective signal profile.

[0137] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0138] Selecting a time window range on the noise profile according to the effective reflection signal event axis;

[0139] The effective reflection signal event axis and the noise energy distribution characteristics on the noise profile are determined based on the time window range.

[0140] In one embodiment, the spatial properties of the structure element include the scale and amplitude of the structure element;

[0141] When the processor executes the computer program, it also performs the following steps:

[0142] Determining the scale and amplitude of the structural element of the structural element according to the effective reflection signal event axis and the noise energy distribution characteristics;

[0143] Based on the scale and amplitude of the structural element, the noise profile is filtered in a preset filtering manner along the spatial direction, the effective reflection signal event axis of the noise profile is separated from the noise, and the effective signal event axis is obtained.

[0144] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0145] Get the scale and amplitude of multiple structural elements;

[0146] According to the effective reflection signal event axis and the noise energy distribution characteristics, a structural element with a scale greater than a preset scale and an amplitude less than a preset amplitude is selected, and the scale and amplitude of the structural element are determined.

[0147] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0148] The initial signal is subjected to denoising processing by using a plurality of denoising methods respectively, so as to obtain a plurality of initial noise profiles;

[0149] The noise profile is obtained by superimposing a plurality of the initial noise profiles.

[0150] In one embodiment, the denoising method includes: a denoising method for removing surface waves, a denoising method for removing random noise, and a denoising method for removing linear interference.

[0151] In one embodiment, the preset filtering method includes a filtering method based on mathematical morphology.

[0152] Embodiment 6

[0153] In this embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0154] De-noising the initial signal to obtain a noise profile and an initial effective signal profile;

[0155] Determining effective reflection signal event axes and noise energy distribution characteristics on the noise profile;

[0156] Determining the spatial attributes of the structural element according to the effective reflection signal event axis and noise energy distribution characteristics;

[0157] Based on the spatial attribute, the noise profile is filtered by a preset filtering method, and the effective reflection signal event axis of the noise profile is separated from the noise to obtain the effective signal event axis;

[0158] The effective signal event axis is backfilled into the initial effective signal profile to obtain a denoised effective signal profile.

[0159] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0160] Selecting a time window range on the noise profile according to the effective reflection signal event axis;

[0161] The effective reflection signal event axis and the noise energy distribution characteristics on the noise profile are determined based on the time window range.

[0162] In one embodiment, the spatial properties of the structure element include the scale and amplitude of the structure element;

[0163] When the computer program is executed by the processor, the following steps are also performed:

[0164] Determining the scale and amplitude of the structural element of the structural element according to the effective reflection signal event axis and the noise energy distribution characteristics;

[0165] Based on the scale and amplitude of the structural element, the noise profile is filtered in a preset filtering manner along the spatial direction, the effective reflection signal event axis of the noise profile is separated from the noise, and the effective signal event axis is obtained.

[0166] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0167] Get the scale and amplitude of multiple structural elements;

[0168] According to the effective reflection signal event axis and the noise energy distribution characteristics, a structural element with a scale greater than a preset scale and an amplitude less than a preset amplitude is selected, and the scale and amplitude of the structural element are determined.

[0169] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0170] The initial signal is subjected to denoising processing by using a plurality of denoising methods respectively, so as to obtain a plurality of initial noise profiles;

[0171] The noise profile is obtained by superimposing a plurality of the initial noise profiles.

[0172] In one embodiment, the denoising method includes: a denoising method for removing surface waves, a denoising method for removing random noise, and a denoising method for removing linear interference.

[0173] In one embodiment, the preset filtering method includes a filtering method based on mathematical morphology.

[0174] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0175] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0176] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A method for filtering and processing seismic data, characterized in that: include: De-noising the initial signal to obtain a noise profile and an initial effective signal profile; Determining effective reflection signal event axes and noise energy distribution characteristics on the noise profile; Determining the spatial attributes of the structural element according to the effective reflection signal event axis and noise energy distribution characteristics; Based on the spatial attribute, the noise profile is filtered by a preset filtering method, and the effective reflection signal event axis of the noise profile is separated from the noise to obtain the effective signal event axis; The effective signal event axis is backfilled into the initial effective signal profile to obtain a denoised effective signal profile.

2. The method according to claim 1, characterized in that The step of determining the effective reflection signal event axis and noise energy distribution characteristics on the noise profile comprises: Selecting a time window range on the noise profile according to the effective reflection signal event axis; The effective reflection signal event axis and the noise energy distribution characteristics on the noise profile are determined based on the time window range.

3. The method according to claim 1, characterized in that The spatial properties of the structure element include the scale and amplitude of the structure element; The step of determining the spatial attribute of the structural element according to the effective reflection signal event axis and noise energy distribution characteristics comprises: Determining the scale and amplitude of the structural element of the structural element according to the effective reflection signal event axis and the noise energy distribution characteristics; The step of filtering the noise profile using a preset filtering method based on the spatial attribute, separating the effective reflection signal event axis of the noise profile from the noise, and obtaining the effective signal event axis includes: Based on the scale and amplitude of the structural element, the noise profile is filtered in a preset filtering manner along the spatial direction, the effective reflection signal event axis of the noise profile is separated from the noise, and the effective signal event axis is obtained.

4. The method according to claim 3, characterized in that The step of determining the scale and amplitude of the structural element according to the effective reflection signal event axis and the noise energy distribution characteristics comprises: Get the scale and amplitude of multiple structural elements; According to the effective reflection signal event axis and the noise energy distribution characteristics, a structural element with a scale greater than a preset scale and an amplitude less than a preset amplitude is selected, and the scale and amplitude of the structural element are determined.

5. The method according to claim 1, characterized in that The step of performing denoising on the initial signal to obtain a noise profile comprises: The initial signal is subjected to denoising processing by using a plurality of denoising methods respectively, so as to obtain a plurality of initial noise profiles; The noise profile is obtained by superimposing a plurality of the initial noise profiles.

6. The method according to claim 5, characterized in that In the step of denoising the initial signal using a plurality of denoising methods, the denoising methods include: a denoising method for removing surface waves, a denoising method for removing random noise, and a denoising method for removing linear interference.

7. The method according to any one of claims 1 to 6, characterized in that The preset filtering method includes a filtering method based on mathematical morphology.

8. A seismic data filtering and processing device, characterized in that: include: An initial denoising module is used to denoise the initial signal to obtain a noise profile and an initial effective signal profile; An effective signal determination module, used to determine the effective reflection signal event axis and noise energy distribution characteristics on the noise profile; A spatial attribute determination module, used to determine the spatial attribute of the structural element according to the effective reflection signal event axis and noise energy distribution characteristics; A signal-to-noise separation module, configured to filter the noise profile using a preset filtering method based on the spatial attribute, separate the effective reflection signal event axis of the noise profile from the noise, and obtain an effective signal event axis; A backfilling module is used to backfill the effective signal event axis into the initial effective signal profile to obtain a denoised effective signal profile.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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