Seismic data processing method, device, equipment and storage medium

Abstract

The application discloses a seismic data processing method, device and equipment and a storage medium, and belongs to the technical field of seismic exploration. The method first extracts downgoing wave field water detection data from first water detection data and extracts downgoing wave field land detection data from first land detection data, then determines a first calibration operator based on the downgoing wave field water detection data and the downgoing wave field land detection data, and preliminarily separates upgoing wave field data and downgoing wave field data based on the first calibration operator. Downgoing wave field data is extracted from the first upgoing wave field data and the first downgoing wave field data obtained through preliminary separation, second downgoing wave field data and third downgoing wave field data are obtained, a second calibration operator is determined based on the second downgoing wave field data and the third downgoing wave field data, and further separation is performed on the upgoing wave field data and the downgoing wave field data based on the second calibration operator. As can be seen, the method separates the upgoing wave field data and the downgoing wave field data through the first calibration operator and the second calibration operator, and the separation effect can be 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] Data collected by OBC (Ocean Bottom Cable) / OBN (Ocean Bottom Node) provides both underwater and land data at the same location. These data are collected using underwater and land geophones, respectively. Due to different acquisition mechanisms, the data collected by these two geophones exhibit different characteristics. Land data is generally calibrated using a calibration operator. Upgoing and downgoing wavefield data can be separated based on the underwater and calibrated land data. The underwater data includes both upgoing and downgoing wavefield data, while the land data includes both upgoing and downgoing wavefield data.

[0003] In related art, when determining a calibration operator, a water and land inspection data interval that may contain both an upgoing wave field and a downgoing wave field is picked up, and the calibration operator is determined based on the water and land inspection data in the interval.

[0004] However, since the data used in determining the calibration operator by this method includes both upgoing and downgoing wavefield data, the calibration operator determined by this method cannot completely separate the upgoing and downgoing wavefield data, resulting in poor separation effect. Summary of the Invention

[0005] The present invention provides a method, apparatus, device, and storage medium for processing seismic data, which can improve the separation of uplink and downlink wavefield data. The technical solution is as follows:

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

[0007] Acquiring first water detection data in a vertical intercept-horizontal slowness domain, first land detection data in a vertical intercept-horizontal slowness domain, and a first time window function, wherein the first time window function is used to represent a relationship between an offset and time;

[0008] extracting downlink wavefield water detection data from the first water detection data and extracting downlink wavefield land detection data from the first land detection data based on the first time window function;

[0009] determining a first calibration operator based on the downlink wavefield water detection data and the downlink wavefield land detection data;

[0010] Preliminarily separating the upgoing and downgoing wavefield data based on the first calibration operator, the first water detection data, and the first land detection data to obtain first upgoing wavefield data and first downgoing wavefield data;

[0011] obtaining a second time window function, and extracting second downgoing wavefield data from the first upgoing wavefield data and third downgoing wavefield data from the first downgoing wavefield data based on the second time window function;

[0012] determining a second calibration operator based on the second downlink wavefield data and the third downlink wavefield data;

[0013] Based on the second calibration operator, the first upgoing wavefield data, and the first downgoing wavefield data, the upgoing and downgoing wavefield data are further separated to obtain separated upgoing wavefield data and separated downgoing wavefield data.

[0014] In another aspect, a seismic data processing device is provided, comprising:

[0015] an acquisition module, configured to acquire first water detection data in a vertical intercept-horizontal slowness domain, first land detection data in a vertical intercept-horizontal slowness domain, and a first time window function, wherein the first time window function is used to represent a relationship between an offset and time;

[0016] a first extraction module, configured to extract downlink wavefield water detection data from the first water detection data and extract downlink wavefield land detection data from the first land detection data based on the first time window function;

[0017] A first determination module is configured to determine a first calibration operator based on the downlink wavefield water detection data and the downlink wavefield land detection data;

[0018] a first separation module, configured to perform preliminary separation on the upgoing and downgoing wavefield data based on the first calibration operator, the first water detection data, and the first land detection data, to obtain first upgoing wavefield data and first downgoing wavefield data;

[0019] a second extraction module, configured to obtain a second time window function, and extract second downgoing wavefield data from the first upgoing wavefield data and third downgoing wavefield data from the first downgoing wavefield data based on the second time window function;

[0020] a second determining module, configured to determine a second calibration operator based on the second downlink wavefield data and the third downlink wavefield data;

[0021] The second separation module is configured to further separate the upgoing and downgoing wavefield data based on the second calibration operator, the first upgoing wavefield data, and the first downgoing wavefield data to obtain separated upgoing wavefield data and separated downgoing wavefield data.

[0022] 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.

[0023] 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.

[0024] 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.

[0025] An embodiment of the present application provides a seismic data processing method. The method first extracts downgoing wavefield water detection data from first water detection data and extracts downgoing wavefield land detection data from first land detection data. Then, based on the downgoing wavefield water detection data and the downgoing wavefield land detection data, a first calibration operator is determined. Based on the first calibration operator, the upgoing and downgoing wavefield data are preliminarily separated to obtain first upgoing wavefield data and first downgoing wavefield data. Then, downgoing wavefield data is respectively extracted from the first upgoing wavefield data and the first downgoing wavefield data to obtain second downgoing wavefield data and third downgoing wavefield data. Based on the second downgoing wavefield data and the third downgoing wavefield data, a second calibration operator is determined. Based on the second calibration operator, the upgoing and downgoing wavefield data are further separated to obtain separated upgoing wavefield data and separated downgoing wavefield data. It can be seen that this method separates the uplink and downlink wavefield data through the first calibration operator and the second calibration operator in sequence. Since the data used to determine the second calibration operator are the uplink and downlink wavefield data after preliminary separation, the second calibration operator determined by this method can effectively separate the uplink and downlink wavefield data, thereby improving the separation effect.

[0026] It should 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

[0027] Figure 1 is a schematic diagram of an implementation environment of a seismic data processing method provided in an embodiment of the present application;

[0028] Figure 2 is a flow chart of a seismic data processing method provided in an embodiment of the present application;

[0029] Figure 3This is a schematic diagram of synthetic water inspection data provided by an embodiment of the present application;

[0030] Figure 4 is a schematic diagram of synthetic land inspection data provided in an embodiment of the present application;

[0031] Figure 5 is a schematic diagram of upgoing wavefield data separated by the method in the related art;

[0032] Figure 6 is a schematic diagram of downlink wavefield data separated by methods in related technologies;

[0033] Figure 7 This is a schematic diagram of upgoing wavefield data separated by the method provided in an embodiment of the present application;

[0034] Figure 8 This is a schematic diagram of downlink wavefield data separated by the method provided in an embodiment of the present application;

[0035] Figure 9 This is a schematic diagram of water inspection data of an actual common receiving point gather provided in an embodiment of the present application;

[0036] Figure 10 This is a schematic diagram of land inspection data of an actual common receiving point gather provided in an embodiment of the present application;

[0037] Figure 11 is a schematic diagram of upgoing wavefield data separated by the method in the related art;

[0038] Figure 12 is a schematic diagram of downlink wavefield data separated by methods in related technologies;

[0039] Figure 13 This is a schematic diagram of upgoing wavefield data separated by the method provided in an embodiment of the present application;

[0040] Figure 14 This is a schematic diagram of downlink wavefield data separated by the method provided in an embodiment of the present application;

[0041] Figure 15 yes Figure 9 A partial enlarged view of the water inspection data;

[0042] Figure 16 yes Figure 10 A partial enlarged view of the Central Land Inspection data;

[0043] Figure 17 yes Figure 11 A partial magnified view of the mid-upward wavefield data;

[0044] Figure 18yes Figure 12 A partial magnified view of the mid-downstream wavefield data;

[0045] Figure 19 yes Figure 13 A partial magnified view of the mid-upward wavefield data;

[0046] Figure 20 yes Figure 14 A partial magnified view of the mid-downstream wavefield data;

[0047] Figure 21 This is a structural diagram of a seismic data processing device provided in an embodiment of the present application;

[0048] Figure 22 This is a structural block diagram of a terminal provided in an embodiment of the present application. DETAILED DESCRIPTION

[0049] 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.

[0050] The terms "first," "second," "third," and "fourth," etc. in the specification and claims of this application and the accompanying drawings are used to distinguish different objects, not 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 apparatus comprising a series of steps or elements is not limited to the listed steps or elements, but may optionally include steps or elements not listed, or may optionally include other steps or elements inherent to the process, method, product, or apparatus.

[0051] 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, storage, and display, 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 the relevant countries and regions. For example, the water inspection data, land inspection data, uplink wave field data, and downlink wave field data involved in this application were all obtained with full authorization.

[0052] Figure 1 This 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 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.

[0053] If the electronic device is provided as the terminal 101 , the terminal 101 processes the water detection data and the land detection data, thereby separating the uplink and downlink wavefield data.

[0054] If the electronic device is provided as a terminal 101 and a server 102 , the terminal 101 sends the water detection data and the land detection data to the server 102 , and the server 102 processes the water detection data and the land detection data to separate the uplink and downlink wavefield data, and then returns the separated uplink and downlink wavefield data to the terminal 101 .

[0055] The terminal 101 is at least one of a mobile phone, a tablet computer, a PC (Personal Computer), an intelligent voice interaction device, and an in-vehicle terminal. The server 102 can be at least one of a single server, a server cluster consisting of multiple servers, a cloud server, a cloud computing platform, and a virtualization center.

[0056] Figure 2 This is a flow chart of a seismic data processing method provided by an embodiment of the present application, which is executed by an electronic device. Figure 2 , the method comprising:

[0057] Step 201: The electronic device obtains first water detection data in the vertical intercept-horizontal slowness domain, first land detection data in the vertical intercept-horizontal slowness domain, and a first time window function.

[0058] The electronic device acquires water detection data and land detection data in the time-space domain, converts the water detection data in the time-space domain into a vertical intercept-horizontal slowness domain to obtain first water detection data, and converts the land detection data in the time-space domain into a vertical intercept-horizontal slowness domain to obtain first land detection data.

[0059] In the embodiment of the present application, the water inspection data in the time-space domain can be expressed as h(m,n)=h(x m , t n ), the land inspection data in the time-space domain can be expressed as g(m,n)=g(x m , t n ), where m = 1, 2, 3...NN, m represents the sequence number of the time sampling point in the time-space domain, NN represents the total number of time sampling points; m = 1, 2, 3...MM, m represents the sequence number of the space sampling point in the time-space domain, MM represents the total number of space sampling points, t n Indicates the time of the nth time sampling point, in seconds (s); x m Indicates the offset of the mth spatial sampling point in meters (m).

[0060] make t=τ+px,

[0061] Where p represents the derivative of time with respect to space in the time-space domain, called horizontal slowness (inverse speed), with units of seconds per meter (s / m); t = τ + px represents a straight line in the time-space domain with slope p and intercept τ, where τ is the vertical intercept, with units of seconds (s).

[0062] based on With t = τ + px, the water and land inspection data in the time-space domain can be converted to the vertical intercept-horizontal slowness domain, see the following formulas (1) and (2).

[0063]

[0064]

[0065] Among them, t n =τ j +p i x m , H[i, j] represents the water inspection data in the vertical intercept-horizontal slowness domain. In this step, H[i, j] represents the first water inspection data; G[i, j] represents the land inspection data in the vertical intercept-horizontal slowness domain. In this step, G[i, j] represents the first land inspection data; j=1, 2, 3…NJ, j represents the sequence number of the vertical intercept sampling point in the vertical intercept-horizontal slowness domain, and NJ represents the total number of vertical intercept sampling points; i=1, 2, 3…NI, i represents the sequence number of the horizontal slowness sampling point in the vertical intercept-horizontal slowness domain, and NI represents the total number of horizontal slowness sampling points.

[0066] The first time window function is used to express the relationship between offset and time. It is a vertical intercept-horizontal slowness domain downlink wavefield extraction function, which is used to extract downlink wavefield water detection data from the first water detection data and extract downlink wavefield land detection data from the first land detection data.

[0067] In the embodiment of the present application, the electronic device can obtain a first time window function input by the user, and the first time window function can be expressed as W d [i, j].

[0068] Step 202: The electronic device extracts downlink wavefield water detection data from the first water detection data and extracts downlink wavefield land detection data from the first land detection data based on the first time window function.

[0069] The electronic device determines the product of the first time window function and the first water detection data to obtain the downlink wave field water detection data H u [i, j]; determine the product of the first time window function and the first land inspection data to obtain the downlink wave field land inspection data G u [i, j], this process can refer to the following formulas (3) and (4).

[0070] H u [i, j] = W d [i,j]H[i,j] (3)

[0071] G u [i, j] = W d [i,j]G[i,j] (4)

[0072] Step 203: The electronic device determines a first calibration operator based on the downlink wavefield water detection data and the downlink wavefield land detection data.

[0073] This step can be achieved by following the steps (1) to (4), including:

[0074] (1) The electronic device determines a first autocorrelation sequence based on the downlink wavefield land inspection data.

[0075] The electronic device can determine a first autocorrelation sequence based on the downlink wavefield land inspection data by using the following formula (5). The first autocorrelation sequence is used to represent the degree of correlation between the land inspection data.

[0076]

[0077] Among them, φ u [k] represents the first autocorrelation sequence, k is the sequence number of the first autocorrelation sequence element, and is also the sequence number of the first calibration operator element, k = -NK, -NK+1, -NK+2, ...NK, the length of the first autocorrelation sequence is (2NK+1), which is also the length of the first calibration operator.

[0078] (2) The electronic device determines a first cross-correlation sequence based on the downlink wavefield water detection data and the downlink wavefield land detection data.

[0079] The electronic device can determine the first cross-correlation sequence based on the downlink wave field water detection data and the downlink wave field land detection data by the following formula (6): The first cross-correlation sequence is used to indicate the degree of correlation between the water inspection data and the land inspection data.

[0080]

[0081] (3) The electronic device constructs a first objective function based on the first autocorrelation sequence and the first cross-correlation sequence.

[0082] Step (3) can be achieved by the following steps (3-1) to (3-5), including:

[0083] (3-1) The electronic device constructs a first autocorrelation matrix based on the first autocorrelation sequence; and constructs a first mutual correlation vector based on the first mutual correlation sequence.

[0084] Based on the first autocorrelation sequence, the electronic device can construct the first autocorrelation matrix Φ by the following formula (7): u Based on the first mutual correlation sequence, the second mutual correlation vector is constructed by the following formula (8): Determine the transpose vector of the second cross-correlation vector to obtain the first cross-correlation vector ψ u . Where T represents the transpose of a vector or matrix.

[0085]

[0086]

[0087] (3-2) The electronic device determines a transposed matrix of the first autocorrelation matrix to obtain a second autocorrelation matrix.

[0088] The second autocorrelation matrix can be expressed as

[0089] (3-3) The electronic device determines a first autocorrelation tensor matrix based on the first autocorrelation matrix and the second autocorrelation matrix.

[0090] The electronic device determines the first autocorrelation tensor matrix φ based on the first autocorrelation matrix and the second autocorrelation matrix by the following formula (9): uu .

[0091]

[0092] (3-4) The electronic device determines a first mutual correlation tensor vector based on the second autocorrelation matrix and the first mutual correlation vector.

[0093] The electronic device determines the first cross-correlation tensor vector ψ based on the second autocorrelation matrix and the first cross-correlation vector by the following formula (10): uu .

[0094]

[0095] (3-5) The electronic device constructs a first objective function based on the first autocorrelation tensor matrix, the first cross-correlation tensor vector and the first calibration operator vector.

[0096] The electronic device sets the first calibration operator to C u [k],C u [k] represents the kth element value in the first calibration operator. Based on the first calibration operator, the second calibration operator vector is constructed by the following formula (11): Determine the transposed vector of the second calibration operator vector to obtain the first calibration operator vector c u .

[0097]

[0098] The electronic device constructs a first objective function using the following formula (12) based on the first autocorrelation tensor matrix, the first cross-correlation tensor vector and the first calibration operator vector.

[0099] Φ uu c u =Ψ uu (12)

[0100] (4) The electronic device determines a first calibration operator based on the first objective function.

[0101] The electronic device deforms the first objective function and obtains Solve c by minimizing u Get the first calibration operator C u [k].

[0102] In the embodiment of the present application, the electronic device can obtain the downlink wavefield data D based on the downlink wavefield water detection data and the downlink wavefield land detection data through the following formula (13): u [i, j].

[0103]

[0104] The electronic device can construct the third objective function based on the downlink wavefield data using the following formula (14).

[0105]

[0106] Based on formula (13), formula (15) can be obtained:

[0107]

[0108] One thing that needs to be explained is that The effect of squaring is that k is different before and after squaring, so we use f to distinguish them: f = -NK, -NK + 1, -NK + 2, ... NK. That is, the range of f is the same as that of k, from -NK to NK.

[0109] Substituting formula (15) into formula (14), we can obtain formula (16):

[0110]

[0111] make

[0112]

[0113] Substituting into formula (16) we can get formula (17):

[0114]

[0115] Based on formula (17) u Taking the derivative of [k], we get formula (18):

[0116]

[0117] Let the right side of formula (18) be zero and simplify it to get formula (19):

[0118]

[0119] make

[0120]

[0121]

[0122] Then formula (19) can be simplified to the following formula (20):

[0123] Φ u c u =Ψ u (20)

[0124] In order to increase the stability of the solution, both sides of formula (20) are multiplied by the second autocorrelation matrix Then we can get formula (21):

[0125]

[0126] make Then formula (21) can be simplified to Φ uu c u =Ψ uu , which is formula (12). It can be seen from this that the electronic device can determine the first calibration operator through the above steps (1) to (4) in reverse.

[0127] Step 204: The electronic device performs preliminary separation on the upgoing and downgoing wavefield data based on the first calibration operator, the first water detection data, and the first land detection data to obtain first upgoing wavefield data and first downgoing wavefield data.

[0128] This step can be achieved by following the steps (1) to (3), including:

[0129] (1) The electronic device calibrates the first land inspection data based on the first calibration operator to obtain second land inspection data.

[0130] The electronic device can calibrate the first land inspection data based on the first calibration operator by the following formula (22) to obtain the second land inspection data G c [i,j].

[0131]

[0132] (2) The electronic device determines the sum of 1 / 2 of the first water detection data and 1 / 2 of the second land detection data to obtain first upgoing wavefield data.

[0133] The electronic device can determine the first upgoing wavefield data U[i,j] by the following formula (23).

[0134]

[0135] (3) The electronic device determines the difference between 1 / 2 of the first water detection data and 1 / 2 of the second land detection data to obtain first downlink wavefield data.

[0136] The electronic device can determine the first downlink wavefield data D[i, j] by the following formula (24).

[0137]

[0138] In this embodiment of the present application, the method for minimizing the downgoing wavefield energy in the upgoing wavefield in the vertical intercept-horizontal slowness domain is able to completely separate the downgoing wavefield data. As a result, the downgoing wavefield data contains almost no residual upgoing wavefield data, while the upgoing wavefield data still contains residual downgoing wavefield data. To eliminate this residual downgoing wavefield data from the upgoing wavefield data, it is necessary to separate the residual downgoing wavefield data from the upgoing wavefield data and append it to the downgoing wavefield data, ultimately separating the upgoing and downgoing wavefield data. The following describes the process of separating the residual downgoing wavefield data.

[0139] Step 205: The electronic device obtains a second time window function, and based on the second time window function, extracts second downlink wavefield data from the first uplink wavefield data, and extracts third downlink wavefield data from the first downlink wavefield data.

[0140] The second time window function is similar to the first time window function and is also a vertical intercept-horizontal slowness domain downgoing wavefield extraction function, used to extract the second downgoing wavefield data from the first upgoing wavefield data and to extract the third downgoing wavefield data from the first downgoing wavefield data.

[0141] In the embodiment of the present application, the second time window function can be expressed as W g [i, j], the relationship between the first time window function and the second time window function can be expressed as: g [i, j] = W d [i, j / 3].

[0142] The electronic device determines the product of the second time window function and the first upgoing wavefield data to obtain the second downgoing wavefield data Ud [i, j]; determine the product of the second time window function and the first downlink wave field data to obtain the third downlink wave field data D d [i, j], this process can be referred to the following formulas (25) and (26).

[0143] U d [i, j] = W g [i,j]U[i,j] (25)

[0144] Dd[i, j] = W g [i,j]D[i,j] (26)

[0145] Step 206: The electronic device determines a second calibration operator based on the second downlink wavefield data and the third downlink wavefield data.

[0146] This step can be achieved by following the steps (1) to (4), including:

[0147] (1) The electronic device determines a second autocorrelation sequence based on the third downlink wavefield data.

[0148] The electronic device can determine a second autocorrelation sequence based on the third downlink wavefield data using the following formula (27), where the second autocorrelation sequence is used to represent the degree of correlation between the downlink wavefield data.

[0149]

[0150] Among them, φ g [l] represents the second autocorrelation sequence, l is the sequence number of the second autocorrelation sequence element, and is also the sequence number of the second calibration operator element, l = -NG, -NG+1, -NG+2, ...NG, the length of the second autocorrelation sequence is (2NG+1), which is also the length of the second calibration operator.

[0151] (2) The electronic device determines a second cross-correlation sequence based on the second downlink wavefield data and the third downlink wavefield data.

[0152] Based on the second downlink wavefield data and the third downlink wavefield data, the electronic device can determine the second cross-correlation sequence by the following formula (28): The second cross-correlation sequence is used to indicate the degree of correlation between the upgoing wavefield data and the downgoing wavefield data.

[0153]

[0154] (3) The electronic device constructs a second objective function based on the second autocorrelation sequence and the second cross-correlation sequence.

[0155] Step (3) can be achieved by the following steps (3-1) to (3-5), including:

[0156] (3-1) The electronic device constructs a third autocorrelation matrix based on the second autocorrelation sequence; and constructs a third mutual correlation vector based on the second mutual correlation sequence.

[0157] Based on the second autocorrelation sequence, the electronic device can construct the third autocorrelation matrix Φ by the following formula (29): g Based on the second mutual correlation sequence, the fourth mutual correlation vector is constructed by the following formula (30): Determine the transpose vector of the fourth cross-correlation vector to obtain the third cross-correlation vector Ψ g .

[0158]

[0159]

[0160] (3-2) The electronic device determines a transposed matrix of the third autocorrelation matrix to obtain a fourth autocorrelation matrix.

[0161] The fourth autocorrelation matrix can be expressed as

[0162] (3-3) The electronic device determines a second autocorrelation tensor matrix based on the third autocorrelation matrix and the fourth autocorrelation matrix.

[0163] The electronic device determines the second autocorrelation tensor matrix Φ based on the third autocorrelation matrix and the fourth autocorrelation matrix by the following formula (31): gg .

[0164]

[0165] (3-4) The electronic device determines a second cross-correlation tensor vector based on the fourth autocorrelation matrix and the third cross-correlation vector.

[0166] The electronic device determines the second cross-correlation tensor vector Ψ based on the fourth autocorrelation matrix and the third cross-correlation vector by the following formula (32): gg .

[0167]

[0168] (3-5) The electronic device constructs a second objective function based on the second autocorrelation tensor matrix, the second cross-correlation tensor vector and the third calibration operator vector.

[0169] The electronic device sets the second calibration operator to C g [l],C g [l] represents the lth element value in the second calibration operator. Based on the second calibration operator, the fourth calibration operator vector is constructed by the following formula (33): Determine the transposed vector of the fourth calibration operator vector to obtain the third calibration operator vector c g .

[0170]

[0171] The electronic device constructs a second objective function through the following formula (34) based on the second autocorrelation tensor matrix, the second cross-correlation tensor vector and the third calibration operator vector.

[0172] Φ gg c g =Ψ gg (34)

[0173] (4) The electronic device determines a second calibration operator based on the second objective function.

[0174] The electronic device deforms the second objective function and obtains Solve c by minimizing g Get the second calibration operator C g [l].

[0175] In the embodiment of the present application, the electronic device sets the second calibration operator C g [1] Based on the second calibration operator, the first downlink wavefield data is calibrated by the following formula (35) to obtain the residual downlink wavefield data U g [i, j].

[0176]

[0177] The electronic device can construct a fourth objective function based on the second downlink wavefield data and the residual downlink wavefield data using the following formula (36).

[0178]

[0179] Substituting formula (35) into formula (36), we obtain formula (37):

[0180]

[0181] One thing that needs to be explained is that d [i, j]-U g [i, j]| 2 The effect of squaring is that l is not the same before and after squaring. Therefore, we use q to distinguish, q = -NG, -NG + 1, -NG + 2, ... NG. In other words, the range of q is the same as that of l, from -NG to NG.

[0182] make

[0183] Substituting into formula (37) we can obtain formula (38):

[0184]

[0185] Based on formula (38) g [l] Take the derivative and get formula (39):

[0186]

[0187] Let the right side of formula (39) be zero and simplify it to obtain formula (40):

[0188]

[0189] make

[0190]

[0191]

[0192] Then formula (40) can be simplified to the following formula (41):

[0193] Φ g c g =Ψ g (41)

[0194] In order to increase the stability of the solution, both sides of formula (41) are multiplied by the fourth autocorrelation matrix The following formula (42) can be obtained:

[0195]

[0196] make Then formula (42) can be simplified to Φ gg c g =Ψ gg , which is formula (34).

[0197] It can be seen from this that the electronic device can determine the second calibration operator through (1) to (4) in the above step 206 in reverse.

[0198] Step 207: The electronic device further separates the upgoing and downgoing wavefield data based on the second calibration operator, the first upgoing wavefield data, and the first downgoing wavefield data to obtain separated upgoing wavefield data and separated downgoing wavefield data.

[0199] This step can be achieved by following the steps (1) to (3), including:

[0200] (1) The electronic device calibrates the first downlink wavefield data based on the second calibration operator to obtain residual downlink wavefield data.

[0201] The electronic device can calibrate the first downlink wavefield data using the above formula (35) to obtain residual downlink wavefield data.

[0202] (2) The electronic device determines the difference between the first upgoing wavefield data and the residual downgoing wavefield data to obtain the separated upgoing wavefield data.

[0203] The electronic device can determine the separated upgoing wave field data U by the following formula (43): U [i, j].

[0204] U U [i, j] = U [i, j] + U g [i,j] (43)

[0205] (3) The electronic device determines the sum of the first downlink wavefield data and the residual downlink wavefield data to obtain the separated downlink wavefield data.

[0206] The electronic device can determine the separated downlink wave field data D by the following formula (44): U [i, j].

[0207] D U [i, j] = U [i, j] + U g [i,j] (44)

[0208] In the embodiment of the present application, the separated upgoing wavefield data and the separated downgoing wavefield data are both data in the vertical intercept-horizontal slowness domain. The electronic device can convert the separated upgoing wavefield data and the separated downgoing wavefield data into the time-space domain based on the following formulas (45) and (46), respectively.

[0209]

[0210]

[0211] Among them, t n =τ j +p i x m , U E [m, n] represents the upgoing wave field data in the time-space domain, D E [m, n] represents the downlink wavefield data in the time-space domain.

[0212] After obtaining the upgoing wavefield data and downgoing wavefield data in the time-space domain, the electronic device can perform upgoing and downgoing wavefield joint deconvolution, multiple wave processing, and mirror migration imaging processing based on the upgoing wavefield data and downgoing wavefield data in the time-space domain.

[0213] The method provided in the embodiment of the present application determines the primary ghost reflection of the seabed by picking up the direct wave in the near-offset channel. Both the direct wave and the primary ghost reflection of the seabed are downlink wavefield data, which are used to separate the uplink and downlink wavefield data of the water and land inspection data. Simultaneously, multi-channel weighted processing in the spatial direction is performed, which not only takes into account the spatial directional changes of the water and land inspection data, but also increases the noise resistance of the calibration operator, thereby improving the processing capability of the uplink and downlink wavefield separation of the water and land inspection data. The present application constructs a first objective function using a first autocorrelation sequence and a first cross-correlation sequence, determines a first calibration operator by minimizing the first objective function, and performs initial separation of the uplink and downlink wavefield data using the first calibration operator. On the basis of the initial separation, a second objective function is constructed through the second autocorrelation sequence and the second cross-correlation sequence. The second calibration operator is determined by minimizing the second objective function. The uplink and downlink wavefield data are further separated by the second calibration operator, achieving the purpose of optimal separation of the uplink and downlink wavefields of the water and land inspection data. The optimal uplink and downlink wavefield data are provided for subsequent uplink and downlink wavefield joint deconvolution and mirror migration imaging processing. The method is accurate, time-saving, fast and has high computational efficiency.

[0214] In order to further illustrate the technical effects of the method provided by this application, the following will be verified by the accompanying drawings. Figures 3 to 8 , Figure 3 is the synthetic water inspection data, Figure 4 is the synthetic land inspection data, Figure 5 It is through the method in the related technology that Figure 3 and Figure 4 The upgoing wave field data is obtained by separating the data in Figure 6 It is through the method in the related technology that Figure 3 and Figure 4 The downlink wavefield data is obtained by separating the data in . Figure 7 Through the method provided by this application, Figure 3 and Figure 4 The upgoing wave field data is obtained by separating the data in Figure 8 Through the method provided by this application, Figure 3 and Figure 4 The downlink wavefield data is obtained by separating the data in .

[0215] according to Figure 6 and Figure 8 It can be seen that the methods in the related art and the method provided in this application have similar effects on the separation of downlink wavefield data. Figure 5 and Figure 7 It can be seen that Figure 5 It also contains strong downtrend wave field data, and Figure 7There is almost no residual downlink wavefield data in the image, which shows that the method provided by the present application can completely separate the uplink wavefield data from the downlink wavefield data, especially the uplink wavefield data, and there is almost no residual downlink wavefield data.

[0216] See also Figures 9 to 14 , Figure 9 It is the water inspection data corresponding to the actual common receiving point gather. Figure 10 It is the land inspection data corresponding to the actual common receiving point gather. Figure 11 It is through the method in the related technology that Figure 9 and Figure 10 The upgoing wave field data is obtained by separating the data in Figure 12 It is through the method in the related technology that Figure 9 and Figure 10 The downlink wavefield data is obtained by separating the data in . Figure 13 Through the method provided by this application, Figure 9 and Figure 10 The upgoing wave field data is obtained by separating the data in Figure 14 Through the method provided by this application, Figure 9 and Figure 10 The downlink wavefield data is obtained by separating the data in .

[0217] according to Figure 11 and Figure 13 It can be seen that the upgoing wavefield data separated by the method in the related art and the method provided by this application can hardly see the seabed ghost reflection (around 470ms). The separation effect of upgoing and downgoing wavefield data is comparable, but the method provided by this application is better than the method in the related art in local details, especially Figure 14 The effective signal under the seabed ghost reflection is significantly better than Figure 12 .

[0218] See also Figures 15 to 20 , Figure 15 yes Figure 9 A partial enlarged view of the water inspection data. Figure 16 yes Figure 10 A partial enlarged view of the Zhonglujian data, including track numbers 1-162 and time 1250-2420ms. Figure 17 yes Figure 11 A partial enlarged view of the mid-upward wavefield data. Figure 18 yes Figure 12 A partial magnified view of the mid-downstream wavefield data. Figure 19 yes Figure 13 A partial enlarged view of the mid-upward wavefield data. Figure 20 yes Figure 14 A partial magnified view of the mid-downstream wavefield data.

[0219] according to Figure 17and Figure 19 It can be seen that Figure 19 The continuity of the event axis is significantly better than Figure 17 The time is around 1400ms. Figure 17 There is a strong residual of down-going wave field data in the second-order seabed ghost reflection phase axis. Figure 19 No residual downlink wavefield data can be seen in the image, and the separation is very clean, indicating that the method provided by the present application can completely separate the uplink wavefield data from the downlink wavefield data, especially that the residual downlink wavefield data in the uplink wavefield data is very small.

[0220] In summary, the method provided in this application can completely separate the uplink and downlink wave fields in water and land inspection data, meeting the needs of actual seismic data processing.

[0221] An embodiment of the present application provides a seismic data processing method. The method first extracts downgoing wavefield water detection data from first water detection data and extracts downgoing wavefield land detection data from first land detection data. Then, based on the downgoing wavefield water detection data and the downgoing wavefield land detection data, a first calibration operator is determined. Based on the first calibration operator, the upgoing and downgoing wavefield data are preliminarily separated to obtain first upgoing wavefield data and first downgoing wavefield data. Then, downgoing wavefield data is respectively extracted from the first upgoing wavefield data and the first downgoing wavefield data to obtain second downgoing wavefield data and third downgoing wavefield data. Based on the second downgoing wavefield data and the third downgoing wavefield data, a second calibration operator is determined. Based on the second calibration operator, the upgoing and downgoing wavefield data are further separated to obtain separated upgoing wavefield data and separated downgoing wavefield data. It can be seen that this method separates the uplink and downlink wavefield data through the first calibration operator and the second calibration operator in sequence. Since the data used to determine the second calibration operator are the uplink and downlink wavefield data after preliminary separation, the second calibration operator determined by this method can effectively separate the uplink and downlink wavefield data, thereby improving the separation effect.

[0222] Figure 21 This is a structural diagram of a seismic data processing device provided in an embodiment of the present application, see Figure 21 , the device comprises:

[0223] An acquisition module 2101 is configured to acquire first water-based detection data in a vertical intercept-horizontal slowness domain, first land-based detection data in a vertical intercept-horizontal slowness domain, and a first time window function, where the first time window function is used to represent a relationship between offset and time.

[0224] A first extraction module 2102 is configured to extract downlink wavefield water detection data from the first water detection data and extract downlink wavefield land detection data from the first land detection data based on a first time window function;

[0225] A first determination module 2103 is configured to determine a first calibration operator based on the downlink wavefield water detection data and the downlink wavefield land detection data;

[0226] A first separation module 2104 is configured to perform preliminary separation on the upgoing and downgoing wavefield data based on the first calibration operator, the first water detection data, and the first land detection data to obtain first upgoing wavefield data and first downgoing wavefield data;

[0227] The second extraction module 2105 is configured to obtain a second time window function, and based on the second time window function, extract the second downgoing wavefield data from the first upgoing wavefield data, and extract the third downgoing wavefield data from the first downgoing wavefield data;

[0228] A second determining module 2106 is configured to determine a second calibration operator based on the second downlink wavefield data and the third downlink wavefield data;

[0229] The second separation module 2107 is configured to further separate the upgoing and downgoing wavefield data based on the second calibration operator, the first upgoing wavefield data and the first downgoing wavefield data to obtain separated upgoing wavefield data and separated downgoing wavefield data.

[0230] In one possible implementation, the first determination module 2103 is configured to determine a first autocorrelation sequence based on the downlink wavefield land inspection data, where the first autocorrelation sequence is used to indicate the degree of correlation between the land inspection data; determine a first cross-correlation sequence based on the downlink wavefield water inspection data and the downlink wavefield land inspection data, where the first cross-correlation sequence is used to indicate the degree of correlation between the water inspection data and the land inspection data; construct a first objective function based on the first autocorrelation sequence and the first cross-correlation sequence; and determine a first calibration operator based on the first objective function.

[0231] In another possible implementation, the first determination module 2103 is used to construct a first autocorrelation matrix based on the first autocorrelation sequence; construct a first mutual correlation vector based on the first mutual correlation sequence; determine the transpose matrix of the first autocorrelation matrix to obtain a second autocorrelation matrix; determine a first autocorrelation tensor matrix based on the first autocorrelation matrix and the second autocorrelation matrix; determine a first mutual correlation tensor vector based on the second autocorrelation matrix and the first mutual correlation vector; construct a first objective function based on the first autocorrelation tensor matrix, the first mutual correlation tensor vector and the first calibration operator vector, wherein the first calibration operator vector includes multiple first calibration operators.

[0232] In another possible implementation, the first separation module 2104 is configured to calibrate the first land detection data based on the first calibration operator to obtain second land detection data; determine the sum of 1 / 2 of the first water detection data and 1 / 2 of the second land detection data to obtain first upgoing wavefield data; and determine the difference between 1 / 2 of the first water detection data and 1 / 2 of the second land detection data to obtain first downgoing wavefield data.

[0233] In another possible implementation, the second determining module 2106 is configured to determine a second autocorrelation sequence based on the third downlink wavefield data, the second autocorrelation sequence being used to indicate the degree of correlation between the downlink wavefield data; determine a second cross-correlation sequence based on the second downlink wavefield data and the third downlink wavefield data, the second cross-correlation sequence being used to indicate the degree of correlation between the uplink wavefield data and the downlink wavefield data; construct a second objective function based on the second autocorrelation sequence and the second cross-correlation sequence; and determine a second calibration operator based on the second objective function.

[0234] In another possible implementation, the second separation module 2107 is configured to calibrate the first downgoing wavefield data based on the second calibration operator to obtain residual downgoing wavefield data; determine a difference between the first upgoing wavefield data and the residual downgoing wavefield data to obtain separated upgoing wavefield data; and determine a sum of the first downgoing wavefield data and the residual downgoing wavefield data to obtain separated downgoing wavefield data.

[0235] An embodiment of the present application provides a seismic data processing device that first extracts downgoing wavefield water detection data from first water detection data and extracts downgoing wavefield land detection data from first land detection data. A first calibration operator is then determined based on the downgoing wavefield water detection data and the downgoing wavefield land detection data. Based on the first calibration operator, the upgoing and downgoing wavefield data are initially separated to obtain first upgoing wavefield data and first downgoing wavefield data. Downgoing wavefield data is then extracted from the first upgoing wavefield data and the first downgoing wavefield data, respectively, to obtain second downgoing wavefield data and third downgoing wavefield data. Based on the second downgoing wavefield data and the third downgoing wavefield data, a second calibration operator is determined. Based on the second calibration operator, the upgoing and downgoing wavefield data are further separated to obtain separated upgoing wavefield data and separated downgoing wavefield data. It can be seen that the device separates the uplink and downlink wavefield data through the first calibration operator and the second calibration operator in sequence. Since the data used to determine the second calibration operator are the uplink and downlink wavefield data after preliminary separation, the second calibration operator determined by the device can effectively separate the uplink and downlink wavefield data, thereby improving the separation effect.

[0236] refer to Figure 22 , Figure 22The following is a block diagram of a terminal 2200 according to an exemplary embodiment of the present application. Terminal 2200 may be a portable mobile terminal, such as a smartphone, tablet computer, MP3 player (Moving Picture Experts Group Audio Layer III), MP4 player (Moving Picture Experts Group Audio Layer IV), laptop computer, or desktop computer. Terminal 2200 may also be referred to as user equipment, portable terminal, laptop terminal, desktop terminal, or other similar names. Typically, terminal 2200 includes a processor 2201 and a memory 2202.

[0237] The processor 2201 may include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor 2201 may be implemented in at least one hardware form of DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), or PLA (Programmable Logic Array). The processor 2201 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 2201 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 2201 may also include an AI (Artificial Intelligence) processor, which is used to process computing operations related to machine learning.

[0238] The memory 2202 may include one or more computer-readable storage media, which may be non-transitory. The memory 2202 may also include high-speed random access memory and non-volatile memory, such as one or more disk storage devices and flash memory storage devices. In some embodiments, the non-transitory computer-readable storage medium in the memory 2202 is used to store at least one program code, which is executed by the processor 2201 to implement the seismic data processing method provided in the method embodiment of the present application.

[0239] In some embodiments, terminal 2200 may optionally include a peripheral device interface 2203 and at least one peripheral device. Processor 2201, memory 2202, and peripheral device interface 2203 may be connected via a bus or signal lines. Each peripheral device may be connected to peripheral device interface 2203 via a bus, signal lines, or circuit boards. Specifically, the peripheral device may include at least one of a radio frequency circuit 2204, a display screen 2205, a camera assembly 2206, an audio circuit 2207, and a power supply 2208.

[0240] The peripheral device interface 2203 can be used to connect at least one I / O (Input / Output)-related peripheral device to the processor 2201 and the memory 2202. In some embodiments, the processor 2201, the memory 2202, and the peripheral device interface 2203 are integrated on the same chip or circuit board; in some other embodiments, any one or two of the processor 2201, the memory 2202, and the peripheral device interface 2203 can be implemented on separate chips or circuit boards, which is not limited in this embodiment.

[0241] The RF circuit 2204 is used to receive and transmit RF (Radio Frequency) signals, also known as electromagnetic signals. The RF circuit 2204 communicates with communication networks and other communication devices via electromagnetic signals. The RF circuit 2204 converts electrical signals into electromagnetic signals for transmission, or converts received electromagnetic signals into electrical signals. Optionally, the RF circuit 2204 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 RF circuit 2204 can communicate with other terminals via at least one wireless communication protocol. Such wireless communication protocols include, but are not limited to, the World Wide Web, metropolitan area networks, intranets, various generations of mobile communication networks (2G, 3G, 4G, and 5G), wireless local area networks, and / or WiFi (Wireless Fidelity) networks. In some embodiments, the RF circuit 2204 may also include circuits related to NFC (Near Field Communication), which is not limited in this application.

[0242] The display screen 2205 is used to display a UI (User Interface). The UI may include graphics, text, icons, videos, and any combination thereof. When the display screen 2205 is a touch screen display, the display screen 2205 also has the ability to collect touch signals on the surface or above the surface of the display screen 2205. The touch signal can be input as a control signal to the processor 2201 for processing. At this time, the display screen 2205 can also be used to provide virtual buttons and / or virtual keyboards, also known as soft buttons and / or soft keyboards. In some embodiments, there can be one display screen 2205, which is set on the front panel of the terminal 2200; in other embodiments, there can be at least two display screens 2205, which are respectively set on different surfaces of the terminal 2200 or in a folding design; in other embodiments, the display screen 2205 can be a flexible display screen, which is set on the curved surface or folding surface of the terminal 2200. Even more, the display screen 2205 can be set to a non-rectangular irregular shape, that is, a special-shaped screen. The display screen 2205 can be made of materials such as LCD (Liquid Crystal Display) and OLED (Organic Light-Emitting Diode).

[0243] The camera assembly 2206 is used to capture images or videos. Optionally, the camera assembly 2206 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 panoramic shooting and VR (Virtual Reality) shooting function or other fusion shooting functions. In some embodiments, the camera assembly 2206 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.

[0244] The audio circuit 2207 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 that are input into the processor 2201 for processing, or input into the radio frequency circuit 2204 to achieve voice communication. For the purpose of stereo sound collection or noise reduction, there can be multiple microphones, each located in different parts of the terminal 2200. The microphone can also be an array microphone or an omnidirectional collection microphone. The speaker is used to convert electrical signals from the processor 2201 or the radio frequency circuit 2204 into sound waves. The speaker can be a traditional thin film speaker or a piezoelectric ceramic speaker. When the speaker is a piezoelectric ceramic speaker, it can not only convert electrical signals into sound waves audible to humans, but also convert electrical signals into sound waves inaudible to humans for purposes such as ranging. In some embodiments, the audio circuit 2207 also includes a headphone jack.

[0245] Power supply 2208 is used to power various components in terminal 2200. Power supply 2208 can be AC ​​power, DC power, a disposable battery, or a rechargeable battery. When power supply 2208 includes a rechargeable battery, the rechargeable battery can be a wired rechargeable battery or a wireless rechargeable battery. A wired rechargeable battery is charged via a wired line, while a wireless rechargeable battery is charged via a wireless coil. The rechargeable battery can also support fast charging technology.

[0246] In some embodiments, the terminal 2200 further includes one or more sensors 2209 , including but not limited to: an acceleration sensor 2210 , a gyroscope sensor 2211 , a pressure sensor 2212 , an optical sensor 2213 , and a proximity sensor 2214 .

[0247] The accelerometer 2210 can detect the magnitude of acceleration along the three coordinate axes of the coordinate system established by the terminal 2200. For example, the accelerometer 2210 can be used to detect the components of gravity acceleration along the three coordinate axes. The processor 2201 can control the display screen 2205 to display the user interface in a landscape or portrait view based on the gravity acceleration signal collected by the accelerometer 2210. The accelerometer 2210 can also be used to collect game or user motion data.

[0248] The gyroscope sensor 2211 can detect the orientation and rotation angle of the terminal 2200. It can also work with the accelerometer 2210 to collect the user's 3D movements on the terminal 2200. Based on the data collected by the gyroscope sensor 2211, the processor 2201 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.

[0249] The pressure sensor 2212 can be set on the side frame of the terminal 2200 and / or the lower layer of the display screen 2205. When the pressure sensor 2212 is set on the side frame of the terminal 2200, it can detect the user's grip signal of the terminal 2200, and the processor 2201 performs left and right hand recognition or shortcut operations based on the grip signal collected by the pressure sensor 2212. When the pressure sensor 2212 is set on the lower layer of the display screen 2205, the processor 2201 controls the operable controls on the UI interface based on the user's pressure operation on the display screen 2205. Operable controls include at least one of button controls, scroll bar controls, icon controls, and menu controls.

[0250] Optical sensor 2213 is used to detect ambient light intensity. In one embodiment, processor 2201 can control the display brightness of display screen 2205 based on the ambient light intensity detected by optical sensor 2213. Specifically, when the ambient light intensity is high, the display brightness of display screen 2205 is increased; when the ambient light intensity is low, the display brightness of display screen 2205 is decreased. In another embodiment, processor 2201 can also dynamically adjust the shooting parameters of camera assembly 2206 based on the ambient light intensity detected by optical sensor 2213.

[0251] Proximity sensor 2214, also known as a distance sensor, is typically located on the front panel of terminal 2200. Proximity sensor 2214 is used to detect the distance between the user and the front of terminal 2200. In one embodiment, when proximity sensor 2214 detects that the distance between the user and the front of terminal 2200 is gradually decreasing, processor 2201 controls display screen 2205 to switch from the screen-on state to the screen-off state. When proximity sensor 2214 detects that the distance between the user and the front of terminal 2200 is gradually increasing, processor 2201 controls display screen 2205 to switch from the screen-off state to the screen-on state.

[0252] Those skilled in the art will understand that Figure 22 The structure shown in the figure does not constitute a limitation on the terminal 2200, and the terminal 2200 may include more or fewer components than shown in the figure, or combine certain components, or adopt a different component arrangement.

[0253] In an exemplary embodiment, a computer-readable storage medium is further provided. The computer-readable medium stores at least one program code. The at least one program code is loaded and executed by a processor to implement the seismic data processing method in the above embodiment.

[0254] In an exemplary embodiment, a computer program product is further 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.

[0255] Those skilled in the art will understand that all or part of the steps to implement the above embodiments may be accomplished by hardware, or may be accomplished by a program to instruct the relevant hardware, 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.

[0256] The above description is only for the purpose of facilitating those skilled in the art to understand the technical solution of this application and is not intended to limit this application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of this application shall be included in the scope of protection of this application.

Claims

1. A seismic data processing method, characterized in that: The method comprises: Acquiring first water detection data in a vertical intercept-horizontal slowness domain, first land detection data in a vertical intercept-horizontal slowness domain, and a first time window function, wherein the first time window function is used to represent a relationship between an offset and time; extracting downlink wavefield water detection data from the first water detection data and extracting downlink wavefield land detection data from the first land detection data based on the first time window function; determining a first calibration operator based on the downlink wavefield water detection data and the downlink wavefield land detection data; Preliminarily separating the upgoing and downgoing wavefield data based on the first calibration operator, the first water detection data, and the first land detection data to obtain first upgoing wavefield data and first downgoing wavefield data; obtaining a second time window function, and extracting second downgoing wavefield data from the first upgoing wavefield data and third downgoing wavefield data from the first downgoing wavefield data based on the second time window function; determining a second calibration operator based on the second downlink wavefield data and the third downlink wavefield data; Based on the second calibration operator, the first upgoing wavefield data, and the first downgoing wavefield data, the upgoing and downgoing wavefield data are further separated to obtain separated upgoing wavefield data and separated downgoing wavefield data.

2. The method according to claim 1, characterized in that The determining of a first calibration operator based on the downlink wavefield water detection data and the downlink wavefield land detection data includes: determining a first autocorrelation sequence based on the downlink wavefield land inspection data, wherein the first autocorrelation sequence is used to represent the degree of correlation between the land inspection data; determining a first cross-correlation sequence based on the downlink wavefield water detection data and the downlink wavefield land detection data, wherein the first cross-correlation sequence is used to represent a degree of correlation between the water detection data and the land detection data; constructing a first objective function based on the first autocorrelation sequence and the first mutual correlation sequence; Based on the first objective function, the first calibration operator is determined.

3. The method according to claim 2, characterized in that The constructing a first objective function based on the first autocorrelation sequence and the first mutual correlation sequence includes: constructing a first autocorrelation matrix based on the first autocorrelation sequence; constructing a first mutual correlation vector based on the first mutual correlation sequence; Determining a transposed matrix of the first autocorrelation matrix to obtain a second autocorrelation matrix; Determining a first autocorrelation tensor matrix based on the first autocorrelation matrix and the second autocorrelation matrix; determining a first cross-correlation tensor vector based on the second autocorrelation matrix and the first cross-correlation vector; The first objective function is constructed based on the first autocorrelation tensor matrix, the first cross-correlation tensor vector and a first calibration operator vector, where the first calibration operator vector includes a plurality of first calibration operators.

4. The method according to claim 1, wherein The preliminarily separating the upgoing and downgoing wavefield data based on the first calibration operator, the first water detection data, and the first land detection data to obtain first upgoing wavefield data and first downgoing wavefield data includes: calibrating the first land inspection data based on the first calibration operator to obtain second land inspection data; determining a sum of 1 / 2 of the first water detection data and 1 / 2 of the second land detection data to obtain the first upgoing wavefield data; A difference between 1 / 2 of the first water detection data and 1 / 2 of the second land detection data is determined to obtain the first downlink wavefield data.

5. The method according to claim 1, wherein The determining a second calibration operator based on the second downlink wavefield data and the third downlink wavefield data includes: determining a second autocorrelation sequence based on the third downlink wavefield data, wherein the second autocorrelation sequence is used to represent a degree of correlation between the downlink wavefield data; determining a second mutual correlation sequence based on the second downgoing wavefield data and the third downgoing wavefield data, wherein the second mutual correlation sequence is used to represent a degree of correlation between the upgoing wavefield data and the downgoing wavefield data; constructing a second objective function based on the second autocorrelation sequence and the second cross-correlation sequence; Based on the second objective function, the second calibration operator is determined.

6. The method according to claim 1, characterized in that The further separating the upgoing and downgoing wavefield data based on the second calibration operator, the first upgoing wavefield data, and the first downgoing wavefield data to obtain separated upgoing wavefield data and separated downgoing wavefield data includes: calibrating the first downlink wavefield data based on the second calibration operator to obtain residual downlink wavefield data; determining a difference between the first upgoing wavefield data and the residual downgoing wavefield data to obtain the separated upgoing wavefield data; A sum of the first downlink wavefield data and the residual downlink wavefield data is determined to obtain the separated downlink wavefield data.

7. A seismic data processing device, characterized in that: The device comprises: an acquisition module, configured to acquire first water detection data in a vertical intercept-horizontal slowness domain, first land detection data in a vertical intercept-horizontal slowness domain, and a first time window function, wherein the first time window function is used to represent a relationship between an offset and time; a first extraction module, configured to extract downlink wavefield water detection data from the first water detection data and extract downlink wavefield land detection data from the first land detection data based on the first time window function; A first determination module is configured to determine a first calibration operator based on the downlink wavefield water detection data and the downlink wavefield land detection data; a first separation module, configured to perform preliminary separation on the upgoing and downgoing wavefield data based on the first calibration operator, the first water detection data, and the first land detection data, to obtain first upgoing wavefield data and first downgoing wavefield data; a second extraction module, configured to obtain a second time window function, and extract second downgoing wavefield data from the first upgoing wavefield data and third downgoing wavefield data from the first downgoing wavefield data based on the second time window function; a second determining module, configured to determine a second calibration operator based on the second downlink wavefield data and the third downlink wavefield data; The second separation module is configured to further separate the upgoing and downgoing wavefield data based on the second calibration operator, the first upgoing wavefield data, and the first downgoing wavefield data to obtain separated upgoing wavefield data and separated downgoing wavefield data.

8. 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 6.

9. A computer-readable storage medium, characterized in that At least one program code is stored in the computer-readable storage medium, 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 6.

10. A computer program product, characterized in that 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 according to any one of claims 1 to 6.

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