Method and system for evaluating aliasing acquisition design parameters
By forwardly simulating aliasing noise and calculating coherence and artillery coherence evaluation values, the advantages and disadvantages of aliasing acquisition design parameters are directly evaluated, and the problem of inefficient evaluation in the existing technology is solved, efficient and objective parameter optimization guidance is achieved, and exploration and acquisition costs are reduced.
Patent Information
- Application Number
- CN202510391648.4
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-03-31
- Publication Date
- 2025-07-04
AI Technical Summary
In the prior art, the evaluation method of aliasing acquisition design parameters is inefficient and lacks objectivity, making it difficult to effectively guide the optimization direction.
By using seismic data without aliasing to simulate aliasing noise, the track coherence evaluation value and gun coherence evaluation value of aliasing noise are calculated, and the advantages and disadvantages of aliasing acquisition design parameters are directly evaluated, including the calculation of track coherence evaluation value and the statistical mean of gun coherence evaluation value.
The evaluation efficiency and objectivity of aliased acquisition design parameters are improved, quantitative optimization basis is provided, exploration and acquisition costs are reduced, and high test costs and subsequent processing costs are saved.
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Figure CN120254938A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of geophysical seismic exploration acquisition, and particularly to an evaluation method and system for aliased acquisition design parameters. Background Art
[0002] In oil and gas exploration, the acquisition of seismic exploration data accounts for a relatively large cost, and this part of the cost is closely related to the construction period of exploration acquisition: the longer the acquisition time, the higher the cost.
[0003] In traditional acquisition methods, whether offshore or onshore, a single seismic source is first excited, and after all the signals generated by this seismic source are acquired, the next seismic source is excited and acquired. That is, within a record length greater than or equal to one, there is exactly one seismic source excitation. The signals acquired in this way do not overlap with each other, and after simple data arrangement, they can be directly processed by processing software.
[0004] In order to improve acquisition efficiency and save costs, the academic and industrial communities have proposed and implemented a new acquisition method - aliased acquisition: within a seismic trace record length cycle, several seismic sources are simultaneously excited, and the signals generated by these seismic sources are acquired. Compared with the traditional acquisition method, the use of this technology will greatly shorten the acquisition time. Application examples at home and abroad show that in the case of the same exploration acquisition data quality, the use of aliased acquisition technology can save up to more than 50% of the cost.
[0005] In aliased acquisition, the interval between the excitation times of seismic sources is short, resulting in aliasing of the seismic waves generated by different seismic sources, seriously affecting the signal-to-noise ratio of the original seismic data and its imaging quality. Therefore, aliased acquisition data needs to be first subjected to post-indoor deblending processing to separate the aliased signals generated by different excitation sources to form a traditional acquisition data trace gather without aliased noise, and then processed using a conventional process.
[0006] Deblending processing is the key to realizing aliased acquisition, and the randomness of aliased noise determines the final effect of deblending processing. Deblending processing techniques can be divided into two categories: denoising and inversion. No matter which method is used, it is necessary to utilize the coherence of the effective signals in the data in a certain trace gather domain (such as common receiver trace gather, common offset trace gather, common Channel trace gather, etc.) and the randomness (incoherence, weak coherence) characteristics of aliased noise in the same trace gather domain.
[0007] Therefore, the aliasing acquisition design and the de-aliasing processing technology are interdependent and complementary: 1) When the aliasing acquisition design parameters are relatively ideal, the randomness of the aliasing noise in the gather is good and the noise is easy to separate, so the requirements for the de-aliasing processing technology are reduced; 2) The higher the level of the de-aliasing processing technology, the higher the tolerance for the coherence of the aliasing noise, and the lower the requirements for the acquisition design, making it easier to implement the acquisition in the field.
[0008] At present, how to evaluate the quality of aliasing acquisition design parameters remains a hot research topic in the academic and industrial circles. One existing evaluation method in the industrial circle is as follows: Using the aliasing acquisition design parameters and the non-aliased data to forward model the aliased acquisition data, and then performing de-aliasing processing on the aliased data. By analyzing and comparing the differences between the results of the de-aliasing processing and the original non-aliased data, the quality of the acquisition design parameters is evaluated. This method is cumbersome to implement and has low efficiency; due to relying on the quality of the de-aliasing processing technology itself, its objectivity is not high; at the same time, it can only evaluate the overall situation of the acquisition design parameters and lacks an evaluation mechanism and criteria for individuals (such as the design parameters of a certain shot).
[0009] Therefore, providing an evaluation method and system for aliasing acquisition design parameters, improving the efficiency and objectivity of parameter evaluation, and providing guiding and clear information for the optimization direction of aliasing acquisition parameters are technical problems that the academic and industrial circles urgently need to solve. Summary of the Invention
[0010] In view of this, the present invention aims to propose an evaluation method and system for aliasing acquisition design parameters, providing guiding and clear information for the optimization direction of aliasing acquisition parameters, and improving the efficiency and objectivity of aliasing acquisition parameter evaluation.
[0011] To achieve the above object, the technical solution of the present invention is realized as follows: In the first aspect of the embodiments of the present invention, an evaluation method for aliasing acquisition design parameters is provided, including:
[0012] According to the aliasing acquisition design parameters, using the non-aliased seismic data, forward model the aliasing noise of the aliasing acquisition design parameters;
[0013] For the aliasing noise, convert it to the common receiver domain or common offset domain data, and for each trace of the aliasing noise data, calculate the trace coherence evaluation value with its adjacent traces of the aliasing noise;
[0014] For the trace coherence evaluation values of the aliasing noise, calculate the shot coherence evaluation value of the aliasing noise for each shot point;
[0015] According to the shot coherence evaluation value of the aliasing noise and its statistical mean value, evaluate the quality of the aliasing acquisition design parameters.
[0016] Further, the aliasing acquisition design parameters include: the source spacing of synchronous excitation and the source excitation time; the non-aliased seismic data includes: the non-aliased seismic data collected by the field actual construction operation in the traditional manner, or the non-aliased seismic data simulated by indoor digital forward modeling.
[0017] The steps for forward modeling the aliasing noise of the aliasing acquisition design parameters include:
[0018] Convert the non-aliased seismic data to the common receiver domain.
[0019] For each trace of the non-aliased seismic data in each common receiver domain, calculate the time period of its source response according to its simulated excitation time and recording length, that is: excitation time ~ excitation time + recording length.
[0020] In a common receiver domain data, for the current trace of the non-aliased seismic data, retrieve the response time periods of all other non-aliased seismic data traces except the current one. If the response time period overlaps with the response time period of the current one, intercept the data of the overlapping response time period of other non-aliased seismic data traces as the aliasing noise source data of the current trace.
[0021] In a common receiver domain data, for the current trace of the non-aliased seismic data, sum up the aforementioned intercepted aliasing noise source data belonging to it according to time to obtain the forward modeled aliasing noise of this trace.
[0022] For each trace of the non-aliased seismic data in each common receiver domain data, process it according to the aforementioned steps to obtain the forward modeled aliasing noise of the aliasing acquisition design parameters.
[0023] Further, the calculation method of the trace coherence evaluation value includes:
[0024] Convert the forward modeled aliasing noise to the common receiver domain or the common offset domain, and arrange it as three-dimensional data according to the spatial position of the shot points.
[0025] For each trace of the aliasing noise, sequentially extract each trace that is spatially adjacent to it to form M groups of two traces, where one trace is the current trace data and the other trace is the adjacent trace data, and M is a real number 1, 2, 3, or 4.
[0026] For each group of the aforementioned M groups of two traces, starting from the first sample point at the beginning, intercept data with a time window length of NT, and slide the time window sample by sample until the end of the data.
[0027] Calculate the correlation coefficient of the two traces in each time window and the root mean square amplitude value of the samples in the time window, and use the product value of the two as the value of the sample at the midpoint position of the time window to obtain a weighted correlation coefficient trace.
[0028] For the samples at the head and tail of the data that are less than the NT length, the window length is gradually reduced point by point and the aforementioned value is calculated until the window length is less than half of NT, and the values of the other remaining samples at the head and tail of the data are set to 0;
[0029] The average value of the obtained M-channel result data is calculated over time, that is, the sum is divided by M to obtain the initial coherence evaluation value of each channel of the aliasing noise;
[0030] The obtained initial coherence evaluation values are combined for adjacent channels to obtain the channel coherence evaluation value of each channel of data.
[0031] Furthermore, the value range of the window length NT is 100 milliseconds to the recording length.
[0032] The obtained initial coherence evaluation values are combined for adjacent channels to obtain the channel coherence evaluation value of each channel of data, including: setting the adjacent channel combination channel value N, and N takes values of 0, 1, 2, 3, 4 or 5;
[0033] When N is 0, that is, no combination is made, and the initial coherence evaluation value is used as the channel coherence evaluation value;
[0034] When N is 1, centered on the current channel, each channel that is immediately adjacent to it in three-dimensional space is retrieved, and the average value of the initial coherence evaluation values of the current channel and the adjacent channels is calculated as the channel coherence evaluation value of the current channel;
[0035] When N is 2, centered on the current channel, each two channels that are immediately adjacent to it in three-dimensional space are retrieved, and the average value of the initial coherence evaluation values of the current channel and the adjacent channels is calculated as the channel coherence evaluation value of the current channel;
[0036] When N is 3, centered on the current channel, each three channels that are immediately adjacent to it in three-dimensional space are retrieved, and the average value of the initial coherence evaluation values of the current channel and the adjacent channels is calculated as the channel coherence evaluation value of the current channel;
[0037] When N is 4, centered on the current channel, each four channels that are immediately adjacent to it in three-dimensional space are retrieved, and the average value of the initial coherence evaluation values of the current channel and the adjacent channels is calculated as the channel coherence evaluation value of the current channel;
[0038] When N is 5, centered on the current channel, each five channels that are immediately adjacent to it in three-dimensional space are retrieved, and the average value of the initial coherence evaluation values of the current channel and the adjacent channels is calculated as the channel coherence evaluation value of the current channel.
[0039] Furthermore, calculating the shot coherence evaluation value of the aliasing noise for each shot point includes:
[0040] For each shot point, the root mean square value of the channel coherence evaluation values of all the aliasing noise generated by it is calculated as the shot coherence evaluation value of this shot point;
[0041] Evaluate the pros and cons of the aliasing acquisition design parameters according to the shot coherence evaluation value of the aliasing noise, including:
[0042] Calculate the average value of the shot coherence evaluation values of the aliasing noise for all shot points to obtain a statistical mean value;
[0043] The larger the shot coherence evaluation value of the aliasing noise at a shot point, the stronger the coherence of the aliasing noise generated by this shot; the smaller the shot coherence evaluation value, the weaker the coherence of the aliasing noise generated by this shot;
[0044] For the aliasing acquisition design parameters, the smaller the statistical mean value of the shot coherence evaluation value, the weaker the coherence of the aliasing noise generated by this parameter, the easier the subsequent de-aliasing processing, and the better the acquisition design parameters.
[0045] The second aspect of the embodiments of the present invention provides an evaluation system for aliasing acquisition design parameters, which implements any of the above evaluation methods. The system includes:
[0046] An aliasing noise forward simulation module, configured to forward simulate the aliasing noise of the aliasing acquisition design parameters according to the aliasing acquisition design parameters and using the non-aliased seismic data;
[0047] A trace coherence evaluation value calculation module, configured to convert the aliasing noise generated by the aliasing noise forward simulation module into common receiver domain or common offset domain data, and calculate the trace coherence evaluation value for each trace of the aliasing noise data;
[0048] A shot coherence evaluation value calculation module, configured to calculate the shot coherence evaluation value of the aliasing noise for each shot point according to the trace coherence evaluation value of the aliasing noise generated by the trace coherence evaluation value calculation module, and transmit it to the acquisition design parameter evaluation module;
[0049] An acquisition design parameter evaluation module, configured to output the shot coherence evaluation value and its statistical mean value for each shot point, and evaluate the acquisition parameters.
[0050] Further, the aliasing noise forward simulation module includes:
[0051] A first trace gather preprocessing unit, configured to convert the non-aliased seismic data into the common receiver trace gather domain, and for each trace of data, calculate the time period of the source response of this trace according to the acquisition design parameters;
[0052] An aliasing noise simulation unit, configured to search, in a non-aliased common receiver trace gather domain data, for all other seismic data traces that overlap with the source response time period of this trace, and accumulate the sampled amplitude values of the overlapping time periods of the other seismic data traces one by one according to time points, as the simulated aliasing noise of this trace;
[0053] The second trace coherence evaluation value calculation module includes:
[0054] The second trace gather preprocessing unit is used to convert the forward modeling aliasing noise into the common receiver domain or the common offset domain, and arrange it into three-dimensional data according to the spatial position of the shot points;
[0055] The weighted correlation coefficient calculation unit is used to extract the current trace and an adjacent trace, slide a time window with a length of NT point by point, calculate the correlation coefficient of the two traces in the current time window and the root mean square amplitude value of the samples in the time window, and form a weighted correlation coefficient trace with the product value of the two;
[0056] The initial coherence evaluation value calculation unit is used to calculate the average value of all weighted correlation coefficient traces of the current trace to obtain the initial coherence evaluation value;
[0057] The trace coherence evaluation value calculation unit is used to perform adjacent trace combination on the obtained initial coherence evaluation value to obtain the trace coherence evaluation value of each trace data.
[0058] Furthermore, the shot coherence evaluation value calculation module includes:
[0059] The third trace gather preprocessing unit is used to convert the seismic data traces formed by the trace coherence evaluation values of the aliasing noise into the common receiver trace gather domain;
[0060] The trace coherence evaluation value collection unit retrieves the overlapping area of the source response time periods of other shots except the current shot in each trace coherence evaluation value common receiver trace gather domain according to the time period of each shot source response calculated by the first trace gather preprocessing unit, and accordingly collects the trace coherence evaluation values of each trace and each time sampling point to the shot point that generates the aliasing noise of this sample point;
[0061] The shot coherence evaluation value calculation unit calculates the root mean square value of all sampling points of this shot point according to the collection result of the shot coherence evaluation values of each shot point obtained by the trace coherence evaluation value collection unit to obtain the shot coherence evaluation value of this shot point;
[0062] The acquisition design parameter evaluation module is used for:
[0063] Calculating the average value of the shot coherence evaluation values of all shot points to obtain its statistical mean value;
[0064] Outputting the shot coherence evaluation values and the statistical mean value of each shot point to the display terminal or the disk file.
[0065] Furthermore, in the trace coherence evaluation value calculation module, for the time window with a length of NT in the weighted correlation coefficient calculation unit, the value range of NT is 100 milliseconds to the recording length;
[0066] In the channel coherence evaluation value calculation unit, for the adjacent channel combination, the value range of the number of combined channels N is: 0, 1, 2, 3, 4, or 5.
[0067] In the third aspect of the embodiments of the present invention, an evaluation system for aliased acquisition design parameters is provided, including a processor and a memory for storing processor-executable instructions. When the instructions are executed by the processor, the following steps are implemented:
[0068] According to the aliased acquisition design parameters, using non-aliased seismic data, forward simulate the aliasing noise of the aliased acquisition design parameters;
[0069] For the aliasing noise, convert it to common receiver domain or common offset domain data, and for each channel of aliasing noise data, calculate the channel coherence evaluation value of the aliasing noise;
[0070] For the channel coherence evaluation value of the aliasing noise, calculate the shot coherence evaluation value of the aliasing noise for each shot point;
[0071] According to the shot coherence evaluation value of the aliasing noise, calculate its statistical mean, and output the shot coherence evaluation value and the statistical mean to a display terminal or a disk file.
[0072] Compared with the prior art, the evaluation method and system for aliased acquisition design parameters of the present invention have the following advantages: According to the aliased acquisition design parameters, using non-aliased seismic data, forward simulate the aliasing noise, and calculate the channel coherence evaluation value, shot coherence evaluation value, and statistical mean of the shot coherence evaluation value of the aliasing noise. The obtained shot coherence evaluation value and its statistical mean can be directly used to evaluate the quality of the acquisition design parameters, without the need for de-aliasing processing for evaluation, improving the efficiency and objectivity of the evaluation of aliased acquisition design parameters, providing a quantitative basis and a clear direction for the optimization of aliased acquisition design parameters.
[0073] The shot coherence evaluation value and the statistical mean obtained by the present invention can be used to evaluate the quality of the acquisition design parameters, without the need for field actual acquisition and de-aliasing processing for evaluation, improving the efficiency and objectivity of the evaluation of aliased acquisition design parameters, significantly reducing the exploration and acquisition cost, and expected to generate good economic and social benefits.
[0074] (1) Compared with the traditional acquisition method, aliased acquisition can save more than 50% of the exploration and acquisition cost. Aliased acquisition design is the first step in implementing aliased acquisition, and the quality of the design determines the quality of the seismic data obtained by aliased acquisition. The present invention provides a method and system for evaluating the quality of aliased acquisition design;
[0075] (2) The evaluation of the pros and cons of the aliasing acquisition design of the present invention does not require field actual acquisition tests, saving high test costs; nor is it the evaluation after anti-aliasing processing after acquisition construction, and such an evaluation is of no avail; the present invention can avoid huge construction costs caused by acquisition design mistakes;
[0076] (3) The evaluation method and system provided by the present invention are objective evaluations with quantitative data, rather than empirical subjective evaluations. BRIEF DESCRIPTION OF THE DRAWINGS
[0077] The drawings constituting a part of the present invention are used to provide a further understanding of the present invention. The schematic embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. For those of ordinary skill in the art, other drawings can also be obtained based on these drawings without creative efforts. In the drawings:
[0078] Figure 1 is a schematic flowchart of a method of an embodiment of a method for evaluating aliasing acquisition design parameters provided by the present invention;
[0079] Figure 2 is a cross-sectional view of non-aliased seismic data in the common geophone domain in an embodiment of the present invention;
[0080] Figure 3 is the aliasing noise forward-simulated according to non-aliased seismic data in an embodiment of the present invention;
[0081] Figure 4 is the aliasing acquisition data obtained according to non-aliased seismic data in an embodiment of the present invention;
[0082] Figure 5 is the trace coherence evaluation value profile calculated in an embodiment of the present invention;
[0083] Figure 6 is a schematic two-dimensional plan view of the shot coherence evaluation value calculated in an embodiment of the present invention;
[0084] Figure 7 is a schematic diagram of the coherence evaluation statistical mean of 4 groups of acquisition parameters calculated in an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS
[0085] It should be noted that, without conflict, the embodiments in the present invention and the features in the embodiments can be combined with each other.
[0086] In the description of the present invention, unless otherwise specified, the meaning of "a plurality of" is two or more.
[0087] The present invention will be described in detail below with reference to the drawings and in combination with the embodiments.
[0088] In the first aspect of the embodiments of the present invention, an evaluation method for aliased acquisition design parameters is proposed. Compared with traditional acquisition methods, the aliased acquisition technology can greatly save the acquisition cost while maintaining the same exploration acquisition data quality. In aliased acquisition, aliased noise will seriously affect the signal-to-noise ratio of seismic data and its imaging quality. Therefore, de-aliasing processing is the key to realizing aliased acquisition. De-aliasing processing depends on the randomness (incoherence) of aliased noise in the processed gather domain, and the randomness of aliased noise is determined by aliased acquisition design parameters. The embodiments of the present invention evaluate the quality of aliased acquisition design parameters by forward simulating aliased noise and calculating the shot coherence evaluation value of aliased noise. The evaluation method and system for the aliased acquisition design parameters do not require de-aliasing processing, can improve the efficiency and objectivity of the evaluation of acquisition design parameters, and provide quantitative and guiding information for the optimization direction of aliased acquisition parameters. Specifically, as Figure 1 shown, the method includes:
[0089] S1. According to the aliased acquisition design parameters, use non-aliased seismic data to forward simulate the aliased noise of the aliased acquisition design parameters;
[0090] Among them, the non-aliased seismic data includes: non-aliased seismic data collected by field actual construction operations in the traditional manner, or non-aliased seismic data digitally forward simulated indoors; within a time period greater than or equal to one record length, there is only one seismic source excitation for the non-aliased data.
[0091] The aliased acquisition design parameters include: the source spacing (spatial position) of synchronous excitation, and the source excitation time;
[0092] The theoretical basis for the forward simulation of aliased noise is shown in the following formula (1):
[0093] d = Γm (1)
[0094] Formula (1) is an aliasing model (Berkhout, 2008), where d is the aliased data obtained by acquisition, m is the data collected by the non-aliased traditional method, and Γ is an aliasing matrix operator that contains the spatial and time information of seismic source excitation.
[0095] According to formula (1), when designing the time and spatial position of seismic source excitation in aliased acquisition, the aliased data can be forward simulated.
[0096] The method of the present invention does not forward simulate the aliased data, but directly forward simulates the aliased noise:
[0097] 1) Convert the non-aliased seismic data that has applied the aliased acquisition design parameters and contains the source excitation time and spatial information to the common receiver domain;
[0098] 2) For each aliasing-free seismic data in a common receiver domain, calculate the time period of its source response according to its source excitation time and recording length, that is: excitation time ~ excitation time + recording length;
[0099] 3) In a common receiver domain data, for the current aliasing-free seismic data, retrieve the source response time periods of all other aliasing-free seismic data traces except the current one. If it is found that the response time period of this shot trace overlaps with the response time period of the current one, then intercept the data of the overlapping response time period of this aliasing-free seismic data trace as the aliasing noise source data at the current trace (shot) position; at the current trace (shot point) position, there may be aliasing noise source data generated by multiple seismic traces (i.e., multiple shot points) simultaneously;
[0100] 4) In a common receiver domain data, for the current aliasing-free seismic data, add the aliasing noise source data intercepted in the previous step at this trace (i.e., shot point) position according to the time subscript of the samples to obtain the forward modeled aliasing noise at this trace (shot point) position;
[0101] 5) For each aliasing-free seismic data trace in each common receiver domain data, process it according to the foregoing steps to obtain the forward modeled aliasing noise of this aliasing acquisition design parameter.
[0102] Figure 2 is a common receiver gather of an aliasing-free seismic data in an embodiment of the present invention, showing only two shot lines; Figure 3 is the aliasing noise of this data forward modeled according to the method of the present invention, Figure 4 is the corresponding aliased data obtained by adding the aliasing-free data and the forward modeled noise.
[0103] S2. Convert the forward modeled aliasing noise to the common receiver domain or common offset domain data, and calculate the trace coherence evaluation value of the noise according to the set time window length and the number of adjacent traces.
[0104] 1) Convert the forward modeled aliasing noise to the common receiver domain or common offset domain, and arrange it as three-dimensional data according to the spatial position of the shot points;
[0105] 2) For each trace data of the aliasing noise, sequentially extract each trace data that is spatially adjacent to it to form M groups of two trace data (one current trace and one adjacent trace). According to the different spatial positions of the current trace (i.e., the spatial position determined by the coordinates of the shot point where this trace of aliasing noise is located), the value of M is a real number 1, 2, 3, or 4;
[0106] 3) For each two trace data in the M groups obtained in the previous step, starting from the first sample at the beginning, intercept data with a time window length of NT, and slide the time window sample by sample downward until the end of the data;
[0107] The value range of NT is from 100 milliseconds to the record length;
[0108] 4) Calculate the correlation coefficient of these two data in each time window and the root mean square amplitude value of the samples within the time window, and use the product value of the two as the value of the sample at the midpoint position of the time window to obtain a weighted correlation coefficient trace;
[0109] For the samples at the head and tail of the data that are less than the NT length, gradually reduce the time window length and calculate the aforementioned values until the time window length is less than half of NT, and set the values of the other remaining samples at the head and tail of the data to zero;
[0110] The specific calculation formula is as follows:
[0111] Correlation coefficient:
[0112] Root mean square amplitude:
[0113] Weighted correlation coefficient: C(x,y) = A RMS ×ρ xy (4)
[0114] In the above formula, x and y are the time window data of the current trace and an adjacent trace respectively, n is the number of samples within the time window, and i is the time subscript of the samples within the time window.
[0115] 5) Repeat steps 3 and 4 to obtain the weighted correlation coefficient traces of M traces, and calculate the average value of the M traces of data over time, that is, divide the sum by M to obtain the initial coherence evaluation value of each trace of aliasing noise;
[0116] Initial coherence evaluation value:
[0117] In the above formula, k is the time subscript of the sampling point, i is the horizontal subscript of the shot point position, j is the vertical subscript of the shot point position, x is the current trace, and y is the adjacent trace.
[0118] According to the different shot point positions of the current trace, the actual value of M may be 1, 2, 3, 4, and the possible values of y are: x i-1,j , x i+1,j , x i,j-1 , x i,j+1 .
[0119] 6) Perform adjacent trace combination on the obtained initial coherence evaluation value to obtain the trace coherence evaluation value of each trace:
[0120] Set the adjacent trace combination trace value N, and the value range of N is 0, 1, 2, 3, 4, 5:
[0121] When N is 0, that is, no combination is performed, and the initial coherence evaluation value is used as the trace coherence evaluation value, that is:
[0122] Channel coherence evaluation value: U i,j,k =T i,j,k (6)
[0123] When N is not 0, we have:
[0124] Channel coherence evaluation value:
[0125] In the above formula, k is the time subscript of the sampling point, i and l are the horizontal subscripts of the shot point position, j and p are the vertical subscripts of the shot point position, T is the initial coherence evaluation value, N is the set value of the combined channel number, and m is the actual combined channel number at the current position. (At the boundary of the work area or the position where the view is short of shots, the actual combined channel number cannot reach the set value N).
[0126] Formula (7) is decomposed as follows when N is different:
[0127] When N is 1, take the current track as the center, search each track that is adjacent to it in the three-dimensional space, calculate the average of the initial coherence evaluation values of the current track and the adjacent tracks, and use it as the track coherence evaluation value of the current track;
[0128] When N is 2, take the current track as the center, search every two tracks that are adjacent to it in the three-dimensional space, calculate the average of the initial coherence evaluation values of the current track and the adjacent tracks, and use it as the track coherence evaluation value of the current track;
[0129] When N is 3, take the current track as the center, search every three tracks that are adjacent to it in the three-dimensional space, calculate the average of the initial coherence evaluation values of the current track and the adjacent tracks, and use it as the track coherence evaluation value of the current track;
[0130] When N is 4, take the current track as the center, search every four tracks adjacent to it in the three-dimensional space, calculate the average of the initial coherence evaluation values of the current track and the adjacent tracks, and use it as the track coherence evaluation value of the current track;
[0131] When N is 5, with the current track as the center, every five tracks adjacent to it in three-dimensional space are retrieved, and the average of the initial coherence evaluation values of the current track and the adjacent tracks is calculated as the track coherence evaluation value of the current track.
[0132] Figure 5 This is a trace coherence evaluation value profile calculated using aliasing noise simulated by forward modeling in an embodiment of the present invention, using a 200 millisecond time window and setting the number of adjacent trace combinations to 1.
[0133] S3, the trace coherence evaluation value of the aliasing noise is aggregated to the corresponding shot points and the statistical mean is obtained, and the shot coherence evaluation value of the aliasing noise of each shot point is calculated;
[0134] 1) Convert the calculated data traces of the trace coherence evaluation value to the common receiver gather domain.
[0135] 2) For each shot in a common receiver gather, calculate the time period of its source response according to the firing time of the shot point, that is: firing time ~ firing time + recording length;
[0136] 3) For each shot in a common receiver gather, retrieve the source response time periods of all other shots except itself. If the response time periods of other shots overlap with the response time period of the current shot, intercept the trace coherence evaluation value data of the overlapping time period of other shots for processing, and increment the counter of the noise coverage times recording the samples of this overlapping time period by 1;
[0137] 4) For each shot in a common receiver gather, perform square accumulation on all the data of the overlapping time periods intercepted in the previous step, as shown in the following formula:
[0138] Single geophone shot coherence cumulative value:
[0139] In the formula, s is the shot number index, r is the geophone number index, k is the number of retrieved overlapping time periods, indicates performing summation accumulation on all overlapping time periods, j is the time subscript of the sample, n1~n2 is the subscript range of a certain overlapping time period, F is the sample noise coverage times, U is the trace coherence evaluation value, and V is the shot coherence cumulative value of the shot point s at the geophone r.
[0140] 5) Repeat the above steps 2~4 for each common receiver gather, and accumulate the obtained shot coherence cumulative values and finally calculate the root mean square value to obtain the shot coherence evaluation value of this shot point:
[0141] Shot coherence evaluation value:
[0142] In the formula, indicates performing summation accumulation on the results of all geophones, and n is the total number of samples of the trace coherence evaluation value used to calculate the coherence evaluation value of this shot.
[0143] S4. Calculate the statistical mean of the shot coherence evaluation values of the aliasing noise, and output the shot coherence evaluation value and its statistical mean for acquisition parameter evaluation. The smaller the value, the better the parameter.
[0144] Calculate the average value of the shot coherence evaluation values of all shot points to obtain its statistical mean;
[0145] Output the shot coherence evaluation values and statistical means of each shot point to the display terminal or disk file.
[0146] The greater the shot coherence evaluation value of the aliasing noise at a shot point, the stronger the coherence of the aliasing noise generated by this shot, and the worse the acquisition design parameters of this shot;
[0147] The smaller the shot coherence evaluation value of the aliasing noise at a shot point, the weaker the coherence of the aliasing noise generated by this shot, and the better the acquisition design parameters of this shot;
[0148] For the aliasing acquisition design parameters, the smaller the statistical mean value of the shot coherence evaluation value, the weaker the coherence of the aliasing noise generated by this parameter, the easier the subsequent anti-aliasing processing, and the better the acquisition design parameters.
[0149] Figure 6 It is a schematic diagram of the calculated shot coherence evaluation value in the embodiment of the present invention: Most of the shot coherence evaluation values in the figure are less than 1. For the shots with larger values, it indicates that the aliasing noise generated by these shots has strong coherence, which will cause trouble for anti-aliasing processing. When optimizing and improving the acquisition parameters, these shots with larger coherence evaluation values should be focused on.
[0150] Figure 7 It is a schematic diagram of the statistical mean value of the calculated shot coherence evaluation value in the embodiment of the present application: For the same set of non-aliased seismic data, 4 groups of different aliasing acquisition design parameters are adopted, showing 4 statistical mean values; among them, the value of the fourth group of parameters is the smallest, indicating that the overall coherence of its aliasing noise is the weakest and the acquisition parameters are relatively the best.
[0151] In the second aspect of the embodiment of the present invention, an evaluation system for aliasing acquisition design parameters is proposed. Implementing any of the above evaluation methods, the system includes:
[0152] An aliasing noise forward simulation module, configured to forward simulate the aliasing noise of the aliasing acquisition design parameters according to the aliasing acquisition design parameters and using non-aliased seismic data;
[0153] A trace coherence evaluation value calculation module, configured to convert the aliasing noise generated by the aliasing noise forward simulation module into common receiver domain or common offset domain data, and calculate the trace coherence evaluation value for each trace of aliasing noise data;
[0154] A shot coherence evaluation value calculation module, configured to calculate the shot coherence evaluation value of the aliasing noise at each shot point according to the trace coherence evaluation value of the aliasing noise generated by the trace coherence evaluation value calculation module, and transmit it to the acquisition design parameter evaluation module;
[0155] An acquisition design parameter evaluation module, configured to output the shot coherence evaluation value and its statistical mean value of each shot point, and evaluate the acquisition parameters.
[0156] Further, in another embodiment of the system, the aliasing noise forward simulation module includes:
[0157] The first gather preprocessing unit is used to convert the aliasing-free seismic data into the common receiver gather domain, and for each trace of data, calculate the time period of the source response of this trace (i.e., the shot point) according to the acquisition design parameters.
[0158] The aliasing noise simulation unit is used to search, within the data of an aliasing-free common receiver gather domain, for all other seismic data traces whose source response time periods overlap with that of a given trace, and accumulate the sampled amplitude values at the overlapping time periods of the other seismic data traces point by point in time to obtain the simulated aliasing noise for this trace.
[0159] In another embodiment of the system, the trace coherence evaluation value calculation module includes:
[0160] The second gather preprocessing unit is used to convert the forward modeled aliasing noise into the common receiver domain or the common offset domain, and arrange it as three-dimensional data according to the spatial position of the shot points.
[0161] The weighted correlation coefficient calculation unit is used to extract a current trace and an adjacent trace, slide a time window of length NT point by point, calculate the correlation coefficient between the two traces within the current time window and the root mean square amplitude value of the samples within the time window, and form a weighted correlation coefficient trace with the product value of the two.
[0162] In the weighted correlation coefficient calculation unit, the value range of the time window length NT is: 100 milliseconds to the record length.
[0163] The initial coherence evaluation value calculation unit is used to calculate the average value of all the weighted correlation coefficient traces of a current trace to obtain the initial coherence evaluation value.
[0164] The trace coherence evaluation value calculation unit is used to perform adjacent trace combination on the obtained initial coherence evaluation value to obtain the trace coherence evaluation value for each trace of data.
[0165] In another embodiment of the system, the trace coherence evaluation value calculation unit is used to set the adjacent trace combination number value N, and the value of the combination number N is: 0, 1, 2, 3, 4 or 5.
[0166] When N is 0, that is, no combination is performed, and the initial coherence evaluation value is used as the trace coherence evaluation value.
[0167] When N is 1, centered on the current trace, search for each trace adjacent to it in three-dimensional space, and calculate the average value of the initial coherence evaluation values of the current trace and the adjacent traces as the trace coherence evaluation value of the current trace.
[0168] When N is 2, centered on the current trace, search for each two traces adjacent to it in three-dimensional space, and calculate the average value of the initial coherence evaluation values of the current trace and the adjacent traces as the trace coherence evaluation value of the current trace.
[0169] When N is 3, centered on the current trace, retrieve every three traces adjacent to it in three-dimensional space, and calculate the average value of the initial coherence evaluation values of the current trace and the adjacent traces as the trace coherence evaluation value of the current trace.
[0170] When N is 4, centered on the current trace, retrieve every four traces adjacent to it in three-dimensional space, and calculate the average value of the initial coherence evaluation values of the current trace and the adjacent traces as the trace coherence evaluation value of the current trace;
[0171] When N is 5, centered on the current trace, retrieve every five traces adjacent to it in three-dimensional space, and calculate the average value of the initial coherence evaluation values of the current trace and the adjacent traces as the trace coherence evaluation value of the current trace.
[0172] In another embodiment of the system, the shot coherence evaluation value calculation module includes:
[0173] The third trace gather preprocessing unit is used to convert the seismic data traces formed by the trace coherence evaluation values of the aliasing noise to the common receiver gather domain;
[0174] The trace coherence evaluation value collection unit, for each trace (i.e., shot point) in each common receiver gather, according to the time period of its source response, retrieves the overlapping regions of the source response time periods of all other traces (i.e., shot points) except itself in each common receiver gather. If the response time period of other traces overlaps with the response time period of the current trace, then intercept the trace coherence evaluation value data of the overlapping time period of other traces and collect them to this current trace (i.e., shot point);
[0175] The shot coherence evaluation value calculation unit calculates the root mean square value of all sampling points of the shot point according to the collection result of the trace coherence evaluation value of each shot point obtained by the trace coherence evaluation value collection unit to obtain the shot coherence evaluation value of the shot point;
[0176] In another embodiment of the system, the acquisition design parameter evaluation module is used for:
[0177] Calculate the average value of the shot coherence evaluation values of all shot points to obtain its statistical mean value;
[0178] Output the shot coherence evaluation values of each shot point and the statistical mean value to a display terminal or a disk file.
[0179] In the third aspect of the embodiments of the present invention, an evaluation system for aliased acquisition design parameters is proposed, including a processor and a memory for storing instructions executable by the processor. When the instructions are executed by the processor, the following steps are implemented:
[0180] According to the aliased acquisition design parameters, use the non-aliased seismic data to forward simulate the aliasing noise of the aliased acquisition design parameters;
[0181] For aliasing noise, convert it to common-receiver domain or common-offset domain data, and for each trace of aliasing noise data, calculate the trace coherence evaluation value of the aliasing noise;
[0182] For the trace coherence evaluation value of the said aliasing noise, calculate the shot coherence evaluation value of the aliasing noise for each shot point;
[0183] According to the shot coherence evaluation value of the aliasing noise, calculate its statistical mean value, and output the shot coherence evaluation value and the statistical mean value to a display terminal or a disk file.
[0184] Using each embodiment of the present invention, the obtained shot coherence evaluation value and statistical mean value can be used to evaluate the advantages and disadvantages of acquisition design parameters, without the need for actual field acquisition and evaluation after de-aliasing processing, improving the efficiency and objectivity of aliasing acquisition design parameter evaluation, and reducing the exploration acquisition cost.
[0185] The above are only the preferred embodiments of the present invention, rather than all embodiments, and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.
Claims
1. An evaluation method for aliasing acquisition design parameters, characterized in that Including: According to the aliasing acquisition design parameters, using non-aliased seismic data, forward model the aliasing noise of the aliasing acquisition design parameters; For the aliasing noise, convert it to common receiver domain or common offset domain data, and for each trace of aliasing noise data, calculate the trace coherence evaluation value with the adjacent trace of the aliasing noise; For the trace coherence evaluation value of the aliasing noise, calculate the shot coherence evaluation value of the aliasing noise for each shot point; According to the shot coherence evaluation value of the aliasing noise and its statistical mean value, evaluate the quality of the aliasing acquisition design parameters.
2. The evaluation method for aliasing acquisition design parameters according to claim 1, wherein: The aliasing acquisition design parameters include: the source spacing of synchronous excitation, the source excitation time; the non-aliased seismic data includes: non-aliased seismic data collected by field actual construction operations in the traditional manner, or non-aliased seismic data simulated digitally in the laboratory; The steps of forward modeling the aliasing noise of the aliasing acquisition design parameters include: Convert the non-aliased seismic data to the common receiver domain; For each trace of non-aliased seismic data in each common receiver domain, calculate the time period of its source response according to its simulated excitation time and recording length, that is: excitation time ~ excitation time + recording length; In a common receiver domain data, for the current trace of non-aliased seismic data, retrieve the response time periods of all other non-aliased seismic data traces except the current one. If there is an overlap between the response time periods, intercept the data of the overlapping response time periods of other non-aliased seismic data traces as the aliasing noise source data of the current trace; In a common receiver domain data, for the current trace of non-aliased seismic data, sum up the previously intercepted aliasing noise source data belonging to it in time to obtain the forward modeled aliasing noise of this trace; For each trace of non-aliased seismic data in each common receiver domain data, process it according to the above steps to obtain the forward modeled aliasing noise of the aliasing acquisition design parameters.
3. The evaluation method for aliasing acquisition design parameters according to claim 2, wherein: The calculation method of the trace coherence evaluation value includes: Convert the forward modeled aliasing noise to the common receiver domain or common offset domain, and arrange it as three-dimensional data according to the spatial position of the shot points; For each trace of the aliasing noise, sequentially extract each trace that is spatially adjacent to it to form M groups of two traces, where one trace is the current trace data and the other trace is the adjacent trace data, and M is a real number 1, 2, 3, or 4; For each two traces in the above M groups, starting from the first sample point at the beginning, intercept data with a time window length of NT, and slide the time window one sample point downward until the end of the data; Calculate the correlation coefficient of these two traces in each time window and the root mean square amplitude value of the sample points in the time window, and use the product value of the two as the value of the sample point at the midpoint position of the time window to obtain a weighted correlation coefficient trace; For the sample points at the head and tail of the data that are less than NT in length, gradually reduce the time window length and calculate the above values until the time window length is less than half of NT, and set the values of the other remaining sample points at the head and tail of the data to 0; Average the obtained M trace result data in time, that is, sum and then divide by M to obtain the initial coherence evaluation value of each trace of the aliasing noise; Perform adjacent trace combination on the obtained initial coherence evaluation values to obtain the trace coherence evaluation values for each trace of data.
4. The evaluation method for aliasing acquisition design parameters according to claim 3, wherein: The value range of the time window length NT is from 100 milliseconds to the recording length; Perform adjacent trace combination on the obtained initial coherence evaluation values to obtain the trace coherence evaluation values for each trace of data, including: setting the adjacent trace combination trace number N, and N takes values of 0, 1, 2, 3, 4, or 5; When N is 0, that is, no combination is performed, and the initial coherence evaluation value is used as the trace coherence evaluation value; When N is 1, centered on the current trace, retrieve each trace that is adjacent to it in the three-dimensional space, and calculate the average value of the initial coherence evaluation values of the current trace and the adjacent traces as the trace coherence evaluation value of the current trace; When N is 2, centered on the current trace, retrieve every two traces that are adjacent to it in the three-dimensional space, and calculate the average value of the initial coherence evaluation values of the current trace and the adjacent traces as the trace coherence evaluation value of the current trace; When N is 3, centered on the current trace, retrieve every three traces that are adjacent to it in the three-dimensional space, and calculate the average value of the initial coherence evaluation values of the current trace and the adjacent traces as the trace coherence evaluation value of the current trace; When N is 4, centered on the current trace, retrieve every four traces that are adjacent to it in the three-dimensional space, and calculate the average value of the initial coherence evaluation values of the current trace and the adjacent traces as the trace coherence evaluation value of the current trace; When N is 5, centered on the current trace, retrieve every five traces that are adjacent to it in the three-dimensional space, and calculate the average value of the initial coherence evaluation values of the current trace and the adjacent traces as the trace coherence evaluation value of the current trace.
5. The evaluation method of aliasing acquisition design parameters according to claim 1, wherein: Calculate the shot coherence evaluation values of the aliasing noise for each shot point, including: For each shot point, calculate the root mean square value of the trace coherence evaluation values of all the aliasing noise generated by it as the shot coherence evaluation value of this shot point; According to the shot coherence evaluation values of the aliasing noise, evaluate the advantages and disadvantages of the aliasing acquisition design parameters, including: Calculate the average value of the shot coherence evaluation values of the aliasing noise for all shot points to obtain a statistical mean value; The larger the shot coherence evaluation value of the aliasing noise of a shot point, the stronger the coherence of the aliasing noise generated by this shot, and the smaller the shot coherence evaluation value, the weaker the coherence of the aliasing noise generated by this shot; For the aliasing acquisition design parameters, the smaller the statistical mean value of the shot coherence evaluation values, the weaker the coherence of the aliasing noise generated by this parameter, the easier the subsequent de-aliasing processing, and the better the acquisition design parameters.
6. An evaluation system for aliasing acquisition design parameters, characterized in that: Implement the evaluation method according to any one of claims 1-5, and the system includes: An aliasing noise forward simulation module, which is used to forward simulate the aliasing noise of the aliasing acquisition design parameters by using the non-aliased seismic data according to the aliasing acquisition design parameters; A trace coherence evaluation value calculation module, which is used to convert the aliasing noise generated by the aliasing noise forward simulation module into common receiver domain or common offset domain data, and calculate the trace coherence evaluation value for each trace of aliasing noise data; A shot coherence evaluation value calculation module, which is used to calculate the shot coherence evaluation values of the aliasing noise for each shot point according to the trace coherence evaluation values of the aliasing noise generated by the trace coherence evaluation value calculation module, and transmit them to the acquisition design parameter evaluation module; An acquisition design parameter evaluation module, which is used to output the shot coherence evaluation values of each shot point and their statistical mean values, and evaluate the acquisition parameters.
7. An evaluation system for aliasing acquisition design parameters according to claim 6, characterized in that: Aliasing noise forward simulation module, including: The first trace gather preprocessing unit is used to convert the alias-free seismic data into the common receiver gather domain, and for each trace of data, calculate the time period of the source response of this trace according to the acquisition design parameters; The aliasing noise simulation unit is used to search, within the data of an alias-free common receiver gather domain, for all other seismic data traces whose source response time periods overlap with the source response time period of this trace, and accumulate the sampled amplitude values of the overlapping time periods of the other seismic data traces point by point according to time points, as the simulated aliasing noise of this trace; Trace coherence evaluation value calculation module, including: The second trace gather preprocessing unit is used to convert the forward simulated aliasing noise into the common receiver domain or the common offset domain, and arrange it as three-dimensional data according to the spatial position of the shot points; The weighted correlation coefficient calculation unit is used to extract the current trace and an adjacent trace, slide a time window with a length of NT point by point, calculate the correlation coefficient of the two traces of data within the current time window and the root mean square amplitude value of the samples within the time window, and form a weighted correlation coefficient trace with the product value of the two; The initial coherence evaluation value calculation unit is used to calculate the average value of all weighted correlation coefficient traces of the current trace to obtain the initial coherence evaluation value; The trace coherence evaluation value calculation unit is used to perform adjacent trace combination on the obtained initial coherence evaluation value to obtain the trace coherence evaluation value of each trace of data.
8. An evaluation system for aliasing acquisition design parameters according to claim 7, characterized in that: Shot coherence evaluation value calculation module, including: The third trace gather preprocessing unit is used to convert the seismic data traces formed by the trace coherence evaluation values of the aliasing noise into the common receiver gather domain; The trace coherence evaluation value collection unit, according to the time period of the source response of each shot calculated by the first trace gather preprocessing unit, retrieves the overlapping area of the source response time periods of other shots except the current shot in each common receiver gather domain of the trace coherence evaluation value, and accordingly collects the trace coherence evaluation value of each trace and each time sampling point to the shot point that generates the aliasing noise of this sample point; The shot coherence evaluation value calculation unit, according to the collection result of the shot coherence evaluation value of each shot point obtained by the trace coherence evaluation value collection unit, calculates the root mean square value of all sampling points of this shot point to obtain the shot coherence evaluation value of this shot point; The acquisition design parameter evaluation module is used for: Calculating the average value of the shot coherence evaluation values of all shot points to obtain its statistical mean value; Outputting the shot coherence evaluation value and the statistical mean value of each shot point to the display terminal or the disk file.
9. An evaluation system for aliasing acquisition design parameters according to claim 7, characterized in that: In the trace coherence evaluation value calculation module, the time window with a length of NT in the weighted correlation coefficient calculation unit, the value range of NT is 100 milliseconds to the record length; In the trace coherence evaluation value calculation unit, for the adjacent trace combination, the value of the combination trace number N is: 0, 1, 2, 3, 4 or 5.
10. An evaluation system for aliasing acquisition design parameters, characterized in that: Including a processor and a memory for storing processor-executable instructions, when the instructions are executed by the processor, the following steps are implemented: According to the aliasing acquisition design parameters, using the alias-free seismic data, forward simulate the aliasing noise of the aliasing acquisition design parameters; For aliasing noise, convert it to common receiver domain or common offset domain data. For each trace of aliasing noise data, calculate the trace coherence evaluation value of the aliasing noise; For the trace coherence evaluation value of the aliasing noise, calculate the shot coherence evaluation value of the aliasing noise for each shot point; According to the shot coherence evaluation value of the aliasing noise, calculate its statistical mean, and output the shot coherence evaluation value and the statistical mean to the display terminal or disk file.