CN117368969A - Method, device and equipment for simulating far-field wavelet based on near-field recording - Google Patents
Method, device and equipment for simulating far-field wavelet based on near-field recording Download PDFInfo
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Abstract
The invention discloses a method, a device and equipment for simulating far-field wavelets based on near-field recording, wherein the method can comprise the following steps: determining the distance from the source to the near-field detector and the distance from the virtual source to the near-field detector based on the near-field record of the near-field detector, the motion speed of the near-field detector and the travel time of each sampling time to construct an ideal wavelet corresponding to each sampling time; determining the distance from a seismic source to a far-field point and the distance from a virtual seismic source to the far-field point based on the acquired near-field record of the near-field detector; determining the travel time of far-field wavelets right below the seismic source array based on the corresponding sampling points and time direction sampling intervals during travel; the far-field wavelet is simulated based on the distance of the source to the far-field point, the distance of the virtual source to the far-field point, the travel time of the far-field wavelet directly under the source array, and the ideal wavelet. The method considers the influence of the motion of the bubble and the gun array in the time domain, can more accurately simulate far-field wavelets, and is more in line with the actual situation.
Description
Technical Field
The invention relates to the technical field of geophysical exploration, in particular to a method, a device and equipment for simulating far-field wavelets based on near-field recording.
Background
In marine seismic data processing, signal deconvolution is a fundamental and critical step that suppresses bubbles, ghosts, and simultaneously achieves zero phasing of wavelets. Signal deconvolution must require an accurate wavelet information, the wavelet determines the effect of signal deconvolution, and we therefore first calculate the wavelet.
In data processing, there are various methods for obtaining wavelets, and methods based on far-field wavelets and seismic data driving are commonly used. The conventional far-field wavelet is a theoretical wavelet obtained by forward modeling under the assumed hydrostatic condition, and has larger wavelet difference from the actual acquisition, so that the subsequent deconvolution effect is sometimes poor; the method for driving the seismic data utilizes the seismic data to extract wavelets, so that the effect is good, but in shallow water areas, as various seismic waves are mixed together, an ideal wavelet is difficult to extract; and the data driving method is a statistical method based on multiple gathers, and is difficult to realize gather-by-gather processing.
Disclosure of Invention
The present invention has been made in view of the above problems, and it is an object of the present invention to provide a method, apparatus and device for simulating far-field wavelets based on near-field recording that overcomes or at least partially solves the above problems.
In a first aspect, an embodiment of the present invention provides a method for simulating a far-field wavelet based on near-field recording, which may include:
determining a motion speed of the near field pickup based on a speed of the source vessel;
determining travel time for each sampling instant based on the time-wise sampling interval;
determining the distance from a seismic source to the near-field detector and the distance from a virtual seismic source to the near-field detector based on near-field recording of the near-field detector, the motion speed of the near-field detector and the travel time of each sampling time to construct an ideal wavelet corresponding to each sampling time;
determining the distance from a seismic source to a far-field point and the distance from a virtual seismic source to the far-field point based on the acquired near-field record of the near-field detector;
determining the travel time of far-field wavelets right below the seismic source array based on the corresponding sampling points and time direction sampling intervals during travel;
the far-field wavelet is simulated based on the distance of the source to the far-field point, the distance of the virtual source to the far-field point, the travel time of the far-field wavelet directly below the source array, and the ideal wavelet.
Optionally, the method may further include:
a near field recording and a time-wise sampling interval of the near field pickup are acquired.
Optionally, the distance from the source to the near field pickup is determined based on the near field record of the near field pickup, the motion speed of the near field pickup and the travel time of each sampling time, and is determined by the following formula:
wherein i is the near field pickup number, j is the air gun number, j=1, 2, …, n, n is the number of air guns; x is x j ，y j Respectively the horizontal and vertical coordinates of the air gun; z j Is the depth of the air gun; t is t k Is the moment of seismic data acquisition; v B Is a bubbleThe speed of the floating is generally 1m/s.
Optionally, the distance from the virtual source to the near field pickup is determined based on the near field record of the near field pickup, the motion speed of the near field pickup, and the travel time of each sampling time, and is determined by the following formula:
wherein i is the near field pickup number, j is the air gun number, j=1, 2, …, n, n is the number of air guns; x is x j ，y j Respectively the horizontal and vertical coordinates of the air gun; z j Is the depth of the air gun; t is t k Is the moment of seismic data acquisition; v B The speed of the air bubbles floating is generally 1m/s.
Optionally, the constructing the ideal wavelet corresponding to each sampling time is determined by the following formula:
wherein v is the propagation speed of the seismic wave in the water, and is generally 1500m/s; c is the reflection coefficient of the sea surface, typically 1.0;
and->For non-integer sampling points, interpolation using spline functions or sinc functions is required.
Optionally, the distance from the source to the far-field point is determined based on the acquired near-field record of the near-field detector, and is determined by the following formula:
wherein i is the near field pickup number, j is the air gun number, j=1, 2, …, n, n is the number of air guns; x and Y are the horizontal and vertical coordinates of the center of the air gun array respectively; z is the depth of the far field point, typically 10000m; x is x j ，y j Respectively the horizontal and vertical coordinates of the air gun; z j Is the depth of the air gun.
Optionally, the distance from the virtual source to the far-field point is determined based on the acquired near-field record of the near-field detector, and is determined by the following formula:
wherein i is the near field pickup number, j is the air gun number, j=1, 2, …, n, n is the number of air guns; x and Y are the horizontal and vertical coordinates of the center of the air gun array respectively; z is the depth of the far field point, typically 10000m; x is x j ，y j Respectively the horizontal and vertical coordinates of the air gun; z j Is the depth of the air gun.
Optionally, the modeling the far-field wavelet is determined by the following formula based on the distance from the source to the far-field point, the distance from the virtual source to the far-field point, the travel time of the far-field wavelet directly under the airgun array, and the ideal wavelet:
wherein p' i Ideal wavelets for each airgun; v is the propagation velocity of the seismic wave in the water, generally 1500m/s; c is the reflection coefficient of the sea surface, typically 1.0;
and->For non-integral sampling points, spline functions or sinc functions are needed to be used for interpolationValues.
In a second aspect, an embodiment of the present invention provides an apparatus for simulating a far-field wavelet based on near-field recording, which may include:
the motion speed determining module is used for determining the motion speed of the near-field geophone based on the speed of the source ship;
a travel time determining module for determining a travel time of each sampling time based on the time direction sampling interval;
the ideal wavelet construction module is used for determining the distance from a seismic source to the near-field detector and the distance from a virtual seismic source to the near-field detector based on the near-field record of the near-field detector, the motion speed of the near-field detector and the travel time of each sampling moment so as to construct ideal wavelets corresponding to each sampling moment;
the far-field point distance determining module is used for determining the distance from the source to the far-field point and the distance from the virtual source to the far-field point based on the acquired near-field record of the near-field detector;
the far-field wavelet travel time determining module is used for determining the travel time of the far-field wavelet under the air gun array based on the corresponding sampling point number and the time direction sampling interval during travel;
the far-field wavelet simulation module is used for simulating the far-field wavelet based on the distance from the source to the far-field point, the distance from the virtual source to the far-field point, the travel time of the far-field wavelet right below the air gun array and the ideal wavelet.
In a third aspect, an embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored, which program, when being executed by a processor, implements a method of simulating far-field wavelets based on near-field recording as described in the first aspect.
In a fourth aspect, an embodiment of the present invention provides a computer device, including a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the method for simulating far-field wavelets based on near-field recording according to the first aspect when executing the program.
The technical scheme provided by the embodiment of the invention has the beneficial effects that at least:
the embodiment of the invention provides a method, a device and equipment for simulating far-field wavelets based on near-field recording. Compared with a frequency domain method, the embodiment of the invention considers the influence of bubbles and gun array motion in the time domain, can more accurately simulate far-field wavelets, and is more in line with the actual situation. The method can provide more accurate wavelets for signal deconvolution and the like, and is mainly used for providing more accurate wavelets for the steps of subsequent seismic processing such as signal deconvolution and the like after simulating far field wavelets, so that better processing results are obtained for the signal deconvolution and the like.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention may be realized and attained by the structure particularly pointed out in the written description and drawings.
The technical scheme of the invention is further described in detail through the drawings and the embodiments.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
FIG. 1 is a flow chart of a method for simulating far-field wavelets based on near-field recording provided in an embodiment of the present invention;
fig. 2 is an example of near field recording provided in an embodiment of the invention;
FIG. 3 is an idealized wavelet determined based on FIG. 2 provided in an embodiment of the present invention;
FIG. 4 is a far-field wavelet based on the simulation of FIG. 3 provided in an embodiment of the present invention;
fig. 5 is a schematic structural diagram of an apparatus for simulating far-field wavelets based on near-field recording according to an embodiment of the present invention.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
Term interpretation:
near field recording: english near field hydrophone, in petroleum exploration, is generally translated as: near field recording. Since the near field pickups are one meter directly above each gun, these pickups are called near field pickups (hydrophones), where near field refers to being very close to the gun array, typically 1m.
Far field: theoretically the distance of the far field is to satisfyf is the frequency, D is the maximum size of the gun array space, and v is the propagation velocity of the acoustic wave in the water. It is generally required that it is more than 300m from the airgun array.
Far-field wavelet: the wavelet measured by the far-field detector is the far-field wavelet. If actually measured, the requirements are: a deep water area with calm sea surface is selected, and a detector for detecting far-field wavelets is placed in deep water of hundreds of meters below the air gun array, wherein the depth of the detector is related to the size of the air gun array. To avoid contamination of the far-field wavelet, the detector-to-seafloor distance needs to be kept large enough so that the seafloor reflection reaches the detector much longer than the source wavelet reaches the detector. The method for obtaining far-field wavelets by actual measurement has high environmental requirements, needs to place detectors at a certain depth (usually hundreds of meters underwater), has high measurement cost and high operation difficulty, and is not used much in actual seismic exploration. In practical seismic data processing, data-driven methods (extraction from seismic data) and near-field recording-based methods are often employed.
OBN Ocean Bottom Node, a submarine node for short, is a multi-component seismic acquisition mode which is positioned on the seabed and can independently acquire and record seismic signals, and is the most rapidly developed marine seismic exploration mode at present.
The embodiment of the invention provides a method for simulating far-field wavelets based on near-field recording, which utilizes near-field recording to simulate far-field wavelets in the marine seismic data processing process, provides wavelet information for subsequent wavelet deconvolution, multiple wave suppression and other processes, and further improves the imaging quality of seismic data.
Referring to fig. 1, the method may include:
and S11, acquiring near field recording and time direction sampling intervals of the near field detector.
The step is to acquire the acquired data, namely acquiring the near-field record p i (x i ,y i ,z i ) And a time-wise sampling interval Δt;
where i is the near field pickup number, i=1, 2, …, m, and m is the number of near field pickup. X is x i ，y i The horizontal and vertical coordinates of the near field detector; z i Is the depth of the near field pickup.
Referring to fig. 2, an example of a near field recording is obtained, in which the gun array is composed of 18 source-excited air guns, and 18 near field recordings are corresponding.
And step S12, determining the movement speed of the near-field geophone based on the speed of the source boat.
Obtaining the motion speed v of the near-field detector in the x and y directions x And v y ：
v x ＝v boat ·cosθ (1)
v y ＝v boat ·sinθ (2)
Wherein v is boat The speed of the seismic source ship is obtained by field recording or calculated by the distance and time between two ships when the seismic source is excited; θ is the angle between the heading of the source vessel and the x-axis.
Step S13, determining the travel time of each sampling moment based on the time direction sampling interval.
Calculating travel time t of each sampling time k ：
t k ＝(k-1)Δt (3)
Where k is the sequence number of the sampling instant and Δt is the time-wise sampling interval.
And S14, determining the distance from the source to the near-field detector and the distance from the virtual source to the near-field detector based on the near-field record of the near-field detector, the motion speed of the near-field detector and the travel time of each sampling time so as to construct an ideal wavelet corresponding to each sampling time.
After the air gun is excited, the excited energy is downwards spread to form earthquake waves as a seismic source; but some of the energy propagates upwards, and as the water surface is a very good reflecting surface, these waves are reflected by the water surface after reaching the water surface, and propagate downwards again to form new seismic waves, which can be regarded as being emitted by a virtual source, which is symmetrical with the gun array (source) about the water surface. The air gun taking ideal wavelets as a seismic source in the embodiment of the invention is a gun array consisting of a plurality of air guns, and the wavelets excited by each air gun are the ideal wavelets.
On the one hand, each sampling instant is determined, and the distance r from the source (air gun) to the near-field detector ij ：
On the other hand, determining the distance from the virtual focus to the near-field detector at each sampling moment
Wherein i is the near field pickup number, j is the air gun number, j=1, 2, …, n, n is the number of air guns; x is x j ，y j Respectively of air gunsHorizontal and vertical coordinates; z j Is the depth of the air gun; t is t k Is the moment of seismic data acquisition; v B The speed of the air bubble floating is generally 1m/s;
then, an ideal wavelet corresponding to each sampling moment is constructed based on the following formula (6):
wherein v is the propagation speed of the seismic wave in the water, and is generally 1500m/s; c is the reflection coefficient of the sea surface, typically 1.0;
and->For non-integer sampling points, interpolation using spline functions or sinc functions is required. An example of a determined ideal wavelet is shown with reference to fig. 3.
And S15, determining the distance from the source to the far-field point and the distance from the virtual source to the far-field point based on the acquired near-field record of the near-field detector.
In the embodiment of the invention, the air gun used as the seismic source is a gun array consisting of a plurality of air guns, and the gun array is generally rectangular, and the coordinates of the center of the gun array are X and Y. Thus, the distance of the source to the far field point is determined by the following equation (7):
determining the distance of the virtual source to the far field point by the following equation (8):
where j is the air gun number, j=1,2, …, n, n is the number of air guns; x and Y are the horizontal and vertical coordinates of the center of the air gun array respectively; z is the depth of the far field point, typically 10000m; x is x j ，y j Respectively the horizontal and vertical coordinates of the air gun; z j Is the depth of the air gun.
And S16, determining the travel time of far-field wavelets right below the seismic source array based on the corresponding sampling points and the time direction sampling intervals during travel.
Travel time t of far-field wavelet directly below air gun array l ：
t l ＝(l-1)Δt (9)
Where l is the number of samples corresponding to the travel time and Δt is the time-wise sampling interval.
And S17, simulating and generating far-field wavelets based on the distance from the source to the far-field point, the distance from the virtual source to the far-field point, the travel time of the far-field wavelets right below the source array and the ideal wavelets.
Is determined by the following formula:
wherein p' i Ideal wavelets for each airgun; v is the propagation velocity of the seismic wave in the water, generally 1500m/s; c is the reflection coefficient of the sea surface, typically 1.0;
and->For non-integer sampling points, interpolation using spline functions or sinc functions is required.
Referring to fig. 4, an example of a simulated far-field wavelet is shown.
The invention utilizes near field record to calculate ideal wavelet, then calculates vertical far field wavelet, and realizes the calculation process in time domain. Compared with a frequency domain method, the embodiment of the invention considers the influence of bubbles and gun array motion in the time domain, can more accurately simulate far-field wavelets, and is more in line with the actual situation. The method can provide more accurate wavelets for signal deconvolution and the like, and is mainly used for providing more accurate wavelets for the steps of subsequent seismic processing such as signal deconvolution and the like after simulating far field wavelets, so that better processing results are obtained for the signal deconvolution and the like.
Based on the same inventive concept, the embodiment of the invention also provides a device for simulating far-field wavelets based on near-field recording, and referring to fig. 5, the device may include: the working principles of the acquisition module 11, the motion speed determination module 12, the travel time determination module 13, the ideal wavelet construction module 14, the far-field point distance determination module 15, the far-field wavelet travel time determination module 16 and the far-field wavelet simulation module 17 are as follows:
the acquisition module 11 is used for acquiring the near field record and the time direction sampling interval of the near field detector;
the motion speed determining module 12 is used for determining the motion speed of the near-field geophone based on the speed of the source boat;
the travel time determining module 13 is configured to determine a travel time of each sampling time based on the time direction sampling interval;
the ideal wavelet construction module 14 is configured to determine a distance from a source to the near-field pickup and a distance from a virtual source to the near-field pickup based on a near-field record of the near-field pickup, a motion speed of the near-field pickup, and a travel time of each sampling time, so as to construct an ideal wavelet corresponding to each sampling time;
the far-field point distance determining module 15 is configured to determine a distance from a source to a far-field point and a distance from a virtual source to the far-field point based on the acquired near-field record of the near-field detector;
the far-field wavelet travel time determination module 16 is configured to determine a travel time of a far-field wavelet directly below the air gun array based on a corresponding number of sampling points and a time-wise sampling interval at the time of travel;
the far-field wavelet simulation module 17 is configured to simulate the far-field wavelet based on the distance of the source to the far-field point, the distance of the virtual source to the far-field point, the travel time of the far-field wavelet directly under the airgun array, and the ideal wavelet.
Alternatively, the ideal wavelet construction module 14 is specifically configured to: based on the near field record of the near field geophone, the motion speed of the near field geophone and the travel time of each sampling time, determining the distance from the source to the near field geophone, namely by the following formula:
where j is the air gun number, j=1, 2, …, n, n is the number of air guns; x is x j ，y j Respectively the horizontal and vertical coordinates of the air gun; z j Is the depth of the air gun; t is t k Is the moment of seismic data acquisition; v B The speed of the air bubbles floating is generally 1m/s.
The ideal wavelet construction module 14 is specifically configured to determine a distance from the virtual source to the near-field geophone based on a near-field record of the near-field geophone, a motion speed of the near-field geophone, and a travel time of each sampling time, i.e. by the following formula:
wherein i is the near field pickup number, j is the air gun number, j=1, 2, …, n, n is the number of air guns; x is x j ，y j Respectively the horizontal and vertical coordinates of the air gun; z j Is the depth of the air gun; t is t k Is the moment of seismic data acquisition; v B The speed of the air bubbles floating is generally 1m/s.
The ideal wavelet construction module 14 is specifically configured to: the ideal wavelet corresponding to each sampling moment is constructed, namely, the ideal wavelet is determined by the following formula:
wherein v is the propagation speed of the seismic wave in the water, and is generally 1500m/s; c is the reflection coefficient of the sea surface, typically 1.0;
and->For non-integer sampling points, interpolation using spline functions or sinc functions is required.
The far-field point distance determining module 15 is specifically configured to determine, based on the acquired near-field record of the near-field pickup, a distance from the source to the far-field point, where the distance is determined by the following formula:
where j is the air gun number, j=1, 2, …, n, n is the number of air guns; x and Y are the horizontal and vertical coordinates of the center of the air gun array respectively; z is the depth of the far field point, typically 10000m; x is x j ，y j Respectively the horizontal and vertical coordinates of the air gun; z j Is the depth of the air gun.
The far-field point distance determining module 15 is specifically configured to determine, based on the acquired near-field record of the near-field detector, a distance from the virtual source to the far-field point, where the distance is determined by the following formula:
where j is the air gun number, j=1, 2, …, n, n is the number of air guns; x and Y are the horizontal and vertical coordinates of the center of the air gun array respectively; z is the depth of the far field point, typically 10000m; x is x j ，y j Respectively the horizontal and vertical coordinates of the air gun; z j Is the depth of the air gun.
The far-field wavelet simulation module 17 is specifically configured to simulate the far-field wavelet based on the distance from the source to the far-field point, the distance from the virtual source to the far-field point, the travel time of the far-field wavelet directly under the air gun array, and the ideal wavelet, that is, the far-field wavelet is determined by the following formula:
wherein p' i Ideal wavelets for each airgun; v is the propagation velocity of the seismic wave in the water, generally 1500m/s; c is the reflection coefficient of the sea surface, typically 1.0;
and->For non-integer sampling points, interpolation using spline functions or sinc functions is required.
Based on the same inventive concept, the embodiment of the invention also provides a computer readable storage medium, on which a computer program is stored, which when being executed by a processor, implements the method for simulating far-field wavelets based on near-field recording.
Based on the same inventive concept, the embodiment of the invention also provides a computer device, which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor realizes the method for simulating far-field wavelets based on near-field recording when executing the program.
The principles of the problems solved by the device, the client, the medium, the related devices and the system in the embodiments of the present invention are similar to those of the foregoing method, so the implementation of the method may be referred to the implementation of the foregoing method, and the repetition is omitted.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, magnetic disk storage, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (11)
1. A method for simulating a far-field wavelet based on near-field recording, comprising:
determining a motion speed of the near field pickup based on a speed of the source vessel;
determining travel time for each sampling instant based on the time-wise sampling interval;
determining the distance from a seismic source to the near-field detector and the distance from a virtual seismic source to the near-field detector based on near-field recording of the near-field detector, the motion speed of the near-field detector and the travel time of each sampling time to construct an ideal wavelet corresponding to each sampling time;
determining the distance from a seismic source to a far-field point and the distance from a virtual seismic source to the far-field point based on the acquired near-field record of the near-field detector;
determining the travel time of far-field wavelets right below the seismic source array based on the corresponding sampling points and time direction sampling intervals during travel;
the far-field wavelet is simulated based on the distance of the source to the far-field point, the distance of the virtual source to the far-field point, the travel time of the far-field wavelet directly below the source array, and the ideal wavelet.
2. The method as recited in claim 1, further comprising:
a near field recording and a time-wise sampling interval of the near field pickup are acquired.
3. The method of claim 1, wherein the distance from the source to the near field pickup is determined based on near field recordings of the near field pickup, a velocity of motion of the near field pickup, and a travel time for each sampling instant, by the following formula:
wherein i is the near field detector sequence number; j is the air gun number, j=1, 2, …, n, n is the number of air guns; x is x j ，y j Respectively the horizontal and vertical coordinates of the air gun; z j Is the depth of the air gun; t is t k Is the moment of seismic data acquisition; v B The speed of the air bubbles floating is generally 1m/s.
4. A method according to claim 3, wherein the distance of the virtual source to the near field pickup is determined based on near field recordings of the near field pickup, the velocity of movement of the near field pickup and the travel time for each sample instant, by the following formula:
wherein i is the near field pickup number, j is the air gun number, j=1, 2, …, n, n is the number of air guns; x is x j ，y j Respectively the horizontal and vertical coordinates of the air gun; z j Is the depth of the air gun; t is t k Is the moment of seismic data acquisition; v B The speed of the air bubbles floating is generally 1m/s.
5. The method of claim 4, wherein the constructing the ideal wavelet for each sampling instant is determined by the following formula:
wherein v is the propagation speed of the seismic wave in the water, and is generally 1500m/s; c is the reflection coefficient of the sea surface, typically 1.0;
and->For non-integer sampling points, interpolation using spline functions or sinc functions is required.
6. The method of claim 1, wherein the determining the distance of the source to the far field point based on the acquired near field recordings of the near field detectors is determined by the following equation:
where j is the air gun number, j=1, 2, …, n, n is the number of air guns; x and Y are the horizontal and vertical coordinates of the center of the air gun array respectively; z is the depth of the far field point, typically 10000m; x is x j ，y j Respectively the horizontal and vertical coordinates of the air gun; z j Is the depth of the air gun.
7. The method of claim 6, wherein the determining the distance of the virtual source to the far field point based on the acquired near field recordings of the near field detectors is determined by the following equation:
where j is the air gun number, j=1, 2, …, n, n is the number of air guns; x and Y are the horizontal and vertical coordinates of the center of the air gun array respectively; z is the depth of the far field point, typically 10000m; x is x j ，y j Respectively the horizontal and vertical coordinates of the air gun; z j Is the depth of the air gun.
8. The method of claim 7, wherein the modeling the far-field wavelet is determined based on a distance of the source to a far-field point, a distance of a virtual source to the far-field point, a travel time of a far-field wavelet directly below the airgun array, and the ideal wavelet by:
wherein p' i Ideal wavelets for each airgun; v is the propagation velocity of the seismic wave in the water, generally 1500m/s; c is the reflection coefficient of the sea surface, typically 1.0;
know->For non-integer sampling points, interpolation using spline functions or sinc functions is required.
9. An apparatus for simulating a far-field wavelet based on near-field recording, comprising:
the motion speed determining module is used for determining the motion speed of the near-field geophone based on the speed of the source ship;
a travel time determining module for determining a travel time of each sampling time based on the time direction sampling interval;
the ideal wavelet construction module is used for determining the distance from a seismic source to the near-field detector and the distance from a virtual seismic source to the near-field detector based on the near-field record of the near-field detector, the motion speed of the near-field detector and the travel time of each sampling moment so as to construct ideal wavelets corresponding to each sampling moment;
the far-field point distance determining module is used for determining the distance from the source to the far-field point and the distance from the virtual source to the far-field point based on the acquired near-field record of the near-field detector;
the far-field wavelet travel time determining module is used for determining the travel time of the far-field wavelet under the air gun array based on the corresponding sampling point number and the time direction sampling interval during travel;
the far-field wavelet simulation module is used for simulating the far-field wavelet based on the distance from the source to the far-field point, the distance from the virtual source to the far-field point, the travel time of the far-field wavelet right below the air gun array and the ideal wavelet.
10. A computer readable storage medium having stored thereon a computer program, which when executed by a processor implements the method of simulating far-field wavelets based on near-field recording as claimed in any one of claims 1 to 8.
11. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the method of simulating far-field wavelets based on near-field recording according to any one of claims 1 to 8 when executing the program.
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