Design method, device, equipment and medium for coverage density of seismic observation system

Abstract

The application provides a design method, device, equipment and medium for coverage density of a seismic observation system. The method comprises the following steps: calculating single-coverage noise energy of previous seismic data through a result of comparative processing of the previous seismic data and a result of noise energy statistics based on Q compensation effect; estimating single-coverage noise energy of to-be-acquired seismic data according to the single-coverage noise energy of the previous seismic data; combining the single-coverage noise energy of the to-be-acquired seismic data and a signal-to-noise ratio of a target layer meeting migration imaging requirements of a proposed seismic acquisition project, to establish a quantitative relationship with coverage density as an independent variable and Q compensation cutoff frequency as a dependent variable; and designing the coverage density of the seismic observation system according to the quantitative relationship and in combination with the Q compensation cutoff frequency of the target layer meeting the migration imaging requirements of the proposed seismic acquisition project.

Description

Technical Field

[0001] This invention relates to the field of seismic survey technology, and in particular to a method, apparatus, equipment, and medium for designing the coverage density of a seismic observation system. Background Technology

[0002] Among the attribute parameters of a seismic observation system, coverage density is the parameter with the greatest weight in affecting the migration imaging quality and seismic acquisition cost of seismic data.

[0003] On the one hand, the improvement of migration imaging quality by cover density is also affected by the level of noise development in the exploration area, the absorption and attenuation of the earth, and the burial depth and seismic response characteristics of the target layer. Furthermore, seismic data has a limited bandwidth, so the improvement in migration imaging quality does not continuously increase with increasing cover density. Instead, there is an inflection point. Within this inflection point, the migration imaging quality improves significantly with increasing cover density; beyond this inflection point, further increases in cover density have little effect on improving migration imaging quality. The inflection point value for cover density varies for different regions, burial depths, and target layers with varying complexity. On the other hand, increasing cover density inevitably leads to increased fieldwork and higher acquisition costs. Overly intensive observation schemes can also cause excessive redundancy in seismic data, further increasing the workload of seismic data processing. Therefore, scientifically designing cover density is crucial for ensuring the quality of seismic acquisition and controlling its costs.

[0004] Currently, the design of earthquake observation systems adopts a hybrid argumentation and analysis method based on post-stack and pre-stack theoretical analysis and actual data comparison processing. These methods mainly have two problems: first, theoretical analysis cannot provide a quantitative relationship between the observation system's attribute parameters and migration imaging effects; second, if the migration imaging requirements of the proposed observation system are higher than the migration imaging effects of the actual data used for comparison processing, the actual data comparison processing method is not applicable.

[0005] Therefore, in order to solve the problems existing in the current hybrid demonstration and analysis methods, it is necessary to establish a quantitative relationship between the coverage density of the seismic observation system and the migration imaging effect. However, there is no technical solution to establish this quantitative relationship in the relevant technologies. Summary of the Invention

[0006] In view of the above problems, embodiments of the present invention provide a method, apparatus, equipment and medium for designing the coverage density of an earthquake observation system, so as to overcome the above problems or at least partially solve the above problems.

[0007] A first aspect of this invention provides a method for designing the coverage density of a seismic observation system, comprising:

[0008] Based on the results of comparative processing of previous earthquake data and the results of noise energy statistics based on Q compensation effect, the single-coverage noise energy of previous earthquake data was calculated.

[0009] Based on the single-coverage noise energy of the previous seismic data, estimate the single-coverage noise energy of the seismic data to be acquired.

[0010] By combining the single-pass coverage noise energy of the proposed seismic data and the signal-to-noise ratio of the target layer that meets the migration imaging requirements of the proposed seismic acquisition project, a quantitative relationship is established with coverage density as the independent variable and Q-compensation cutoff frequency as the dependent variable.

[0011] Based on the quantization relationship and the Q-compensation cutoff frequency of the target layer that meets the migration imaging requirements of the proposed seismic acquisition project, the coverage density of the seismic observation system is designed.

[0012] Optionally, after establishing the quantization relationship with coverage density as the independent variable and Q-compensation cutoff frequency as the dependent variable, the method further includes:

[0013] Given different values ​​of the Q-compensation cutoff frequency, calculate the coverage density corresponding to the different values ​​of the Q-compensation cutoff frequency according to the quantization relationship;

[0014] Based on the coverage density corresponding to different values ​​of the Q compensation cutoff frequency, a coverage density design guidance curve is fitted, and the coverage density design guidance curve has a coverage density inflection point value.

[0015] Optionally, the result of the noise energy statistics based on the Q compensation effect is obtained according to the following steps:

[0016] Establish nonlinear equations | SNR E -SNR Q (E N If |=0, the SNR E The SNR (Signal-to-Noise Ratio) represents the signal-to-noise ratio of the target layer on the pre-stack time-migrating profile after Q-compensation. It is an actual value based on seismic data statistics. Q (E N ) indicates that the noise energy is E N The theoretical value of the target layer signal-to-noise ratio on the pre-stack time-off profile after Q compensation;

[0017] Based on the Q-compensated pre-stack time-migrating profile, the signal-to-noise ratio of the target layer and the equivalent quality factor Q from the surface to the target layer are... eff The statistical relationship is used to determine the SNR. Q (E N The theoretical calculation formula for ) is as follows:

[0018]

[0019] Among them, f c f represents the Q-compensated cutoff frequency. s1 f e1 The f represents the start and end frequencies for calculating the effective signal energy. s2 f e2 Q represents the start and end frequencies for calculating noise energy. eff The equivalent quality factor from the surface to the target layer is represented by T, the reflection time corresponding to the target layer is represented by S(f), and the amplitude spectrum of the excitation wavelet used by the seismic observation system is represented by S(f).

[0020] Determine the nonlinear equation |SNR E -SNR Q (E N The values ​​of the parameters in |=0 include: the parameter SNR determined based on the previous seismic data. E f s1 f e1 f s2 f e2 Q eff The values ​​of T and S(f);

[0021] Based on the comparative processing of the aforementioned previous seismic data, different cover densities D(i) and their corresponding Q-compensation cutoff frequencies f were determined. c (i);

[0022] Combined with the Q-compensated cutoff frequency f c (i) Solve the nonlinear equation |SNR E -SNR Q (E N If | ) = 0, then the noise energy E corresponding to the different coverage densities D(i) is obtained. N (i).

[0023] Optionally, the single-coverage noise energy of previous earthquake data is calculated based on the results of comparative processing of previous earthquake data and the results of noise energy statistics based on Q compensation effect, including:

[0024] Based on the aforementioned previous earthquake data, the formula is determined. The values ​​of parameters N and Cell are given in the text, where N represents the number of different coverage density schemes extracted in the comparative processing of seismic data, and Cell represents the area of ​​the cell used when processing seismic data.

[0025] Combining the different coverage densities D(i) and the corresponding noise energy values ​​E N (i), according to the formula Calculate the single-coverage noise energy E′ of the aforementioned previous seismic data. N .

[0026] Optionally, the single-coverage noise energy of the seismic data to be acquired is estimated based on the single-coverage noise energy of the previous seismic data, including:

[0027] Based on the differences in excitation and reception methods between the proposed seismic data and the previous seismic data, the formula E″ is determined. N =ηE′ N The value of the noise energy adjustment coefficient η for single coverage;

[0028] Calculate the single-coverage noise energy E″ of the data to be collected according to the formula. N .

[0029] Optionally, by combining the single-shot coverage noise energy of the seismic data to be acquired and the signal-to-noise ratio of the target layer that meets the migration imaging requirements of the proposed seismic acquisition project, a quantization relationship is established with coverage density as the independent variable and Q-compensation cutoff frequency as the dependent variable, including:

[0030] Establish nonlinear equations | SNR E -SNR Q (D)|=0, the SNR Q (D) represents the theoretical value of the target layer signal-to-noise ratio (SNR) on the pre-stack time-migrating profile after Q compensation, given a coverage density of D. Q The theoretical calculation formula for (D) is as follows;

[0031]

[0032] Determine the nonlinear equation |SNR E -SNR Q The values ​​of the parameter in (D)|=0 include: determining the parameter f based on the information of the proposed seismic acquisition project. s1 f e1 f s2 f e2 Q eff The values ​​of T and S(f) are determined based on the migration imaging requirements of the proposed seismic acquisition project, and the parameter SNR is given. E The value of parameter E″ is determined based on the single-pass coverage noise energy of the seismic data to be acquired. N The possible values ​​of ;

[0033] Combining the aforementioned nonlinear equation |SNR E -SNR Q The parameter values ​​in (D)|=0 and the SNR Q The theoretical expression for (D) is established with coverage density D as the independent variable and Q-compensated cutoff frequency f. c This represents the quantitative relationship of the dependent variable.

[0034] Optionally, based on the quantization relationship and the Q-compensation cutoff frequency of the target layer that meets the migration imaging requirements of the proposed seismic acquisition project, the coverage density of the seismic observation system is determined, including:

[0035] Based on the migration imaging requirements of the proposed seismic acquisition project, the Q-compensation cutoff frequency f is given. c The value of is used to determine the coverage density D of the seismic observation system based on the quantization relationship.

[0036] A second aspect of the present invention also provides a device for designing the coverage density of a seismic observation system, comprising:

[0037] The calculation module is used to calculate the single-coverage noise energy of previous earthquake data by combining the results of comparative processing of previous earthquake data and the results of noise energy statistics based on Q compensation effect.

[0038] The estimation module is used to estimate the single-coverage noise energy of the seismic data to be acquired based on the single-coverage noise energy of the previous seismic data.

[0039] The quantization relationship establishment module is used to combine the single coverage noise energy of the seismic data to be acquired and the signal-to-noise ratio of the target layer that meets the migration imaging requirements of the proposed seismic acquisition project to establish a quantization relationship with coverage density as the independent variable and Q compensation cutoff frequency as the dependent variable.

[0040] The coverage density design module is used to determine the coverage density of the seismic observation system based on the quantization relationship and the Q-compensation cutoff frequency of the target layer that meets the migration imaging requirements of the proposed seismic acquisition project.

[0041] Optionally, the device further includes:

[0042] The coverage density design curve fitting module is used to determine the coverage density corresponding to different values ​​of the Q compensation cutoff frequency based on the quantization relationship, and to fit a coverage density design guidance curve based on the coverage density corresponding to the different values ​​of the Q compensation cutoff frequency. The coverage density design guidance curve has a coverage density inflection point value.

[0043] Optionally, the device further includes:

[0044] The first nonlinear equation establishment submodule is used to establish the nonlinear equation |SNR E -SNR Q (E N If |=0, the SNR E The SNR (Signal-to-Noise Ratio) represents the signal-to-noise ratio of the target layer on the pre-stack time-migrating profile after Q-compensation. It is an actual value based on seismic data statistics. Q(E N ) indicates that the noise energy is E N The theoretical value of the target layer signal-to-noise ratio on the pre-stack time-off profile after Q compensation;

[0045] The theoretical calculation formula determination submodule is used to determine the signal-to-noise ratio of the target layer on the pre-stack time migration profile after Q compensation and the equivalent quality factor Q from the surface to the target layer. eff The statistical relationship is used to determine the SNR. Q (E N The theoretical calculation formula for ) is as follows:

[0046]

[0047] Among them, f c f represents the Q-compensated cutoff frequency. s1 f e1 The f represents the start and end frequencies for calculating the effective signal energy. s2 f e2 Q represents the start and end frequencies for calculating noise energy. eff The equivalent quality factor from the surface to the target layer is represented by T, the reflection time corresponding to the target layer is represented by S(f), and the amplitude spectrum of the excitation wavelet used by the seismic observation system is represented by S(f).

[0048] The first parameter value submodule is used to determine the nonlinear equation |SNR E -SNR Q (E N The values ​​of the parameters in |=0 include: the parameter SNR determined based on the previous seismic data. E f s1 f e1 f s2 f e2 Q eff The values ​​of T and S(f);

[0049] The previous earthquake data comparison and processing submodule is used to determine different cover densities D(i) and corresponding Q-compensation cutoff frequencies f based on the comparison and processing of the previous earthquake data. c (i);

[0050] The noise energy statistics submodule is used to combine the Q-compensated cutoff frequency f c (i) Solve the nonlinear equation |SNR E -SNR Q (E N If | ) = 0, then the noise energy E corresponding to the different coverage densities D(i) is obtained. N (i).

[0051] Optionally, the quantification relationship establishment module includes:

[0052] The second nonlinear equation establishment submodule is used to establish the nonlinear equation |SNR E -SNR Q (D)|=0, the SNR Q (D) represents the theoretical value of the target layer signal-to-noise ratio (SNR) on the pre-stack time-migrating profile after Q compensation, given a coverage density of D. Q The theoretical calculation formula for (D) is as follows;

[0053]

[0054] The second parameter value submodule is used to determine the nonlinear equation |SNR E -SNR Q The values ​​of the parameter in (D)|=0 include: determining the parameter f based on the information of the proposed seismic acquisition project. s1 f e1 f s2 f e2 Q eff The values ​​of T and S(f) are determined based on the migration imaging requirements of the proposed seismic acquisition project, and the parameter SNR is given. E The value of parameter E″ is determined based on the single-pass coverage noise energy of the seismic data to be acquired. N The possible values ​​of ;

[0055] The quantification relation establishment submodule is used to combine the nonlinear equation |SNR E -SNR Q The parameter values ​​in (D)|=0 and the SNR Q The theoretical expression for (D) is established with coverage density D as the independent variable and Q-compensated cutoff frequency f. c This represents the quantitative relationship of the dependent variable.

[0056] A third aspect of this invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps in the method for designing the coverage density of the seismic observation system described in the first aspect of this invention.

[0057] A fourth aspect of this invention also provides a computer-readable storage medium storing a computer program / instructions thereon, which, when executed by a processor, implements the steps in the method for designing the coverage density of the seismic observation system described in the first aspect of this invention.

[0058] The method provided in this invention includes: calculating the single-pass coverage noise energy of previous seismic data based on the results of comparative processing of previous seismic data and the results of noise energy statistics based on Q-compensation effect; estimating the single-pass coverage noise energy of the seismic data to be acquired based on the single-pass coverage noise energy of the previous seismic data; establishing a quantitative relationship with coverage density as the independent variable and Q-compensation cutoff frequency as the dependent variable by combining the single-pass coverage noise energy of the seismic data to be acquired with the signal-to-noise ratio of the target layer that meets the migration imaging requirements of the proposed seismic acquisition project; and designing the coverage density of the seismic observation system based on the quantitative relationship and the Q-compensation cutoff frequency of the target layer that meets the migration imaging requirements of the proposed seismic acquisition project. Compared with the hybrid demonstration and analysis method in the prior art based on post-stack and pre-stack theoretical analysis and actual data comparison processing, this invention establishes a quantitative relationship between the coverage density of the seismic observation system and the migration imaging effect, which can give a prediction of the migration imaging effect of the proposed observation system that is close to the actual situation, and realizes the technical and economic integration of seismic observation system coverage density parameter design. Attached Figure Description

[0059] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0060] Figure 1 This is a flowchart illustrating the steps of a method for designing the coverage density of an earthquake observation system according to an embodiment of the present invention.

[0061] Figure 2 These are pre-stack time migration profiles of two previous seismic acquisition projects, ST1 and ST1E, located in the western exploration area of ​​China, provided in this embodiment of the invention.

[0062] Figure 3 The coverage density of 3,993,600 lanes / km provided in this embodiment of the invention. 2 Scheme 1 corresponds to pre-stack time migration profiles after high-pass scanning in different frequency ranges;

[0063] Figure 4 This is a schematic diagram of the coverage density design guidance curve for a proposed seismic acquisition project located in a western exploration area of ​​China, provided by an embodiment of the present invention.

[0064] Figure 5 This is a schematic diagram of the structure of a design device for the coverage density of an earthquake observation system proposed in an embodiment of this application;

[0065] Figure 6This is a schematic diagram of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0066] Exemplary embodiments of the present invention will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the invention are shown in the drawings, it should be understood that the invention may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this invention will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.

[0067] This invention provides a method for designing the coverage density of a seismic observation system, referring to... Figure 1 , Figure 1 A flowchart illustrating the steps of a method for designing the coverage density of a seismic observation system, as provided in an embodiment of the present invention, is shown below. Figure 1 As shown, it includes:

[0068] Step 101: Based on the results of comparative processing of previous earthquake data and the results of noise energy statistics based on Q compensation effect, calculate the single-coverage noise energy of previous earthquake data. The specific implementation steps are as follows:

[0069] (1) Comparison processing of previous seismic data of the exploration area with different cover densities was performed. The Q-compensation cutoff frequency of the target layer was statistically analyzed from the pre-stack time migration profile after comparison processing. The Q-compensation cutoff frequency of the target layer on the pre-stack time migration profile corresponding to multiple cover density schemes was obtained. The specific steps are as follows:

[0070] (a) Determine previous seismic acquisition projects based on the location of the exploration area, and collect previous seismic data, including the following information:

[0071] Observation system parameters: excitation line spacing, excitation point spacing, receiver line spacing, receiver point spacing, coverage times, and cell size, etc.

[0072] Excitation parameters: When the excitation type is a controllable source, the starting frequency, ending frequency, scan length, and starting slope of the scanning signal are collected; when the excitation type is explosive, the amount of excitation charge and well depth are collected.

[0073] Seismic acquisition data: Seismic acquisition auxiliary SPS files and seismic acquisition single-shot data;

[0074] Absorption attenuation Q model: Based on the micrologging data and VSP logging data in the previous seismic acquisition project area, the surface Q value and the mid-deep Q value are calculated respectively, and then the absorption attenuation Q model is constructed according to the geological stratification.

[0075] Seismic data processing results: pre-stack time migration profile data volumes used for data interpretation and corresponding seismic data processing workflows.

[0076] (b) Based on the basic parameters of the previous observation system, according to different basic parameters, such as excitation line spacing, excitation point spacing, receiver line spacing, receiver point spacing, number of receiver lines, and number of receiver points, extract the corresponding seismic data to obtain a scheme with a coverage density of D(i), where f = 1, 2, ..., N, and N represents the number of schemes for extracting coverage density;

[0077] (c) The same seismic data processing procedure is used to process the seismic data corresponding to the scheme with coverage density D(i) obtained in step (b) to obtain the pre-stack time migration profile corresponding to the scheme with coverage density D(i).

[0078] (d) High-pass filtering is performed on the pre-stack time migration profile corresponding to the scheme with coverage density D(i) according to the frequency parameter [F1, F1+5Hz]. The frequency value F1 corresponding to the time migration profile of the target layer that cannot be effectively identified is taken as the Q compensation cutoff frequency, where F1∈[10Hz, 100Hz], with an interval of 2Hz.

[0079] (e) Calculate the cutoff frequency f corresponding to different coverage densities D(i) sequentially according to step (d). c (i).

[0080] (2) Noise energy statistics based on Q compensation effect

[0081] (a) Establish the nonlinear equation |SNR E -SNR Q (E N SNR = 0 E The SNR (Signal-to-Noise Ratio) represents the signal-to-noise ratio of the target layer on the pre-stack time-migrating profile after Q-compensation. It is an actual value based on seismic data statistics. Q (E N () represents the theoretical value of the target layer signal-to-noise ratio on the pre-stack time-off profile after Q compensation, given a noise energy of 0.

[0082] (b) Based on the Q-compensated pre-stack time-migrating profile, the signal-to-noise ratio of the target layer and the equivalent quality factor Q from the surface to the target layer. eff Based on the statistical relationships, the calculation formula is determined as follows:

[0083]

[0084] Among them, f c f represents the Q-compensated cutoff frequency. s1 f e1 The f represents the start and end frequencies for calculating the effective signal energy. s2 f e2 Q represents the start and end frequencies for calculating noise energy.eff The equivalent quality factor from the surface to the target layer is represented by T, the reflection time corresponding to the target layer is represented by S(f), and the amplitude spectrum of the excitation wavelet used by the seismic observation system is represented by S(f).

[0085] (c) Determine the nonlinear equation |SNR E -SNR Q (E N The values ​​of the parameters in |=0 include: the parameter SNR determined based on the previous seismic data. E f s1 f e1 f s2 f e2 Q eff The values ​​of T and S(f);

[0086] (d) Based on the comparative processing of the aforementioned previous seismic data, determine the different cover densities D(i) and the corresponding Q-compensation cutoff frequencies f. c (i);

[0087] (e) Combining the Q-compensation cutoff frequency f c (i) Solve the nonlinear equation |SNR E -SNRQ(EN) = 0, thus obtaining the different cover densities D i The corresponding noise energy ENi.

[0088] (3) Based on the results of comparative processing of previous earthquake data and the results of noise energy statistics based on Q compensation effect, the single-coverage noise energy of previous earthquake data was determined:

[0089] Based on the aforementioned previous earthquake data, the formula is determined. The values ​​of parameters N and Cell are given in the text, where N represents the number of different coverage density schemes extracted in the comparative processing of seismic data, and Cell represents the area of ​​the cell used when processing seismic data.

[0090] Combining the different coverage densities D(i) and the corresponding noise energy values ​​E N (i), according to the formula Calculate the single-coverage noise energy E′ of the aforementioned previous seismic data. N .

[0091] Step 102: Estimate the single-coverage noise energy of the earthquake data to be acquired based on the single-coverage noise energy of the previous earthquake data.

[0092] Based on the differences in excitation and reception methods between the proposed seismic data and previous seismic data, the formula E″ is determined. N =ηE′ NThe value of the noise energy adjustment coefficient η for single coverage;

[0093] Calculate the single-coverage noise energy E″ of the data to be collected according to the formula. N .

[0094] Step 103: Combining the single-pass coverage noise energy of the seismic data to be acquired and the signal-to-noise ratio of the target layer that meets the migration imaging requirements of the proposed seismic acquisition project, establish a quantitative relationship with coverage density as the independent variable and Q-compensation cutoff frequency as the dependent variable.

[0095] (1) Establish the nonlinear equation |SNR E -SNR Q (D)|=0, the SNR Q (D) represents the theoretical value of the target layer signal-to-noise ratio (SNR) on the pre-stack time-migrating profile after Q compensation, given a coverage density of D. Q The theoretical calculation formula for (D) is as follows;

[0096]

[0097] (2) Determine the nonlinear equation |SNR E -SNR Q The values ​​of the parameter in (D)|=0 include: determining the parameter f based on the information of the proposed seismic acquisition project. s1 f e1 f s2 f e2 Q eff The values ​​of T and S(f) are determined based on the migration imaging requirements of the proposed seismic acquisition project, and the parameter SNR is given. E The value of parameter E″ is determined based on the single-pass coverage noise energy of the seismic data to be acquired. N The possible values ​​of ;

[0098] (3) Combining the aforementioned nonlinear equation |SNR E -SNR Q The parameter values ​​in (D)|=0 and the SNR Q The theoretical expression for (D) is established with coverage density D as the independent variable and Q-compensated cutoff frequency f. c This represents the quantitative relationship of the dependent variable.

[0099] Step 104: Based on the quantization relationship and the Q-compensation cutoff frequency of the target layer that meets the migration imaging requirements of the proposed seismic acquisition project, design the coverage density of the seismic observation system.

[0100] Based on the migration imaging requirements of the proposed seismic acquisition project, the Q-compensation cutoff frequency f is given. cThe value of is used to determine the coverage density D of the seismic observation system based on the quantization relationship.

[0101] In one embodiment, after establishing the quantitative relationship with cover density as the independent variable and Q-compensation cutoff frequency as the dependent variable, the present invention can also fit a cover density design guidance curve. Taking a proposed seismic acquisition project in the western exploration area of ​​China as an example, the specific implementation method is as follows:

[0102] Step 101: Based on the results of comparative processing of previous earthquake data and the results of noise energy statistics based on Q compensation effect, calculate the single-coverage noise energy of previous earthquake data. The specific implementation steps are as follows:

[0103] (1) Based on the location of the exploration area in western China, two previous seismic acquisition projects were identified, namely ST1 and ST1 E. The previous seismic data of these two projects were compared and processed with different coverage densities.

[0104] (a) Collect historical earthquake data, including the following information:

[0105] Observation system parameters: The observation system parameters for the two seismic acquisition projects, ST1 and ST1 E, are consistent (see Table 1), with a coverage density of 3,993,600 channels / km². 2 .

[0106] Table 1 - Parameters of the Work Area Observation System

[0107]

[0108] Excitation parameters: Both previous seismic acquisition projects used controlled source excitation, and the excitation parameters were consistent (see Table 2 for parameters).

[0109] Excitation Parameter Table-2

[0110]

[0111] Seismic acquisition data: A block of seismic acquisition data with an area larger than the pre-stack migration aperture and its corresponding SPS file were read from previous seismic acquisition projects for comparison processing.

[0112] Absorption attenuation Q model: An absorption attenuation Q model was constructed based on micrologging data, VSP logging data and geological stratification results in the seismic acquisition project area (Q model is shown in Table 3).

[0113] Absorption Attenuation Q Model Table-3

[0114] 1 High-speed top interface 0.03 429 2.1 2 Cretaceous top 1.52 2237 82.3 3 Jurassic top 2.71 2773 132.0 4 Jurassic Badaowan Formation, first section top 3.35 3438 211.8 5 Top of the Permian Baikouquan Formation 3.85 4000 295.6 6 The top of the first section of the Jiamuhe Formation in the Triassic system 4.15 4333 352.4

[0115] Seismic data processing results: This includes the pre-stack time migration profile data volumes used for data collection and interpretation, and the corresponding seismic data processing workflow. Pre-stack time migration data was read from the comparison processing locations for subsequent target layer signal-to-noise ratio calculations. The pre-stack time migration profiles for ST1 and ST1 E are shown below. Figure 2 As shown in the figure, the time window for calculating the signal-to-noise ratio is indicated by the black rectangle in the figure.

[0116] (b) Based on the observation system parameters of previous earthquake projects ST1 and ST1 E, five sets of corresponding earthquake data were extracted according to different basic parameters to obtain five schemes with coverage density of , and the specific schemes are shown in Table 4.

[0117] Comparison of treatment plans - Table 4

[0118]

[0119]

[0120] (c) For the five sets of extracted seismic data mentioned above, the same processing procedure was used to process the data to obtain the pre-stack time migration profiles corresponding to the five cover density schemes.

[0121] (d) The Q-compensation cutoff frequency of the target layer of the Permian system on the pre-stack time migration profile corresponding to Scheme 1 is statistically analyzed using a high-pass frequency scanning method, such as... Figure 3 As shown;

[0122] Figure 3 The pre-stack time migration profile in the data is from Scheme 1 (cover density 3.9936 million channels / km). 2 Figure 1 shows the pre-stack time migration profiles after high-pass scanning at different frequency ranges. Figure (a) shows the high-pass scanning profile at 10Hz-15Hz, Figure (b) shows the high-pass scanning profile at 20Hz-25Hz, Figure (c) shows the high-pass scanning profile at 30Hz-35Hz, and Figure (d) shows the high-pass scanning profile at 38Hz-43Hz. The red dashed box in the figures indicates the location of the target Permian system. As can be seen from Figure (d), the reflection phase axis of the target Permian system cannot be effectively identified on the profile after high-pass scanning at 38Hz-43Hz. Therefore, Scheme 1 has a coverage density of 3,993,600 channels / km. 2 The corresponding Q-compensation cutoff frequency is 38Hz.

[0123] (e) Calculate the Q-compensation cutoff frequency of the target Permian strata on the pre-stack time migration profile corresponding to schemes 2-5 in sequence according to step (d) (see Table 5).

[0124] Target Layer Q-Compensation Cutoff Frequency Statistics Table-5

[0125] <![CDATA[areal coverage density (10,000 traces / km 2 )]]> 399.36 199.68 99.84 49.92 24.96 Number of Coverages 1248 624 312 156 78 Q-compensation cutoff frequency (Hz) 38 34 32 26 24

[0126] (2) Noise energy statistics based on Q compensation effect;

[0127] Noise Level Statistics Table-6

[0128]

[0129]

[0130] (3) Based on the results of comparative processing of previous earthquake data and the results of noise energy statistics based on Q compensation effect, the single-coverage noise energy of previous earthquake data was determined:

[0131] After calculating the noise energy values ​​corresponding to different coverage times, the single-coverage noise energy values ​​for different schemes are then calculated. Finally, the average value is taken as the single-coverage noise energy of previous seismic data in the exploration area, E′. N =2.7646.

[0132] Step 102: Estimate the single-coverage noise energy of the earthquake data to be acquired based on the single-coverage noise energy of the previous earthquake data.

[0133] The proposed seismic data is identical to previous seismic data in terms of excitation and reception methods. The single-coverage noise energy adjustment coefficient η = 1. Therefore, the single-coverage noise energy value E″ of the proposed seismic data for the exploration area is... N =2.7646.

[0134] After step 103, fit the coverage density design curve;

[0135] Based on the nonlinear equation |SNR E -SNR Q (D)|=0, given different Q-compensation cutoff frequencies, the coverage density parameters (such as...) are calculated. Figure 4 (As shown). Figure 4 The curves corresponding to the diamond-shaped points in the diagram represent the Q-compensation cutoff frequencies for different cover densities calculated using the method of this invention for the proposed seismic acquisition project. The curves corresponding to the rectangular points represent the Q-compensation cutoff frequencies for the target Permian strata corresponding to different cover density parameters obtained through comparative processing of previous seismic projects ST1 and ST1E, and are plotted based on Table 5.

[0136] This invention also provides an apparatus for designing the coverage density of a seismic observation system, with reference to... Figure 5 , Figure 5 This is a schematic diagram of a device for designing the coverage density of a seismic observation system according to an embodiment of this application. Figure 5 As shown, the device includes:

[0137] The calculation module is used to calculate the single-coverage noise energy of previous earthquake data by combining the results of comparative processing of previous earthquake data and the results of noise energy statistics based on Q compensation effect.

[0138] The estimation module is used to estimate the single-coverage noise energy of the seismic data to be acquired based on the single-coverage noise energy of the previous seismic data.

[0139] The quantization relationship establishment module is used to combine the single coverage noise energy of the seismic data to be acquired and the signal-to-noise ratio of the target layer that meets the migration imaging requirements of the proposed seismic acquisition project to establish a quantization relationship with coverage density as the independent variable and Q compensation cutoff frequency as the dependent variable.

[0140] The coverage density design module is used to design the coverage density of the seismic observation system based on the quantization relationship and the Q-compensation cutoff frequency of the target layer that meets the migration imaging requirements of the proposed seismic acquisition project.

[0141] In one embodiment, the device further includes:

[0142] The coverage density design curve fitting module is used to determine the coverage density corresponding to different values ​​of the Q compensation cutoff frequency based on the quantization relationship, and to fit a coverage density design guidance curve based on the coverage density corresponding to the different values ​​of the Q compensation cutoff frequency. The coverage density design guidance curve has a coverage density inflection point value.

[0143] In one embodiment, the device further includes:

[0144] The first nonlinear equation establishment submodule is used to establish the nonlinear equation |SNR E -SNR Q (E N If |=0, the SNR E The SNR (Signal-to-Noise Ratio) represents the signal-to-noise ratio of the target layer on the pre-stack time-migrating profile after Q-compensation. It is an actual value based on seismic data statistics. Q (E N ) indicates that the noise energy is E N The theoretical value of the target layer signal-to-noise ratio on the pre-stack time-off profile after Q compensation;

[0145] The theoretical calculation formula determination submodule is used to determine the signal-to-noise ratio of the target layer on the pre-stack time migration profile after Q compensation and the equivalent quality factor Q from the surface to the target layer. eff The statistical relationship is used to determine the SNR. Q (E N The theoretical calculation formula for ) is as follows:

[0146]

[0147] Among them, f c f represents the Q-compensated cutoff frequency. s1 f e1 The f represents the start and end frequencies for calculating the effective signal energy. s2 f e2 Q represents the start and end frequencies for calculating noise energy. eff The equivalent quality factor from the surface to the target layer is represented by T, the reflection time corresponding to the target layer is represented by S(f), and the amplitude spectrum of the excitation wavelet used by the seismic observation system is represented by S(f).

[0148] The first parameter value submodule is used to determine the nonlinear equation |SNR E -SNR Q (E N The values ​​of the parameters in |=0 include: the parameter SNR determined based on the previous seismic data. E f s1 f e1 f s2 f e2 Q eff The values ​​of T and S(f);

[0149] The previous earthquake data comparison and processing submodule is used to determine different cover densities D(i) and corresponding Q-compensation cutoff frequencies f based on the comparison and processing of the previous earthquake data. c (i);

[0150] The noise energy statistics submodule is used to combine the Q-compensated cutoff frequency f c (i) Solve the nonlinear equation |SNR E -SNR Q (E N If | ) = 0, then the noise energy E corresponding to the different coverage densities D(i) is obtained. N (i).

[0151] In one embodiment, the quantification relationship establishment module includes:

[0152] The second nonlinear equation establishment submodule is used to establish the nonlinear equation |SNR E -SNR Q (D)|=0, the SNR Q (D) represents the theoretical value of the target layer signal-to-noise ratio (SNR) on the pre-stack time-migrating profile after Q compensation, given a coverage density of D. Q The theoretical calculation formula for (D) is as follows;

[0153]

[0154] The second parameter value submodule is used to determine the nonlinear equation |SNR E -SNR Q The values ​​of the parameter in (D)|=0 include: determining the parameter f based on the information of the proposed seismic acquisition project. s1 f e1 f s2 f e2 Q eff The values ​​of T and S(f) are determined based on the migration imaging requirements of the proposed seismic acquisition project, and the parameter SNR is given. E The value of parameter E″ is determined based on the single-pass coverage noise energy of the seismic data to be acquired. N The possible values ​​of ;

[0155] The quantification relation establishment submodule is used to combine the nonlinear equation |SNR E -SNR Q The parameter values ​​in (D)|=0 and the SNR Q The theoretical expression for (D) is established with coverage density D as the independent variable and Q-compensated cutoff frequency f. c This represents the quantitative relationship of the dependent variable.

[0156] This invention also provides an electronic device, with reference to... Figure 6 , Figure 6 This is a schematic diagram of the electronic device proposed in an embodiment of this application. Figure 6 As shown, the electronic device 100 includes a memory 110 and a processor 120. The memory 110 and the processor 120 are connected via a bus for communication. The memory 110 stores a computer program that can run on the processor 120 to implement the steps in the design method of the coverage density of an earthquake observation system disclosed in the embodiments of this application.

[0157] This application also provides a computer-readable storage medium storing a computer program / instructions thereon, which, when executed by a processor, implements the steps in the design method for the coverage density of the seismic observation system as disclosed in this application.

[0158] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0159] Embodiments of the present invention are described with reference to flowchart illustrations and / or block diagrams of methods, apparatuses, electronic devices, and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing terminal device to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal device, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0160] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing terminal device to operate in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0161] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal equipment, causing a series of operational steps to be performed on the computer or other programmable terminal equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable terminal equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0162] Although preferred embodiments of the present invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of the embodiments of the present invention.

[0163] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or terminal device that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or terminal device. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or terminal device that includes said element.

[0164] The above provides a detailed description of the design method, apparatus, equipment, and medium for the coverage density of an earthquake observation system provided by the present invention. Specific examples have been used to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method for designing the coverage density of a seismic observation system, characterized in that, The method includes: Based on the results of comparative processing of previous earthquake data and the results of noise energy statistics based on Q compensation effect, the single-coverage noise energy of previous earthquake data was calculated. Based on the single-coverage noise energy of the previous seismic data, estimate the single-coverage noise energy of the seismic data to be acquired. By combining the single-pass coverage noise energy of the proposed seismic data and the signal-to-noise ratio of the target layer that meets the migration imaging requirements of the proposed seismic acquisition project, a quantitative relationship is established with coverage density as the independent variable and Q-compensation cutoff frequency as the dependent variable. Based on the quantization relationship and combined with the Q-compensation cutoff frequency of the target layer that meets the migration imaging requirements of the proposed seismic acquisition project, the coverage density of the seismic observation system is designed. Based on the aforementioned previous earthquake data, the formula is determined. Parameters in and The value of, the This indicates the number of different cover density schemes extracted during the comparative processing of seismic data. This represents the area of ​​the cells used when processing seismic data; according to the formula... Calculate the single-pass coverage noise energy of the seismic data to be acquired. ;in, Indicates the noise energy value. This represents the single-coverage noise energy of the aforementioned previous earthquake data. This represents the noise energy adjustment factor for a single coverage operation. Combining the single-pass coverage noise energy of the proposed seismic data with the signal-to-noise ratio of the target layer that meets the migration imaging requirements of the proposed seismic acquisition project, a quantization relationship is established with coverage density as the independent variable and Q-compensation cutoff frequency as the dependent variable, including: Establish nonlinear equations The The term represents the signal-to-noise ratio of the target layer on the pre-stack time-off profile after Q-compensation. This indicates that the coverage density is In the case of the theoretical value of the target layer signal-to-noise ratio on the pre-stack time migration profile after Q compensation, the The theoretical calculation formula is as follows; in, Indicates the Q-compensation cutoff frequency. , Indicates the start and end frequencies for calculating the effective signal energy; , Indicates the start and end frequencies for calculating noise energy. This represents the equivalent quality factor from the surface to the target layer. Indicates the reflection time corresponding to the target layer. This represents the amplitude spectrum of the excited wavelet used by the seismic observation system; Determine the nonlinear equation The values ​​of the parameters include: determining the parameters based on the information of the proposed seismic acquisition project. and The value of the parameter is given based on the migration imaging requirements of the proposed seismic acquisition project. The value of the parameter is determined based on the single-pass coverage noise energy of the seismic data to be acquired. The possible values ​​of ; Combining the aforementioned nonlinear equations The parameter values ​​and the results described The theoretical expression is established based on coverage density. The independent variable is Q, and the cutoff frequency is compensated. This represents the quantitative relationship of the dependent variable.

2. The method according to claim 1, characterized in that, After establishing the quantization relationship with coverage density as the independent variable and Q-compensation cutoff frequency as the dependent variable, the method further includes: Given different values ​​of the Q-compensation cutoff frequency, calculate the coverage density corresponding to the different values ​​of the Q-compensation cutoff frequency according to the quantization relationship; Based on the coverage density corresponding to different values ​​of the Q compensation cutoff frequency, a coverage density design guidance curve is fitted, and the coverage density design guidance curve has a coverage density inflection point value.

3. The method according to claim 1, characterized in that, The results of the noise energy statistics based on the Q compensation effect are obtained according to the following steps: Establish nonlinear equations The This represents the signal-to-noise ratio of the target layer on the pre-stack time migration profile after Q-compensation, and is based on actual values ​​from seismic data statistics. This indicates that the noise energy is The theoretical value of the target layer signal-to-noise ratio on the pre-stack time-off profile after Q compensation; Based on the target layer signal-to-noise ratio and the equivalent quality factor from the surface to the target layer on the Q-compensated pre-stack time-migrating profile. The statistical relationship is used to determine the... The theoretical calculation formula is as follows: in, Indicates the Q-compensation cutoff frequency. , Indicates the start and end frequencies for calculating the effective signal energy; , Indicates the start and end frequencies for calculating noise energy. This represents the equivalent quality factor from the surface to the target layer. Indicates the reflection time corresponding to the target layer. This represents the amplitude spectrum of the excited wavelet used by the seismic observation system; Determine the nonlinear equation The values ​​of the parameters include: parameters determined based on the aforementioned previous seismic data. and The possible values ​​of ; Based on the comparative processing of the aforementioned previous earthquake data, different cover densities were determined. and the corresponding Q-compensation cutoff frequency ; Combined with the Q-compensated cutoff frequency Solve the nonlinear equation The different coverage densities were obtained. Corresponding noise energy .

4. The method according to claim 3, characterized in that, Based on the results of comparative processing of previous earthquake data and the statistical results of noise energy based on Q compensation effect, the single-coverage noise energy of previous earthquake data was calculated, including: Combining the different coverage densities and the corresponding noise energy value According to the formula Calculate the single-coverage noise energy of the aforementioned previous seismic data. .

5. The method according to claim 4, characterized in that, Based on the single-coverage noise energy of the previously obtained seismic data, the single-coverage noise energy of the seismic data to be acquired is estimated, including: Based on the differences in excitation and reception methods between the proposed seismic data and the previous seismic data, the formula is determined. Medium single-coverage noise energy adjustment coefficient The value of .

6. The method according to claim 1, characterized in that, Based on the quantization relationship and the Q-compensation cutoff frequency of the target layer that meets the migration imaging requirements of the proposed seismic acquisition project, the coverage density of the seismic observation system is determined, including: Based on the migration imaging requirements of the proposed seismic acquisition project, the Q-compensation cutoff frequency is given. The value of is used to determine the coverage density of the seismic observation system based on the quantization relationship. .

7. A device for designing the coverage density of a seismic observation system, applied to the method for designing the coverage density of a seismic observation system as described in claim 1, characterized in that, include: The calculation module is used to calculate the single-coverage noise energy of previous earthquake data by combining the results of comparative processing of previous earthquake data and the results of noise energy statistics based on Q compensation effect. The estimation module is used to estimate the single-coverage noise energy of the seismic data to be acquired based on the single-coverage noise energy of the previous seismic data. The quantization relationship establishment module is used to combine the single coverage noise energy of the seismic data to be acquired and the signal-to-noise ratio of the target layer that meets the migration imaging requirements of the proposed seismic acquisition project to establish a quantization relationship with coverage density as the independent variable and Q compensation cutoff frequency as the dependent variable. The coverage density design module is used to determine the coverage density of the seismic observation system based on the quantization relationship and the Q-compensation cutoff frequency of the target layer that meets the migration imaging requirements of the proposed seismic acquisition project.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory, characterized in that, The processor executes the computer program to implement the steps in the method for designing the coverage density of the seismic observation system according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program / instructions stored thereon, characterized in that, When the computer program / instructions are executed by the processor, they implement the steps in the method for designing the coverage density of the seismic observation system as described in any one of claims 1 to 6.

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