Seismic data processing method and device, equipment and storage medium

Abstract

The invention discloses a seismic data processing method and device, equipment and a storage medium, and belongs to the technical field of seismic exploration. The method comprises the following steps: performing Fourier transform on first seismic data and seismic wavelets to obtain a first frequency spectrum and a second frequency spectrum respectively, determining a reflection coefficient data body based on the first frequency spectrum and the second frequency spectrum, converting the reflection coefficient data body into a lithologic wave impedance body, and performing lithologic replacement on the lithologic wave impedance body to obtain an igneous rock wave impedance body. Converting the igneous rock wave impedance body into igneous rock reflection signal data, and finally separating the igneous rock reflection signal data from the first seismic data. Therefore, according to the method, the igneous rock strong reflection signal is only removed from the seismic data, and the reservoir effective signal is reserved, so that reservoir prediction can be carried out based on the reservoir effective signal, and the accuracy of reservoir prediction is improved.

Description

Technical Field

[0001] The present application relates to the field of seismic exploration technology, and in particular to a seismic data processing method, device, equipment and storage medium. Background Art

[0002] With the continuous deepening of oil and gas exploration and development, lithologic oil and gas reservoirs have become an important target for increasing reserves and production in mature exploration areas, and it is necessary to finely characterize the lateral changes and superposition relationships of thin inter-reservoir layers. Due to the development of special lithologies near reservoirs in some areas, such as igneous rocks, they often show a strong reflection phase axis in seismic data, which has a strong shielding effect on the reservoirs developed immediately above and below, often resulting in poor reservoir prediction results.

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

[0004] However, due to the limited distribution of igneous rocks and the relatively strong reflection of reservoirs, this method can easily strip off the effective signals of reservoirs that are not affected by igneous rocks during use, affecting the accuracy of reservoir prediction. Summary of the invention

[0005] The embodiment of the present application provides a seismic data processing method, which can remove the strong reflection signal of igneous rock from the seismic data and retain the effective signal of the reservoir, thereby improving the accuracy of reservoir prediction. The technical solution is as follows:

[0006] In one aspect, a method for processing seismic data is provided, the method comprising:

[0007] Acquire the first seismic data and seismic wavelet of the target work area;

[0008] Performing Fourier transformation on the first seismic data to obtain a first spectrum and performing Fourier transformation on the seismic wavelet to obtain a second spectrum;

[0009] 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 between the first spectrum, the second spectrum and the reflection coefficient data volume;

[0010] Based on the second relationship data, the reflection coefficient data volume is converted into a lithology wave impedance volume; wherein the second relationship data is used to represent the relationship between the reflection coefficient data volume and the lithology wave impedance volume;

[0011] Based on the igneous rock wave impedance threshold and the sandstone wave impedance threshold, performing lithology replacement on the lithology wave impedance body to obtain the igneous rock wave impedance body;

[0012] Based on the third relationship data, the igneous rock wave impedance body is converted into igneous rock reflection signal data; wherein the third relationship data is used to represent the relationship between the igneous rock wave impedance body and the igneous rock reflection signal data;

[0013] The igneous rock reflection signal data is separated from the first seismic data.

[0014] In a possible implementation, the lithology wave impedance body includes lithology wave impedance values ​​corresponding to a plurality of moments;

[0015] The step of performing lithology replacement on the lithology wave impedance body based on the igneous rock wave impedance threshold and the sandstone wave impedance threshold to obtain the igneous rock wave impedance body comprises:

[0016] Obtain the average wave impedance value of igneous rock and the average wave impedance value of mudstone;

[0017] For the lithologic wave impedance value corresponding to the first moment, if the lithologic wave impedance value corresponding to the first moment is not less than the igneous rock wave impedance threshold, the lithologic wave impedance value corresponding to the first moment is replaced by the igneous rock average wave impedance value; wherein the first moment is any moment among the multiple moments;

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

[0019] The igneous rock wave impedance volume is determined based on the average wave impedance values ​​of the igneous rock or the average wave impedance values ​​of the mudstone corresponding to the multiple moments.

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

[0021] Get the sampling time interval;

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

[0023] Based on the igneous rock wave impedance body, determining a first wave impedance value corresponding to the first moment and a second wave impedance value corresponding to the second moment; wherein the first wave impedance value corresponding to the first moment 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 moment is the average wave impedance value of the igneous rock or the average wave impedance value of the mudstone;

[0024] Substituting the first wave impedance value, the second wave impedance value, and the seismic wavelet corresponding to the first moment into the third relationship data to obtain the reflection signal data corresponding to the first moment;

[0025] The igneous rock reflection signal data is determined based on the reflection signal data corresponding to the multiple time moments.

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

[0027] Determine the separation correction factor;

[0028] Determine the product of the separation correction coefficient and the igneous rock reflection signal data to obtain igneous rock correction data;

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

[0030] In another possible implementation, performing Fourier transform on the first seismic data to obtain a first spectrum includes:

[0031] 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;

[0032] Determine a sum of the first offset and the first time window length to obtain an upper limit value;

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

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

[0035] In another possible implementation manner, determining a reflection coefficient data volume based on the first relationship data, the first spectrum, and the second spectrum includes:

[0036] Substituting the first spectrum and the second spectrum into the first relationship data to determine odd components and even components of the reflection coefficient data volume;

[0037] The sum of the odd component and the even component of the reflection coefficient data volume is determined to obtain the reflection coefficient data volume.

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

[0039] Obtain the initial wave impedance value;

[0040] Substituting the initial wave impedance value and the reflection coefficient data body into the second relationship data, the lithology wave impedance body is obtained.

[0041] In another aspect, a seismic data processing device is provided, the device comprising:

[0042] An acquisition module, used for acquiring the first seismic data and seismic wavelet of the target work area;

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

[0044] A first determining module, 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 between the first spectrum, the second spectrum, and the reflection coefficient data volume;

[0045] A first conversion module, 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;

[0046] A second conversion module is used to perform lithology replacement on the lithology wave impedance body based on the igneous rock wave impedance threshold and the sandstone wave impedance threshold to obtain the igneous rock wave impedance body;

[0047] A third conversion module, used 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 the relationship between the igneous rock wave impedance body and the igneous rock reflection signal data;

[0048] A separation module is used to separate the igneous rock reflection signal data from the first seismic data.

[0049] In a possible implementation, the lithology wave impedance body includes lithology wave impedance values ​​corresponding to a plurality of moments;

[0050] The second conversion module is used to obtain the average wave impedance value of igneous rock and the average wave impedance value of mudstone; for the lithology wave impedance value corresponding to the first moment, if the lithology wave impedance value corresponding to the first moment is not less than the igneous rock wave impedance threshold, the lithology wave impedance value corresponding to the first moment is replaced by the average wave impedance value of the igneous rock; wherein the first moment is any moment of the multiple moments; if the lithology wave impedance value corresponding to the first moment is less than the sandstone wave impedance threshold, the lithology wave impedance value corresponding to the first moment is replaced by the average wave impedance value of the mudstone; based on the average wave impedance values ​​of the igneous rock or the average wave impedance values ​​of the mudstone corresponding to the multiple moments, the igneous rock wave impedance body is determined.

[0051] In another possible implementation, the third conversion module is used to obtain a sampling time interval; determine the sum of the first moment and the sampling time interval to obtain a second moment; determine a first wave impedance value corresponding to the first moment and a second wave impedance value corresponding to the second moment based on the igneous rock wave impedance body; wherein the first wave impedance value corresponding to the first moment 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 moment is the average wave impedance value of the igneous rock or the average wave impedance value of the mudstone; substitute the first wave impedance value, the second wave impedance value, and the seismic wavelet corresponding to the first moment into the third relationship data to obtain the reflection signal data corresponding to the first moment; and determine the igneous rock reflection signal data based on the reflection signal data corresponding to the multiple moments.

[0052] In another possible implementation, the separation module is used 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; determine the difference between the first seismic data and the igneous rock correction data to obtain second seismic data.

[0053] In another possible implementation, the transformation module is used 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 the 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; perform Fourier transform on the first seismic data within a time range corresponding to the upper limit value and the lower limit value to obtain the first spectrum.

[0054] In another possible implementation, the first determination module is used to substitute the first spectrum and the second spectrum into the first relationship data to determine the odd component and the even component of the reflection coefficient data body; determine the sum of the odd component and the even component of the reflection coefficient data body to obtain the reflection coefficient data body.

[0055] In another possible implementation, the first conversion module is used to obtain an initial wave impedance value; substitute the initial wave impedance value and the reflection coefficient data body into the second relationship data to obtain the lithology wave impedance body.

[0056] On the other hand, an electronic device is provided, comprising a processor and a memory, wherein the memory stores at least one program code, and the at least one program code is loaded and executed by the processor to implement any of the above-mentioned seismic data processing methods.

[0057] On the other hand, a computer-readable storage medium is provided, in which at least one program code is stored. The at least one program code is loaded and executed by a processor to implement any of the above-mentioned seismic data processing methods.

[0058] On the other hand, a computer program product is provided, wherein at least one program code is stored in the computer program product, and the at least one program code is loaded and executed by a processor to implement any of the above-mentioned seismic data processing methods.

[0059] The embodiment of the present application provides a method for processing seismic data, which performs Fourier transform on first seismic data and seismic wavelets to obtain a first spectrum and a second spectrum respectively, then determines a reflection coefficient data body based on the first spectrum and the second spectrum, converts the reflection coefficient data body into a lithology wave impedance body, then performs lithology replacement on the lithology wave impedance body to obtain an igneous rock wave impedance body, converts the igneous rock wave impedance body 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 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, thereby improving the accuracy of reservoir prediction.

[0060] It is to be understood that the foregoing general description and the following detailed description are exemplary only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 It is a schematic diagram of an implementation environment of a seismic data processing method provided in an embodiment of the present application;

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

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

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

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

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

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

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

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

[0070] Figure 5 b is a schematic diagram after the strong reflection signal of igneous rock is removed by using the traditional wavelet decomposition and reconstruction method;

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

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

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

[0074] Fig. 9 a is a schematic diagram of a root mean square amplitude attribute before stripping a strong reflection signal of igneous rock provided in an embodiment of the present application;

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

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

[0077] Fig.11 It is a structural block diagram of a terminal provided in an embodiment of the present application;

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

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

[0080] The terms "first", "second", "third" and "fourth" etc. in the specification and claims of the present application and the drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices.

[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 used for analysis, stored data, displayed data, etc.) and signals involved in this application are all authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with the relevant laws, regulations and standards of relevant countries and regions. For example, the seismic data and well logging data involved in this application are all obtained with full authorization.

[0082] Figure 1 is a schematic diagram of an implementation environment of a seismic data processing method provided in 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 can be provided 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 via 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 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 , and 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), an intelligent voice interaction device, a vehicle-mounted terminal, etc. The server 102 can be at least one of a server, a server cluster consisting of multiple servers, a cloud server, a cloud computing platform, and a virtualization center.

[0086] Figure 2 is a flowchart of a seismic data processing method provided in an embodiment of the present application, which is executed by an electronic device, see Figure 2 , the method comprising:

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

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

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

[0090] The process of the electronic device acquiring the seismic wavelet may be: the electronic device acquires well logging data, and determines the seismic wavelet by finely calibrating the well logging data. The well logging data is data collected by detecting the wells in the target work area.

[0091] In the embodiment of the present application, the first seismic data and the seismic wavelet are both data that change 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] by Figure 3 Taking the geological model shown in a as an example, according to the method provided in this application, Figure 3 The seismic data shown in b is stripped of the strong reflection signal of igneous rock.

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

[0094] Figure 3 Two sets of horizons are explained in the seismic data shown in b. The first set of horizons explains the seismic wave peak horizons of the target layer, and the second set of horizons explains the layered interpolation horizons of the top surface of the igneous rock.

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

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

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

[0098] The length of the first time window 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. The first time window length can be expressed as t w , 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 an upper limit value.

[0100] The upper limit is the upper limit 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 a lower limit value.

[0102] The lower limit is the lower limit 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 a time range corresponding to the upper limit value and the lower limit value to obtain a first frequency spectrum.

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

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

[0106] Among them, S(t w , f) represents the first spectrum, f represents the frequency, and i represents the 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 frequency spectrum.

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

[0109] Among them, the fifth relation data can be expressed as: W(f) represents the second spectrum.

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

[0111] This step can be achieved by following the steps (1) to (2), including:

[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 reflection coefficient data volume.

[0113] The first relationship data is used to represent the relationship between the first spectrum, the second spectrum, and the odd components and even components of the reflection coefficient data volume.

[0114] The first relation data can be expressed as:

[0115]

[0116] Among them, r o (t) and r e (t) represent the odd and even components of the reflection coefficient data volume, T(t) represents the time window length, and f L represents the low frequency cutoff value, f H represents the high frequency cutoff value, α o and α e They are the weight coefficients of the odd and even components, respectively, which are used to adjust the noise and resolution. Re means taking the real part, and Im means taking 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 by the least squares conjugate gradient method, and calculates the r corresponding to the minimum value of the first relationship data. o (t) and r e (t) is determined as the odd and even components of the reflection coefficient data volume. It can be seen that the odd and even components of the reflection coefficient 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 volume to obtain the reflection coefficient data volume.

[0120] The reflection coefficient data volume can be expressed as r(t), then r(t) = r e (t)+r o (t).

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

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

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

[0124] The second relational data can be expressed as:

[0125] Among them, I(t) represents the lithologic wave impedance body. It can be seen that the lithologic wave impedance body also changes with time. The lithologic wave impedance values ​​corresponding to different moments constitute the lithologic wave impedance body. Therefore, the lithologic wave impedance body includes the lithologic wave impedance values ​​corresponding to multiple moments. It represents the initial wave impedance value, which can be calculated by electronic equipment through drilling data.

[0126] See also Figure 4 a, Figure 4 a shows the use of Figure 3 b shows the lithologic wave impedance volume obtained after spectral inversion of the seismic data.

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

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

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

[0130] By performing a fine physical analysis on the rock, the average wave impedance value of the igneous rock and the average wave impedance value of the mudstone can be determined, 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, by performing a fine physical analysis on the rock, the wave impedance threshold of the igneous rock and the wave impedance threshold of the sandstone can also be clarified.

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

[0132] (2) For the lithologic wave impedance value corresponding to the first moment, if the lithologic wave impedance value corresponding to the first moment is not less than the igneous rock wave impedance threshold, the electronic device replaces the lithologic wave impedance value corresponding to the first moment with the igneous rock average wave impedance value. The first moment is any moment among the multiple moments.

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

[0134] (4) The electronic device determines the igneous rock wave impedance volume based on the average wave impedance values ​​of the igneous rock or the average wave impedance values ​​of the mudstone corresponding to multiple moments.

[0135] The electronic device determines the wave impedance value corresponding to each moment, which is the average wave impedance value of the igneous rock or the average wave impedance value of the mudstone, and the wave impedance values ​​corresponding to multiple moments form an igneous rock wave impedance body.

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

[0137] The sixth relationship data is:

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

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

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

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

[0142] (1) The electronic device obtains the sampling time interval.

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

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

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

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

[0147] The igneous rock wave impedance body is composed of wave impedance values ​​corresponding to multiple moments, and the electronic device determines the first wave impedance value corresponding to the first moment and the second wave impedance value corresponding to the second moment. Among them, the first wave impedance value corresponding to the first moment 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 moment 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 moment can be expressed as I f (t0), the second wave impedance value corresponding to the second moment can be expressed 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 moment into the third relationship data to obtain the reflection signal data corresponding to the first moment.

[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. The third relationship data can be expressed as:

[0150] Among them, 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 moment into the third relationship data to obtain the reflection signal data corresponding to the first moment. The reflection signal data corresponding to the first moment can be expressed 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 periods.

[0153] The electronic device combines the reflection signal data corresponding to a plurality of moments into igneous rock reflection signal data.

[0154] See also Figure 4 c, Figure 4 c shows the igneous rock reflection signal data obtained after forward modeling 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 the separation correction coefficient, determines the product of the separation correction coefficient and the igneous rock reflection signal data, obtains the igneous rock correction data, determines the difference between the first seismic data and the igneous rock correction data, and obtains the second seismic data. The second seismic data is the seismic data after the igneous rock reflection signal data is separated.

[0157] The separation correction coefficient can be determined based on the energy matching relationship between the igneous rock development zone and the non-development zone, ranging from 0.5 to 1.5, that is, λ∈[0.5,1.5], where λ represents the separation correction coefficient. The closer the energy between the igneous rock development zone and the non-development zone is, the closer the separation correction coefficient is to 1.

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

[0159] The first seismic data is composed of the third seismic data corresponding to multiple moments. The electronic device determines the difference between the third seismic data corresponding to each moment and the first correction data corresponding to the moment, and obtains the fourth seismic data corresponding to the moment. The electronic device combines the fourth seismic data corresponding to multiple moments into the second seismic data. The second seismic data can be expressed as: S p (t) = S (t) - λS q (t), S p (t) represents the second seismic data.

[0160] For example, the separation correction factor is 1, based on which, see Figure 4 d, Figure 4 d shows the seismic data obtained after stripping the igneous rock reflection signal data from the seismic data, wherein the target layer window is parallel to the target layer seismic wave peak layer.

[0161] pass Figure 3 b. Figure 4 d and Figure 3 From the comparison of a, we can see that due to the strong reflection shielding effect of igneous rock, it is difficult to identify the boundary of the sand body with the original seismic data. However, after stripping the igneous rock reflection signal data, four independently distributed phase axes can be clearly seen, and the pinch-out point of the sand body can be clearly identified.

[0162] Figure 5 The result shown in a is the effect of stripping the strong reflection signal of igneous rock by the method provided in this application using the target layer window parallel to the layer interpolation layer of the top well of the igneous rock. Figure 5 The result shown in b is the result of removing the strong reflection signal of igneous rock by using the traditional wavelet decomposition and reconstruction method. Figure 5 a and Figure 4 d Comparison shows that no matter the target layer window is parallel to the target layer seismic wave peak layer or parallel to the layered interpolation layer of the top well of the igneous rock, the method provided by this application has a relatively ideal effect of stripping the strong reflection signal of the igneous rock, and the difference is small, indicating that the method provided by this application is relatively insensitive to the quality of the layer interpretation. Figure 5 b and Figure 4 d Comparison shows that the method provided by this application is better than the traditional wavelet decomposition and reconstruction method. The traditional method obviously removes the effective signal of the sand body at the W2 well, and the lateral changes of the sand body are still difficult to identify. However, the location of the pinch-out point identified by the method provided by this application is basically consistent with the location of the pinch-out point of the sand body in the geological model, and the geological significance of the stripped signal is clear, that is, the reflection signal of igneous rock.

[0163] In an embodiment of the present application, after the electronic device determines the second seismic data, it can characterize the reservoir based on the second seismic data and perform reservoir prediction.

[0164] One thing that needs to be explained is that the matching pursuit method can also be used in related technologies to suppress strong reflection events. The matching pursuit method is a wavelet algorithm based on projection pursuit and step-by-step recursion, which continuously performs optimal matching on the residual signal obtained in each iteration. However, this method is also prone to stripping off effective reservoir signals that are not affected by igneous rocks. In addition, the stripping effect of the matching pursuit method and the multi-wavelet decomposition and reconstruction method on the strong reflection signal of igneous rocks is greatly affected by the quality of the stratigraphic interpretation, and the geological significance of the stripped signal is unclear.

[0165] The present application proposes a method for stripping off the strong reflection signal of igneous rock based on forward and inversion. The method first uses the spectrum inversion method to perform lithology inversion to obtain the lithology wave impedance body, then performs lithology replacement to obtain the igneous rock wave impedance body, and further uses the forward simulation technology to obtain the strong reflection signal of igneous rock. Finally, the strong reflection signal of igneous rock is stripped off from the original seismic data to obtain the seismic data after stripping off the strong reflection signal of igneous rock. See Figure 6. This method breaks away from the idea of ​​energy stripping of all seismic trace data in the study area using the matching pursuit method and the multi-wavelet decomposition and reconstruction method, and makes full use of drilling data information. It first characterizes the thickness and distribution range of igneous rock development, and on this basis, extracts the strong reflection signal of igneous rock, and then strips the strong reflection signal of igneous rock from the original seismic data. This method can accurately restore the effective signal of the reservoir shielded by the strong reflection of igneous rock, enhance the ability of seismic data to identify the vertical and horizontal distribution of the reservoir, and solve the problem of easy elimination of effective reservoir signals and easy occurrence of abnormal traces in related technologies. In addition, the quality of stratigraphic interpretation has relatively little effect on the stripping effect, and the stripped strong reflection signal has a clear geological significance.

[0166] To further illustrate the effect of the method provided by this application, the following is an example of actual data from a certain exploration block in an oil field. Figure 7 , Figure 7 The original seismic data collected shows that: due to the development of igneous rocks 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. Figure 8 , Figure 8 To strip the seismic data of the strong reflection signal of igneous rock, it can be seen that the event axis of the seismic data after removing the strong reflection signal of igneous rock changes naturally, the energy is uniform, and the event axis energy change and superposition relationship of the target layer are clearer.

[0167] See also Fig. 9 a and Fig. 9 b, Fig. 9 a is the root mean square amplitude attribute before stripping the strong reflection signal of igneous rock, Fig. 9 b is the root mean square attribute after stripping the strong reflection signal of igneous rock. Fig. 9 a and Fig. 9 b. Before stripping off the strong reflection signal of igneous rock, the attribute energy is concentrated, and the abnormal area mainly reflects the igneous rock development area, which cannot characterize the change law of sand body. After stripping off the strong reflection signal of igneous rock, the attribute details are richer, which can better reflect the change of sand body.

[0168] It can be seen that the method provided in this application has good application effect and can lay a reliable data foundation for further reservoir inversion and fine characterization of sand bodies.

[0169] The embodiment of the present application provides a method for processing seismic data, which performs Fourier transform on first seismic data and seismic wavelets to obtain a first spectrum and a second spectrum respectively, then determines a reflection coefficient data body based on the first spectrum and the second spectrum, converts the reflection coefficient data body into a lithology wave impedance body, then performs lithology replacement on the lithology wave impedance body to obtain an igneous rock wave impedance body, converts the igneous rock wave impedance body 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 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, thereby improving the accuracy of reservoir prediction.

[0170] Fig.10 is a structural diagram of a seismic data processing device provided in an embodiment of the present application, see Fig.10 , the device comprises:

[0171] An acquisition module 1001 is used to acquire first seismic data and seismic wavelets of a target work area;

[0172] The transformation module 1002 is used to perform Fourier transformation on the first seismic data to obtain a first spectrum and to perform Fourier transformation on the seismic wavelet to obtain a second spectrum;

[0173] A first determination module 1003 is used to determine a reflection coefficient data volume based on first relationship data, a first spectrum and a second spectrum; wherein the first relationship data is used to represent the relationship between the first spectrum, the second spectrum and the reflection coefficient data volume;

[0174] A first conversion module 1004 is used to convert the reflection coefficient data volume into a lithology wave impedance volume based on the 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 used to perform lithology replacement on the lithology wave impedance body based on the igneous rock wave impedance threshold and the sandstone wave impedance threshold to obtain the igneous rock wave impedance body;

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

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

[0178] In a possible implementation, the lithology wave impedance body includes lithology wave impedance values ​​corresponding to a plurality of moments;

[0179] The second conversion module 1005 is used to obtain the average wave impedance value of igneous rock and the average wave impedance value of mudstone; for the lithology wave impedance value corresponding to the first moment, if the lithology wave impedance value corresponding to the first moment is not less than the igneous rock wave impedance threshold, the lithology wave impedance value corresponding to the first moment is replaced by the average wave impedance value of igneous rock; wherein the first moment is any moment of multiple moments; if the lithology wave impedance value corresponding to the first moment is less than the sandstone wave impedance threshold, the lithology wave impedance value corresponding to the first moment is replaced by the average wave impedance value of mudstone; based on the average wave impedance values ​​of igneous rock or the average wave impedance values ​​of mudstone corresponding to multiple moments, the igneous rock wave impedance body is determined.

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

[0181] In another possible implementation, the separation module 1007 is used 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; 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 used 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 the 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; perform Fourier transform on the first seismic data within a time range corresponding to the upper limit value and the lower limit value to obtain a first spectrum.

[0183] In another possible implementation, the first determination module 1003 is used to substitute the first spectrum and the second spectrum into the first relationship data to determine the odd component and the even component of the reflection coefficient data body; 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 used to obtain an initial wave impedance value; substitute the initial wave impedance value and the reflection coefficient data body into the second relationship data to obtain a lithology wave impedance body.

[0185] The embodiment of the present application provides a seismic data processing device, which performs Fourier transform on first seismic data and seismic wavelets to obtain a first spectrum and a second spectrum respectively, and then determines a reflection coefficient data body based on the first spectrum and the second spectrum, converts the reflection coefficient data body into a lithology wave impedance body, and then performs lithology replacement on the lithology wave impedance body to obtain an igneous rock wave impedance body, converts the igneous rock wave impedance body 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, thereby improving the accuracy of reservoir prediction.

[0186] refer to Fig.11 , Fig.11 The structure block diagram of a terminal 1100 provided by an exemplary embodiment of the present application is shown. The terminal 1100 may be a portable mobile terminal, such as a smart phone, a tablet computer, an MP3 player (Moving Picture Experts Group Audio Layer III), an MP4 player (Moving Picture Experts Group Audio Layer IV), a laptop computer or a desktop computer. The terminal 1100 may also be called a user device, a portable terminal, a laptop terminal, a desktop terminal or other names.

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

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

[0189] The memory 1102 may include one or more computer-readable storage media, which may be non-transitory. The memory 1102 may also include a high-speed random access memory, and a non-volatile memory, such as one or more disk storage devices, flash memory 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, which is used to be executed by the processor 1101 to implement the operation performed by the terminal in the seismic data processing method provided in the method embodiment of the present application.

[0190] In some embodiments, the terminal 1100 may further 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 may be connected via a bus or a signal line. Each peripheral device may be connected to the peripheral device interface 1103 via 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 device interface 1103 may be used to connect at least one peripheral device related to I / O (Input / Output) to the processor 1101 and the memory 1102. In some embodiments, the processor 1101, the memory 1102, and the peripheral device 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 device interface 1103 may be implemented on a separate chip or circuit board, which is not limited in this embodiment.

[0192] The radio frequency circuit 1104 is used to receive and transmit RF (Radio Frequency) signals, also known as electromagnetic signals. The radio frequency circuit 1104 communicates with the communication network and other communication devices through electromagnetic signals. The radio frequency circuit 1104 converts the electrical signal into an electromagnetic signal for transmission, or converts the received electromagnetic signal into an electrical signal. 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 user 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 may also include circuits related to NFC (Near Field Communication), which is not limited in this application.

[0193] The display screen 1105 is used to display a UI (User Interface). The UI may include graphics, text, icons, videos, and any combination thereof. When the display screen 1105 is a touch display screen, the display screen 1105 also has the ability to collect touch signals on the surface or above the surface of the display screen 1105. The touch signal can be input to the processor 1101 as a control signal for processing. At this time, the display screen 1105 can also be used to provide virtual buttons and / or virtual keyboards, also known as soft buttons and / or soft keyboards. In some embodiments, the display screen 1105 can be one, set on the front panel of the terminal 1100; in other embodiments, the display screen 1105 can be at least two, respectively set 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, set on a curved surface or a folding surface of the terminal 1100. Even, the display screen 1105 can also be set to a non-rectangular irregular shape, that is, a special-shaped screen. The display screen 1105 can be made of materials such as LCD (Liquid Crystal Display) and OLED (Organic Light-Emitting Diode).

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

[0195] The audio circuit 1107 may include a microphone and a speaker. The microphone is used to collect sound waves from the user and the environment, and convert the sound waves into electrical signals and input them into the processor 1101 for processing, or input them into the radio frequency circuit 1104 to achieve voice communication. For the purpose of stereo acquisition or noise reduction, there may be multiple microphones, which are respectively arranged at different parts of the terminal 1100. The microphone may also be an array microphone or an omnidirectional acquisition 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 may be a traditional film speaker or a piezoelectric ceramic speaker. When the speaker is a piezoelectric ceramic speaker, it can not only convert the electrical signal into sound waves audible to humans, but also convert the electrical signal into sound waves inaudible to humans for purposes such as ranging. In some embodiments, the audio circuit 1107 may also include a headphone jack.

[0196] The power supply 1108 is used to power various components in the terminal 1100. The power supply 1108 can be an alternating current, a direct current, a disposable battery, or a rechargeable battery. When the power supply 1108 includes a rechargeable battery, the rechargeable battery can be a wired rechargeable battery or a wireless rechargeable battery. A wired rechargeable battery is a battery charged through a wired line, and a wireless rechargeable 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 further includes one or more sensors 1109 , including but 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 magnitude of acceleration on the 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 gravity acceleration on the three coordinate axes. The processor 1101 can control the display screen 1105 to display the user interface in a horizontal view or a vertical view based on the gravity acceleration signal collected by the acceleration sensor 1110. The acceleration sensor 1110 can also be used to collect game or user motion data.

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

[0200] The pressure sensor 1112 may be provided at the side frame of the terminal 1100 and / or the lower layer of the display screen 1105. When the pressure sensor 1112 is provided at the side frame of the terminal 1100, it may detect the user's holding signal of the terminal 1100, and the processor 1101 may perform left and right hand recognition or shortcut operation based on the holding signal collected by the pressure sensor 1112. When the pressure sensor 1112 is provided at the lower layer of the display screen 1105, the processor 1101 may control the operability control on the UI interface based on the user's pressure operation on the display screen 1105. The operability control includes at least one of a button control, a scroll bar control, an icon control, and a 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 parameters of the camera assembly 1106 based on the ambient light intensity collected by the optical sensor 1113.

[0202] The proximity sensor 1114, also called a distance sensor, is usually arranged on 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 is gradually decreasing, the processor 1101 controls the display screen 1105 to switch from the screen-on state to the screen-off state; when the proximity sensor 1114 detects that the distance between the user and the front of the terminal 1100 is gradually increasing, the processor 1101 controls the display screen 1105 to switch from the screen-off state to the screen-on state.

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

[0204] The server structure diagram can be found in Fig.12The server 1200 may have relatively large differences due to different configurations or performances, and may include a processor (Central Processing Units, CPU) 1201 and a memory 1202, wherein the memory 1202 stores at least one program code, which is loaded and executed by the processor 1201 to implement the operations performed by the server in the above-mentioned seismic data processing method. Of course, the server 1200 may also have components such as a wired or wireless network interface, a keyboard, and an input and output interface for input and output. The server 1200 may also include other components for implementing device functions, which will not be described in detail here.

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

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

[0207] A person skilled in the art will understand that all or part of the steps to implement the above embodiments may be accomplished by hardware or by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, and the above-mentioned storage medium may be a read-only memory, a disk or an optical disk, etc.

[0208] The above description is only for the purpose of facilitating those skilled in the art to understand the technical solution of the present application and is not intended to limit the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for processing seismic data, characterized in that: The method comprises: Acquire the first seismic data and seismic wavelet of the target work area; Performing Fourier transformation on the first seismic data to obtain a first spectrum and performing Fourier transformation on the seismic wavelet to obtain a second spectrum; 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 between the first spectrum, the second spectrum and the reflection coefficient data volume; Based on the second relationship data, the reflection coefficient data volume is converted into a lithology wave impedance volume; wherein the second relationship data is used to represent the relationship between the reflection coefficient data volume and the lithology wave impedance volume; Based on the igneous rock wave impedance threshold and the sandstone wave impedance threshold, performing lithology replacement on the lithology wave impedance body to obtain the igneous rock wave impedance body; Based on the third relationship data, the igneous rock wave impedance body is converted into igneous rock reflection signal data; wherein the third relationship data is used to represent the relationship between the igneous rock wave impedance body and the igneous rock reflection signal data; The igneous rock reflection signal data is separated from the first seismic data.

2. The method according to claim 1, characterized in that: The lithology wave impedance body includes lithology wave impedance values ​​corresponding to multiple moments; The step of performing lithology replacement on the lithology wave impedance body based on the igneous rock wave impedance threshold and the sandstone wave impedance threshold to obtain the igneous rock wave impedance body comprises: Obtain the average wave impedance value of igneous rock and the average wave impedance value of mudstone; For the lithologic wave impedance value corresponding to the first moment, if the lithologic wave impedance value corresponding to the first moment is not less than the igneous rock wave impedance threshold, the lithologic wave impedance value corresponding to the first moment is replaced by the igneous rock average wave impedance value; wherein the first moment is any moment among the multiple moments; If the lithology wave impedance value corresponding to the first moment is less than the sandstone wave impedance threshold, the lithology wave impedance value corresponding to the first moment is replaced by the mudstone average wave impedance value; The igneous rock wave impedance volume is determined based on the average wave impedance values ​​of the igneous rock or the average wave impedance values ​​of the mudstone corresponding to the multiple moments.

3. The method according to claim 2, characterized in that The converting the igneous rock wave impedance body into igneous rock reflection signal data based on the third relationship data comprises: Get the sampling time interval; Determine the sum of the first moment and the sampling time interval to obtain a second moment; Based on the igneous rock wave impedance body, determining a first wave impedance value corresponding to the first moment and a second wave impedance value corresponding to the second moment; wherein the first wave impedance value corresponding to the first moment 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 moment is the average wave impedance value of the igneous rock or the average wave impedance value of the mudstone; Substituting the first wave impedance value, the second wave impedance value, and the seismic wavelet corresponding to the first moment into the third relationship data to obtain the reflection signal data corresponding to the first moment; The igneous rock reflection signal data is determined based on the reflection signal data corresponding to the multiple time moments.

4. The method according to claim 1, characterized in that: The step of separating the igneous rock reflection signal data from the first seismic data comprises: Determine the separation correction factor; Determine the product of the separation correction coefficient and the igneous rock reflection signal data to obtain igneous rock correction data; The difference between the first seismic data and the igneous rock correction data is determined to obtain second seismic data.

5. The method according to claim 1, characterized in that The performing Fourier transform on the first seismic data to obtain a first spectrum includes: 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 a sum of the first offset and the first time window length to obtain an upper limit value; Determine a difference between the first offset and the first time window length to obtain a lower limit value; Within a time range corresponding to the upper limit value and the lower limit value, Fourier transform is performed on the first seismic data to obtain the first frequency spectrum.

6. The method according to claim 1, characterized in that The step of determining a reflection coefficient data volume based on the first relationship data, the first spectrum and the second spectrum comprises: Substituting the first spectrum and the second spectrum into the first relationship data to determine odd components and even components of the reflection coefficient data volume; The sum of the odd component and the even component of the reflection coefficient data volume is determined to obtain the reflection coefficient data volume.

7. The method according to claim 1, characterized in that The step of converting the reflection coefficient data volume into a lithology wave impedance volume based on the second relationship data comprises: Obtain the initial wave impedance value; Substituting the initial wave impedance value and the reflection coefficient data body into the second relationship data, the lithology wave impedance body is obtained.

8. A seismic data processing device, characterized in that: The device comprises: An acquisition module, used for acquiring the first seismic data and seismic wavelet of the target work area; A transformation module, configured to perform Fourier transformation on the first seismic data to obtain a first spectrum and to perform Fourier transformation on the seismic wavelet to obtain a second spectrum; A first determining module, 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 between the first spectrum, the second spectrum, and the reflection coefficient data volume; A first conversion module, 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; A second conversion module is used to perform lithology replacement on the lithology wave impedance body based on the igneous rock wave impedance threshold and the sandstone wave impedance threshold to obtain the igneous rock wave impedance body; A third conversion module, used 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 the relationship between the igneous rock wave impedance body and the igneous rock reflection signal data; A separation module is used to separate the igneous rock reflection signal data from the first seismic data.

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

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