Method, device and equipment for determining residual static correction and storage medium

Abstract

The application provides a method and device for determining residual static correction, equipment and storage medium. The method comprises the following steps: calculating, by a computing node of a parallel processing system, a shot point static correction amount RDD of each shot point and a geophone static correction amount RDD of each geophone; sending the shot point static correction amount RDD of each shot point and the geophone static correction amount RDD of each geophone to a master node; and determining, by the master node, a target shot point static correction amount and a target geophone static correction amount.

Description

Technical Field

[0001] The present application relates to the technical field of petroleum geophysical exploration, and in particular to a method, apparatus, device and storage medium for determining residual static correction. Background Art

[0002] Currently, the combined application of datum statics and reflected wave residual statics is the core technical approach for resolving static correction problems both domestically and internationally. Static corrections for medium and long wavelengths are addressed through datum statics (also known as primary statics) methods, including field statics, tomographic statics, and refraction statics. Short-wavelength statics are then addressed through an iterative process of reflected wave residual statics and velocity analysis.

[0003] The nonlinear reflection wave residual static correction method, based on the maximum energy method, optimizes the final superposition energy rather than the extreme value of the cross-correlation function, resulting in better noise immunity. This method offers significant advantages over traditional linear methods for static correction of low signal-to-noise ratio data and large time differences.

[0004] However, the main difficulties faced by existing methods lie in the following three aspects: 1) Nonlinear optimization algorithms are computationally intensive, hundreds or even thousands of times more computationally intensive than ordinary linear algorithms; 2) Reflection wave residual static correction involves surface consistency processing, which is a non-dense parallel problem and requires switching back and forth between shot gathers, receiver point sets, and CDP gathers, making it difficult to parallelize; 3) The pre-stack gather data must be accessed hundreds or even thousands of times during the iteration process, resulting in a huge amount of data. Summary of the Invention

[0005] To address the above problems, the present application provides a method, apparatus, device, and storage medium for determining residual static correction, which can improve computational efficiency through parallel computing.

[0006] The present application provides a method for determining residual statics, which is applied to a computing node of a parallel processing system, comprising:

[0007] Obtaining a common-center-point seismic data elastic distributed dataset (RDD), performing stacking based on the common-center-point seismic data RDD to obtain a stacked trace RDD, and calculating a model trace RDD based on the stacked trace RDD;

[0008] Applying a static correction amount to the common-center point seismic data RDD to obtain corrected first common-center point seismic data RDD, wherein the static correction amount is determined by a master node of the parallel processing system based on total energy of the corrected common-center point seismic data;

[0009] Calculating pre-stack correlation trace data RDD between the corrected common center point seismic data RDD and the model trace RDD;

[0010] determine a shot point correlation curve RDD of each shot point and a receiver point correlation curve RDD of each receiver point based on the pre-stack correlation trace data RDD;

[0011] determine a shot point static correction amount RDD of each shot point using a maximum energy method based on the shot point correlation curve RDD, and determine a receiver point static correction amount RDD of each receiver point using a maximum energy method based on the receiver point correlation curve RDD;

[0012] send the shot point static correction amount RDD of each shot point and the receiver point static correction amount RDD of each receiver point to the master node, so that the master node determines a target shot point static correction amount and a target receiver point static correction amount based on the shot point static correction amount RDD of each shot point and the receiver point static correction amount RDD of each receiver point.

[0013] In some embodiments, the calculating the model trace RDD based on the stack trace RDD comprises:

[0014] acquiring a data range of the model trace RDD;

[0015] finding a preset number of stack traces around each stack trace according to a seismic grid;

[0016] summing the preset number of stack traces around the stack trace to obtain a summation result;

[0017] dividing the summation result by the preset number to obtain a model trace corresponding to each stack trace;

[0018] reducing the model trace corresponding to each stack trace to obtain the model trace RDD.

[0019] In some embodiments, the determining the shot point correlation curve RDD of each shot point and the receiver point correlation curve RDD of each receiver point based on the pre-stack correlation trace data RDD comprises:

[0020] determining the shot point correlation curve RDD of each shot point based on a shot point number of each pre-stack correlation trace data;

[0021] determining the receiver point correlation curve RDD of each receiver point based on a receiver point number of each pre-stack correlation trace data.

[0022] Embodiments of the present application provide a method for determining residual static correction, applied to a master node of a parallel processing system, and the method comprises:

[0023] acquiring a shot point static correction amount RDD of each shot point and a receiver point static correction amount RDD of each receiver point sent by a computing node;

[0024] determining a first static correction amount of a shot point based on the shot point static correction amount RDD, and determining a second static correction amount of a receiver point based on the receiver point static correction amount RDD.

[0025] apply the first statics and the second statics to the common point seismic data to obtain corrected second common point seismic data, and calculate a first total energy of the second common point seismic data;

[0026] In a case where the first total energy is greater than a second total energy of the first common point seismic data and a difference between the first total energy and the second total energy is less than a preset percentage of the second total energy, determine a statics corresponding to the first common point seismic data as a target statics, wherein the first common point seismic data is obtained by applying the statics to the common point seismic data.

[0027] In some embodiments, the method further comprises:

[0028] In a case where the first total energy is greater than the second total energy and a difference between the first total energy and the second total energy is greater than a preset percentage of the second total energy, or in a case where a set number of iterations is not reached, send the first statics and the second statics to each computing node to enable each computing node to update the statics based on the first statics and the second statics.

[0029] In some embodiments, the method further comprises:

[0030] obtain common point seismic data;

[0031] determine a common point seismic data RDD based on the common point seismic data;

[0032] distribute the common point seismic data RDD to each computing node to enable each computing node to perform iterative calculation and send a shot point statics RDD of each shot point and a receiver statics RDD of each receiver to the master node.

[0033] Embodiments of the present application provide a determination apparatus of residual statics, applied to a computing node of a parallel processing system, comprising:

[0034] a first obtaining module, configured to obtain a common point seismic data elastic distributed data set (RDD), perform stacking based on the common point seismic data RDD to obtain a stacked trace RDD, and calculate a model trace RDD based on the stacked trace RDD;

[0035] a first correction module, configured to apply statics to the common point seismic data RDD to obtain corrected first common point seismic data RDD, wherein the statics are determined by a master node of a parallel processing system based on a total energy of the corrected common point seismic data;

[0036] a calculation module, configured to calculate a pre-stack correlation trace data RDD between the corrected common depth point seismic data RDD and the model trace RDD;

[0037] a first determination module, configured to determine a shot point correlation curve RDD of each shot point and a receiver correlation curve RDD of each receiver based on the pre-stack correlation trace data RDD;

[0038] a second determination module, configured to determine a shot point static correction amount RDD of each shot point using a maximum energy method based on the shot point correlation curve RDD, and determine a receiver static correction amount RDD of each receiver using the maximum energy method based on the receiver correlation curve RDD;

[0039] a sending module, configured to send the shot point static correction amount RDD of each shot point and the receiver static correction amount RDD of each receiver to a master node, so that the master node determines a target shot point static correction amount and a target receiver static correction amount based on the shot point static correction amount RDD of each shot point and the receiver static correction amount RDD of each receiver.

[0040] Embodiments of the present application provide a determination apparatus of residual static correction, applied to a master node of a parallel processing system, comprising:

[0041] a second acquisition module, configured to acquire the shot point static correction amount RDD of each shot point and the receiver static correction amount RDD of each receiver sent by a calculation node;

[0042] a third determination module, configured to determine a first static correction amount of a shot point based on the shot point static correction amount RDD, and determine a second static correction amount of a receiver based on the receiver static correction amount RDD;

[0043] a second correction module, configured to apply the first static correction amount and the second static correction amount to the common depth point seismic data to obtain corrected second common depth point seismic data, and calculate a first total energy of the second common depth point seismic data;

[0044] a determination module, configured to determine a static correction amount corresponding to first common depth point seismic data as a target static correction amount in a case that the first total energy is greater than a second total energy of the first common depth point seismic data, and a difference between the first total energy and the second total energy is less than a preset percentage of the second total energy, wherein the first common depth point seismic data is obtained by applying the static correction amount to the common depth point seismic data for correction.

[0045] Embodiments of the present application provide a calculation node, comprising a memory and a processor, and the memory stores a computer program, which is executed by the processor to execute the determination method of residual static correction in any of the above embodiments.

[0046] The embodiment of the present application provides a master node, comprising a memory and a processor, wherein the memory stores a computer program, and the computer program is executed by the processor to execute the remaining static correction determination method in any of the above.

[0047] The embodiment of the present application provides a parallel processing system, comprising the computing node and the master node.

[0048] The embodiment of the present application provides a storage medium, wherein the storage medium stores a computer program, the computer program can be executed by one or more processors, and the computer program can be used to implement the remaining static correction determination method in any of the above.

[0049] The embodiment of the present application provides a remaining static correction determination method, device, equipment and storage medium, the computing node of the parallel processing system calculates the shot point static correction amount RDD of each shot point and the geophone static correction amount RDD of each geophone, the shot point static correction amount RDD of each shot point and the geophone static correction amount RDD of each geophone are sent to the master node, and the master node determines the target shot point static correction amount and the target geophone static correction amount, so that parallel calculation can be realized, and the calculation efficiency can be improved. BRIEF DESCRIPTION OF DRAWINGS

[0050] In the following, the present application will be described in more detail based on the embodiments and with reference to the drawings.

[0051] Figure 1 The implementation flowchart of the remaining static correction determination method provided by the embodiment of the present application is shown in the figure.

[0052] Figure 2 The implementation flowchart of another remaining static correction determination method provided by the embodiment of the present application is shown in the figure.

[0053] Figure 3 The comparison chart of the static correction amount before and after the application of the static correction amount obtained by using the parallel processing system provided by the embodiment of the present application is shown in the figure.

[0054] Figure 4 The composition structure diagram of the electronic equipment provided by the embodiment of the present application is shown in the figure.

[0055] In the drawings, the same components use the same reference numerals, and the drawings are not drawn according to the actual scale. DETAILED DESCRIPTION

[0056] In order to make the purpose, technical scheme and advantages of the present application more clear, the present application will be further described in detail below with reference to the drawings, and the described embodiments should not be regarded as limiting the present application, and all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0057] In the following description, reference is made to "some embodiments", which describe a subset of all possible embodiments, but it is to be understood that "some embodiments" can be the same or different from one another and can be combined with one another without conflict.

[0058] If the similar description of "first\second\third" appears in the application file, the following description is added: In the following description, the term "first\second\third" referred to is only to distinguish similar objects, and does not represent a specific order of the objects. It can be understood that "first\second\third" can be interchanged in a specific order or sequence as allowed, so that the embodiments of the application described herein can be implemented in an order other than that illustrated or described herein.

[0059] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of the application only and is not intended to limit the application.

[0060] Example One

[0061] Based on the problems in the related art, the embodiments of the application provide a method for determining residual statics, the execution subject of the method can be a computing node in a parallel processing system, and the computing node can be an electronic device. In the embodiments of the application, the parallel processing system includes a master node and a computing node, and the parallel processing system can be a Spark-based parallel processing system. The method for determining residual statics provided by the embodiments of the application can realize the functions by calling program codes by the processor of the computing node, and the program codes can be stored in a computer storage medium.

[0062] The embodiments of the application provide a method for determining residual statics, Figure 1 The implementation flowchart of the method for determining residual statics provided by the embodiments of the application is shown in FIG. 1, which includes the following steps. Figure 1

[0063] In step S101, a common point seismic data elastic distributed data set RDD is obtained, stacking is performed based on the common point seismic data RDD to obtain a stacked trace RDD, and a model trace RDD is calculated based on the stacked trace RDD.

[0064] In the embodiments of the application, the master node can obtain common point seismic data, determine a common point seismic data RDD based on the common point seismic data, and distribute the common point seismic data RDD to each computing node, so that the computing node obtains the common point seismic data elastic distributed data set RDD. ​

[0065] For the i-th common midpoint gather data, denoted as cmp i , containing n traces of data, for the j-th trace of data, denoted as cmp ij(j∈[1,n]) , the stack trace of cmp i may be stackCmp i =∑ j∈[1,n] cmp ij .

[0066] In the embodiments of the present application, the key of the stack trace RRD is (line, cdp), and the value is a stack trace data.

[0067] In the embodiments of the present application, the model trace RDD can be calculated based on the stack trace RDD calculation model, and the calculation can be achieved by the following steps:

[0068] Step S11, obtaining the data range of the model trace RDD;

[0069] Step S12, finding a preset number of stack traces around each stack trace according to the seismic grid;

[0070] Step S13, summing the preset number of stack traces around the stack trace to obtain a summation result;

[0071] Step S14, dividing the summation result by the preset number to obtain the model trace corresponding to each stack trace, and reducing the model trace according to the key-value pair of each stack trace to obtain the model trace RDD.

[0072] In the embodiments of the present application, the model trace elastic distributed data set can be calculated by using the flatMap and reduceByKey operators of the computing node. In the calculation process of the model trace, the stack trace information of multiple surrounding traces is needed, that is, the current trace is used in the calculation process of multiple model traces. Therefore, the flatMap is used to flatten and place the current trace data on the surrounding data, and then the reduceByKey is used to reduce the data with the same key.

[0073] Exemplarily, when calculating, the range of the calculation model trace data given by the parameter card is obtained, m k , which belongs to [1, 10]; for the stack trace data stackCmp i , the surrounding ssn=(2*m k +1)*(2*m k +1)-1 stack traces are found according to the seismic data grid, which are respectively recorded as {stackCmp1, stackCmp2, …, stackCmp ssn}, and the model trace is modelCmp i =∑stackCmp m / ssn, m∈[1, ssn].

[0074] In the embodiment of the present application, the center point seismic data RDD can be stored in the computing node after being acquired, so as to be called in the subsequent iterative calculation process.

[0075] In step S102, the static correction amount is applied to the common center point seismic data RDD to obtain the corrected first common center point seismic data RDD, wherein the static correction amount is determined by the master node of the parallel processing system based on the total energy of the corrected first common center point seismic data.

[0076] In the embodiment of the present application, the static correction amount includes the static correction amount of the shot point and the static correction amount of the receiver point, and the static correction amount of the shot point and the static correction amount of the receiver point can be applied to the common center point seismic data RDD to obtain the corrected first common center point seismic data RDD.

[0077] For example, the static correction amount of all shot points is recorded as {shts1, shts2, …, shtsm}, and there are m shot points. m The static correction amount of all receiver points is recorded as {rcvs1, rcvs2, …, rcvsn}, and there are n receiver points. n

[0078] For cmp ij(j∈[1,n]) , the static correction amount of the shot point and the receiver point is applied to the common center point seismic data to form staCmp ij(j∈[1,n]) , that is, for the jth data, which contains sn sampling points, the corresponding static correction amount of the shot point is shts k , the corresponding static correction amount of the receiver point is rcvs t , and in the first calculation, the static correction amount of the shot point and the receiver point are recorded as 0 values. The static correction amount corresponding to the jth data of the ith common center point gather is recorded as srs ij = shts k + rcvs t , and after being applied to the data, the overall data is shifted by srs ij sampling points; for the ith common center point gather, the jth data applied with the static correction amount can be expressed as staCmp ij(j∈[1,n]) .

[0079] ​In the embodiments of the present application, after the calculation node calculates once, the shot point static correction amount RDD of each shot point and the receiver point static correction amount RDD of each receiver point are determined, and the calculation node sends the shot point static correction amount RDD of each shot point and the receiver point static correction amount RDD of each receiver point to the master node, and the master node acquires the shot point static correction amount RDD of each shot point and the receiver point static correction amount RDD of each receiver point sent by the calculation node; the first static correction amount of the shot point is determined based on the shot point static correction amount RDD, and the second static correction amount of the receiver point is determined based on the receiver point static correction amount RDD; the first static correction amount and the second static correction amount are applied to the common midpoint seismic data to obtain the corrected second common midpoint seismic data, the first total energy of the second common midpoint seismic data is calculated, and in the case that the first total energy is greater than the second total energy, and the difference between the first total energy and the second total energy is greater than the preset percentage of the second total energy, or in the case that the set number of iterations is not reached, the first static correction amount and the second static correction amount are sent to each calculation node, so that each calculation node updates the static correction amount based on the first static correction amount and the second static correction amount.

[0080] In step S103, the pre-stack correlation trace data RDD between the corrected common midpoint seismic data RDD and the model trace RDD is calculated.

[0081] In the embodiments of the present application, the calculation node uses leftOuterjoin to first link the common midpoint seismic data RDD and the model trace RDD together, and then calculates the pre-stack correlation trace data RDD through the map operator, and the calculation process is as follows: the correlation curve length of each trace is c l For any point therein, the calculation method is corrd ijk =∑staCmp ij(m+k) *modelCmp im ,m∈[snt,snb],k∈[1,c l ], wherein snt and snb are the time window range given according to the parameter card.

[0082] In step S104, the shot point correlation curve RDD of each shot point and the receiver point correlation curve RDD of each receiver point are determined based on the pre-stack correlation trace data RDD.

[0083] In the embodiments of the present application, the shot point correlation curve RDD of each shot point can be determined based on the shot point number of each pre-stack correlation trace data, and the receiver point correlation curve RDD of each receiver point can be determined based on the receiver point number of each pre-stack correlation trace data.

[0084] In the embodiment of the application, the computing nodes use the flatMap and reduceByKey operators to form the shot-correlation curve elastic distributed dataset and the receiver-correlation curve elastic distributed dataset respectively. The computing nodes first use the flatMap to flatten the pre-stack correlation trace data RDD, replace the key with the shot station number (shotStation), use the reduceByKey to reduce the pre-stack correlation traces with the same key together to form the shot-correlation curve RDD. In the same way, according to the receiver station number (rcvStation), the receiver-correlation curve RDD can be obtained. Then the shot-correlation curve RDD and the receiver-correlation curve RDD are persisted respectively.

[0085] In the embodiment of the application, for any correlation trace corrd ij , it corresponds to a shot and a receiver; for the kth shot, assuming that the correlation trace corresponding to the shot has sm traces, the correlation trace of the shot k shtCorrd k =∑corrd ij ,staCorrd k is all the correlation traces corresponding to the shot k; for the tth receiver, assuming that the correlation trace corresponding to the receiver has rm traces, the correlation trace of the receiver t rcvCorrd t =∑corrd ij ,rcvCorrd t is all the correlation traces corresponding to the receiver t.

[0086] In step S105, the maximum energy method is used to determine the shot static correction amount RDD of each shot based on the shot-correlation curve RDD, and the maximum energy method is used to determine the receiver static correction amount RDD of each receiver based on the receiver-correlation curve RDD.

[0087] In the embodiment of the application, for the correlation trace shtCorrd k of the shot k, the shot static correction amount shts k is calculated according to the maximum energy method; for the correlation trace rcvCorrd t of the receiver t, the receiver static correction amount rcvs t is calculated according to the maximum energy method.

[0088] In step S106, the shot static correction amount RDD of each shot and the receiver static correction amount RDD of each receiver are sent to the master node, so that the master node determines the target shot static correction amount and the target receiver static correction amount based on the shot static correction amount RDD of each shot and the receiver static correction amount RDD of each receiver.

[0089] In the embodiment of the present application, the master node obtains the shot static correction amount RDD of each shot point and the receiver static correction amount RDD of each receiver point sent by the computing node; the master node determines the first static correction amount of the shot point based on the shot static correction amount RDD, and determines the second static correction amount of the receiver point based on the receiver static correction amount RDD; the first static correction amount and the second static correction amount are applied to the common depth point seismic data to obtain the corrected second common depth point seismic data, the first total energy of the second common depth point seismic data is calculated, and in the case that the first total energy is greater than the second total energy, and the difference between the first total energy and the second total energy is greater than the preset percentage of the second total energy, or the set number of iterations is not reached, the first static correction amount and the second static correction amount are sent to each computing node, so that each computing node updates the static correction amount based on the first static correction amount and the second static correction amount, so that the computing node performs the next iteration calculation.

[0090] In the embodiment of the present application, in the case that the first total energy is greater than the second total energy of the first common depth point seismic data, and the difference between the first total energy and the second total energy is less than the preset percentage of the second total energy, the master node determines the static correction amount corresponding to the first common depth point seismic data as the target static correction amount.

[0091] The present application provides a method for determining residual static correction, which calculates the shot static correction amount RDD of each shot point and the receiver static correction amount RDD of each receiver point through the computing node of the parallel processing system, sends the shot static correction amount RDD of each shot point and the receiver static correction amount RDD of each receiver point to the master node, and the master node determines the target shot static correction amount and the target receiver static correction amount, so that parallel calculation is realized and the calculation efficiency is improved.

[0092] Example Two

[0093] Based on the foregoing embodiments, the present application further provides a method for determining residual static correction, and the execution subject of the method can be a master node in a parallel processing system. In the embodiment of the present application, the parallel processing system includes a master node and a computing node, and the parallel processing system can be a Spark-based parallel processing system. The function realized by the method for determining residual static correction provided in the embodiment of the present application can be realized by calling program code by the processor of the master node, and the program code can be saved in a computer storage medium.

[0094] The embodiment of the present application provides a method for determining residual static correction, Figure 2 The implementation flowchart of the method for determining residual static correction provided in the embodiment of the present application is shown in Figure 2 as follows, which includes:

[0095] Step S201, obtaining the shot statics RDD of each shot point and the receiver statics RDD of each receiver point sent by the computing node.

[0096] In the embodiment of the application, the master node can use the collect operator to collect the shot statics RDD of each shot point and the receiver statics RDD of each receiver point of each computing node, and combine them into a shot statics Hash table HashMap<shotSta, shotStatics> and a receiver statics Hash table HashMap<rcvSta, rcvStatics>, respectively.

[0097] Step S202, applying the first statics and the second statics to the common- midpoint seismic data to obtain corrected second common- midpoint seismic data, and calculating the first total energy of the second common- midpoint seismic data.

[0098] In the embodiment of the application, the calculation method of the first total energy of the second common- midpoint seismic data adopts a data stacking trace method along one stacking surface. The calculation method takes the data along a stacking surface, i.e., a line, as a basic unit. In the data set, the adjacent trace data are multiplied and added: assuming that the stacking data along a line are stackCmp i , i∈line1, the calculation formula of the stacking energy value can be represented as: en=∑∑stackCmp ij *stackCmp (i+1)*j , thereby the first total energy can be calculated.

[0099] In the embodiment of the application, the master node can use the map operator to replace the key with the line number, and then use the reduceByKey to reduce the data with the same line number together. After sorting according to the point number, the total energy on each line is calculated, and finally the reduce is reduced to the master node to obtain the stacking total energy.

[0100] Step S203, in the case that the first total energy is greater than the second total energy of the first common- midpoint seismic data, and the difference between the first total energy and the second total energy is less than the preset percentage of the second total energy, determining the statics corresponding to the first common- midpoint seismic data as the target statics, wherein the first common- midpoint seismic data is obtained by correcting the common- midpoint seismic data by applying the statics.

[0101] In the embodiment of the application, the preset percentage can be one ten-thousandth.

[0102] In some embodiments, after step S202, the method further comprises:

[0103] Step S204, in a case where the first total energy is greater than the second total energy, and a difference between the first total energy and the second total energy is greater than a preset percentage of the second total energy, or a set number of iterations is not reached, the first static correction amount and the second static correction amount are sent to each computing node, so that each computing node updates a static correction amount based on the first static correction amount and the second static correction amount.

[0104] In the embodiments of the present application, after the static correction amount is updated, the computing node iteratively performs the following steps:

[0105] The static correction amount is applied to the common midpoint seismic data RDD to obtain corrected first common midpoint seismic data RDD; pre-stack correlation trace data RDD between the corrected common midpoint seismic data RDD and the model trace RDD is calculated; a shot point correlation curve RDD of each shot point and a receiver correlation curve RDD of each receiver are determined based on the pre-stack correlation trace data RDD; a shot point static correction amount RDD of each shot point is determined based on the shot point correlation curve RDD using the maximum energy method, and a receiver static correction amount RDD of each receiver is determined based on the receiver correlation curve RDD using the maximum energy method; the shot point static correction amount RDD of each shot point and the receiver static correction amount RDD of each receiver are sent to the master node until the master node determines the target static correction amount and stops execution.

[0106] In some embodiments, the method further comprises:

[0107] Step S301, common midpoint seismic data is obtained.

[0108] Step S302, common midpoint seismic data RDD is determined based on the common midpoint seismic data;

[0109] In the embodiments of the present application, the common midpoint seismic data can be corrected to a unified reference surface, and deconvolution and cutting are performed, and outlier and wild value rejection operations are required, and single-channel multi-time window amplitude equalization is performed.

[0110] In the embodiments of the present application, the master node can use the elastic distributed data set RDD of Spark to import common midpoint seismic data (cmpData) in parallel, which is marked as InputRdd, the key of the data set is a tuple composed of the line number and the point number of cmpData, that is, (line, cdp), and the value is the file header, trace header, and trace data information of cmpData; according to the parameter time window parameter, the InputRdd is mapped to the common midpoint seismic data elastic distributed data set required in the algorithm within the time window using the map operator, and the data is persisted, the key of the data is also (line, cdp), and the value is a tuple composed of shot-receiver coordinates, shot-receiver station number, and trace data.

[0111] Step S303, the common point seismic data RDD is distributed to each computing node, so that each computing node performs iterative calculation and sends the shot point static correction amount RDD of each shot point and the receiver static correction amount RDD of each receiver to the master node.

[0112] The application provides a method for determining residual static correction. The shot point static correction amount RDD of each shot point and the receiver static correction amount RDD of each receiver are calculated by the computing nodes of the parallel processing system, and are sent to the master node. The master node determines the target shot point static correction amount and the target receiver static correction amount. Parallel calculation is realized, and the calculation efficiency is improved.

[0113] Example Three

[0114] Based on the foregoing embodiments, the application provides a specific example application. The test data used is certain work area data, the signal-to-noise ratio is low, and there is a serious short-wavelength static correction problem. The work area data includes 30822 shots, 91662 receivers, 104 million traces, 445 square kilometers of one-time coverage, 120 times of full-coverage, 4s in length, 4ms in sampling rate, and 356G in data size. The calculation results obtained by using the serial version calculation and the parallel processing system provided by the application are basically consistent.

[0115] Figure 3 The application provides a comparison chart of the static correction amount obtained by using the parallel processing system before and after application, as shown in Figure 3 In the chart, Figure 3 A is a schematic diagram of a stack profile without processing, Figure 3 B is a schematic diagram of a stack profile after the static correction amount obtained by using the parallel processing system is applied. It can be seen that the stack profile after application is more continuous and has stronger energy.

[0116] For the work area data, the serial version data calculation time needs to be more than 3h, and the running time of the parallel processing system based on Spark is 0.5h. When the cluster size is larger, the calculation time will be further shortened. When the cluster size is larger, the amount of data that can be processed will be larger.

[0117] In the embodiment of the present application, based on the Spark parallel framework and the elastic distributed dataset, the common point gather seismic data is converted in the form of RDD according to the business method, and the data stream is converted through data stacking, model calculation in the grid range, calculation of pre-stack correlation traces, resetting in the shot point and receiver point domain to form shot point and receiver point correlation trace data, and iterative cycle process such as calculation of shot-receiver static correction amount according to the maximum energy method. Finally, the shot-receiver static correction amount is calculated. The embodiment of the present application solves the difficulties in conventional software coding, uses the method based on the Spark parallel framework to solve the non-dense parallelism, that is, the difficult parallelism problem, greatly improves the calculation efficiency and the adaptability of the method application, can effectively reduce the use cost, and has good economic and social benefits.

[0118] Example Four

[0119] Based on the foregoing embodiments, the embodiment of the present application provides a residual static correction determination device. Each module included in the device and each unit included in each module can be realized by a processor in a computer device. Of course, it can also be realized by a specific logic circuit. In the implementation process, the processor can be a central processing unit (CPU), a microprocessor unit (MPU), a digital signal processor (DSP), or a field programmable gate array (FPGA).

[0120] The embodiment of the present application provides a residual static correction determination device. The residual static correction determination device comprises:

[0121] A first acquisition module is configured to acquire an elastic distributed dataset (RDD) of common point seismic data, perform stacking based on the RDD of the common point seismic data to obtain a stacked trace RDD, and calculate a model trace RDD based on the stacked trace RDD.

[0122] A first correction module is configured to apply a static correction amount to the RDD of the common point seismic data to obtain a corrected first RDD of the common point seismic data, wherein the static correction amount is determined by a master node of a parallel processing system based on the total energy of the corrected common point seismic data.

[0123] A calculation module is configured to calculate pre-stack correlation trace data RDD between the corrected RDD of the common point seismic data and the model trace RDD.

[0124] A first determination module is configured to determine a shot point correlation curve RDD of each shot point and a receiver point correlation curve RDD of a receiver point based on the pre-stack correlation trace data RDD.

[0125] a second determining module, configured to determine a shot point static correction quantity RDD of each shot point based on the shot point correlation curve RDD by using a maximum energy method, and determine a receiver point static correction quantity RDD of each receiver point based on the receiver point correlation curve RDD by using the maximum energy method;

[0126] a sending module, configured to send the shot point static correction quantity RDD of each shot point and the receiver point static correction quantity RDD of each receiver point to the master node, so that the master node determines a target shot point static correction quantity and a target receiver point static correction quantity based on the shot point static correction quantity RDD of each shot point and the receiver point static correction quantity RDD of each receiver point.

[0127] In some embodiments, the calculating the model trace RDD based on the stack trace RDD comprises:

[0128] acquiring a data range of the model trace RDD;

[0129] finding a preset number of stack traces around each stack trace according to a seismic grid;

[0130] summing the preset number of stack traces around the stack trace to obtain a summation result;

[0131] dividing the summation result by the preset number to obtain a model trace corresponding to each stack trace;

[0132] reducing the model trace corresponding to each stack trace to obtain the model trace RDD.

[0133] In some embodiments, the determining the shot point correlation curve RDD of each shot point and the receiver point correlation curve RDD of each receiver point based on the pre-stack correlation trace data RDD comprises:

[0134] determining the shot point correlation curve RDD of each shot point based on a shot point number of each pre-stack correlation trace data;

[0135] determining the receiver point correlation curve RDD of each receiver point based on a receiver point number of each pre-stack correlation trace data.

[0136] Embodiments of the present application further provide a determination apparatus of residual static correction, applied to a master node of a parallel processing system, comprising:

[0137] a second acquiring module, configured to acquire the shot point static correction quantity RDD of each shot point and the receiver point static correction quantity RDD of each receiver point sent by the computing node;

[0138] a third determining module, configured to determine a first static correction quantity of a shot point based on the shot point static correction quantity RDD, and determine a second static correction quantity of a receiver point based on the receiver point static correction quantity RDD;

[0139] a second correction module, configured to apply the first statics and the second statics to the common point seismic data to obtain corrected second common point seismic data, and calculate a first total energy of the corrected second common point seismic data;

[0140] a determination module, configured to determine the statics corresponding to the first common point seismic data as target statics in a case that the first total energy is greater than a second total energy of the first common point seismic data, and a difference between the first total energy and the second total energy is less than a preset percentage of the second total energy, wherein the first common point seismic data is obtained by applying the statics to the common point seismic data.

[0141] In some embodiments, the determination apparatus of the residual statics is further configured to:

[0142] In a case that the first total energy is greater than the second total energy, and a difference between the first total energy and the second total energy is greater than a preset percentage of the second total energy, or a case that the set number of iterations is not reached, the first statics and the second statics are sent to each computing node to enable each computing node to update the statics based on the first statics and the second statics.

[0143] In some embodiments, the determination apparatus of the residual statics is further configured to:

[0144] obtain the common point seismic data;

[0145] determine a common point seismic data RDD based on the common point seismic data;

[0146] distribute the common point seismic data RDD to each computing node to enable each computing node to perform iterative calculation and send a shot point statics RDD of each shot point and a receiver statics RDD of each receiver to the master node.

[0147] It should be noted that, in the embodiment of the present application, if the above-mentioned method for determining the residual static correction is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the methods described in each embodiment of the present application. The aforementioned storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a magnetic disk or an optical disk. In this way, the embodiment of the present application is not limited to any specific combination of hardware and software.

[0148] Accordingly, an embodiment of the present application provides a storage medium having a computer program stored thereon, characterized in that when the computer program is executed by a processor, the steps of the method for determining the residual static correction provided in the above embodiment are implemented.

[0149] Example Five

[0150] An embodiment of the present application provides an electronic device, which may be a master node or a computing node. Figure 4 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application is shown in FIG. Figure 4 As shown, the electronic device 700 includes: a processor 701, at least one communication bus 702, a user interface 703, at least one external communication interface 704, and a memory 705. The communication bus 702 is configured to enable communication between these components. The user interface 703 may include a display screen, and the external communication interface 704 may include a standard wired interface and a wireless interface. The processor 701 is configured to execute a program for determining residual statics stored in the memory to implement the steps of the method for determining residual statics provided in the above-described embodiment.

[0151] An embodiment of the present application provides a parallel processing system, including: a master node or a computing node.

[0152] The description of the master node, computing node, and storage medium embodiments above is similar to the description of the method embodiment above, and has similar beneficial effects as the method embodiment. For technical details not disclosed in the computer device and storage medium embodiments of this application, please refer to the description of the method embodiment of this application for understanding.

[0153] It should be understood that every feature, structure, or characteristic described herein is within a preferred embodiment of the present application. Thus, it is meant that the features, structures, or characteristics can be combined with each other in any manner within a preferred embodiment of the present application. In addition, it is contemplated that each feature, structure, or characteristic can be implemented in hardware, software, or a combination thereof.

[0154] It should be noted that, as used herein, the articles "a", "an", "the", and "at least one" are intended to mean that there is one or more of the elements in the preceding descriptions. The articles "a" (or "an"), as well as the first article "the" and "at least one" do not denote a limitation of quantity, and are used with their plain, ordinary meaning. Thus, these articles should be interpreted in the manner it is employed by those having ordinary skill in the art to indicate that the accompanying recited elements can be included either singly or in multiple number, that the referenced member or elements can be selected from the group consisting of one or more member or elements.

[0155] In several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The above-described device embodiments are merely illustrative, for example, the division of the units is only a logical function division, and actual implementation can have another division manner, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the displayed or discussed components can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0156] The units described above as separate components may or may not be physically separate, and the components displayed as units may or may not be physical units; they can be located in one place or distributed on multiple network units; some or all of the units can be selected according to actual needs to achieve the purpose of the embodiment.

[0157] In addition, each functional unit in each embodiment of the present application can be integrated into one processing unit, or each unit can be a unit alone, or two or more units can be integrated into one unit; the integrated unit can be realized in the form of hardware or hardware plus software functional unit.

[0158] Those skilled in the art can understand that all or part of the steps of the above-mentioned method embodiments can be completed by program instruction related hardware, and the foregoing program can be stored in a computer readable storage medium, and the program performs the steps of the above-mentioned method embodiments when executed; and the foregoing storage medium includes a mobile storage device, a read only memory (ROM), a magnetic disc or an optical disc, and various storage medium capable of storing program codes.

[0159] Alternatively, the integrated units of the present application can be stored in a computer readable storage medium if they are realized in the form of software function modules and sold or used as independent products. Based on this understanding, the technical solutions of the embodiments of the present application can be embodied in the form of software products, and the computer software products are stored in a storage medium, including a plurality of instructions for causing a controller to execute all or part of the methods described in the embodiments of the present application. The foregoing storage medium includes a mobile storage device, a ROM, a magnetic disc or an optical disc, and various storage medium capable of storing program codes.

[0160] The above is only an embodiment of the present application, but the protection scope of the present application is not limited thereto, and any person skilled in the art can easily think of changes or replacements within the technical range disclosed in the present application, which should be covered in the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A method for determining residual statics, characterized in that: Applied to a computing node of a parallel processing system, the method comprises: Obtaining a common-center-point seismic data elastic distributed dataset (RDD), performing stacking based on the common-center-point seismic data RDD to obtain a stacked trace RDD, and calculating a model trace RDD based on the stacked trace RDD; Applying a static correction amount to the common-center point seismic data RDD to obtain corrected first common-center point seismic data RDD, wherein the static correction amount is determined by a master node of the parallel processing system based on total energy of the corrected common-center point seismic data; Calculating pre-stack correlation trace data RDD between the corrected common center point seismic data RDD and the model trace RDD; Determine a shot point correlation curve RDD of each shot point and a receiver point correlation curve RDD of each receiver point based on the pre-stack correlation trace data RDD; Determine the shot point statics RDD of each shot point using the maximum energy method based on the shot point correlation curve RDD, and determine the detection point statics RDD of each detection point using the maximum energy method based on the detection point correlation curve RDD; The shot point statics RDD of each shot point and the detection point statics RDD of each detection point are sent to the master node, so that the master node determines the target shot point statics and the target detection point statics based on the shot point statics RDD of each shot point and the detection point statics RDD of each detection point.

2. The method according to claim 1, characterized in that The calculation of the model channel RDD based on the superimposed channel RDD includes: Get the data range of the model RDD; Search for a preset number of stack traces around each stack trace according to the seismic grid; Summing a predetermined number of superposition channels around the superposition channel to obtain a summation result; Dividing the summation result by the preset number to obtain the model channel corresponding to each superposition channel; The model channel is reduced by the key value of each superimposed channel to obtain the model channel RDD.

3. The method according to claim 1, characterized in that The determining of a shot point correlation curve RDD of each shot point and a detector point correlation curve RDD of each detector point based on the pre-stack correlation trace data RDD includes: Determine the shot point correlation curve RDD of each shot point based on the shot point number of each pre-stack correlation trace data; The detection point correlation curve RDD of each detection point is determined based on the detection point number of each pre-stack correlation trace data.

4. A method for determining residual static correction, characterized in that: Applied to a master node of a parallel processing system, the method comprises: Obtain the shot point static correction RDD of each shot point and the detector point static correction RDD of each detector point sent by the computing node; Determine a first static correction value of a shot point based on the shot point static correction value RDD, and determine a second static correction value of a detection point based on the detection point static correction value RDD; Applying the first static correction amount and the second static correction amount to the common-center point seismic data to obtain corrected second common-center point seismic data, and calculating a first total energy of the second common-center point seismic data; When the first total energy is greater than the second total energy of the first common-center point seismic data, and the difference between the first total energy and the second total energy is less than a preset percentage of the second total energy, the static correction amount corresponding to the first common-center point seismic data is determined as the target static correction amount, wherein the first common-center point seismic data is obtained by applying the static correction amount to the common-center point seismic data for correction.

5. The method according to claim 4, characterized in that The method further comprises: When the first total energy is greater than the second total energy and the difference between the first total energy and the second total energy is greater than a preset percentage of the second total energy, or when the set number of iterations is not reached, the first static correction amount and the second static correction amount are sent to each computing node so that each computing node updates the static correction amount based on the first static correction amount and the second static correction amount.

6. The method according to claim 4, characterized in that The method further comprises: Acquire common center point seismic data; Determine common center point seismic data RDD based on the common center point seismic data; The common center point seismic data RDD is distributed to each computing node, so that each computing node performs iterative calculation and sends the shot point static correction RDD of each shot point and the detection point static correction RDD of each detection point to the master node.

7. A device for determining residual static correction, characterized in that: Computing nodes used in parallel processing systems include: A first acquisition module is configured to acquire a common-center-point seismic data elastic distributed dataset (RDD), perform stacking based on the common-center-point seismic data RDD to obtain a stacked trace RDD, and calculate a model trace RDD based on the stacked trace RDD; a first correction module, configured to apply a static correction amount to the common-center point seismic data RDD to obtain corrected first common-center point seismic data RDD, wherein the static correction amount is determined by a master node of the parallel processing system based on total energy of the corrected common-center point seismic data; A calculation module, configured to calculate pre-stack correlation trace data RDD between the corrected common center point seismic data RDD and the model trace RDD; A first determining module is configured to determine a shot point correlation curve RDD of each shot point and a detector point correlation curve RDD of each detector point based on the pre-stack correlation trace data RDD; a second determining module, configured to determine a shot point static correction RDD of each shot point using a maximum energy method based on the shot point correlation curve RDD, and to determine a detection point static correction RDD of each detection point using a maximum energy method based on the detection point correlation curve RDD; The sending module is used to send the shot point static correction value RDD of each shot point and the detection point static correction value RDD of each detection point to the master node, so that the master node determines the target shot point static correction value and the target detection point static correction value based on the shot point static correction value RDD of each shot point and the detection point static correction value RDD of each detection point.

8. A device for determining residual static correction, characterized in that: The master node used in parallel processing systems includes: The second acquisition module is used to acquire the shot point static correction value RDD of each shot point and the detection point static correction value RDD of each detection point sent by the computing node; a third determining module, configured to determine a first static correction value of a shot point based on the shot point static correction value RDD, and determine a second static correction value of a detection point based on the detection point static correction value RDD; a second correction module, configured to apply the first static correction amount and the second static correction amount to the common-center point seismic data to obtain corrected second common-center point seismic data, and calculate a first total energy of the second common-center point seismic data; A determination module is used to determine the static correction amount corresponding to the first common-center point seismic data as the target static correction amount when the first total energy is greater than the second total energy of the first common-center point seismic data and the difference between the first total energy and the second total energy is less than a preset percentage of the second total energy, wherein the first common-center point seismic data is obtained by applying the static correction amount to the common-center point seismic data for correction.

9. A computing node, characterized in that: The method comprises a memory and a processor, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the method for determining the residual static correction according to any one of claims 1 to 3 is executed.

10. A master node, characterized in that: The method comprises a memory and a processor, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the method for determining the residual static correction according to any one of claims 4 to 6 is executed.

11. A parallel processing system, characterized in that: include: The computing node of claim 9 and the master node of claim 10.

12. A storage medium, characterized in that: The computer program stored in the storage medium can be executed by one or more processors and can be used to implement the method for determining the residual static correction as claimed in any one of claims 1 to 6.

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