Seismic data processing method, device, equipment and storage medium

Abstract

The application discloses a kind of seismic data processing method, device, equipment and storage medium, belong to the technical field of seismic exploration.The method is by Fourier transform to first seismic data and seismic wavelet, respectively obtain first spectrum and second spectrum, then based on first spectrum and second spectrum, determine the reflectivity data volume, convert the reflectivity data volume into lithology wave impedance body, again lithology replaces lithology wave impedance body, obtain igneous rock wave impedance body, convert igneous rock wave impedance body into igneous rock reflection signal data, finally, igneous rock reflection signal data is separated from first seismic data.It can be seen from this, the method only removes igneous rock strong reflection signal from seismic data, retains reservoir effective signal, so that reservoir prediction can be carried out based on reservoir effective signal, to improve the accuracy of reservoir prediction.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of seismic exploration, and particularly relates to a seismic data processing method, device, equipment and storage medium. BACKGROUND

[0002] With the deepening of oil and gas exploration and development, lithologic oil and gas reservoirs have become important targets for increasing reserves and production in mature exploration areas, and it is necessary to finely depict the lateral variation and superimposed relationship of thin interbedded reservoirs. Due to the development of special lithology near the reservoir in some areas, such as igneous rocks, it often shows a strong reflection event in seismic data, which has a strong shielding effect on the reservoirs developed above and below it, often resulting in poor reservoir prediction results.

[0003] In related technologies, a multi-wavelet decomposition and reconstruction method is mainly used to suppress the strong reflection event. The method first decomposes seismic data into multiple wavelet components of different frequencies, amplitudes and phases, then discards the wavelet corresponding to the strong shielding layer, and then reconstructs, so as to achieve the effect of removing the strong shielding.

[0004] However, due to the limited distribution of igneous rocks and the relatively strong reflection of the reservoir, the method is prone to strip the effective signals of the reservoirs not affected by the igneous rocks in use, affecting the accuracy of reservoir prediction. SUMMARY

[0005] The embodiments of the present application provide a seismic data processing method, which can strip the strong reflection signals of igneous rocks from seismic data and retain the effective signals of the reservoirs, thereby improving the accuracy of reservoir prediction. The technical solution is as follows:

[0006] On the one hand, a seismic data processing method is provided, and the method comprises:

[0007] obtaining first seismic data and a seismic wavelet of a target work area;

[0008] performing Fourier transform on the first seismic data to obtain a first frequency spectrum, and performing Fourier transform on the seismic wavelet to obtain a second frequency spectrum;

[0009] determining a reflection coefficient data body based on first relationship data, the first frequency spectrum and the second frequency spectrum; wherein the first relationship data is used to represent the relationship among the first frequency spectrum, the second frequency spectrum and the reflection coefficient data body;

[0010] converting the reflection coefficient data body into a lithology wave impedance body based on second relationship data; wherein the second relationship data is used to represent the relationship between the reflection coefficient data body and the lithology wave impedance body;

[0011] performing lithology replacement on the lithology wave impedance body based on an igneous rock wave impedance threshold and a sandstone wave impedance threshold to obtain an igneous rock wave impedance body.

[0012] convert the igneous rock wave impedance volume into igneous rock reflection signal data based on third relationship data, wherein the third relationship data is used to represent a relationship between the igneous rock wave impedance volume and the igneous rock reflection signal data;

[0013] separate the igneous rock reflection signal data from the first seismic data.

[0014] In a possible implementation, the lithology wave impedance volume includes lithology wave impedance values corresponding to a plurality of time points;

[0015] The lithology replacement of the lithology wave impedance volume based on the igneous rock wave impedance threshold and the sandstone wave impedance threshold to obtain the igneous rock wave impedance volume includes:

[0016] obtain an igneous rock average wave impedance value and a mudstone average wave impedance value;

[0017] For a lithology wave impedance value corresponding to a first time point, if the lithology wave impedance value corresponding to the first time point is not less than the igneous rock wave impedance threshold, the lithology wave impedance value corresponding to the first time point is replaced by the igneous rock average wave impedance value; wherein the first time point is any time point in the plurality of time points;

[0018] If the lithology wave impedance value corresponding to the first time point is less than the sandstone wave impedance threshold, the lithology wave impedance value corresponding to the first time point is replaced by the mudstone average wave impedance value;

[0019] Determine the igneous rock wave impedance volume based on the igneous rock average wave impedance values or the mudstone average wave impedance values corresponding to the plurality of time points.

[0020] In another possible implementation, the conversion of the igneous rock wave impedance volume into igneous rock reflection signal data based on the third relationship data includes:

[0021] obtain a sampling time interval;

[0022] Determine the sum of the first time point and the sampling time interval to obtain a second time point;

[0023] Determine a first wave impedance value corresponding to the first time point and a second wave impedance value corresponding to the second time point based on the igneous rock wave impedance volume; wherein the first wave impedance value corresponding to the first time point is the igneous rock average wave impedance value or the mudstone average wave impedance value, and the second wave impedance value corresponding to the second time point is the igneous rock average wave impedance value or the mudstone average wave impedance value;

[0024] The first wave impedance value, the second wave impedance value and the seismic wavelet corresponding to the first time are substituted into the third relationship data to obtain reflection signal data corresponding to the first time;

[0025] Based on the reflection signal data corresponding to the plurality of times, the igneous rock reflection signal data is determined.

[0026] In another possible implementation, the separating the igneous rock reflection signal data from the first seismic data comprises:

[0027] A separation correction coefficient is determined.

[0028] A product of the separation correction coefficient and the igneous rock reflection signal data is determined to obtain igneous rock correction data.

[0029] A difference between the first seismic data and the igneous rock correction data is determined to obtain second seismic data.

[0030] In another possible implementation, the Fourier transform of the first seismic data to obtain a first frequency spectrum comprises:

[0031] A first time window length and a first offset are obtained; the first time window length is half of a time window length, and the first offset is an offset of a center point of the time window relative to a coordinate zero point;

[0032] A sum of the first offset and the first time window length is determined to obtain an upper limit value;

[0033] A difference between the first offset and the first time window length is determined to obtain a lower limit value;

[0034] The Fourier transform of the first seismic data is performed within a time range corresponding to the upper limit value and the lower limit value to obtain the first frequency spectrum.

[0035] In another possible implementation, the determining reflection coefficient data based on the first relationship data, the first frequency spectrum and the second frequency spectrum comprises:

[0036] The first frequency spectrum and the second frequency spectrum are substituted into the first relationship data to determine odd components and even components of the reflection coefficient data;

[0037] A sum of the odd components and the even components of the reflection coefficient data is determined to obtain the reflection coefficient data.

[0038] In another possible implementation, the converting the reflection coefficient data into a lithology wave impedance body based on the second relationship data comprises:

[0039] An initial wave impedance value is obtained;

[0040] substituting the initial wave impedance value and the reflection coefficient data body into the second relationship data, to obtain the lithology wave impedance body.

[0041] In another aspect, a seismic data processing apparatus is provided, and the apparatus comprises:

[0042] an acquisition module configured to acquire first seismic data and a seismic wavelet of a target work area;

[0043] a transformation module configured to perform Fourier transform on the first seismic data to obtain a first frequency spectrum and perform Fourier transform on the seismic wavelet to obtain a second frequency spectrum;

[0044] a first determination module configured to determine a reflection coefficient data body based on first relationship data, the first frequency spectrum and the second frequency spectrum; wherein the first relationship data is used to represent a relationship among the first frequency spectrum, the second frequency spectrum and the reflection coefficient data body;

[0045] a first conversion module configured to convert the reflection coefficient data body into a lithology wave impedance body based on second relationship data; wherein the second relationship data is used to represent a relationship between the reflection coefficient data body and the lithology wave impedance body;

[0046] a second conversion module configured to perform lithology replacement on the lithology wave impedance body based on a felsic rock wave impedance threshold and a sandstone wave impedance threshold to obtain a felsic rock wave impedance body;

[0047] a third conversion module configured to convert the felsic rock wave impedance body into felsic rock reflection signal data based on third relationship data; wherein the third relationship data is used to represent a relationship between the felsic rock wave impedance body and the felsic rock reflection signal data;

[0048] a separation module configured to separate the felsic rock reflection signal data from the first seismic data.

[0049] In a possible implementation manner, the lithology wave impedance body comprises lithology wave impedance values corresponding to a plurality of time instants.

[0050] The second conversion module is configured to: obtain an average wave impedance value of the igneous rock and an average wave impedance value of the mudstone; for a lithology wave impedance value corresponding to a first time, if the lithology wave impedance value corresponding to the first time is not less than the igneous rock wave impedance threshold value, replace the lithology wave impedance value corresponding to the first time with the average wave impedance value of the igneous rock; the first time is any time in the plurality of times; if the lithology wave impedance value corresponding to the first time is less than the sandstone wave impedance threshold value, replace the lithology wave impedance value corresponding to the first time with the average wave impedance value of the mudstone; and determine the igneous rock wave impedance body based on the average wave impedance value of the igneous rock or the average wave impedance value of the mudstone corresponding to the plurality of times.

[0051] In another possible implementation, the third conversion module is configured to: obtain a sampling time interval; determine a sum value of the first time and the sampling time interval to obtain a second time; determine a first wave impedance value corresponding to the first time and a second wave impedance value corresponding to the second time based on the igneous rock wave impedance body; the first wave impedance value corresponding to the first time is the average wave impedance value of the igneous rock or the average wave impedance value of the mudstone, and the second wave impedance value corresponding to the second time is the average wave impedance value of the igneous rock or the average wave impedance value of the mudstone; and obtain reflection signal data corresponding to the first time by substituting the first wave impedance value, the second wave impedance value, and a seismic wavelet corresponding to the first time into the third relationship data; and determine the igneous rock reflection signal data based on the reflection signal data corresponding to the plurality of times.

[0052] In another possible implementation, the separation module is configured to: determine a separation correction coefficient; determine igneous rock correction data by multiplying the separation correction coefficient and the igneous rock reflection signal data; and determine the second seismic data by determining a difference between the first seismic data and the igneous rock correction data.

[0053] In another possible implementation, the transformation module is configured to: obtain a first time window length and a first offset; the first time window length is half of a time window length, and the first offset is an offset of a center point of a time window relative to a coordinate zero point; determine an upper limit value by determining a sum value of the first offset and the first time window length; determine a lower limit value by determining a difference between the first offset and the first time window length; and perform Fourier transform on the first seismic data in a time range corresponding to the upper limit value and the lower limit value to obtain the first frequency spectrum.

[0054] In a possible implementation, the first determining module is configured to substitute the first frequency spectrum and the second frequency spectrum into the first relationship data to determine odd components and even components of the reflectivity data volume; and determine a sum of the odd components and the even components of the reflectivity data volume to obtain the reflectivity data volume.

[0055] In a possible implementation, the first converting module is configured to obtain an initial wave impedance value; and substitute the initial wave impedance value and the reflectivity data volume into the second relationship data to obtain the lithology wave impedance volume.

[0056] In another aspect, an electronic device is provided, which includes a processor and a memory having at least one program code stored therein, the at least one program code being loaded and executed by the processor to implement the seismic data processing method according to any one of the preceding aspects.

[0057] In another aspect, a computer readable storage medium is provided, which has at least one program code stored therein, the at least one program code being loaded and executed by a processor to implement the seismic data processing method according to any one of the preceding aspects.

[0058] In another aspect, a computer program product is provided, which has at least one program code stored therein, the at least one program code being loaded and executed by a processor to implement the seismic data processing method according to any one of the preceding aspects.

[0059] The embodiments of the present application provide a seismic data processing method. The method performs Fourier transform on first seismic data and a seismic wavelet to obtain a first frequency spectrum and a second frequency spectrum, respectively, determines a reflectivity data volume based on the first frequency spectrum and the second frequency spectrum, converts the reflectivity data volume into a lithology wave impedance volume, performs lithology replacement on the lithology wave impedance volume to obtain an igneous rock wave impedance volume, converts the igneous rock wave impedance volume into igneous rock reflection signal data, and finally separates the igneous rock reflection signal data from the first seismic data. It can be seen that the method only removes the strong reflection signal of the igneous rock from the seismic data, and retains the effective signal of the reservoir. Thus, the reservoir prediction can be performed based on the effective signal of the reservoir, so that the accuracy of the reservoir prediction is improved.

[0060] It should be understood that the foregoing general description and the following detailed description are only examples, and cannot limit the present disclosure. BRIEF DESCRIPTION OF DRAWINGS

[0061] Figure 1 FIG. 1 is a schematic diagram of an implementation environment of a seismic data processing method provided by the embodiments of the present application;

[0062] Figure 2is a flow chart of a seismic data processing method provided by an embodiment of the present application;

[0063] Figure 3 a is a schematic diagram of a geological model provided by an embodiment of the present application;

[0064] Figure 3 b is a schematic diagram of seismic data provided by an embodiment of the present application;

[0065] Figure 4 a is a schematic diagram of a lithology wave impedance body provided by an embodiment of the present application;

[0066] Figure 4 b is a schematic diagram of an igneous rock wave impedance body provided by an embodiment of the present application;

[0067] Figure 4 c is a schematic diagram of igneous rock reflection signal data provided by an embodiment of the present application;

[0068] Figure 4 d is a schematic diagram of seismic data obtained after stripping igneous rock reflection signal data when a target layer window is parallel to a target layer seismic wave peak horizon provided by an embodiment of the present application;

[0069] Figure 5 a is a schematic diagram of seismic data obtained after stripping igneous rock reflection signal data when a target layer window is parallel to an igneous rock top surface well separated interpolation horizon provided by an embodiment of the present application;

[0070] Figure 5 b is a schematic diagram of seismic data obtained after stripping igneous rock reflection signal data using a traditional wavelet decomposition and reconstruction method provided by an embodiment of the present application;

[0071] Figure 6 is a schematic diagram of igneous rock reflection signal data provided by an embodiment of the present application;

[0072] Figure 7 is a schematic diagram of original seismic data provided by an embodiment of the present application;

[0073] Figure 8 is a schematic diagram of seismic data obtained after stripping igneous rock reflection signal data provided by an embodiment of the present application;

[0074] Figure 9 a is a schematic diagram of a root mean square amplitude attribute before stripping igneous rock reflection signal data provided by an embodiment of the present application;

[0075] Figure 9 b is a schematic diagram of a root mean square amplitude attribute after stripping igneous rock reflection signal data provided by an embodiment of the present application;

[0076] Figure 10is a structural schematic diagram of a seismic data processing device provided by an embodiment of the present application;

[0077] Figure 11 is a structural block diagram of a terminal provided by an embodiment of the present application;

[0078] Figure 12 is a structural block diagram of a server provided by an embodiment of the present application. DETAILED DESCRIPTION

[0079] In order to make the technical solutions and advantages of the present application clearer, the embodiments of the present application are described in further detail below.

[0080] The terms "first", "second", "third", and "fourth" and the like in the specification and claims of the present application and the drawings are used to distinguish different objects, and are not used to describe a particular order. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not limited to the listed steps or units, but can optionally include steps or units not listed, or can optionally include other steps or units inherent to the process, method, product, or device.

[0081] It should be noted that the information (including but not limited to user device information, user personal information, etc.), data (including but not limited to data for analysis, stored data, displayed data, etc.), and signals involved in the present application are all authorized by the user or fully authorized by all parties, and the collection, use, and processing of related data need to comply with relevant laws, regulations, and standards of relevant countries and regions. For example, the seismic data, logging data, etc. involved in the present application are obtained under full authorization.

[0082] Figure 1 is a schematic diagram of an implementation environment of a seismic data processing method provided by an embodiment of the present application, see Figure 1 The implementation environment includes an electronic device, which can be provided as a terminal 101 or as a terminal 101 and a server 102. If the electronic device is provided as a terminal 101 and a server 102, the terminal 101 and the server 102 can be connected through a wireless or wired network. In the embodiments of the present application, the electronic device is not specifically limited.

[0083] If the electronic device is provided as a terminal 101, the terminal 101 processes the seismic data.

[0084] If the electronic device is provided as a terminal 101 and a server 102, the terminal 101 sends the seismic data to the server 102, the server 102 processes the seismic data, and then returns the processing result to the terminal 101.

[0085] The terminal 101 is at least one of a mobile phone, a tablet computer, a PC (Personal Computer) device, a smart voice interaction device, and a vehicle-mounted terminal.

[0086] Figure 2 is a flowchart of a seismic data processing method provided by an embodiment of the present application, executed by an electronic device, referring to Figure 2 The method comprises the following steps.

[0087] Step 201: The electronic device acquires first seismic data and a seismic wavelet of a target work area.

[0088] The target work area is an area where a reservoir to be predicted is located.

[0089] The process of acquiring the first seismic data by the electronic device can be that the electronic device acquires the first seismic data input by a user or acquires the first seismic data from another electronic device, which is not limited specifically. The first seismic data is data collected by exciting seismic waves in the target work area.

[0090] The process of acquiring the seismic wavelet by the electronic device can be that the electronic device acquires logging data, and determines the seismic wavelet by fine well-seismic calibration on the logging data. The logging data is data collected by detecting a well in the target work area.

[0091] In the embodiment of the present application, the first seismic data and the seismic wavelet are both data varying with time, for example, the first seismic data can be represented as S(t), and the seismic wavelet can be represented as w(t).

[0092] For example, according to the method provided by the present application, the strong reflection signal stripping of the igneous rock of the seismic data shown in Figure 3 a is performed. Figure 3

[0093] In the geological model shown in Figure 3 a, the velocity of the igneous rock is 4000 m / s, the density is 2.45 g / cm 3 , the velocity of the sandstone is 3000 m / s, the density is 2.28 g / cm 3 , and the velocity of the mudstone is 2200 m / s, the density is 2.11 g / cm 3 ​And set the work area has 3 wells, respectively, W1, W2 and W3. Among them, the igneous rock speed refers to the propagation speed of seismic waves in igneous rocks, the mudstone speed refers to the propagation speed of seismic waves in mudstone, and the sandstone speed refers to the propagation speed of seismic waves in sandstone. The seismic wavelet is the average wavelet formed by all well calibration, and the average wavelet main frequency is 20Hz, zero phase.

[0094] Figure 3 The first set of layers explained in the seismic data shown in Figure b is the peak layer of the seismic wave of the target layer, and the second set of layers explained is the top surface well interpolation layer of the igneous rock.

[0095] Step 202: The electronic device performs Fourier transform on the first seismic data to obtain the first frequency spectrum, and performs Fourier transform on the seismic wavelet to obtain the second frequency spectrum.

[0096] The process of performing Fourier transform on the first seismic data by the electronic device to obtain the first frequency spectrum can be realized by the following steps (1) to (4), including:

[0097] (1) The electronic device obtains the first time window length and the first offset.

[0098] The first time window length is half of the time window length, and the first offset is the offset of the center point of the time window relative to the coordinate zero point. Wherein, the first time window length can be expressed as t w , and the first offset can be expressed as Δt.

[0099] (2) The electronic device determines the sum of the first offset and the first time window length to obtain the upper limit value.

[0100] The upper limit value is the upper limit value of the integral in the Fourier transform, which can be expressed as Δt+t w .

[0101] (3) The electronic device determines the difference between the first offset and the first time window length to obtain the lower limit value.

[0102] The lower limit value is the lower limit value of the integral in the Fourier transform, which can be expressed as Δt-t w .

[0103] (4) The electronic device performs Fourier transform on the first seismic data within the time range corresponding to the upper limit value and the lower limit value to obtain the first frequency spectrum.

[0104] The electronic device can perform Fourier transform on the first seismic data within the time range corresponding to the upper limit value and the lower limit value based on the fourth relationship data to obtain the first frequency spectrum.

[0105] The fourth relationship data can be expressed as:

[0106] wherein S(t w , f) represents the first spectrum, f represents frequency, and i represents an imaginary unit.

[0107] The electronic device substitutes the upper limit value, the lower limit value, and the first seismic data into the fourth relationship data to obtain the first spectrum.

[0108] The process in which the electronic device performs Fourier transform on the seismic wavelet to obtain the second spectrum can be: the electronic device substitutes the seismic wavelet into the fifth relationship data to obtain the second spectrum.

[0109] The fifth relationship data can be represented as: W(f) represents the second spectrum.

[0110] Step 203: The electronic device determines the reflectivity data volume based on the first relationship data, the first spectrum, and the second spectrum.

[0111] This step can be implemented through the following steps (1) to (2), comprising:

[0112] (1) The electronic device substitutes the first spectrum and the second spectrum into the first relationship data to determine the odd component and the even component of the reflectivity data volume.

[0113] The first relationship data is used to represent the relationship among the first spectrum, the second spectrum, the odd component, and the even component of the reflectivity data volume.

[0114] The first relationship data can be represented as:

[0115]

[0116] wherein r o (t) and r e (t) represent the odd component and the even component of the reflectivity data volume respectively, T(t) represents the time window length, f L represents the low-frequency cutoff value, f H represents the high-frequency cutoff value, and α o and α e are the weight coefficients of the odd component and the even component respectively, which are used to adjust the noise and the resolution, Re represents the real part, and Im represents the imaginary part.

[0117] The electronic device substitutes the first spectrum and the second spectrum into the first relationship data, determines the minimum value of the first relationship data through the least square conjugate gradient method, and determines the odd component and the even component of the reflectivity data volume as r o (t) and r e (t) corresponding to the minimum value of the first relationship data. It can be seen that the odd component and the even component of the reflectivity data volume also change with time.

[0118] For example, the low frequency cutoff value is 0 Hz, the high frequency cutoff value is 150 Hz, the weight coefficient of the odd component is 1, and the weight coefficient of the even component is 3.

[0119] (2) The electronic device determines the sum of the odd component and the even component of the reflection coefficient data body, to obtain the reflection coefficient data body.

[0120] The reflection coefficient data body can be represented as r(t), and r(t) = r e (t) + r o (t).

[0121] Step 204: The electronic device converts the reflection coefficient data body into a lithology wave impedance body based on second relationship data.

[0122] The second relationship data is used to represent the relationship between the reflection coefficient data body and the lithology wave impedance body.

[0123] The electronic device obtains an initial wave impedance value, and substitutes the initial wave impedance value and the reflection coefficient data body into the second relationship data to obtain the lithology wave impedance body.

[0124] The second relationship data can be represented as:

[0125] Wherein, I(t) represents the lithology wave impedance body, and it can be seen that the lithology wave impedance body also changes with time, and the lithology wave impedance values corresponding to different time points form the lithology wave impedance body, and therefore, the lithology wave impedance body includes a plurality of lithology wave impedance values corresponding to different time points. represents the initial wave impedance value, which can be calculated by the electronic device through drilling data.

[0126] Referring to Figure 4 a, Figure 4 a shows the lithology wave impedance body obtained after spectrum inversion using Figure 3 b shows the seismic data.

[0127] Step 205: The electronic device performs lithology replacement on the lithology wave impedance body based on a threshold value of igneous rock wave impedance and a threshold value of sandstone wave impedance, to obtain an igneous rock wave impedance body.

[0128] This step can be implemented through the following steps (1) to (4), including:

[0129] (1) The electronic device obtains an average wave impedance value of igneous rock and an average wave impedance value of mudstone.

[0130] The fine physical analysis on the rock can determine the average wave impedance value of the igneous rock and the average wave impedance value of the mudstone, and the electronic device obtains the input average wave impedance value of the igneous rock and the average wave impedance value of the mudstone. In addition, the fine physical analysis on the rock can also determine the wave impedance threshold value of the igneous rock and the wave impedance threshold value of the sandstone.

[0131] For example, the wave impedance threshold value of the igneous rock is 9800 g / cm 3 * m / s, the wave impedance threshold value of the sandstone is 6840 g / cm 3 * m / s, the average wave impedance value of the igneous rock is 9800 g / cm 3 * m / s, the average wave impedance value of the mudstone is 4642 g / cm 3 * m / s.

[0132] (2) For the lithology wave impedance value corresponding to the first time, if the lithology wave impedance value corresponding to the first time is not less than the wave impedance threshold value of the igneous rock, the electronic device replaces the lithology wave impedance value corresponding to the first time with the average wave impedance value of the igneous rock. The first time is any time in the plurality of times.

[0133] (3) If the lithology wave impedance value corresponding to the first time is less than the wave impedance threshold value of the sandstone, the electronic device replaces the lithology wave impedance value corresponding to the first time with the average wave impedance value of the mudstone.

[0134] (4) The electronic device determines the igneous rock wave impedance body based on the average wave impedance value of the igneous rock or the average wave impedance value of the mudstone corresponding to the plurality of times.

[0135] The electronic device determines the wave impedance value corresponding to each time, which is the average wave impedance value of the igneous rock or the average wave impedance value of the mudstone, and composes the igneous rock wave impedance body from the wave impedance values corresponding to the plurality of times.

[0136] In the embodiments of the present application, the processes corresponding to steps (2) to (4) can be represented by the following sixth relationship data:

[0137] The sixth relationship data is:

[0138] Wherein, Zm represents the wave impedance threshold value of the igneous rock, Zs represents the wave impedance threshold value of the sandstone, Z1 represents the average wave impedance value of the igneous rock, Z2 represents the average wave impedance value of the mudstone, I f (t) represents the igneous rock wave impedance body, which is the wave impedance body after removing the sandstone.

[0139] Referring to Figure 4 b, Figure 4 b shows the igneous rock wave impedance body obtained after the lithology replacement of the lithology wave impedance body.

[0140] Step 206: The electronic device converts the igneous rock wave impedance body into igneous rock reflection signal data based on the third relationship data.

[0141] This step can be implemented through the following (1) to (5), including:

[0142] (1) The electronic device acquires a sampling time interval.

[0143] The sampling time interval is the sampling interval of the seismic data, which can be represented as Δs. For example, Δs is 1 ms.

[0144] (2) The electronic device determines the sum of the first time and the sampling time interval to obtain the second time.

[0145] For example, the first time is t0, and the second time can be represented as t0+Δs.

[0146] (3) The electronic device determines a first wave impedance value corresponding to the first time and a second wave impedance value corresponding to the second time based on the igneous rock wave impedance body.

[0147] The igneous rock wave impedance body is composed of wave impedance values corresponding to multiple times, and the electronic device determines the first wave impedance value corresponding to the first time and the second wave impedance value corresponding to the second time. The first wave impedance value corresponding to the first time is the average wave impedance value of the igneous rock or the average wave impedance value of the mudstone, and the second wave impedance value corresponding to the second time is the average wave impedance value of the igneous rock or the average wave impedance value of the mudstone. The first wave impedance value corresponding to the first time can be represented as I f (t0), and the second wave impedance value corresponding to the second time can be represented as I f (t0+Δs).

[0148] (4) The electronic device substitutes the first wave impedance value, the second wave impedance value, and the seismic wavelet corresponding to the first time into the third relationship data to obtain the reflection signal data corresponding to the first time.

[0149] The third relationship data is used to represent the relationship between the igneous rock wave impedance body and the igneous rock reflection signal data, and the third relationship data can be represented as:

[0150] Where S q (t) represents the igneous rock reflection signal data.

[0151] The electronic device substitutes the first wave impedance value, the second wave impedance value, and the seismic wavelet corresponding to the first time into the third relationship data to obtain the reflection signal data corresponding to the first time. The reflection signal data corresponding to the first time can be represented as:

[0152] (5) The electronic device determines the igneous rock reflection signal data based on the reflection signal data corresponding to the plurality of time points.

[0153] The electronic device groups the reflection signal data corresponding to the plurality of time points into the igneous rock reflection signal data.

[0154] Referring to Figure 4 c, Figure 4 c shows the igneous rock reflection signal data obtained after the forward simulation of the igneous rock wave impedance body.

[0155] Step 207: The electronic device separates the igneous rock reflection signal data from the first seismic data.

[0156] The electronic device determines a separation correction coefficient, determines the product of the separation correction coefficient and the igneous rock reflection signal data, obtains igneous rock correction data, determines the difference between the first seismic data and the igneous rock correction data, and obtains second seismic data, which is the seismic data after the separation of the igneous rock reflection signal data.

[0157] The separation correction coefficient can be determined according to the energy matching relationship between the igneous rock development area and the non-development area, and the range is between 0.5 and 1.5, that is, λ∈[0.5, 1.5], wherein λ represents the separation correction coefficient. The closer the energy between the igneous rock development area and the non-development area, the closer the separation correction coefficient to 1.

[0158] According to step 206, the igneous rock reflection coefficient includes reflection signal data corresponding to a plurality of time points. The electronic device determines the product of the separation correction coefficient and the reflection signal data corresponding to each time point to obtain first correction data. The igneous rock correction data is composed of a plurality of time points corresponding to the first correction data.

[0159] The first seismic data is composed of a plurality of time points corresponding to the third seismic data, the electronic device determines the difference between the third seismic data corresponding to each time point and the first correction data corresponding to the time point to obtain the fourth seismic data corresponding to the time point, and the electronic device groups the fourth seismic data corresponding to a plurality of time points into the second seismic data. The second seismic data can be represented as: S p (t)=S(t)-λS q (t), S p (t) represents the second seismic data.

[0160] For example, the separation correction coefficient is 1, and on this basis, referring to Figure 4 d, Figure 4 d shows the seismic data obtained after the igneous rock reflection signal data is stripped from the seismic data, wherein the target layer window is parallel to the target layer seismic wave peak horizon.

[0161] Through Figure 3 b,Figure 4 dWith Figure 3 aIt can be seen that due to the strong reflection shielding effect of the igneous rock, the original seismic data is difficult to identify the boundary of the sand body, and after the igneous rock reflection signal data is removed, four independent distributed events can be seen, and the pinchout point of the sand body can be clearly identified.

[0162] Figure 5 aThe effect of removing the strong reflection signal of the igneous rock by the method provided in the application is shown by using a target layer window parallel to the well layer interpolation position of the top surface of the igneous rock, Figure 5 bThe effect of removing the strong reflection signal of the igneous rock by using the traditional wavelet decomposition and reconstruction method is shown. By comparing Figure 5 aWith Figure 4 dIt is found by comparison that no matter whether the target layer window is parallel to the peak layer position of the seismic wave of the target layer or parallel to the well layer interpolation position of the top surface of the igneous rock, the effect of removing the strong reflection signal of the igneous rock by the method provided in the application is relatively ideal, and the difference is small, which indicates that the method provided in the application is relatively insensitive to the layer interpretation quality. By comparing Figure 5 bWith Figure 4 dIt is found by comparison that the method provided in the application has better effect than the traditional wavelet decomposition and reconstruction method, and the traditional method obviously removes the effective signal of the sand body at W2 well, and the change in the lateral direction of the sand body is still difficult to identify. However, the pinchout point position identified after the processing by the method provided in the application is basically consistent with the pinchout point position of the sand body in the geological model, and the removed signal has clear geological significance, that is, the reflection signal of the igneous rock.

[0163] In the embodiment of the application, after the electronic device determines the second seismic data, the reservoir can be characterized based on the second seismic data, and the reservoir prediction can be performed.

[0164] It should be noted that in the related art, the matching pursuit method can also be used to suppress the strong reflection event. The matching pursuit method is based on the projection pursuit, the wavelet algorithm of step-by-step recursion, and the best matching of the residual signal obtained by each iteration. However, the method is also easy to remove the effective signal of the reservoir not affected by the igneous rock. Moreover, the matching pursuit method and the multi-wavelet decomposition and reconstruction method are greatly affected by the layer interpretation quality in removing the strong reflection signal of the igneous rock, and the removed signal has unclear geological significance.

[0165] The application provides a method for removing the strong reflection signal of the igneous rock based on forward and inverse modeling. The method first performs lithology inversion by using the spectral inversion method to obtain a lithology wave impedance body, then performs lithology replacement to obtain an igneous rock wave impedance body, further uses the forward modeling technology to obtain the strong reflection signal of the igneous rock, and finally removes the strong reflection signal of the igneous rock from the original seismic data to obtain the seismic data after removing the strong reflection signal of the igneous rock, which is shown in Figure 6The method breaks away from the idea of energy stripping of all seismic data in the study area by the method of matching pursuit and the method of multi-wavelet decomposition and reconstruction, fully utilizes the information of drilling data, first depicts the thickness and distribution range of the development of the igneous rock, and then extracts the strong reflection signal of the igneous rock, and then strips the strong reflection signal of the igneous rock from the original seismic data. The method can accurately restore the effective signal of the reservoir shielded by the strong reflection of the igneous rock, enhance the identification ability of the seismic data to the longitudinal and horizontal distribution of the reservoir, solve the problems of easy elimination of the effective signal of the reservoir and easy occurrence of abnormal channels in the related technologies, and the influence of the stripping effect on the layer interpretation quality is relatively small, and the strong reflection signal stripped has clear geological significance.

[0166] To further illustrate the effect of the method provided in the application, the actual data of a certain exploration block in a certain oilfield is taken as an example for illustration. Referring to Figure 7 , Figure 7 The original seismic data collected can be seen: due to the development of igneous rock in the target layer, the target layer is a continuous strong reflection signal, and it is difficult to identify the development boundary of the reservoir. Among them, g1 and g2 are two wells. Referring to Figure 8 , Figure 8 The seismic data after stripping the strong reflection signal of the igneous rock can be seen: the seismic data after removing the strong reflection signal of the igneous rock has natural changes in the event, uniform energy, and the energy change and superposition relationship of the event in the target layer are more clear.

[0167] Referring to Figure 9 a and Figure 9 b, Figure 9 a is the root mean square amplitude attribute before stripping the strong reflection signal of the igneous rock, Figure 9 b is the root mean square attribute after stripping the strong reflection signal of the igneous rock, and Figure 9 a and Figure 9 b, before stripping the strong reflection signal of the igneous rock, the attribute energy is concentrated, and the abnormal area mainly reflects the development area of the igneous rock, and cannot represent the change rule of the sand body. After stripping the strong reflection signal of the igneous rock, the attribute details are more abundant, and the change of the sand body is better reflected.

[0168] Therefore, the method provided in the application has good application effect, and can lay a reliable data foundation for further fine description of the sand body by reservoir inversion.

[0169] The embodiment of the present application provides a seismic data processing method, which comprises the following steps: performing Fourier transform on first seismic data and a seismic wavelet to obtain a first spectrum and a second spectrum respectively; determining a reflection coefficient data volume based on the first spectrum and the second spectrum; converting the reflection coefficient data volume into a lithology wave impedance volume; performing lithology replacement on the lithology wave impedance volume to obtain an igneous rock wave impedance volume; converting the igneous rock wave impedance volume into igneous rock reflection signal data; and finally separating the igneous rock reflection signal data from the first seismic data. Therefore, the method only removes the strong reflection signal of the igneous rock from the seismic data, and retains the effective signal of the reservoir, so that the reservoir prediction can be performed based on the effective signal of the reservoir, thereby improving the accuracy of the reservoir prediction.

[0170] Figure 10 is a structural schematic diagram of a seismic data processing device provided by the embodiment of the present application, referring to Figure 10 The device comprises:

[0171] The acquisition module 1001 is configured to acquire first seismic data and a seismic wavelet of a target work area.

[0172] The transform module 1002 is configured to perform Fourier transform on the first seismic data to obtain a first spectrum, and perform Fourier transform on the seismic wavelet to obtain a second spectrum.

[0173] The first determination module 1003 is configured to determine a reflection coefficient data volume based on first relationship data, the first spectrum and the second spectrum, wherein the first relationship data is used to represent the relationship among the first spectrum, the second spectrum and the reflection coefficient data volume.

[0174] The first conversion module 1004 is configured to convert the reflection coefficient data volume into a lithology wave impedance volume based on second relationship data, wherein the second relationship data is used to represent the relationship between the reflection coefficient data volume and the lithology wave impedance volume.

[0175] The second conversion module 1005 is configured to perform lithology replacement on the lithology wave impedance volume based on an igneous rock wave impedance threshold and a sandstone wave impedance threshold to obtain an igneous rock wave impedance volume.

[0176] The third conversion module 1006 is configured to convert the igneous rock wave impedance volume into igneous rock reflection signal data based on third relationship data, wherein the third relationship data is used to represent the relationship between the igneous rock wave impedance volume and the igneous rock reflection signal data.

[0177] The separation module 1007 is configured to separate the igneous rock reflection signal data from the first seismic data.

[0178] In a possible implementation manner, the lithology wave impedance volume comprises lithology wave impedance values corresponding to a plurality of time points.

[0179] The second conversion module 1005 is configured to obtain an igneous rock average wave impedance value and a mudstone average wave impedance value; for the lithology wave impedance value corresponding to the first time, if the lithology wave impedance value corresponding to the first time is not less than the igneous rock wave impedance threshold value, the lithology wave impedance value corresponding to the first time is replaced by the igneous rock average wave impedance value; wherein the first time is any time in the plurality of times; if the lithology wave impedance value corresponding to the first time is less than the sandstone wave impedance threshold value, the lithology wave impedance value corresponding to the first time is replaced by the mudstone average wave impedance value; based on the igneous rock average wave impedance value or the mudstone average wave impedance value corresponding to the plurality of times, the igneous rock wave impedance body is determined.

[0180] In another possible implementation, the third conversion module 1006 is configured to obtain a sampling time interval; determine the sum of the first time and the sampling time interval to obtain a second time; determine a first wave impedance value corresponding to the first time and a second wave impedance value corresponding to the second time based on the igneous rock wave impedance body; wherein the first wave impedance value corresponding to the first time is the igneous rock average wave impedance value or the mudstone average wave impedance value, and the second wave impedance value corresponding to the second time is the igneous rock average wave impedance value or the mudstone average wave impedance value; the first wave impedance value, the second wave impedance value, and the seismic wavelet corresponding to the first time are substituted into the third relationship data to obtain the reflection signal data corresponding to the first time; and the igneous rock reflection signal data is determined based on the reflection signal data corresponding to the plurality of times.

[0181] In another possible implementation, the separation module 1007 is configured to determine a separation correction coefficient; determine the product of the separation correction coefficient and the igneous rock reflection signal data to obtain igneous rock correction data; and determine the difference between the first seismic data and the igneous rock correction data to obtain the second seismic data.

[0182] In another possible implementation, the transformation module 1002 is configured to obtain a first time window length and a first offset; wherein the first time window length is half of the time window length, and the first offset is an offset of the center point of the time window relative to the coordinate zero point; determine the sum of the first offset and the first time window length to obtain an upper limit value; determine the difference between the first offset and the first time window length to obtain a lower limit value; and perform Fourier transform on the first seismic data in the time range corresponding to the upper limit value and the lower limit value to obtain the first frequency spectrum.

[0183] In another possible implementation, the first determination module 1003 is configured to substitute the first frequency spectrum and the second frequency spectrum into the first relationship data to determine the odd component and the even component of the reflection coefficient data body; and determine the sum of the odd component and the even component of the reflection coefficient data body to obtain the reflection coefficient data body.

[0184] In another possible implementation, the first conversion module 1004 is configured to obtain an initial wave impedance value; and substitute the initial wave impedance value and the reflectivity data volume into the second relationship data to obtain a lithology wave impedance volume.

[0185] The embodiment of the present application provides a seismic data processing device, which performs Fourier transform on first seismic data and a seismic wavelet to obtain a first frequency spectrum and a second frequency spectrum respectively, determines a reflectivity data volume based on the first frequency spectrum and the second frequency spectrum, converts the reflectivity data volume into a lithology wave impedance volume, performs lithology replacement on the lithology wave impedance volume to obtain an igneous rock wave impedance volume, converts the igneous rock wave impedance volume into igneous rock reflection signal data, and finally separates the igneous rock reflection signal data from the first seismic data. It can be seen that the device only removes the strong reflection signal of the igneous rock from the seismic data, and retains the effective signal of the reservoir, so that reservoir prediction can be performed based on the effective signal of the reservoir, and therefore the accuracy of reservoir prediction is improved.

[0186] Reference Figure 11 , Figure 11 A structure block diagram of a terminal 1100 is shown, which is provided by an example embodiment of the present application. The terminal 1100 can be a portable mobile terminal, such as a smart phone, a tablet computer, an MP3 (Moving Picture Experts Group Audio Layer III) player, an MP4 (Moving Picture Experts Group Audio Layer IV) player, a notebook computer or a desktop computer. The terminal 1100 can also be referred to as a user equipment, a portable terminal, a laptop terminal, a desktop terminal or other names.

[0187] Generally, the terminal 1100 includes a processor 1101 and a memory 1102.

[0188] The processor 1101 can include one or more processing cores, such as a 4-core processor, an 8-core processor, and the like. The processor 1101 can be implemented in at least one of a hardware form of a DSP (Digital Signal Processing), an FPGA (Field-Programmable Gate Array), a PLA (Programmable Logic Array). The processor 1101 can also include a main processor and a coprocessor, the main processor being a processor for processing data in an awake state, also known as a CPU (Central Processing Unit), and the coprocessor being a low-power processor for processing data in a standby state. In some embodiments, the processor 1101 can be integrated with a GPU (Graphics Processing Unit) for rendering and drawing content required to be displayed by the display screen. In some embodiments, the processor 1101 can also include an AI (Artificial Intelligence) processor for processing computing operations related to machine learning.

[0189] The memory 1102 can include one or more computer-readable storage media that can be non-transitory. The memory 1102 can also include a high-speed random access memory, and a nonvolatile memory such as one or more disk storage devices, flash storage devices. In some embodiments, the non-transitory computer-readable storage medium in the memory 1102 is used to store at least one program code for being executed by the processor 1101 to implement the operations performed by the terminal in the seismic data processing method provided by the method embodiment of the present application.

[0190] In some embodiments, the terminal 1100 can also optionally include a peripheral device interface 1103 and at least one peripheral device. The processor 1101, the memory 1102, and the peripheral device interface 1103 can be connected through a bus or a signal line. Each peripheral device can be connected to the peripheral device interface 1103 through a bus, a signal line, or a circuit board. Specifically, the peripheral device includes at least one of a radio frequency circuit 1104, a display screen 1105, a camera assembly 1106, an audio circuit 1107, and a power supply 1108.

[0191] The peripheral interface 1103 can be used to connect at least one I / O (Input / Output) related peripheral device to the processor 1101 and the memory 1102. In some embodiments, the processor 1101, the memory 1102 and the peripheral interface 1103 are integrated on the same chip or circuit board; in some other embodiments, any one or two of the processor 1101, the memory 1102 and the peripheral interface 1103 can be implemented on a separate chip or circuit board, and the present embodiments are not limited in this regard.

[0192] The radio frequency circuit 1104 is used to receive and send RF (Radio Frequency) signals, also known as electromagnetic signals. The radio frequency circuit 1104 communicates with a communication network and other communication devices through electromagnetic signals. The radio frequency circuit 1104 converts electrical signals into electromagnetic signals for transmission, or converts received electromagnetic signals into electrical signals. Optionally, the radio frequency circuit 1104 includes an antenna system, an RF transceiver, one or more amplifiers, a tuner, an oscillator, a digital signal processor, a codec chipset, a subscriber identity module card, and the like. The radio frequency circuit 1104 can communicate with other terminals through at least one wireless communication protocol. The wireless communication protocol includes but is not limited to the World Wide Web, a metropolitan area network, an intranet, various generations of mobile communication networks (2G, 3G, 4G and 5G), a wireless local area network and / or a WiFi (Wireless Fidelity) network. In some embodiments, the radio frequency circuit 1104 can also include NFC (Near Field Communication) related circuitry, and the present application is not limited in this regard.

[0193] The display screen 1105 is configured to display a UI (User Interface). The UI can include graphics, text, icons, video, and any combination thereof. When the display screen 1105 is a touch display screen, the display screen 1105 is further configured to capture touch signals on or above the surface of the display screen 1105. The touch signals can be input to the processor 1101 as control signals for processing. In this case, the display screen 1105 can also be configured to provide virtual buttons and / or virtual keyboard, also known as soft buttons and / or soft keyboard. In some embodiments, the display screen 1105 can be one, disposed on the front panel of the terminal 1100; in other embodiments, the display screen 1105 can be at least two, respectively disposed on different surfaces of the terminal 1100 or in a folding design; in other embodiments, the display screen 1105 can be a flexible display screen, disposed on a curved surface or a folding surface of the terminal 1100. Even, the display screen 1105 can also be disposed in an irregular shape, i.e., a special-shaped screen. The display screen 1105 can be made of LCD (Liquid Crystal Display), OLED (Organic Light-Emitting Diode), etc.

[0194] The camera assembly 1106 is configured to capture images or videos. Optionally, the camera assembly 1106 includes a front camera and a rear camera. Typically, the front camera is disposed on the front panel of the terminal, and the rear camera is disposed on the back of the terminal. In some embodiments, the rear camera is at least two, which is any one of a main camera, a depth-of-field camera, a wide-angle camera, and a telephoto camera, to realize the background blur function by fusing the main camera and the depth-of-field camera, the panoramic shooting and VR (Virtual Reality) shooting function by fusing the main camera and the wide-angle camera, or other fusion shooting functions. In some embodiments, the camera assembly 1106 can further include a flash. The flash can be a single-color temperature flash or a dual-color temperature flash. The dual-color temperature flash refers to the combination of a warm light flash and a cold light flash, which can be used for light compensation under different color temperatures.

[0195] The audio circuit 1107 can include a microphone and a speaker. The microphone is used to collect sound waves of the user and the environment, and convert the sound waves into an electrical signal input to the processor 1101 for processing, or input to the radio frequency circuit 1104 to realize voice communication. For the purpose of stereo sound collection or noise reduction, the microphone can be multiple, respectively arranged at different parts of the terminal 1100. The microphone can also be an array microphone or an omnidirectional collection type microphone. The speaker is used to convert the electrical signal from the processor 1101 or the radio frequency circuit 1104 into sound waves. The speaker can be a traditional diaphragm speaker, or a piezoelectric ceramic speaker. When the speaker is a piezoelectric ceramic speaker, not only can it convert electrical signals into sound waves that humans can hear, but it can also convert electrical signals into sound waves that humans cannot hear for ranging purposes. In some embodiments, the audio circuit 1107 can also include a headphone jack.

[0196] The power supply 1108 is used to supply power to each component in the terminal 1100. The power supply 1108 can be alternating current, direct current, disposable battery or rechargeable battery. When the power supply 1108 includes a rechargeable battery, the rechargeable battery can be a wired charging battery or a wireless charging battery. The wired charging battery is a battery charged through a wired line, and the wireless charging battery is a battery charged through a wireless coil. The rechargeable battery can also be used to support fast charging technology.

[0197] In some embodiments, the terminal 1100 also includes one or more sensors 1109. The one or more sensors 1109 include, but are not limited to, an acceleration sensor 1110, a gyroscope sensor 1111, a pressure sensor 1112, an optical sensor 1113, and a proximity sensor 1114.

[0198] The acceleration sensor 1110 can detect the acceleration magnitude in three coordinate axes of the coordinate system established by the terminal 1100. For example, the acceleration sensor 1110 can be used to detect the components of the gravitational acceleration in three coordinate axes. The processor 1101 can control the display screen 1105 to display the user interface in a landscape view or a portrait view based on the gravitational acceleration signal collected by the acceleration sensor 1110. The acceleration sensor 1110 can also be used for game or user motion data collection.

[0199] The gyroscope sensor 1111 can detect the body orientation and rotation angle of the terminal 1100, and the gyroscope sensor 1111 can collect 3D actions of the user on the terminal 1100 in cooperation with the acceleration sensor 1110. The processor 1101 can realize the following functions based on the data collected by the gyroscope sensor 1111: motion sensing (such as changing the UI based on the user's tilt operation), image stabilization when shooting, game control, and inertial navigation.

[0200] The pressure sensor 1112 can be disposed at the side frame of the terminal 1100 and / or the lower layer of the display screen 1105. When the pressure sensor 1112 is disposed at the side frame of the terminal 1100, the holding signal of the user to the terminal 1100 can be detected, and the left-hand or right-hand recognition or the shortcut operation can be performed by the processor 1101 based on the holding signal collected by the pressure sensor 1112. When the pressure sensor 1112 is disposed at the lower layer of the display screen 1105, the operability control on the UI interface can be controlled by the processor 1101 based on the pressure operation of the user to the display screen 1105. The operability control includes at least one of the button control, the scroll bar control, the icon control, and the menu control.

[0201] The optical sensor 1113 is used to collect the ambient light intensity. In one embodiment, the processor 1101 can control the display brightness of the display screen 1105 based on the ambient light intensity collected by the optical sensor 1113. Specifically, when the ambient light intensity is high, the display brightness of the display screen 1105 is increased; when the ambient light intensity is low, the display brightness of the display screen 1105 is decreased. In another embodiment, the processor 1101 can also dynamically adjust the shooting parameter of the camera assembly 1106 based on the ambient light intensity collected by the optical sensor 1113.

[0202] The proximity sensor 1114, also called the distance sensor, is usually disposed at the front panel of the terminal 1100. The proximity sensor 1114 is used to collect the distance between the user and the front of the terminal 1100. In one embodiment, when the proximity sensor 1114 detects that the distance between the user and the front of the terminal 1100 gradually decreases, the display screen 1105 is switched from the bright screen state to the off-screen state by the processor 1101; when the proximity sensor 1114 detects that the distance between the user and the front of the terminal 1100 gradually increases, the display screen 1105 is switched from the off-screen state to the bright screen state by the processor 1101.

[0203] Those skilled in the art can understand that Figure 11 The structure shown in the figure does not constitute a limitation on the terminal 1100, and can include more or fewer components than the figure, or combine certain components, or adopt a different component arrangement.

[0204] The structure block diagram of the server can be referred to Figure 12The server 1200 can be different in configuration or performance, and can include a processor (Central Processing Units, CPU) 1201 and a memory 1202, wherein the memory 1202 stores at least one program code, the at least one program code is loaded and executed by the processor 1201 to realize the operation of the server in the above-mentioned seismic data processing method. Of course, the server 1200 can also have a wired or wireless network interface, a keyboard, an input and output interface and other components for realizing the function of the device, so as to input and output, and the server 1200 can also include other components for realizing the function of the device, which will not be described here.

[0205] In an exemplary embodiment, a computer readable storage medium is also provided, and the computer readable medium stores at least one program code, the at least one program code is loaded and executed by the processor to realize the seismic data processing method in the above-mentioned embodiments.

[0206] In an exemplary embodiment, a computer program product is also provided, and the computer program product stores at least one program code, the at least one program code is loaded and executed by the processor to realize the seismic data processing method in the above-mentioned embodiments.

[0207] Those skilled in the art can understand that all or part of the steps of the above-mentioned embodiments can be completed by hardware, or by program to instruct related hardware to complete, and the program can be stored in a computer readable storage medium, and the storage medium mentioned above can be a read-only memory, a magnetic disk or an optical disk.

[0208] The above is only for the convenience of those skilled in the art to understand the technical solutions of the present application, and is not used to limit the present application. Any modification, equivalent replacement, improvement, etc. within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A method of seismic data processing, characterized by, The method comprises: acquiring first seismic data and a seismic wavelet of a target work area; performing Fourier transform on the first seismic data to obtain a first frequency spectrum and performing Fourier transform on the seismic wavelet to obtain a second frequency spectrum; determining a reflection coefficient data volume based on first relationship data, the first frequency spectrum and the second frequency spectrum; wherein the first relationship data is used to represent the relationship among the first frequency spectrum, the second frequency spectrum and the reflection coefficient data volume; convert the reflection coefficient data volume into a lithology wave impedance volume based on second relationship data, wherein the second relationship data is used to represent a relationship between the reflection coefficient data volume and the lithology wave impedance volume, and the second relationship data is represented as ; wherein, represents the lithology wave impedance volume, represents an initial wave impedance value, represents a first offset amount, represents a first time window length, represents the reflection coefficient data volume; performing lithology replacement on the lithology wave impedance volume based on an igneous rock wave impedance threshold and a sandstone wave impedance threshold to obtain an igneous rock wave impedance volume; The igneous rock wave impedance body is converted into igneous rock reflection signal data based on third relationship data, wherein the third relationship data is used to represent a relationship between the igneous rock wave impedance body and the igneous rock reflection signal data, and the third relationship data is represented as ; wherein, represents the igneous rock reflection signal data, represents a sampling time interval, represents a first wave impedance value corresponding to a first time, represents a second wave impedance value corresponding to a second time, represents a seismic wavelet corresponding to the first time. separating the igneous rock reflection signal data from the first seismic data.

2. The method of claim 1, wherein, The lithology wave impedance volume comprises lithology wave impedance values corresponding to a plurality of time points; The lithology replacement on the lithology wave impedance volume based on the igneous rock wave impedance threshold and the sandstone wave impedance threshold to obtain the igneous rock wave impedance volume comprises: acquiring an igneous rock average wave impedance value and a mudstone average wave impedance value; for the lithology wave impedance value corresponding to the first time point, if the lithology wave impedance value corresponding to the first time point is not less than the igneous rock wave impedance threshold, replacing the lithology wave impedance value corresponding to the first time point with the igneous rock average wave impedance value; wherein the first time point is any time point in the plurality of time points; if the lithology wave impedance value corresponding to the first time point is less than the sandstone wave impedance threshold, replacing the lithology wave impedance value corresponding to the first time point with the mudstone average wave impedance value; determining the igneous rock wave impedance volume based on the igneous rock average wave impedance values or the mudstone average wave impedance values corresponding to the plurality of time points.

3. The method of claim 2, wherein, The conversion of the igneous rock wave impedance volume into the igneous rock reflection signal data based on the third relationship data comprises: acquiring the sampling time interval; determining the sum of the first time point and the sampling time interval to obtain the second time point; determining a first wave impedance value corresponding to the first time point and a second wave impedance value corresponding to the second time point based on the igneous rock wave impedance volume; wherein the first wave impedance value corresponding to the first time point is the igneous rock average wave impedance value or the mudstone average wave impedance value, and the second wave impedance value corresponding to the second time point is the igneous rock average wave impedance value or the mudstone average wave impedance value; substituting the first wave impedance value, the second wave impedance value and the seismic wavelet corresponding to the first time point into the third relationship data to obtain reflection signal data corresponding to the first time point; determining the igneous rock reflection signal data based on the reflection signal data corresponding to the plurality of time points.

4. The method of claim 1, wherein, The separation of the igneous rock reflection signal data from the first seismic data comprises: determining a separation correction coefficient; determining the product of the separation correction coefficient and the igneous rock reflection signal data to obtain igneous rock correction data; determining the difference between the first seismic data and the igneous rock correction data to obtain second seismic data.

5. The method of claim 1, wherein, The Fourier transform on the first seismic data to obtain a first frequency spectrum comprises: obtaining the first time window length and the first offset; wherein the first time window length is half of a time window length, and the first offset is an offset of a center point of a time window relative to a coordinate zero point; determining a sum value of the first offset and the first time window length to obtain an upper limit value; determining a difference value of the first offset and the first time window length to obtain a lower limit value; performing Fourier transform on the first seismic data in a time range corresponding to the upper limit value and the lower limit value to obtain the first frequency spectrum.

6. The method of claim 1, wherein, The determining of the reflectivity data volume based on the first relationship data, the first frequency spectrum and the second frequency spectrum comprises: substituting the first frequency spectrum and the second frequency spectrum into the first relationship data to determine odd components and even components of the reflectivity data volume; determining a sum value of the odd components and the even components of the reflectivity data volume to obtain the reflectivity data volume.

7. The method of claim 1, wherein, The converting of the reflectivity data volume into the lithology wave impedance volume based on the second relationship data comprises: obtaining the initial wave impedance value; substituting the initial wave impedance value and the reflectivity data volume into the second relationship data to obtain the lithology wave impedance volume.

8. A seismic data processing apparatus characterized by comprising: The device comprises: an obtaining module configured to obtain first seismic data and a seismic wavelet of a target work area; a transforming module configured to perform Fourier transform on the first seismic data to obtain a first frequency spectrum, and perform Fourier transform on the seismic wavelet to obtain a second frequency spectrum; a first determining module configured to determine a reflectivity data volume based on first relationship data, the first frequency spectrum and the second frequency spectrum; wherein the first relationship data is used to represent a relationship among the first frequency spectrum, the second frequency spectrum and the reflectivity data volume; The first conversion module is configured to convert the reflection coefficient data volume into a lithology wave impedance volume based on second relationship data, wherein the second relationship data is used to represent a relationship between the reflection coefficient data volume and the lithology wave impedance volume, and the second relationship data is represented as ; wherein, represents the lithology wave impedance volume, represents an initial wave impedance value, represents a first offset, represents a first time window length, represents the reflection coefficient data volume; a second converting module configured to perform lithology replacement on the lithology wave impedance volume based on an igneous rock wave impedance threshold and a sandstone wave impedance threshold to obtain an igneous rock wave impedance volume; The third conversion module is configured to convert the igneous rock wave impedance body into igneous rock reflection signal data based on third relationship data, wherein the third relationship data is used to represent a relationship between the igneous rock wave impedance body and the igneous rock reflection signal data, and the third relationship data is represented as ; wherein, represents the igneous rock reflection signal data, represents a sampling time interval, represents a first wave impedance value corresponding to a first time point, represents a second wave impedance value corresponding to a second time point, represents a seismic wavelet corresponding to the first time point. a separating module configured to separate the igneous rock reflection signal data from the first seismic data.

9. An electronic device, comprising: The electronic device comprises a processor and a memory, and the memory stores at least one program code, which is loaded and executed by the processor to implement the seismic data processing method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer readable storage medium stores at least one program code, which is loaded and executed by the processor to implement the seismic data processing method according to any one of claims 1 to 7.

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