Observation scheme optimization method based on uniformity index

Abstract

The invention relates to the technical field of oil and gas seismic exploration data acquisition, in particular to an observation scheme optimization method based on a uniformity index. The method comprises the following steps: S10, collecting and sorting observation parameters for determining an optimization scheme; s20, carrying out optimization design on the observation scheme parameters to obtain N optimized observation schemes; s30, calculating noise elimination response values corresponding to the N optimization observation schemes; s40, calculating noise suppression response values corresponding to the N optimization observation schemes; s50, calculating de-noising response values corresponding to the N optimization observation schemes based on the noise elimination response values and the noise suppression response values corresponding to the N optimization observation schemes; s60, calculating pre-stack time migration response values corresponding to the N optimization observation schemes; and S70, based on the signal-to-noise ratio spectrums and the effective high frequencies of the N optimization observation schemes, and in combination with the index requirements of the signal-to-noise ratio and the highest frequency of the target layer, selecting a final scheme from the N optimization observation schemes.

Description

Technical Field

[0001] The present invention relates to the technical field of oil and gas seismic exploration data acquisition, and particularly to an optimization method for an observation scheme based on a uniformity index. Background Technique

[0002] Seismic exploration is an important method for searching for oil and gas, mainly including three links: seismic data acquisition, processing, and interpretation.

[0003] An important task in seismic data acquisition is to design and optimize the parameters of the observation system. The main parameters of the observation scheme include trace interval, receiver line interval, shot point interval, shot line interval, number of receiver channels, number of receiver lines, fold number, coverage density, aspect ratio, uniformity, roll distance, etc. Among them, trace interval, receiver line interval, shot point interval, shot line interval, number of receiver lines, and number of receiver channels are the basic parameters of the observation system. The selection of the basic parameters determines other parameters. For example, trace interval, receiver line interval, shot point interval, shot line interval, number of receiver channels, and number of receiver lines determine the size of the fold number. Therefore, there is a close connection between these parameters and they have an overall physical meaning. According to the requirements of geological tasks, the evaluation of the observation system is carried out in a way that takes overall consideration and focuses on individual parameters.

[0004] Since 2012, with the successful experiment and wide application of the "two wide and one high" acquisition technology, the coverage density parameter in the observation system has been the main focus in the design and optimization process. Coverage density reflects the number of shot-receiver pairs per unit area and is also called shot-trace density.

[0005] During this period, for complex geological targets and deep geological targets, the optimization of coverage density has effectively improved the quality of seismic data and achieved good exploration results. With the development of seismic exploration targets towards more refined and more complex trends in recent years, and the transformation from oil and gas exploration tasks to development tasks, the requirements for the signal-to-noise ratio and resolution of seismic data are constantly increasing, and more targeted bases need to be formed in the optimization of the seismic acquisition observation scheme. Therefore, in the process of optimizing the observation scheme, in addition to focusing on the coverage density index, the uniformity index should also be emphasized. Uniformity is an important index for measuring the observation system. In the present invention, the uniformity index refers to the ratio of the point interval to the line interval in the observation system. In a conventional observation system, this value ≤ 1. The smaller the ratio, the worse the uniformity, and the larger the ratio, the better the uniformity.

[0006] In view of the current requirements for oil and gas exploration and development, the optimization of the seismic acquisition observation plan should, on the one hand, ensure good prestack time migration effects, and on the other hand, ensure good noise suppression responses. Research shows that there is a linear relationship between the prestack time migration response and the coverage density. As the coverage density increases, the average value of the prestack time migration response increases; the prestack time migration response has a relatively small relationship with the uniformity. There is a positive correlation between the noise suppression response and both the coverage density and the uniformity, that is, as the coverage density increases, the regular noise suppression response is enhanced; as the uniformity improves, the noise suppression response is also strengthened. The denoising response and the prestack time migration response ultimately determine the signal-to-noise ratio of the seismic data, and thus determine the effective high frequency of the data.

[0007] Currently, in the design and optimization of onshore conventional observation plans, more attention is paid to the coverage density index, and less consideration or only qualitative and rough consideration is given to the uniformity index. To solve this technical problem, an optimization method for the observation plan based on the uniformity index is proposed. Summary of the Invention

[0008] To solve the technical problems existing in the above-mentioned prior art, the present invention provides an optimization method for the observation plan based on the uniformity index, and the present invention is more suitable for the original seismic acquisition data that meets the current oil and gas exploration and development requirements.

[0009] To achieve the above object, the embodiments of the present invention provide the following technical solutions:

[0010] In the first aspect, in an embodiment provided by the present invention, an optimization method for the observation plan based on the uniformity index is provided, and the method includes the following steps:

[0011] S10. Collect and sort out the observation parameters for determining the optimization plan;

[0012] S20. Optimize the design of the observation plan parameters to obtain N optimized observation plans;

[0013] S30. Calculate the noise rejection response values corresponding to the N optimized observation plans;

[0014] S40. Calculate the noise suppression response values corresponding to the N optimized observation plans;

[0015] S50. Based on the noise rejection response values and the noise suppression response values corresponding to the N optimized observation plans, calculate the denoising response values corresponding to the N optimized observation plans;

[0016] S60. Calculate the prestack time migration response values corresponding to the N optimized observation plans;

[0017] S70. Based on the signal-to-noise ratio spectrum and effective high frequency of N optimized observation schemes, and combining with the index requirements of the signal-to-noise ratio and the highest frequency of the target layer, select the final scheme from the N optimized observation schemes.

[0018] As a further solution of the present invention, the observation parameters include: geological task requirement parameters, geophysical parameters, basic parameters of the observation scheme, and development characteristic parameters of regular interference waves.

[0019] As a further solution of the present invention, the method for determining the point-line distance parameters of N optimized observation schemes is as follows:

[0020] On the basis of the already formulated three-dimensional observation scheme, increase the point distance to K times, reduce the line distance to 1 / K times and retain it to one decimal place to strictly make the point-line distance ratio reach 1:(N - 1). While keeping the coverage density, aspect ratio, total number of receiving channels, and array size of the already formulated observation scheme basically the same, use the piecing method to determine the specific value of K and the number of receiving channels per single line, and realize the optimized design of the observation scheme with a point-line distance ratio of 1:(N - 1);

[0021] Repeat the above process to optimize and design N optimized observation schemes with point-line distance ratios of 1:(N - 2), 1:(N - 3)……1:1.

[0022] As a further solution of the present invention, the specific steps for calculating the noise rejection response values corresponding to N optimized observation schemes include:

[0023] S301. Obtain the noise-free original single-shot data of the observation scheme with a point-line distance ratio of 1:N;

[0024] S302. Extract the actual noise according to the previous single-shot data in the work area. According to the shot-receiver distance distribution information of the observation scheme with a point-line distance ratio of 1:N, use the interpolation method to obtain the noise data of the observation scheme with a point-line distance ratio of 1:N, and calculate the single-shot noise energy value;

[0025] S303. Add the obtained noise data of the observation scheme with a point-line distance ratio of 1:N to the forward-modeled noise-free single-shot data to obtain the forward-modeled noisy original single-shot data of the observation scheme with a point-line distance ratio of 1:N;

[0026] S304. Perform noise rejection processing on the forward-modeled noisy original single-shot data by the predictive subtraction method to obtain the single-shot data after noise rejection. There will still be residual noise that has not been rejected in this single-shot data. Subtract the forward-modeled noise-free single-shot data from this single-shot data to obtain the residual noise data, and calculate the residual noise energy value;

[0027] S305. Divide the residual noise energy value by the noise energy value of the observation scheme with a point-line distance ratio of 1:N to obtain the noise rejection response value of the observation scheme with a point-line distance ratio of 1:N;

[0028] S306. Repeat steps S301 - S305 to calculate the noise rejection response values for each optimized observation scheme with a point - line distance ratio of 1:(N - 1), 1:(N - 2),..., 1:1 respectively.

[0029] As a further aspect of the present invention, calculating the noise suppression response values corresponding to N optimized observation schemes includes:

[0030] S401. Optimize the observation scheme parameters according to the point - line distance ratio of 1:N, and arrange the shot points, geophone points, and shot - geophone relationships.

[0031] S402. Select a sub - area within the full - coverage area of the optimized observation scheme with a point - line distance ratio of 1:N. According to the velocity of the target layer in the exploration area, the two - way travel time of the target layer reflection, the noise velocity, the minimum noise frequency, and the maximum noise frequency parameters, calculate the noise suppression response values of all bins within a sub - area of the observation scheme with a point - line distance ratio of 1:N through seismic acquisition design software, and take the average value of the noise suppression responses of all bins within this sub - area as the noise suppression response value of the optimized observation scheme with a point - line distance ratio of 1:N.

[0032] S403. Repeat steps S401 - S402 to calculate the noise suppression response values for each optimized observation scheme with a point - line distance ratio of 1:(N - 1), 1:(N - 2),..., 1:1 respectively.

[0033] As a further aspect of the present invention, calculating the denoising response values corresponding to N optimized observation schemes includes the following steps:

[0034] S501. Convert the obtained noise rejection response value of the optimized observation scheme with a point - line distance ratio of 1:N into a basic logarithmic value.

[0035] S502. Convert the obtained noise suppression response value of the optimized observation scheme with a point - line distance ratio of 1:N into a basic logarithmic value.

[0036] S503. Add the response values obtained in steps S501 and S502 to get the denoising response decibel value of the optimized observation scheme with a point - line distance ratio of 1:N, and then convert it into an energy value.

[0037] S504. Repeat steps S501 - S503 to calculate the denoising response values for the remaining optimized observation schemes with a point - line distance ratio of 1:(N - 1), 1:(N - 2),..., 1:1 respectively.

[0038] As a further aspect of the present invention, calculating the prestack time migration response values corresponding to N optimized observation schemes includes the following steps:

[0039] S601. Select the layout results and their sub - area ranges of the optimized observation scheme with a point - line distance ratio of 1:N;

[0040] S602. According to the velocity of the target layer, the main frequency of the target layer, the burial depth of the target layer, the dip angle of the target layer, the sampling interval, and the recording length parameters in the exploration area, calculate the pre - stack time migration response values of all bins in the sub - area of the optimized observation scheme with a point - line distance ratio of 1:N through seismic acquisition design software, and take the mean value of the pre - stack time migration response values of all bins in the sub - area as the pre - stack time migration response value of the observation scheme with a point - line distance ratio of 1:N;

[0041] S603. Repeat steps S601 - S602, and calculate the pre - stack time migration response values of the optimized observation schemes with point - line distance ratios of 1:(N - 1), 1:(N - 2),..., 1:1 respectively.

[0042] As a further scheme of the present invention, based on the signal - to - noise ratio spectra and effective high frequencies of N optimized observation schemes, combined with the index requirements of the signal - to - noise ratio and the highest frequency of the target layer, select the final scheme from the N optimized observation schemes, including the following steps:

[0043] Calculate the signal - to - noise ratio spectra of each optimized observation scheme;

[0044] Calculate the effective high frequencies of each optimized observation scheme based on the signal - to - noise ratio spectra of each optimized observation scheme;

[0045] Combined with the index requirements of the signal - to - noise ratio and the highest frequency of the target layer, select the final scheme from the N optimized observation schemes.

[0046] As a further scheme of the present invention, the calculation of the signal - to - noise ratio spectra of each optimized observation scheme includes:

[0047] Based on the pre - stack time migration response values and denoising response values of each optimized observation scheme, calculate and obtain the signal - to - noise ratio spectra.

[0048] As a further scheme of the present invention, the combination of the index requirements of the signal - to - noise ratio and the highest frequency of the target layer, and the selection of the final scheme from the N optimized observation schemes includes:

[0049] Let min{·} denote taking the minimum value, m be the serial number of the optimization scheme, n = 1, 2,..., N be the serial numbers of the schemes to be optimized, and assume that the maximum frequency required for the exploration target layer is F d , then the formula for determining the optimization scheme is:

[0050] m = min{k = n, and Fmax n >F d}

[0051] That is, the observation scheme with a point - line distance ratio of 1:(N - m + 1) is the final scheme.

[0052] The technical solution provided by the present invention has the following beneficial effects:

[0053] According to the geological task requirements of the work area and in combination with the requirements of economic and technological integration, the present invention first formulates the parameters of the three-dimensional observation scheme for the exploration area. First, calculate the denoising response value of each observation scheme: according to the noise development characteristics of the exploration area, form the forward simulation noisy original single-shot data of each observation scheme, and calculate the noise rejection response through processing means; then calculate the noise superposition suppression response value, and the sum of the two determines the denoising response value of each observation scheme. Next, calculate the prestack time migration response value of the signal for each observation scheme, that is, the reflected wave energy of the target layer after forward simulation of migration imaging in a homogeneous medium divided by the wavelet energy input in the forward simulation. Finally, using the denoising response value and the prestack time migration imaging response value, through formula calculation, obtain the signal-to-noise ratio spectrum corresponding to each observation scheme, calculate the effective high frequency according to the signal-to-noise ratio spectrum threshold, and finally optimize and determine one of the observation schemes by comparing the effective high frequency of each scheme with the highest frequency required for the exploration target layer. The present invention forms an observation scheme optimization method based on the uniformity index, laying a good raw data foundation for obtaining higher-quality seismic data.

[0054] These aspects or other aspects of the present invention will be more clearly understood in the following description of the embodiments. It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or in the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other embodiments can be obtained based on these drawings without creative efforts.

[0056] Figure 1 It is a flowchart of the observation scheme optimization method based on the uniformity index for an embodiment of the present invention.

[0057] Figure 2 It is the original single-shot record diagram of the interference wave development in the work area.

[0058] Figure 3 It is the interference wave frequency spectrum analysis diagram of the work area.

[0059] Figure 4 It is the three-dimensional flat-layer geological model diagram of the work area.

[0060] Figure 5 It is the process diagram of forming the forward simulation noisy original single-shot data of the observation scheme with a point-line distance ratio of 1:10.

[0061] Figure 6 This is the flowchart for noise rejection processing of the 1:10 point-line distance ratio observation scheme.

[0062] Figure 7 This is the layout diagram of shot points and receiving points for the 1:10 point-line distance ratio observation scheme.

[0063] Figure 8 These are the signal-to-noise ratio spectrograms of each scheme.

[0064] Figure 9 These are the curves showing the relationship between the uniformity and effective high frequency of each scheme when the signal-to-noise ratio is the threshold value of 4. Specific implementation manners

[0065] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0066] The flowchart shown in the accompanying drawings is only an example illustration, and does not necessarily include all the contents and operations / steps, nor does it necessarily need to be executed in the described order. For example, some operations / steps can also be decomposed, combined, or partially merged. Therefore, the actual execution order may be changed according to the actual situation.

[0067] It should be understood that the terms used in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the specification of the present invention and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an", and "the" are intended to include the plural forms.

[0068] Specifically, the embodiments of the present invention will be further described below in conjunction with the accompanying drawings.

[0069] Please refer to Figure 1 , Figure 1 This is the flowchart of an observation scheme optimization method based on the uniformity index provided by the embodiments of the present invention. As Figure 1 shown, the observation scheme optimization method based on the uniformity index includes steps S10 to S70.

[0070] S10. Collect and organize the observation parameters for determining the optimization scheme.

[0071] In the embodiments of the present invention, the observation parameters include: geological task requirement parameters, geophysical parameters, basic parameters of the observation scheme, and development characteristics parameters of regular interference waves.

[0072] In an embodiment of the present invention, the geological task requirement parameters include: the signal-to-noise ratio required for accurate imaging of the exploration target, the required dominant frequency, and the required minimum and maximum frequencies.

[0073] The geophysical parameters include: the two-way travel time of the reflection of the target layer, the burial depth of the target layer, the interval velocity of the target layer, the dominant frequency of the target layer, the dip angle of the target layer, and the absorption attenuation quality factor of the target layer.

[0074] The basic parameters of the observation scheme include: the fold, the coverage density, the number of receiving channels per single line, the total number of receiving channels, the longitudinal array length, the maximum non-longitudinal offset, the size of the array patch, and the aspect ratio.

[0075] The development characteristic parameters of the regular interference waves include: the velocity of the interference waves, the dominant frequency of the interference waves, the minimum interference frequency of the interference waves, and the maximum interference frequency of the interference waves.

[0076] S20. Optimize the parameters of the observation scheme to obtain N optimized observation schemes;

[0077] It should be noted that the optimization design of the parameters of the observation scheme to obtain N optimized observation schemes is specifically to keep the coverage density, the number of receiving channels, the aspect ratio, and the size of the array patch of the already formulated three-dimensional observation scheme basically the same, and realize the optimization design of the observation scheme by changing the parameters of the trace interval, the receiver line interval, the shot point interval, the shot line interval, and the number of receiving channels per single line. Assume that the point-line distance ratio of the already formulated three-dimensional observation scheme is 1:N, where N is a natural number greater than 1. Then the point-line distance ratios of the optimized observation schemes are 1:(N - 1), 1:(N - 2),..., 1:1 respectively. Together with the already formulated three-dimensional observation scheme with a point-line distance ratio of 1:N, there are a total of N optimized observation schemes.

[0078] Among them, the method for determining the point-line distance parameters of the N optimized observation schemes is as follows:

[0079] On the basis of the already formulated three-dimensional observation scheme, increase the point distance to K times, reduce the line distance to 1 / K times and retain it to one decimal place to strictly make the point-line distance ratio reach 1:(N - 1). While keeping the coverage density, the aspect ratio, the total number of receiving channels, and the size of the array patch basically the same as the already formulated observation scheme, use the patchwork method to determine the specific value of K and the number of receiving channels per single line, and realize the optimization design of the observation scheme with a point-line distance ratio of 1:(N - 1).

[0080] Repeat the above process to optimize and design N optimized observation schemes with point-line distance ratios of 1:(N - 2), 1:(N - 3),..., 1:1.

[0081] S30. Calculate the noise rejection response values corresponding to the N optimized observation schemes.

[0082] It should be noted that the noise rejection response value refers to the ratio of the residual noise energy to the original noise energy after denoising the original noisy forward single-shot data by the predictive subtraction method.

[0083] In the embodiment of the present invention, the specific steps for calculating the noise rejection response values corresponding to N optimized observation schemes include:

[0084] S301. Obtain the noise-free original single-shot data of the 1:N optimized observation scheme of the point-line distance ratio.

[0085] Among them, obtaining the noise-free original single-shot data of the 1:N optimized observation scheme of the point-line distance ratio includes:

[0086] According to the burial depth and velocity information of the main exploration target layer, establish a flat-layer three-dimensional geological model. The range of the flat-layer three-dimensional geological model only needs to be more than 1.5 times the range of the arranged patch of the proposed observation scheme. Adopt the proposed observation scheme, perform acoustic single-shot forward modeling according to the main frequency parameter of the target layer, and perform 1 shot of forward modeling at the middle position of the flat-layer three-dimensional geological model to form the noise-free original single-shot data of the 1:N optimized observation scheme of the point-line distance ratio.

[0087] S302. Extract the actual noise according to the previous single-shot data in the work area. According to the shot-receiver distance distribution information of the 1:N optimized observation scheme of the point-line distance ratio, use the interpolation method to obtain the noise data of the 1:N optimized observation scheme of the point-line distance ratio, and calculate the single-shot noise energy value.

[0088] S303. Add the obtained noise data of the 1:N optimized observation scheme of the point-line distance ratio to the forward modeled noise-free single-shot data to obtain the forward modeled noisy original single-shot data of the 1:N optimized observation scheme of the point-line distance ratio.

[0089] S304. Perform noise rejection processing on the forward modeled noisy original single-shot data by the predictive subtraction method to obtain the single-shot data after noise rejection. There will still be residual noise that has not been rejected in this single-shot data. Subtract the forward modeled noise-free single-shot data from this single-shot data to obtain the residual noise data, and calculate the residual noise energy value.

[0090] S305. Divide the residual noise energy value by the noise energy value of the 1:N optimized observation scheme of the point-line distance ratio to obtain the noise rejection response value of the 1:N optimized observation scheme of the point-line distance ratio.

[0091] S306. Repeat steps S301 to S305 to calculate the noise rejection response values of each optimized observation scheme with the point-line distance ratios of 1:(N - 1), 1:(N - 2),..., 1:1 respectively.

[0092] S307. Denote the noise rejection response values of each scheme with the point-line distance ratios of 1:N, 1:(N - 1), 1:(N - 2),..., 1:1 as RA1, RA2,..., RAN This is for convenient description.

[0093] S40. Calculate the noise suppression response values corresponding to N optimized observation schemes.

[0094] It should be noted that the noise suppression response refers to the noise energy after multiple stackings divided by the noise energy before stacking. The noise suppression response values are obtained by calculation using seismic acquisition design software.

[0095] In the embodiment of the present invention, the calculation of the noise suppression response values corresponding to N optimized observation schemes includes:

[0096] S401. Optimize the observation scheme parameters according to the point-line distance ratio of 1:N, and arrange the shot points, geophone points, and shot-geophone relationships.

[0097] It should be noted that the arrangement of the shot points, geophone points, and shot-geophone relationships can be carried out through seismic acquisition design software.

[0098] S402. Select a sub-region range within the full-coverage area of the optimized observation scheme with a point-line distance ratio of 1:N. According to the parameters of the target layer velocity, two-way travel time of the target layer reflection, noise velocity, minimum noise frequency, and maximum noise frequency in the exploration area, calculate the noise suppression response values of all bins within a sub-region of the observation scheme with a point-line distance ratio of 1:N through seismic acquisition design software, and take the average value of the noise suppression responses of all bins within the sub-region as the noise suppression response value of the optimized observation scheme with a point-line distance ratio of 1:N.

[0099] S403. Repeat steps S401 to S402, and calculate the noise suppression response values of the optimized observation schemes with point-line distance ratios of 1:(N - 1), 1:(N - 2),..., 1:1 respectively.

[0100] S404. For convenient subsequent description, denote the noise suppression response values of the optimized observation schemes with point-line distance ratios of 1:N, 1:(N - 1), 1:(N - 2),..., 1:1 as RS1, RS2,..., RS respectively. N .

[0101] S50. Based on the noise rejection response values and noise suppression response values corresponding to N optimized observation schemes, calculate the denoising response values corresponding to N optimized observation schemes.

[0102] It should be noted that the denoising response value (R) is the sum of the noise rejection response value and the noise suppression response value.

[0103] In the embodiment of the present invention, the calculation of the denoising response values corresponding to N optimized observation schemes includes the following steps:

[0104] S501. Convert the obtained point-line distance ratio 1:N optimized observation scheme noise rejection response value into a basic logarithmic value, with the unit of decibel, i.e.:

[0105] RAD1 = 10 log(RA1) (1)

[0106] S502. Convert the obtained point-line distance ratio 1:N optimized observation scheme noise suppression response value into a basic logarithmic value, with the unit of decibel, i.e.:

[0107] RSD1 = 10 log(RS1) (2)

[0108] S503. Add the response values obtained in steps S501 and S502 to get the denoising response decibel value of the point-line distance ratio 1:N optimized observation scheme, and then convert it into an energy value, i.e.:

[0109] R1 = 10 ^ (RAD1 + RSD1) (3)

[0110] S504. Repeat steps S501 - S503, and calculate the denoising response values (R2, R3... R N ) for the remaining optimized observation schemes with point-line distance ratios of 1:(N - 1), 1:(N - 2)... 1:1 respectively.

[0111] S60. Calculate the pre-stack time migration response values corresponding to N optimized observation schemes.

[0112] It should be noted that the pre-stack time migration response value (P) refers to the energy of the reflected wave of the target layer after forward modeling of migration imaging in a homogeneous medium divided by the energy of the wavelet input in the forward modeling.

[0113] In the embodiment of the present invention, the calculation of the pre-stack time migration response values corresponding to N optimized observation schemes includes the following steps:

[0114] S601. Select the layout results of the point-line distance ratio 1:N optimized observation scheme and its sub-region range;

[0115] S602. According to the velocity of the target layer, the main frequency of the target layer, the burial depth of the target layer, the dip angle of the target layer, the sampling interval, and the recording length parameters in the exploration area, calculate the pre-stack time migration response values of all bins in the sub-region of the point-line distance ratio 1:N optimized observation scheme through seismic acquisition design software, and take the average value of the pre-stack time migration response values of all bins in the sub-region as the pre-stack time migration response value P1 of the point-line distance ratio 1:N observation scheme;

[0116] S603. Repeat steps S601 - S602, and calculate the pre-stack time migration response values (P2, P3... P N)。

[0117] S70. Based on the signal-to-noise ratio spectrum and effective high frequency of N optimized observation schemes, combined with the index requirements of the signal-to-noise ratio and the highest frequency of the target layer, select the final scheme from the N optimized observation schemes.

[0118] The step of selecting the final scheme from the N optimized observation schemes based on the signal-to-noise ratio spectrum and effective high frequency of the N optimized observation schemes, combined with the index requirements of the signal-to-noise ratio and the highest frequency of the target layer, includes the following steps:

[0119] S701. Calculation of the signal-to-noise ratio spectrum. The signal-to-noise ratio spectrum refers to the signal-to-noise ratio varying with frequency. Based on the pre-stack time migration response value (P1) of the 1:N observation scheme of the point-line distance ratio and the noise reduction response value (R1) of the 1:N observation scheme of the point-line distance ratio.

[0120] Denote the signal-to-noise ratio spectrum of the 1:N observation scheme of the point-line distance ratio as SNR1(f), then:

[0121]

[0122] In the formula, Q represents the absorption attenuation quality factor of the exploration target layer; T0 represents the two-way travel time of the reflection of the exploration target layer; π represents the pi; f is the frequency, and its value is f = [f min , f max , f min ~f max The range includes the lowest frequency and the highest frequency required for the exploration target layer.

[0123] S702. Calculation of the effective high frequency. The effective high frequency refers to the highest frequency corresponding to the signal-to-noise ratio spectrum greater than the threshold. This threshold is equal to the lowest signal-to-noise ratio required for the exploration target layer. Assume that the lowest signal-to-noise ratio required for the exploration target layer is SNR min , denote the inverse function of the signal-to-noise ratio spectrum SNR1(f) as Denote max{·} as taking the maximum value, then the effective high frequency Fmax1 is:

[0124]

[0125] S703. Repeat steps S701 to S702, and calculate the signal-to-noise ratio spectra (SNR2(f), SNR3(f)... SNR N (f)) and the effective high frequency values (Fmax2, Fmax3... Fmax N ) for each of the schemes with point-line distance ratios of 1:(N - 1), 1:(N - 2)... 1:1 respectively.

[0126] S704. Determine the optimization plan. Let min{·} denote taking the minimum value, m be the serial number of the optimization plan, and n = 1, 2... N be the serial numbers of the plans to be optimized. Assume that the maximum frequency required for the exploration target layer is F d , then the formula for determining the optimization plan is:

[0127] m = min{k = n, and Fmax n > F d}} (6)

[0128] That is, the observation plan with a point-line distance ratio of 1:(N - m + 1) is the final plan.

[0129] According to the geological task requirements of the work area and combined with the requirements of economic and technological integration, the present invention first formulates the parameters of the 3D observation plan for the exploration area. On the basis of formulating the observation plan, several observation plans with basically the same coverage density, number of receiving channels, aspect ratio, and size of the arrangement patch but different uniformities (different point-line distance ratios) are optimized and designed. First, calculate the noise reduction response value of each observation plan: According to the noise development characteristics of the exploration area, form the forward simulation noisy original single-shot data of each observation plan, and calculate the noise elimination response through processing means; then calculate the noise superposition suppression response value, and the sum of the two determines the noise reduction response value of each observation plan. Next, calculate the signal pre-stack time migration response value of each observation plan, that is, the reflected wave energy of the target layer after forward simulation of migration imaging in a homogeneous medium divided by the wavelet energy input by forward simulation. Finally, using the noise reduction response value and the pre-stack time migration imaging response value, through formula calculation, obtain the signal-to-noise ratio spectrum corresponding to each observation plan, calculate the effective high frequency according to the signal-to-noise ratio spectrum threshold, and optimize and determine one of the observation plans through the comparison and selection of the effective high frequency of each plan and the highest frequency required for the exploration target layer.

[0130] The present invention mainly optimizes and designs the point spacing, line spacing, and number of single-line receiving channels on the basis of determining the coverage density, number of receiving channels, size of the arrangement patch, and aspect ratio of the observation plan, and determines a more suitable observation plan for geological task requirements through optimization and selection. The present invention has been applied in the 3D seismic acquisition project in the Junggar Basin in western China.

[0131] Embodiment

[0132] The following takes a 3D work area in the Junggar Basin as an example to illustrate the implementation steps and realization methods of the present invention:

[0133] 1. The geological task requirements, geophysical parameters, basic parameters of the observation plan, and development characteristics of regular interference waves in the work area are as follows:

[0134] 1) Geological task requirements

[0135] The surface of this work area is mainly gobi saline-alkali land. The geological task requires precise imaging of the Permian 15m reservoir for seismic data. According to this requirement, the signal-to-noise ratio of the target layer result profile should reach at least 4, and the highest frequency should reach 75Hz.

[0136] 2) Geophysical parameters

[0137] Collect and sort out the geophysical parameters of the exploration target layer in the work area, as shown in Table 1.

[0138] Table 1 Geophysical parameter table of the exploration target layer in the work area

[0139]

[0140] 3) Basic parameters of the observation scheme

[0141] The work area adopts high-density 3D observation. The parameters of the proposed observation scheme are shown in Table 2. This observation scheme is very intensive, but the uniformity (point-line distance ratio) is only 1:10, which is relatively poor. On the premise of keeping the coverage density, array size, number of receiving channels, and transverse-longitudinal ratio basically unchanged, optimize the design of the point distance, line distance, and number of receiving channels per single line.

[0142] Table 2 Observation system parameter table of the work area

[0143]

[0144]

[0145] 4) Development characteristic parameters of regular interference waves

[0146] There are mainly two groups of refraction waves and two groups of surface waves developed in the regular interference waves in the work area, both of which are linear interferences. See Figure 2 、 Figure 3 for details. Extract the characteristic parameters of each interference wave, as shown in Table 3.

[0147] Figure 2 Original single-shot record of the development of interference waves in the work area. The blue line segment in the figure is refraction interference, and the red line segment is surface wave interference; the numerical value in the green box represents the velocity of the interference wave.

[0148] Such as Figure 3 Spectrum analysis of interference waves in the work area. In the figure, a is the spectrum analysis of the first group of refraction waves; b is the spectrum analysis of the second group of refraction waves; c is the spectrum analysis of the first group of surface waves; d is the spectrum analysis of the second group of surface waves.

[0149] Table 3 Characteristic parameter table of regular interference waves in the work area

[0150]

[0151] 2. Optimization design of observation scheme parameters

[0152] According to the parameters of the observation plan already drawn up for this 3D acquisition, the point-line distance ratio is 1:10. Under the condition that the coverage density, arrangement length, number of receiving channels, and transverse-longitudinal ratio remain basically unchanged, by changing the parameters of the point distance, line distance, and number of receiving channels per single line, observation plans with point-line distance ratios of 1:9, 1:8... 1:2, and 1:1 are designed respectively. Together with the already drawn up observation plan, there are a total of 10 plans, as shown in Table 4 for details.

[0153] Table 4 Parameter Design Table for Different Uniformity Observation Plans

[0154]

[0155]

[0156]

[0157]

[0158] 3. Calculation of Noise Rejection Response Value

[0159] (1) Establish a 3D flat-layer geological model with the buried depth of the exploration target layer being 4250 m and the layer velocity being 4500 m / s. The model is 20 km long, 15 km wide, and 4.5 km high, as shown in Figure 4 . Conduct a single-shot forward modeling at the middle position of the model using the observation plan with a point-line distance ratio of 1:10 to form the noise-free forward modeling single-shot original data of the observation plan with a point-line distance ratio of 1:10.

[0160] Such as Figure 4 3D flat-layer geological model of the work area. The green layer in the figure is the ground surface; the red layer in the figure is the exploration target layer.

[0161] (2) According to the previous single-shot data in the work area, extract the actual regular noise through the processing software system. According to the shot-receiver distance distribution information of the observation plan with a point-line distance ratio of 1:10, obtain the noise data of the observation plan with a point-line distance ratio of 1:10 using the interpolation method, and calculate the single-shot noise energy value.

[0162] (3) Add the obtained noise data of the observation plan with a point-line distance ratio of 1:10 to the forward-modeled noise-free single-shot data through the processing system to obtain the forward-modeled noisy original single-shot data of the observation plan with a point-line distance ratio of 1:10, as shown in Figure 5 .

[0163] Figure 5 Formation process of the forward-modeled noisy original single-shot data of the observation plan with a point-line distance ratio of 1:10. In the figure, the left figure is the forward-modeled noise-free 3D original single-shot data; the middle figure is the regular interference noise data of the work area; the right figure is the formed 3D original noisy single-shot data.

[0164] (4) The forward noisy original single-shot data is processed by the prediction subtraction method of the processing system to obtain the single-shot data after noise rejection, as shown in Figure 6 , there will still be residual noise that has not been removed in this data. Use this data to subtract the forward noise-free single-shot data to obtain the residual noise data, and calculate the residual noise energy value.

[0165] Figure 6 Noise rejection processing flow for the observation scheme with a point-line distance ratio of 1:10. In the left figure of the figure is the forward-simulated noisy three-dimensional original single-shot data; the middle figure is the single-shot data after noise rejection; the right figure is the removed noise data.

[0166] (5) Divide the residual noise energy value in (4) by the noise energy value of the observation scheme with a point-line distance ratio of 1:10 in (2) to obtain the noise rejection response value of the observation scheme with a point-line distance ratio of 1:10.

[0167] (6) Repeat the above steps to calculate the noise rejection response values for each scheme with point-line distance ratios of 1:9, 1:8... 1:1 respectively. The noise rejection response values for each scheme are shown in Table 5.

[0168] Table 5 Noise rejection response values for each observation scheme

[0169] Observation plan Noise rejection response value (energy ratio) Dot-line distance ratio 1:10 <![CDATA[RA1 = 0.4182261503]]> Dot-line distance ratio 1:9 <![CDATA[RA2 = 0.3186554265]]> Dot-line distance ratio 1:8 <![CDATA[RA3 = 0.2492867631 <!-- 14 -->]]> Dot-line distance ratio 1:7 <![CDATA[RA4 = 0.2150316122]]> Dot-line distance ratio 1:6 <![CDATA[RA5 = 0.1867314992]]> Dot-line distance ratio 1:5 <![CDATA[RA6 = 0.1610811806]]> Dot-line distance ratio 1:4 <![CDATA[RA7 = 0.1528265364]]> Dot-line distance ratio 1:3 <![CDATA[RA8 = 0.1614153162]]> Dot-line distance ratio 1:2 <![CDATA[RA9 = 0.1525009230]]> Dot-line distance ratio 1:1 <![CDATA[RS 10 = 0.1474213272]]>

[0170] 4. Calculation of noise suppression response value

[0171] (1) For the observation scheme with a point-line distance ratio of 1:10, use seismic acquisition design software to arrange the shot points, geophone points, and shot-geophone relationships, as shown in Figure 7 .

[0172] Figure 7 Shot-geophone layout diagram (partial) for the observation scheme with a point-line distance ratio of 1:10. The red dots in the figure represent the shot points; the blue dots in the figure represent the geophone points.

[0173] (2) Select a sub-region within the full-coverage area of the observation scheme with a point-line distance ratio of 1:10. According to the target layer velocity of 4500 m / s in the exploration area, the two-way travel time of the target layer reflection of 2.56 s, the noise velocities of 1807 m / s, 2725 m / s, 316 m / s, and 625 m / s, the minimum noise interference frequency of 3 Hz, and the maximum noise interference frequency of 30 Hz, calculate the noise suppression response values of all bins within a sub-region of the observation scheme with a point-line distance ratio of 1:10 through seismic acquisition design software, and take the average of the noise suppression responses of all bins within this sub-region as the noise suppression response value of the observation scheme with a point-line distance ratio of 1:10.

[0174] (3) Repeat the above steps to calculate the noise suppression response values for each scheme with point-line distance ratios of 1:9, 1:8... 1:1 respectively. The noise rejection response values for each scheme are shown in Table 6.

[0175] Table 6 Noise suppression response values of each observation scheme

[0176] Observation plan Noise suppression response value (energy ratio) Dot-line distance ratio 1:10 <![CDATA[RS1 = 0.0004847032]]> Dot-line distance ratio 1:9 <![CDATA[RS2 = 0.0005422143]]> Dot-line distance ratio 1:8 <![CDATA[RS3 = 0.0006005158]]> Dot-line distance ratio 1:7 <![CDATA[RS4 = 0.0005779158]]> Dot-line distance ratio 1:6 <![CDATA[RS5 = 0.0006056094]]> Dot-line distance ratio 1:5 <![CDATA[RS6 = 0.0006811547]]> Dot-line distance ratio 1:4 <![CDATA[RS7 = 0.0004822127]]> Dot-line distance ratio 1:3 <![CDATA[RS8 = 0.0003339134]]> Dot-line distance ratio 1:2 <![CDATA[RS9 = 0.0001884040]]> Dot-line distance ratio 1:1 <![CDATA[RS 10 = 0.0000812892]]>

[0177] 5. Calculation of denoising response value

[0178] Convert the noise rejection response value in 3 and the noise suppression response value in 4 into basic logarithmic values respectively, and add the two for the same scheme to obtain the denoising response value of this scheme. The unit is decibel. For subsequent calculation, convert the decibel value of the denoising effect into an energy value, as shown in Table 7.

[0179] Table 7 Noise rejection response values of each observation scheme

[0180]

[0181]

[0182] 6. Calculation of pre-stack time migration response value

[0183] (1) Select the layout results and their sub-region ranges of the 1:10 observation scheme in 4.

[0184] (2) According to the target layer velocity of 4500 m / s, the target layer main frequency of 53 Hz, the target layer burial depth of 4250 m, the target layer dip angle of 8°, the sampling interval of 2 ms and the recording length of 6 s in the exploration area, calculate the pre-stack time migration response values of all bins in the sub-region of the 1:10 observation scheme with the point-line distance ratio through the seismic acquisition design software, and take the mean value of the pre-stack time migration response values of all bins in this sub-region as the pre-stack time migration response value of the 1:10 observation scheme with the point-line distance ratio.

[0185] (3) Repeat the above steps to calculate the pre-stack time migration response values of each scheme with the point-line distance ratios of 1:9, 1:8... 1:1 respectively, as shown in Table 8.

[0186] Table 8 Pre-stack time migration response values of each observation scheme

[0187] Observation plan Pre-stack time migration response value Dot-line distance ratio 1:10 <![CDATA[P1 = 4.76474]]> Dot-line distance ratio 1:9 <![CDATA[P2 = 4.76022]]> Dot-line distance ratio 1:8 <![CDATA[P3 = 4.77110]]> Dot-line distance ratio 1:7 <![CDATA[P4 = 4.76250]]> Dot-line distance ratio 1:6 <![CDATA[P5 = 4.77281]]> Dot-line distance ratio 1:5 <![CDATA[P6 = 4.77040]]> Dot-line distance ratio 1:4 <![CDATA[P7 = 4.76114]]> Dot-line distance ratio 1:3 <![CDATA[P8 = 4.77660]]> Dot-line distance ratio 1:2 <![CDATA[P9 = 4.77263]]> Dot-line distance ratio 1:1 <![CDATA[P 10 = 4.76425]]>

[0188] 7. Determine the optimized observation scheme

[0189] (1) Calculation of signal-to-noise ratio spectrum. According to the pre-stack time migration response value of the 1:10 observation scheme with the point-line distance ratio in 6 and the denoising response value in 5. Q is taken as 58.1; T0 is taken as 2.56 s; f min is taken as 60 Hz; f max is taken as 120 Hz, calculate the signal-to-noise ratio spectrum values of each scheme, and draw the signal-to-noise ratio spectrum diagrams of 10 schemes with the point-line distance ratios of 1:10, 1:9... 1:2, 1:1 according to the calculation results, as shown inFigure 8 。

[0190] Figure 8 The signal-to-noise ratio spectrograms of each scheme. The abscissa is the frequency, and the ordinate is the newly created ratio. The different color curves in the figure represent the signal-to-noise ratio spectrograms of different observation schemes with different point-line distance ratios, a total of 10.

[0191] (2) Effective high-frequency calculation. Select the signal-to-noise ratio threshold of the work area as 4, calculate the effective high-frequency values of each scheme, as shown in Table 9, and draw a curve of the relationship between uniformity and effective high-frequency, as shown in Figure 9 。

[0192] Table 9 Effective high-frequency values of each observation scheme

[0193] Observation plan Effective high-frequency value Dot-line distance ratio 1:10 <![CDATA[Fmax1 = 66]]> Dot-line distance ratio 1:9 <![CDATA[Fmax2 = 68]]> Dot-line distance ratio 1:8 <![CDATA[Fmax3 = 70]]> Dot-line distance ratio 1:7 <![CDATA[Fmax4 = 71]]> Dot-line distance ratio 1:6 <![CDATA[Fmax5 = 72]]> Dot-line distance ratio 1:5 <![CDATA[Fmax6 = 74]]> Dot-line distance ratio 1:4 <![CDATA[Fmax7 = 76]]> Dot-line distance ratio 1:3 <![CDATA[Fmax8 = 79]]> Dot-line distance ratio 1:2 <![CDATA[Fmax9 = 82]]> Dot-line distance ratio 1:1 <![CDATA[Fmax 10 = 90]]>

[0194] Figure 9 Curve of the relationship between uniformity and effective high-frequency of each scheme when the signal-to-noise ratio is the threshold 4. The abscissa is the point-line distance ratio, and the ordinate is the effective high-frequency value.

[0195] (3) Determine the optimized scheme. The maximum frequency required for the exploration target layer is F d is 75 Hz. According to the calculation results of the effective high-frequency of each scheme, determine that m = 7, that is, Scheme 7 is the final optimized scheme, an observation scheme with a point-line distance ratio of 1:4. The specific parameters of this scheme are shown in Table 10.

[0196] Table 10 Parameter table of the finally determined optimized observation scheme in the work area

[0197]

[0198]

[0199] It should be understood that although the above is described in a certain order, these steps are not necessarily executed in the above order. Unless there is a clear description in this article, the execution of these steps has no strict order limit, and these steps can be executed in other orders. Moreover, a part of the steps in this embodiment may include multiple steps or multiple stages. These steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be executed alternately or alternately with at least a part of other steps or steps or stages in other steps.

[0200] Those of ordinary skill in the art should understand that the discussion of any of the above embodiments is merely exemplary and is not intended to imply that the scope of the disclosure of the embodiments of the present invention (including the claims) is limited to these examples; under the concept of the embodiments of the present invention, the technical features in the above embodiments or different embodiments can also be combined, and there are many other variations in different aspects of the embodiments of the present invention as described above, which are not provided in detail for the sake of brevity. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the embodiments of the present invention shall be included within the scope of protection of the embodiments of the present invention.

Claims

1. An optimization method for an observation scheme based on a uniformity index, characterized in that, The method includes: S10. Collect and organize the observation parameters for determining the optimization plan; S20. Optimize the design of the observation plan parameters to obtain N optimized observation plans; S30. Calculate the noise rejection response values corresponding to the N optimized observation plans; S40. Calculate the noise suppression response values corresponding to the N optimized observation plans; S50. Based on the noise rejection response values and noise suppression response values corresponding to the N optimized observation plans, calculate the denoising response values corresponding to the N optimized observation plans; S60. Calculate the prestack time migration response values corresponding to the N optimized observation plans; S70. Based on the signal-to-noise ratio spectrum and effective high frequency of the N optimized observation plans, combined with the signal-to-noise ratio and highest frequency index requirements of the target layer, select the final plan from the N optimized observation plans.

2. The optimization method of the observation scheme based on the uniformity index according to claim 1, wherein The observation parameters include: geological task requirement parameters, geophysical parameters, basic observation plan parameters, and regular interference wave development characteristic parameters.

3. The optimization method of the observation scheme based on the uniformity index according to claim 2, characterized in that The method for determining the point-line distance parameters of the N optimized observation plans is as follows: On the basis of the already formulated three-dimensional observation plan, by increasing the point distance to K times, reducing the line distance to 1 / K times and retaining it to one decimal place to strictly make the point-line distance ratio reach 1:(N - 1), and keeping the coverage density, aspect ratio, total number of receiving channels, and array size basically the same as those of the already formulated observation plan, use the piecing method to determine the specific value of K and the number of receiving channels per single line, and realize the optimized design of the observation plan with a point-line distance ratio of 1:(N - 1); Repeat the above process to optimize and design N optimized observation plans with point-line distance ratios of 1:(N - 2), 1:(N - 3),..., 1:

1.

4. The optimization method of the observation scheme based on the uniformity index according to claim 3, wherein The specific steps for calculating the noise rejection response values corresponding to the N optimized observation plans include: S301. Obtain the noise-free original single-shot data of the optimized observation plan with a point-line distance ratio of 1:N; S302. Extract the actual noise according to the single-shot data of the work area in the past, and according to the shot-receiver distance distribution information of the optimized observation plan with a point-line distance ratio of 1:N, use the interpolation method to obtain the noise data of the optimized observation plan with a point-line distance ratio of 1:N, and calculate the single-shot noise energy value; S303. Add the obtained noise data of the optimized observation plan with a point-line distance ratio of 1:N to the forward-modeled noise-free single-shot data to obtain the forward-modeled noisy original single-shot data of the optimized observation plan with a point-line distance ratio of 1:N; S304. Perform noise rejection processing on the forward-modeled noisy original single-shot data by the prediction subtraction method to obtain the single-shot data after noise rejection, where the single-shot data contains the remaining noise that has not been rejected. Use this single-shot data to subtract the forward-modeled noise-free single-shot data to obtain the remaining noise data, and calculate the remaining noise energy value; S305. Divide the remaining noise energy value by the noise energy value of the optimized observation plan with a point-line distance ratio of 1:N to obtain the noise rejection response value of the optimized observation plan with a point-line distance ratio of 1:N; S306. Repeat steps S301 - S305 to calculate the noise rejection response values of each optimized observation plan with point-line distance ratios of 1:(N - 1), 1:(N - 2),..., 1:1 respectively.

5. The optimization method of the observation scheme based on the uniformity index according to claim 4, characterized in that The calculation of the noise suppression response values corresponding to the N optimized observation plans includes: S401. Optimize the parameters of the observation scheme according to the point-line distance ratio of 1:N, and arrange the shot points, geophone points, and shot-geophone relationships; S402. Select a sub-region within the full-coverage area of the observation scheme optimized with the point-line distance ratio of 1:N. According to the parameters of the target layer velocity, two-way travel time of the target layer reflection, noise velocity, minimum noise frequency, and maximum noise frequency in the exploration area, calculate the noise suppression response values of all bins in a sub-region of the observation scheme with the point-line distance ratio of 1:N through seismic acquisition design software, and take the average value of the noise suppression responses of all bins in this sub-region as the noise suppression response value of the observation scheme optimized with the point-line distance ratio of 1:N; S403. Repeat steps S401 - S402, and calculate the noise suppression response values of the optimized observation schemes with point-line distance ratios of 1:(N - 1), 1:(N - 2),..., 1:1 respectively.

6. The optimization method of the observation scheme based on the uniformity index according to claim 5, characterized in that The calculation of the denoising response values corresponding to N optimized observation schemes includes the following steps: S501. Convert the obtained noise rejection response value of the observation scheme optimized with the point-line distance ratio of 1:N into a basic logarithmic value; S502. Convert the obtained noise suppression response value of the observation scheme optimized with the point-line distance ratio of 1:N into a basic logarithmic value; S503. Add the response values obtained in steps S501 and S502 to get the denoising response decibel value of the observation scheme optimized with the point-line distance ratio of 1:N, and then convert it into an energy value; S504. Repeat steps S501 - S503, and calculate the denoising response values of the remaining optimized observation schemes with point-line distance ratios of 1:(N - 1), 1:(N - 2),..., 1:1 respectively.

7. The method for optimizing an observation scheme based on a uniformity index according to claim 6, wherein The calculation of the prestack time migration response values corresponding to N optimized observation schemes includes the following steps: S601. Select the layout results and sub-region range of the observation scheme optimized with the point-line distance ratio of 1:N; S602. According to the parameters of the target layer velocity, dominant frequency of the target layer, burial depth of the target layer, dip angle of the target layer, sampling interval, and recording length in the exploration area, calculate the prestack time migration response values of all bins in the sub-region of the observation scheme optimized with the point-line distance ratio of 1:N through seismic acquisition design software, and take the average value of the prestack time migration response values of all bins in this sub-region as the prestack time migration response value of the observation scheme with the point-line distance ratio of 1:N; S603. Repeat steps S601 - S602, and calculate the prestack time migration response values of the optimized observation schemes with point-line distance ratios of 1:(N - 1), 1:(N - 2),..., 1:1 respectively.

8. The optimization method of the observation scheme based on the uniformity index according to claim 7, characterized in that The selection of the final scheme from N optimized observation schemes based on the signal-to-noise ratio spectrum and effective high frequency of N optimized observation schemes, combined with the index requirements of the signal-to-noise ratio and the highest frequency of the target layer, includes the following steps: Calculate the signal-to-noise ratio spectrum of each optimized observation scheme; Calculate the effective high frequency of each optimized observation scheme based on the signal-to-noise ratio spectrum of each optimized observation scheme; Combined with the index requirements of the signal-to-noise ratio and the highest frequency of the target layer, select the final scheme from N optimized observation schemes.

9. The method for optimizing the observation scheme based on the uniformity index according to claim 8, wherein, The calculation of the signal-to-noise ratio spectrum of each optimized observation scheme includes: Calculate the signal-to-noise ratio spectrum based on the prestack time migration response value and the denoising response value of each optimized observation scheme.

10. The method for optimizing the observation scheme based on the uniformity index according to claim 9, wherein Combining the SNR of the target layer and the index requirements of the highest frequency, select the final plan from N optimized observation plans, including: Let min{·} denote taking the minimum value, m be the serial number of the optimization plan, and n = 1, 2,..., N be the serial numbers of the plans to be optimized. Assume that the maximum frequency required for the exploration target layer is F d , then the formula for determining the optimization plan is as follows: m = min{k = n, and Fmax n > Fd} That is, the observation plan with a point-line distance ratio of 1:(N - m + 1) is the optimized plan.

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