Method, device and medium for simulating vibroseis aliasing acquisition data

Abstract

The application discloses a controllable source aliasing acquisition data simulation analysis method, comprising the following steps: obtaining exploration area information; determining forward observation parameters based on the exploration area information, the aliasing acquisition noise interference range and the interference energy intensity as standards; performing three-dimensional aliasing acquisition simulation based on the exploration area information and multiple time-distance rules respectively to obtain multiple aliasing acquisition simulation noise data bodies; performing stacking imaging processing on the multiple aliasing acquisition simulation noise data bodies respectively to obtain multiple full-coverage area stacking imaging profiles based on different time-distance rules; and performing quantitative analysis on the aliasing acquisition noise interference degree by taking the signal and noise energy of the multiple full-coverage area stacking imaging profiles as quantitative indexes. The application further discloses a controllable source aliasing acquisition data simulation analysis device, computer equipment and a readable storage medium. The application realizes three-dimensional controllable source aliasing acquisition data fast simulation and aliasing acquisition noise interference quantitative analysis.

Description

Technical Field

[0001] This invention relates to the field of petroleum seismic exploration data acquisition technology, and in particular to a method, apparatus, equipment, and readable medium for simulation analysis of controlled source superimposed acquisition data. Background Technology

[0002] As seismic acquisition technology advances towards high density, wide bandwidth, and wide azimuth, controlled-source efficient aliasing acquisition technology provides technical support for the economic feasibility of "two-wide-one-high" seismic acquisition. Controlled-source efficient aliasing acquisition introduces interference effects from adjacent shots (also known as aliasing acquisition noise). In controlled-source efficient aliasing seismic acquisition, the interference effect of controlled-source aliasing acquisition noise is mainly analyzed through the observation system design and the design and demonstration of controlled-source excitation parameters. Both of these stages require simulating three-dimensional controlled-source aliasing acquisition data under different time interval rules and quantifying the interference degree of aliasing acquisition noise.

[0003] Currently, there are two main categories of methods for simulating controlled-source aliased acquisition data: The first type involves combining conventionally acquired data from controlled sources with time-distance rules to add time-shifted and displacement-added non-aliased data, resulting in simulated aliased acquisition data. This type of method has the following problem: it requires a massive amount of actual acquired data for three-dimensional aliased acquisition simulation, which is difficult to obtain in practical applications. Currently, this type of method mainly achieves two-dimensional aliased acquisition simulation. The second type of method uses controlled-source forward modeling, combining time-distance rules and observation schemes to simulate excitation records at different temporal and spatial locations, obtaining aliased acquisition forward modeling simulation data. Controlled-source forward modeling mainly uses controlled-source scanning signals or force signals as forward modeling wavelets and employs wave equation methods for forward modeling. This type of method has two main problems: First, there is the timeliness of aliased acquisition data simulation. Due to the current limitations of computing resources, the daily timeliness of 3D aliased acquisition data simulation using this method is often measured in months, which seriously affects the timeliness of analysis work based on aliased acquisition data. Second, there is the reliability problem of aliased acquisition data simulation. In terms of signal and noise energy attenuation patterns, there are differences between the energy attenuation of a single shot in forward modeling of aliased acquisition and the energy attenuation of a single shot in actual aliased acquisition, which affects the quantitative analysis conclusions of the degree of noise interference in subsequent aliased acquisition.

[0004] Therefore, there is a need to improve existing technologies for rapid simulation and analysis methods of controlled source aliasing acquisition data. Summary of the Invention

[0005] In view of this, the purpose of this invention is to propose a method, apparatus, device and readable medium for simulating and analyzing controllable source aliasing acquisition data. It performs imaging processing on simulated signals and noise data from three-dimensional aliasing acquisition, uses the signal and noise energy on the imaging profile as quantitative indicators, and forms a quantitative analysis method for the degree of noise interference in aliasing acquisition, thereby realizing rapid simulation and analysis of three-dimensional controllable source aliasing acquisition data.

[0006] To achieve the above objectives, one aspect of the present invention provides a method for simulating and analyzing controllable source superimposed acquisition data, comprising the following steps:

[0007] Acquire seismic acquisition information, field test data for excitation parameter design, geological information, and time-distance rule information;

[0008] Based on seismic acquisition information and geological information, forward modeling observation parameters are determined using the interferometric range of aliased acquisition noise and the interferometric energy intensity as standards.

[0009] Based on seismic acquisition information, excitation parameter design field test data, and forward modeling observation parameters, three-dimensional aliasing acquisition simulations were performed using various time interval rules to obtain various aliasing acquisition simulation noise data volumes.

[0010] Multiple aliased acquisition simulated noise data volumes were superimposed and imaged to obtain multiple full-coverage superimposed imaging profiles based on different time interval rules.

[0011] The signal and noise energy of multiple full-coverage superimposed imaging profiles are used as quantitative indicators to quantitatively analyze the degree of noise interference in aliasing acquisition.

[0012] In some implementations, the seismic acquisition information includes: excitation point and receiver point information, seismic observation scheme, excitation line, receiver line, point distance, sampling time interval, related post-record length, and controlled source scanning signal parameters;

[0013] The field test data for the excitation parameter design include: the length of the excitation test line, relevant pre-shot records and source force signals for different land types;

[0014] Geological information includes: near-surface structure thickness, velocity, and quality factor of the exploration area;

[0015] The time interval rule information includes at least: the first time interval rule and the second time interval rule.

[0016] In some implementations, determining forward modeling observation parameters based on the aliasing acquisition noise interferometry range and interferometry energy intensity includes:

[0017] The forward modeling observation scheme and aliasing acquisition simulation range were designed based on the interference range of aliasing acquisition noise and interference energy intensity. A horizontal layered geological model was established and the forward modeling wavelet was determined.

[0018] In some implementations, the forward modeling observation parameters are determined based on the seismic acquisition information and geological information, using the aliased acquisition noise interferometry range and interferometric energy intensity as standards, including:

[0019] The forward modeling observation parameters include forward modeling wavelet parameters and forward modeling observation system parameters. Based on seismic acquisition information and geological information, the forward modeling wavelet parameters are determined using the aliasing acquisition noise interference range and interference energy intensity as standards. The forward modeling observation system parameters are consistent with the seismic acquisition observation parameters of the exploration area. Forward modeling simulation is performed based on the forward modeling observation parameters. The forward modeling simulation range is the common center line of the full coverage seismic acquisition in the exploration area. Based on the excitation-reception relationship, the information of all shot points and receiver points involved in the full coverage common center line is determined.

[0020] In some implementations, the horizontally layered geological model includes: a near-surface geological model and a mid-to-deep geological model.

[0021] In some implementations, based on the seismic acquisition information, excitation parameters, field test data, and forward modeling observation parameters, three-dimensional aliasing acquisition simulations are performed using various time-distance rules to obtain various aliasing acquisition simulation noise data volumes, including:

[0022] Based on seismic acquisition information, excitation parameters, and field test data of single shots and forward modeling observation parameters, three-dimensional aliasing acquisition simulations were performed using the first and second time-distance rules to obtain the aliasing acquisition simulation noise data volume.

[0023] In some implementations, the quantitative analysis of the degree of interference from aliasing acquisition noise is performed using the signal and noise energy of multiple full-coverage superimposed imaging profiles as quantitative indicators, including:

[0024] Based on the burial depth and velocity information of each target layer in the geological model, the reflection time of each target layer is calculated. Taking the reflection time of the target layer as the center, the interference energy of the noise from the aliasing acquisition of each reflection layer is calculated based on the energy statistical half-time window. The energy values ​​of each CMP point on the superimposed imaging profile of the simulated noise data from the aliasing acquisition under the two time-distance rules are statistically analyzed. The number of coverage times is designed based on the time-distance rules.

[0025] In some implementations, based on the seismic acquisition information, excitation parameters, field test data, and forward modeling observation parameters, three-dimensional aliasing acquisition simulations are performed using various time-distance rules to obtain various aliasing acquisition simulation noise data volumes, including:

[0026] The ray tracing method and the multi-source random aliasing acquisition simulation method, based on the energy attenuation law of actual data, simulate the three-dimensional aliased acquisition data signal and noise data volume.

[0027] In some implementations, the quantitative analysis of the degree of interference from aliasing acquisition noise is performed using the signal and noise energy of multiple full-coverage superimposed imaging profiles as quantitative indicators, including:

[0028] Calculate the superimposed imaging energy of aliased acquired simulated noise data at CMP points on the superimposed imaging profile in the full coverage area;

[0029] The signal-to-noise ratio (SNR) difference coefficient of a single seismic acquisition shot is calculated based on the energy of the superimposed noise data imaging, and the coverage times are designed based on the SNR difference coefficient.

[0030] Based on the energy ratio calculated from the analog signal and noise acquired by aliasing, a quantization evaluation threshold is set. When the energy ratio is greater than or equal to the quantization evaluation threshold, the degree of interference of the aliasing acquisition noise with the target layer imaging is output as acceptable.

[0031] In another aspect of this invention, a controllable source aliasing acquisition data simulation and analysis device is provided, comprising:

[0032] The information acquisition module is configured to acquire seismic acquisition information, excitation parameter design field test data, geological information, and time-distance rule information.

[0033] The observation design module is configured to determine forward modeling observation parameters based on seismic acquisition information and geological information, using the aliased acquisition noise interferometry range and interferometry energy intensity as standards.

[0034] The aliasing acquisition simulation module is configured to perform three-dimensional aliasing acquisition simulations based on seismic acquisition information, excitation parameters, field test data, and forward modeling observation parameters, using various time interval rules to obtain various aliasing acquisition simulation noise data volumes.

[0035] The imaging processing module is configured to perform superimposed imaging processing on various aliased acquisition analog noise data volumes to obtain multiple full-coverage superimposed imaging profiles based on different time interval rules.

[0036] The analysis module is configured to perform quantitative analysis on the degree of noise interference in aliasing acquisition, using the signal and noise energy of multiple full-coverage superimposed imaging profiles as quantitative indicators.

[0037] In another aspect of the present invention, a computer device is provided, comprising: at least one processor; and a memory storing computer instructions executable on the processor, the instructions, when executed by the processor, implementing the steps of the above-described method.

[0038] In another aspect, the present invention provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method steps.

[0039] The present invention has at least the following beneficial technical effects:

[0040] This invention relies on the field test data and shallow, medium, and deep stratigraphic structural parameters of controlled-source seismic acquisition in the exploration area, based on the observation parameters and excitation parameters of the controlled-source seismic acquisition. It designs forward modeling parameters using the maximum interference range and intensity of aliased acquisition noise as the standard, and introduces the signal and noise energy attenuation laws of actual data. It employs ray tracing and multi-source random aliasing acquisition simulation methods based on these laws to achieve rapid simulation of 3D aliased acquisition data. Imaging processing is performed on the simulated signals and noise data of 3D aliased acquisition, using the signal and noise energy on the imaging profile as quantitative indicators to form a quantitative analysis method for the degree of aliased acquisition noise interference. This invention achieves rapid simulation of 3D controlled-source aliased acquisition data and quantitative analysis of aliased acquisition noise interference. It is applied in the design stage of controlled-source aliased seismic acquisition observation parameters and coverage times, and in the analysis and demonstration stage of time-distance rule acquisition effects, providing analytical data support for subsequent acquisition of high-quality data from 3D controlled-source aliased acquisition. Attached Figure Description

[0041] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art 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 embodiments can be obtained based on these drawings without creative effort.

[0042] Figure 1 A schematic diagram illustrating an embodiment of the controllable seismic source aliasing acquisition data simulation and analysis method provided by the present invention;

[0043] Figure 2 A schematic diagram illustrating an embodiment of previous seismic acquisition information in an exploration area provided by the present invention;

[0044] Figure 3 This is a schematic diagram of an embodiment of the forward wavelet-controllable source force signal in the Xiaosha region provided by the present invention;

[0045] Figure 4 A schematic diagram of an embodiment of the controllable seismic source aliasing acquisition simulation noise single shot provided by the present invention;

[0046] Figure 5 A schematic diagram of an embodiment of the controllable seismic source aliasing acquisition simulation noise superposition profile provided by the present invention;

[0047] Figure 6A schematic diagram of an embodiment of the controllable seismic source aliasing acquisition simulation noise energy curve provided by the present invention;

[0048] Figure 7 A schematic diagram of an embodiment of the controllable seismic source aliasing acquisition data simulation and analysis device provided by the present invention;

[0049] Figure 8 A schematic diagram of an embodiment of the computer device provided by the present invention;

[0050] Figure 9 A schematic diagram illustrating an embodiment of the computer-readable storage medium provided by the present invention. Detailed Implementation

[0051] To make the objectives, technical solutions, and advantages of the present invention clearer, the embodiments of the present invention will be further described in detail below with reference to specific examples and the accompanying drawings.

[0052] It should be noted that all uses of "first" and "second" in the embodiments of the present invention are for the purpose of distinguishing two entities or parameters with the same name but different names. It is clear that "first" and "second" are only for the convenience of expression and should not be construed as limiting the embodiments of the present invention. Subsequent embodiments will not explain this in detail.

[0053] The efficient aliasing acquisition of controlled-source seismic data mainly involves the following steps: ① observation system design; ② measurement of excitation and receiver locations; ③ design and verification of controlled-source excitation parameters; ④ deployment of excitation and receiver points; ⑤ on-site seismic acquisition construction. Compared with conventional acquisition, efficient aliasing acquisition of controlled-source seismic data requires analysis of the interference effect of noise in steps ① and ③. Both of these steps require simulation of three-dimensional controlled-source aliasing acquisition data under different time interval rules, and quantitative analysis of the interference degree of aliasing acquisition noise. This invention designs forward modeling parameters based on the maximum interference range and interference intensity of aliasing acquisition noise, introduces the signal and noise energy attenuation law of actual data, and uses a multi-source stochastic forward modeling method based on ray tracing to simulate three-dimensional aliasing acquisition signals and noise data. It also combines the imaging profile of the simulated aliasing acquisition data to form a quantitative analysis method for aliasing acquisition noise interference. In summary, this invention relates to the design of the controlled-source seismic acquisition observation scheme and the design and verification of excitation parameters.

[0054] In a first aspect, an embodiment of a method for simulating and analyzing controllable seismic source aliasing acquisition data is proposed. Figure 1 The diagram shown is a schematic representation of an embodiment of the controllable seismic source aliasing acquisition data simulation and analysis method provided by the present invention. Figure 1 As shown, the controllable source aliasing acquisition data simulation and analysis method of this invention includes the following steps:

[0055] S1. Acquire seismic acquisition information, excitation parameter design field test data, geological information, and time-distance rule information;

[0056] S2. Based on seismic acquisition information and geological information, determine the forward modeling observation parameters using the aliased acquisition noise interference range and interference energy intensity as standards;

[0057] S3. Based on seismic acquisition information, excitation parameter design field test data and forward modeling observation parameters, three-dimensional aliasing acquisition simulation is performed using multiple time interval rules to obtain multiple aliasing acquisition simulation noise data volumes;

[0058] S4. Perform superimposed imaging processing on various mixed acquisition simulated noise data volumes to obtain multiple full-coverage superimposed imaging profiles based on different time interval rules.

[0059] S5. The signal and noise energy of multiple full-coverage superimposed imaging profiles are used as quantitative indicators to quantitatively analyze the degree of noise interference in aliasing acquisition.

[0060] Furthermore, in S1, the seismic acquisition information includes: excitation point and receiver point information, seismic observation scheme, excitation line, receiver line, point distance, sampling time interval, related post-record length, and controlled source scanning signal parameters;

[0061] The field test data for the excitation parameter design include: the length of the excitation test line, relevant pre-shot records and source force signals for different land types;

[0062] Geological information includes: near-surface structure thickness, velocity, and quality factor Q of the exploration area;

[0063] The time-distance rule information is the time-distance rule parameter of the controllable source aliasing acquisition to be analyzed, including at least a first time-distance rule and a second time-distance rule. In some embodiments of the present invention, the first time-distance rule is the previous controllable source acquisition time-distance rule of the exploration area, and the second time-distance rule is the new acquisition time-distance rule.

[0064] Furthermore, in S2, based on seismic acquisition information and geological information, specifically based on near-surface structure and the thickness, velocity, and quality factor Q of major geological strata, a forward modeling observation scheme and aliasing acquisition simulation range are designed, a horizontal layered geological model is established, and the forward modeling wavelet is determined, using the aliasing acquisition noise interferometry range and interferometry energy intensity as standards. Specifically:

[0065] (a) Forward modeling observation scheme and aliasing acquisition simulation range

[0066] The forward modeling observation parameters include the forward modeling wavelet parameters and the forward modeling observation system parameters. The forward modeling simulation observation system parameters are consistent with the seismic acquisition observation parameters of the exploration area. The forward modeling simulation range is: the common center line of the full coverage seismic acquisition in the exploration area is selected, and the information of all shot points and receiver points involved in the full coverage common center line is determined according to the excitation-reception relationship.

[0067] (b) Horizontal layered geological model

[0068] In some implementations, the horizontally layered geological model includes: a near-surface geological model and a mid-to-deep geological model.

[0069] Near-surface geological model: Based on the near-surface structural parameters of the main land types in the work area, calculate the shot-receiver distance range [DX,Dis]. test Initial arrival time within, where DX represents track spacing, and Dis... test The length of the test line for the excitation parameters is indicated; the minimum first arrival of the same shot-receiver distance and its corresponding demonstration point are statistically analyzed, and a near-surface geological model is established based on the near-surface structural geophysical parameters of the demonstration point corresponding to the maximum percentage of the number of traces.

[0070] Medium-deep geological model: Based on the structural characteristics of the exploration area, the location with the maximum burial depth of the target layer is selected, and a medium-deep geological model is established using the geophysical parameters of the main geological strata at that location.

[0071] (c) Orthogonal wavelet

[0072] Harmonic information is extracted from source force signals generated by different land types. The time spectrum of the harmonic information is calculated, and the harmonic order and harmonic energy of each source force signal are statistically analyzed. The source force signal with the highest harmonic order is selected as the forward wavelet. When the harmonic orders are equal, the source force signal with the largest harmonic energy is selected as the forward wavelet.

[0073] Furthermore, forward modeling of the pre-record related to the controllable source specifically includes:

[0074] (a) Perform ray tracing for a given shot-receiver distance x and record the total propagation time T of various seismic waves. sum (i) and its propagation time T between each j-level. layer (i,j), where i represents the identifier of the first arrival wave and the reflection waves of each major geological stratum, i = 1, 2, ... NL represents the reflection waves of each stratum, i = NL+1 represents the first arrival wave, and NL represents the total number of strata in the geological model;

[0075] (b) Define the time series Time = [0, T] b ], a zero matrix Array, whose size is (T b / dt,NL+1), where dt represents the time sampling interval, T bThis indicates the propagation time of the reflected wave from the deepest target layer at the maximum shot-receiver distance; the energy attenuation coefficients of various seismic waves are respectively placed into the zero matrix Array according to formula (1).

[0076]

[0077] In the formula, index represents the time series Time corresponding to the time of seismic wave propagation T. sum (x) The index number corresponding to the minimum difference, i.e., index = {j|min|Time(j)-T} sum (x)|};coeff i (x) represents the energy attenuation coefficient of the first arriving wave and each reflected wave after propagating a distance x, i.e., coeff i (x)=x b b represents the energy attenuation coefficient of the first arrival wave and the reflected wave energy of each major geological stratum in the actual collected data, which is obtained by smoothing and fitting the energy of the first arrival wave and the reflected wave extracted from the gather; R(i) represents the reflection coefficient of each stratum.

[0078] (c) Based on the propagation time of the seismic waves in each layer recorded in step (a), calculate the forward wavelet w after absorption and attenuation according to formula (2). absorb (t,i)

[0079]

[0080] In the formula, fft and ifft represent the forward and inverse Fourier transforms, respectively; w(t) represents the forward wavelet determined in technical step 1); f represents the frequency information of the forward wavelet; Q eff (i) represents the equivalent quality factor of seismic wave propagation.

[0081] (d) Calculate the controllable source correlation pre-record S corresponding to different source-receiver distances x according to formula (3). before (t,x)

[0082]

[0083] Furthermore, in S3, relying on the seismic acquisition information of the exploration area, the aliasing acquisition time-distance rule information, the single-shot acquisition of excitation parameters collected in S1, and the forward modeling parameters designed in S2, three-dimensional aliasing acquisition simulations are performed using various time-distance rules to obtain various aliasing acquisition simulation noise data volumes, specifically including:

[0084] (a) Transform the shot gather information determined by technique S1 into common center point (CMP) gather information, and calculate the shot-receiver distance information x for each channel in each CMP gather. syn The three-dimensional aliased acquisition analog signal data volume S is calculated according to formula (3). signal (t,xsyn ) = S before (t,x syn );

[0085] (b) Define two states of the shot point: the firing state, at station S. Acq Initial excitation time T Acq and coordinate information (X) Acq ,Y Acq Unexcited state, station S unAcq Coordinate information (X) unAcq ,Y unAcq The blast point station number determined in technical step 1) is set to an unexcited state. The first blast point is determined randomly, and the excitation sequence and corresponding start excitation time are calculated according to the following process:

[0086] ①For a certain time T future =max(T) Acq According to formula (4), the station number S that is in the excitation state at this moment is counted. Acq (index), initial excitation time T Acq (index) and coordinate information (X) Acq (index),Y Acq (index));

[0087] index = find{i|T Acq (i)≥ΔT} (4)

[0088] In the formula,

[0089] ② Calculate the distance ΔDis between the unexcited state shot point and the excited state shot point using formula (5). unAcq (j,k), and then combined with the proposed time interval rule to determine the excitation time interval ΔT unAcq (j,k);

[0090]

[0091] In the formula, j = 1, 2, ... N unAcq N unAcq This represents the number of points in the unexcited state; k = 1, 2, ..., N Acq N Acq This represents the number of points in the excited state as counted in formula (4).

[0092] ③ Let T(j,k) = T Acq (index(k))+ΔT unAcq (j,k), determine the blast point station S according to formula (6). unAcq (index j), initial excitation time T (index) j ,index k When the initial firing time of multiple firing points is consistent, one of the firing points is randomly selected as the firing point.

[0093]

[0094] (c) Based on the excitation sequence and excitation start time determined in step (b), perform aliasing acquisition of analog noise data S according to the following procedure. noise :

[0095] ① Let S be a certain firing point. Acq Initial excitation time T Acq and the corresponding detector coordinates (X) R Acq (i),Y R Acq (i)), i = 1, 2, ... N R N R Indicates the firing point S Acq Number of detector points involved;

[0096] ② Statistical time range [T] Acq -T b ,T Acq +T b The initial excitation time T of all excitation points within [ ] Acq (j) and excitation point coordinate information (X) S Acq (j),Y S Acq (j)), j = 1, 2, ... N interf N interf Indicates the firing point S Acq The number of shot points interfering with the data acquisition;

[0097] ③ Let ΔT(j) = T Acq -T Acq (j) Calculate the shot point S according to formula (7) Acq The aliasing noise of the interference in the acquired data correlates with the pre-data S noise (t(j),x(i))

[0098]

[0099] In the formula, x(i) represents the shot point S. Acq The shot-receiver distance to the corresponding i-th receiver point; the time range of the interferometry is expressed as

[0100] (d) Perform cross-correlation operation on the pre-correlation signal and noise data generated in steps (a) and (c) according to formula (8) to obtain the post-correlation signal and noise data volume.

[0101]

[0102] In the formula, t∈[0,T] a ], T a represents the length of the post-seismic acquisition record in the exploration area; f represents the seismic acquisition scan signal in the exploration area.

[0103] Furthermore, in S4, the signal and noise data volumes of the aliased acquisition simulation are superimposed and imaged separately to obtain superimposed imaging profiles of the signal and noise in the full coverage area.

[0104] Furthermore, in S5, the interference degree of aliasing acquisition noise under different time-distance rules is quantitatively evaluated. This is applied in the design stage of the number of coverage acquisitions for controllable source three-dimensional aliasing acquisitions and the analysis and demonstration stage of the acquisition effect under time-distance rules. The quantitative analysis method for aliasing acquisition noise interference includes:

[0105] The energy value of the designated area is calculated according to formula (9) on the imaging profile of the mixed acquisition of analog signal and noise data.

[0106]

[0107] In the formula, Stack data This represents the superimposed profile of the simulated signal or noise data volume Data(t,x) in technical step 3); cmp i Indicates full coverage along the common center point line; T tar T represents the intermediate time in energy statistics; win =2 / (f e -f s ) represents the half-time window for energy calculation, f s f e Indicates the start and end frequencies of the scan signal;

[0108] (b) If, in the design stage of the number of acquisitions for controllable seismic sources, the signal-to-noise ratio difference coefficient η between the previous seismic acquisition time interval rule 1 and the new acquisition time interval rule 2 is calculated according to formula (10), the number of acquisitions for the new acquisition coverage can be expressed as Fold2=η 2 ·Fold1;

[0109]

[0110] In the formula, Energy Noise1 Energy Noise2These represent the superimposed imaging energy of simulated noise data acquired under time-distance rules 1 and 2, respectively; CMPs and CMPe represent the start and end common center point gather numbers on the common center point line with full coverage.

[0111] (c) In the quantitative demonstration of the effect of time-distance rule acquisition, the ratio of aliased acquisition analog signal to noise energy Ratio is calculated according to formula (11), and the quantitative evaluation threshold Threshold is set. When the energy ratio Ratio≥Threshold, it is considered that the interference of aliased acquisition noise on the target layer imaging is acceptable.

[0112]

[0113] In the formula, Energy Signal Energy Noise These represent the superimposed imaging energy of analog signals and noise data acquired at the same time interval using regular aliasing.

[0114] The specific embodiments of the present invention are further described below with reference to specific examples.

[0115] This invention addresses the problem of quantitative analysis of noise interference in controlled-source 3D aliased acquisitions, proposing a rapid simulation and analysis method based on aliased acquisition data. The following example, using the application effect in the design phase of coverage times for controlled-source 3D aliased acquisitions in a western Chinese exploration area, illustrates the implementation steps and method of this invention:

[0116] S1. Acquire seismic acquisition information, excitation parameter design field test data, geological information, and time-distance rule information. Collect acquisition parameters, excitation parameter field test data, geophysical parameter information of major stratigraphic layers in the exploration area, and acquisition time-distance rules for comparative analysis from previous 3D controlled-source seismic acquisition projects P5JQ in the exploration area.

[0117] (a) Seismic acquisition parameters: Seismic acquisition observation parameters are shown in Table 1. Information on seismic acquisition excitation point and receiver point, seismic sampling time interval 2ms, and correlation post-record length 10s; The design results of controllable source scanning signal parameters are as follows: start and end frequency 1.5-96Hz, scan length 20s, start and end slope 0.53s.

[0118] Table 1

[0119]

[0120] (b) Field test data for excitation parameter design: Locations of field tests for excitation parameter design in the exploration area are as follows: Figure 2 Image a shows a satellite image of the exploration area. Figure 2Image a shows previous seismic satellite images of the exploration area. The dashed line in the image is the excitation parameter test line, and the dots in the image represent test points for different land types. The excitation test line is 33km long and collects relevant pre-seismic data and force signals from surface excitation points in farmland, large desert, and small desert areas.

[0121] (c) Near-surface and major geological strata information: The near-surface structural parameters of the main land types in the exploration area are shown in Table 2. Based on the structural characteristics of the exploration area, the location with the maximum burial depth of the target layer was selected, and the burial depth, layer velocity information and quality factor Q of the main geological strata at this location were statistically analyzed, as shown in Table 3, which is the table of main geological strata parameters of the exploration area.

[0122] Table 2

[0123] Argumentation points V0(m / s) H0(m) V1(m / s) H1(m) V2(m / s) farmland area 343 5.5 535 6.5 1788 Dasha District 505 17.7 2016 Xiaosha District 321 2.4 537 8.4 1779

[0124] Table 3

[0125] earthquake horizon geological strata Burial depth (m) Time (s) Layer velocity (m / s) Quality factor Q <![CDATA[T K ]]> Cretaceous base 3910 2.79 2886 144.1 <![CDATA[T J1S2 ]]> San Gonghe Section 2 Top 4232 2.99 3220 183.4 <![CDATA[T J1S ]]> Sangonghe Formation Bottom 4510 3.15 3475 216.9 <![CDATA[T J1b ]]> Jurassic period 5260 3.56 3704 249.6 <![CDATA[T T1b ]]> Baikouquan Formation Bottom 6680 4.23 4207 330.3 <![CDATA[T P2w ]]> Urho Group bottom 7570 4.64 4341 353.9 <![CDATA[T C ]]> Carboniferous top 8533 5.00 4815 444.5

[0126] (d) Acquisition time interval rules: Previous controllable source acquisition time interval rule-1 and new acquisition time interval rule-2 for the exploration area. Controllable source cascading acquisition time interval rules are as follows... Figure 2 As shown in b. Figure 2 b represents different acquisition time interval rules. Time interval rule-1 is the time interval rule used in previous controlled-source seismic acquisitions in the exploration area, and time interval rule-2 is the time interval rule to be used in new acquisitions in the exploration area.

[0127] S2. Based on seismic acquisition information and geological information, determine the forward modeling observation parameters using the aliased acquisition noise interference range and interference energy intensity as standards;

[0128] (a) Forward modeling observation scheme: The forward modeling observation parameters are consistent with the seismic acquisition observation parameters of the exploration area; the common midpoint line of the full coverage seismic acquisition in the exploration area is selected, and the information of all shot points and receiver points involved in the common midpoint (CMP) is determined according to the excitation-reception relationship.

[0129] (b) Geological Model: Based on near-surface thickness and velocity information, the first arrival time within the offset range [25m, 33000m] was calculated to determine the minimum first arrival time of channels with the same offset and their corresponding verification points. The minimum first arrival channel accounts for 98.94% of the verification points for near-surface structures in the Dasha area. This is because the near-surface model in the geological model is determined to be the near-surface structure of the Dasha area.

[0130] (c) Forward Wavelet: The harmonic order and harmonic energy of the source force signals from the excitation points in the farmland area, the large sandy area, and the small sandy area were statistically analyzed. Statistical analysis showed that the source force signal from the small sandy area had the highest harmonic order (8th) and the strongest energy. The forward wavelet selected was the source force signal from the small sandy area, with a wavelet length of 20s. Figure 3 As shown, Figure 3 To design tests based on previous excitation parameters in the exploration area, controllable source force signals were collected from the surface of the small sand area, with a force signal length of 20s.

[0131] S3. Based on seismic acquisition information, excitation parameter design field test data, and forward modeling observation parameters, three-dimensional aliasing acquisition simulations are performed using various time interval rules to obtain various aliasing acquisition simulation noise data volumes.

[0132] Based on seismic acquisition information from the exploration area, the excitation parameters collected in S1 (test-acquired single-shot data) and the design forward modeling parameters in S2 were used to perform a three-dimensional aliased acquisition simulation according to two time-distance rules: the previous acquisition time-distance rule-1 and the new acquisition time-distance rule-2. The resulting noise data volume from the aliased acquisition simulation is shown below. Figure 4 As shown, Figure 4 a represents the noise single-shot data simulated using aliasing acquisition with time-distance rule-1; Figure 4 b represents the noise single-shot data simulated using aliasing acquisition with time-distance rule-2. As can be seen from the figure, the degree of interference of aliasing acquisition noise varies significantly depending on the time-distance rule for controlled-source seismic acquisition. Under the same source spacing conditions, the smaller the excitation time interval, the greater the temporal and spatial range and interference energy level of the aliasing acquisition noise interference.

[0133] S4. Perform superimposed imaging processing on various mixed acquisition simulated noise data volumes to obtain multiple full-coverage superimposed imaging profiles based on different time interval rules.

[0134] The aliased acquisition simulation noise data corresponding to the two time-distance rules in S3 are superimposed for imaging processing. Figure 5 To overlay imaging profiles over partially full-coverage areas Figure 5 a represents the noise superposition profile simulated using time-distance rule-1 for aliasing acquisition; Figure 5 b represents the noise superposition profile simulated using time-distance rule-2 for aliasing acquisition. As can be seen from the figure, the degree of noise interference varies across the noise imaging profiles simulated by aliasing acquisition under different time-distance rules.

[0135] S5. The signal and noise energy of multiple full-coverage superimposed imaging profiles are used as quantitative indicators to quantitatively analyze the degree of noise interference in aliasing acquisition.

[0136] Based on the burial depth and velocity information of each target layer in the geological model constructed by S2, the reflection time of each target layer is calculated. Taking the reflection time of the target layer as the center, the energy statistical half-time window T is used. win=2 / (96Hz-1.5Hz)=0.022s to calculate the noise interference energy of each reflection layer during aliasing acquisition. Taking the noise interference level at 5s in the deepest target layer as an example, the energy values ​​of each CMP point on the superimposed imaging profile of the simulated noise data from the two time-distance rule aliasing acquisitions are statistically analyzed. The energy statistics time window is [4.978s, 5.022s]. Figure 5 As shown in the dashed rectangular box, the energy value statistical curve is as follows: Figure 6 As shown.

[0137] During the coverage design process, the time-distance rule for controllable source overlapping acquisitions in the exploration area was time-distance rule 1, with 1428 coverage times. When the time-distance rule for new acquisitions in the exploration area is time-distance rule 2, the signal-to-noise ratio difference coefficient of a single acquisition shot is... The coverage count is designed as follows

[0138] It should be particularly noted that each step in the various embodiments of the above-mentioned controllable source aliasing acquisition data simulation and analysis method can be interleaved, substituted, added, or deleted. Therefore, these reasonable permutations and combinations of the controllable source aliasing acquisition data simulation and analysis method should also fall within the protection scope of this invention, and the protection scope of this invention should not be limited to the embodiments.

[0139] Based on the above objectives, a second aspect of the present invention proposes a controllable source superimposed acquisition data simulation and analysis device. Figure 7 The diagram shown is a schematic representation of an embodiment of the controllable seismic source aliasing acquisition data simulation and analysis device provided by the present invention. Figure 7 As shown, the controllable seismic source aliasing acquisition data simulation and analysis device of this invention includes the following modules:

[0140] Information acquisition module 011 is configured to acquire seismic acquisition information, excitation parameter design field test data, geological information, and time-distance rule information.

[0141] Observation design module 012 is configured to determine forward modeling observation parameters based on seismic acquisition information and geological information, using the aliased acquisition noise interferometry range and interferometry energy intensity as standards.

[0142] The aliasing acquisition simulation module 013 is configured to perform three-dimensional aliasing acquisition simulation based on seismic acquisition information, excitation parameters, field test data, and forward modeling observation parameters, using various time interval rules to obtain various aliasing acquisition simulation noise data volumes.

[0143] The imaging processing module 014 is configured to perform superimposed imaging processing on multiple aliased acquisition analog noise data volumes to obtain multiple full-coverage superimposed imaging profiles based on different time interval rules.

[0144] Analysis module 015 is configured to perform quantitative analysis on the degree of noise interference in aliasing acquisition using the signal and noise energy of multiple full-coverage superimposed imaging profiles as quantitative indicators.

[0145] In view of the above objectives, a third aspect of the present invention provides a computer device. Figure 8 The diagram shown is a schematic representation of an embodiment of the computer device provided by the present invention. Figure 3 As shown, the computer device of this embodiment includes the following means: at least one processor 021; and a memory 022, the memory 022 storing computer instructions 023 that can be executed on the processor, the instructions implementing the steps of the above method when executed by the processor.

[0146] The present invention also provides a computer-readable storage medium. Figure 9 The diagram shown is a schematic representation of an embodiment of the computer-readable storage medium provided by the present invention. Figure 9 As shown, computer-readable storage medium 031 stores a computer program 032 that, when executed by a processor, performs the methods described above.

[0147] Finally, it should be noted that those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program for the controllable source aliasing acquisition data simulation and analysis method can be stored in a computer-readable storage medium. When executed, the program can include the processes of the embodiments of the above methods. The storage medium for the program can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc. The above computer program embodiments can achieve the same or similar effects as any of the corresponding foregoing method embodiments.

[0148] Furthermore, the method disclosed in the embodiments of the present invention can also be implemented as a computer program executed by a processor, which may be stored in a computer-readable storage medium. When the computer program is executed by the processor, it performs the functions defined in the method disclosed in the embodiments of the present invention.

[0149] Furthermore, the above-described method steps and system units can also be implemented using a controller and a computer-readable storage medium for storing a computer program that enables the controller to perform the functions of the above-described steps or units.

[0150] Those skilled in the art will also understand that the various exemplary logic blocks, modules, circuits, and algorithm steps described in conjunction with the disclosure herein can be implemented as electronic hardware, computer software, or a combination of both. To clearly illustrate this interchangeability between hardware and software, the functionality of various illustrative components, blocks, modules, circuits, and steps has been generally described. Whether this functionality is implemented as software or as hardware depends on the specific application and the design constraints imposed on the system as a whole. Those skilled in the art can implement the functionality in various ways for each specific application, but such implementation decisions should not be construed as departing from the scope of the embodiments disclosed herein.

[0151] In one or more exemplary designs, functionality may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software, the functionality may be stored as one or more instructions or code on or transmitted via a computer-readable medium. Computer-readable media include computer storage media and communication media, including any medium that facilitates the transfer of a computer program from one location to another. Storage media may be any available medium accessible to a general-purpose or special-purpose computer. By way of example, and not limitation, computer-readable media may include RAM, ROM, EEPROM, CD-ROM or other optical disc storage devices, disk storage devices or other magnetic storage devices, or any other medium that may be used to carry or store the required program code in the form of instructions or data structures and is accessible to a general-purpose or special-purpose computer or a general-purpose or special-purpose processor. Furthermore, any connection may be appropriately referred to as computer-readable media. For example, if software is transmitted from a website, server, or other remote source using coaxial cable, fiber optic cable, twisted pair, digital subscriber line (DOL), or wireless technologies such as infrared, radio, and microwave, then the aforementioned coaxial cable, fiber optic cable, twisted pair, DOL, or wireless technologies such as infrared, radio, and microwave are all included in the definition of media. As used herein, disks and optical discs include compact discs (CDs), laser discs, optical discs, digital versatile discs (DVDs), floppy disks, and Blu-ray discs, where disks typically reproduce data magnetically, while optical discs reproduce data optically using lasers. Combinations of the above should also be included within the scope of computer-readable media.

[0152] The above are exemplary embodiments disclosed in this invention. However, it should be noted that various changes and modifications can be made without departing from the scope of the embodiments of this invention as defined by the claims. The functions, steps, and / or actions of the methods according to the disclosed embodiments described herein do not need to be performed in any particular order. Furthermore, although the elements disclosed in the embodiments of this invention may be described or claimed individually, they may be understood as multiple unless explicitly limited to a singular number.

[0153] It should be understood that, as used herein, the singular form “a” is intended to include the plural form as well, unless the context clearly supports an exception. It should also be understood that, as used herein, “and / or” refers to any and all possible combinations of one or more of the associated listed items.

[0154] The embodiment numbers disclosed in the above embodiments of the present invention are merely for description and do not represent the superiority or inferiority of the embodiments.

[0155] Those skilled in the art will understand that all or part of the steps of the above embodiments can be implemented by hardware or by a program instructing related hardware. The program can be stored in a computer-readable storage medium, such as a read-only memory, a disk, or an optical disk.

[0156] Those skilled 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 invention (including the claims) is limited to these examples. Within the framework of the invention, technical features of the above embodiments or different embodiments can be combined, and many other variations of different aspects of the invention exist, which are not provided in the details for the sake of brevity. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the invention should be included within the protection scope of the invention.

Claims

1. A method for simulating and analyzing controllable source superimposed acquisition data, characterized in that, include: Acquire seismic acquisition information, field test data for excitation parameter design, geological information, and time-distance rule information; Based on the aforementioned seismic acquisition information and geological information, the forward modeling observation parameters are determined using the aliased acquisition noise interference range and interference energy intensity as standards. Based on the earthquake acquisition information, excitation parameter design field test data and forward modeling observation parameters, three-dimensional aliasing acquisition simulations were performed using various time interval rules to obtain various aliasing acquisition simulation noise data volumes. The various aliased acquisition simulated noise data volumes are respectively subjected to superimposed imaging processing to obtain multiple full-coverage superimposed imaging profiles based on different time interval rules; The signal and noise energy of multiple full-coverage superimposed imaging profiles are used as quantitative indicators to quantitatively analyze the degree of noise interference in aliasing acquisition; Based on the aforementioned seismic acquisition information and geological information, the forward modeling observation parameters are determined using the aliased acquisition noise interferometry range and interferometry energy intensity as standards, including: The forward modeling observation parameters include forward modeling wavelet parameters and forward modeling observation system parameters. Based on the seismic acquisition information and geological information, the forward modeling wavelet parameters are determined using the aliasing acquisition noise interference range and interference energy intensity as standards. The forward modeling observation system parameters are consistent with the seismic acquisition observation parameters of the exploration area. Forward modeling simulation is performed based on the forward modeling observation parameters. The forward modeling simulation range is the full-coverage common center line of the seismic acquisition in the exploration area. Based on the excitation-reception relationship, the information of all shot points and receiver points involved in the full-coverage common center line is determined. The quantitative analysis of the degree of noise interference in aliasing acquisitions is performed using the signal and noise energy of multiple full-coverage superimposed imaging profiles as quantitative indicators, including: Based on the burial depth and velocity information of each target layer in the geological model, the reflection time of each target layer is calculated. Taking the reflection time of the target layer as the center, the interference energy of the noise from the aliasing acquisition of each reflection layer is calculated based on the energy statistical half-time window. The energy values ​​of each CMP point on the superimposed imaging profile of the simulated noise data of the two time-distance rules are statistically analyzed. The number of coverage times is designed based on the time-distance rules. The superimposed imaging energy of aliased acquired simulated noise data is calculated at CMP points on the superimposed imaging profile of the full coverage area. Based on the noise data superimposed imaging energy, the signal-to-noise ratio difference coefficient of a single seismic acquisition shot under the first and second time-distance rules is calculated, and the number of coverage operations is designed based on the signal-to-noise ratio difference coefficient. Based on the energy ratio calculated from the aliased acquisition analog signal and noise, a quantization evaluation threshold is set. In response to the energy ratio being greater than or equal to the quantization evaluation threshold, the degree of interference of the aliased acquisition noise with the target layer imaging is output as acceptable.

2. The method for simulation and analysis of controllable source superimposed acquisition data according to claim 1, characterized in that, The earthquake acquisition information includes: excitation point and receiver point information, earthquake observation scheme, excitation line, receiver line, point distance, sampling time interval, correlation post-recording length, and controllable source scanning signal parameters; The field test data for the excitation parameter design includes: the length of the excitation test line, the pre-shot records and source force signals collected for different land types; The geological information includes: near-surface structural thickness, velocity, and quality factor of the exploration area; The time interval rule information includes at least: a first time interval rule and a second time interval rule.

3. The method for simulation and analysis of controllable source superimposed acquisition data according to claim 1, characterized in that, The forward modeling observation parameters are determined based on the interferometric range of aliased acquisition noise and the interferometric energy intensity, including: The forward modeling observation scheme and aliasing acquisition simulation range were designed based on the interference range of aliasing acquisition noise and interference energy intensity. A horizontal layered geological model was established and the forward modeling wavelet was determined.

4. The method for simulation and analysis of controllable source superimposed acquisition data according to claim 3, characterized in that, The horizontally layered geological model includes: a near-surface geological model and a mid-to-deep geological model.

5. The method for simulation and analysis of controllable source superimposed acquisition data according to claim 2, characterized in that, Based on the seismic acquisition information, excitation parameter design field test data, and the forward modeling observation parameters, three-dimensional aliasing acquisition simulations are performed using various time-distance rules to obtain various aliasing acquisition simulation noise data volumes, including: Based on the earthquake acquisition information, the single-shot data acquired in the field test of the excitation parameter design, and the forward modeling observation parameters, three-dimensional aliasing acquisition simulation is performed using the first time-distance rule and the second time-distance rule respectively to obtain the aliasing acquisition simulation noise data volume.

6. The method for simulation and analysis of controllable source superimposed acquisition data according to claim 2, characterized in that, Based on the seismic acquisition information, excitation parameter design field test data, and the forward modeling observation parameters, three-dimensional aliasing acquisition simulations are performed using various time-distance rules to obtain various aliasing acquisition simulation noise data volumes, including: The ray tracing method, which uses the energy decay law of actual data, and the multi-source random aliasing acquisition simulation method are used to simulate the three-dimensional aliased acquisition data signal and noise data volume.

7. A controllable source superimposed acquisition data simulation and analysis device, characterized in that, include: The information acquisition module is configured to acquire seismic acquisition information, excitation parameter design field test data, geological information, and time-distance rule information. An observation design module is configured to determine forward modeling observation parameters based on the seismic acquisition information and geological information, using the aliased acquisition noise interferometry range and interferometry energy intensity as standards. The aliasing acquisition simulation module is configured to perform three-dimensional aliasing acquisition simulations based on the seismic acquisition information, excitation parameters, field test data, and forward modeling observation parameters, using various time interval rules to obtain various aliasing acquisition simulation noise data volumes. An imaging processing module is configured to perform superimposed imaging processing on the various aliased acquired simulated noise data volumes respectively to obtain multiple full-coverage superimposed imaging profiles based on different time interval rules. Analysis module, configured to perform quantitative analysis on the degree of interference of aliasing acquisition noise using the signal and noise energy of multiple full-coverage superimposed imaging profiles as quantitative indicators; Based on the aforementioned seismic acquisition information and geological information, the forward modeling observation parameters are determined using the aliased acquisition noise interferometry range and interferometry energy intensity as standards, including: The forward modeling observation parameters include forward modeling wavelet parameters and forward modeling observation system parameters. Based on the seismic acquisition information and geological information, the forward modeling wavelet parameters are determined using the aliasing acquisition noise interference range and interference energy intensity as standards. The forward modeling observation system parameters are consistent with the seismic acquisition observation parameters of the exploration area. Forward modeling simulation is performed based on the forward modeling observation parameters. The forward modeling simulation range is the full-coverage common center line of the seismic acquisition in the exploration area. Based on the excitation-reception relationship, the information of all shot points and receiver points involved in the full-coverage common center line is determined. The quantitative analysis of the degree of noise interference in aliasing acquisitions is performed using the signal and noise energy of multiple full-coverage superimposed imaging profiles as quantitative indicators, including: Based on the burial depth and velocity information of each target layer in the geological model, the reflection time of each target layer is calculated. Taking the reflection time of the target layer as the center, the interference energy of the noise from the aliasing acquisition of each reflection layer is calculated based on the energy statistical half-time window. The energy values ​​of each CMP point on the superimposed imaging profile of the simulated noise data of the two time-distance rules are statistically analyzed. The number of coverage times is designed based on the time-distance rules. The superimposed imaging energy of aliased acquired simulated noise data is calculated at CMP points on the superimposed imaging profile of the full coverage area. Based on the noise data superimposed imaging energy, the signal-to-noise ratio difference coefficient of a single seismic acquisition shot under the first and second time-distance rules is calculated, and the number of coverage operations is designed based on the signal-to-noise ratio difference coefficient. Based on the energy ratio calculated from the aliased acquisition analog signal and noise, a quantization evaluation threshold is set. In response to the energy ratio being greater than or equal to the quantization evaluation threshold, the degree of interference of the aliased acquisition noise with the target layer imaging is output as acceptable.

8. A computer device, characterized in that, include: At least one processor; as well as A memory storing computer instructions executable on the processor, which, when executed by the processor, implement the steps of the method according to any one of claims 1-6.

9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1-6.

Images