Abstract: This disclosure relates to geophysical exploration and seismic imaging, and more particularly to a seismic imaging method, system, and device based on pre-stack high-angle fast Fourier transform (FFT). The method includes: acquiring seismic data acquired during seismic exploration; extracting a common shot point gather from the seismic data followed by conversion into a frequency wavenumber domain common offset gather; calculating wave propagation angles; dividing an imaging region into a first region and a second region; solving constant coefficients of the first region and the second region; performing frequency-division layer-by-layer wavefield continuation on a frequency-wave number domain common offset gather to obtain imaging results at different depths and frequencies; subjecting the imaging results to integration followed by transformation to a spatial domain to obtain common offset imaging profiles; and subjecting the common offset imaging profiles to superposition obtain final imaging results.

Abstract: The seismic imaging resolution analysis method comprises: obtaining common-shot gathers and common-detector gathers; in the common-shot gathers, conducting detector focusing analysis on a focus point at (xj, zn) in each source point gather to obtain a source point focal-beam gather; looping all the focus points at a depth zn, and conducting computation on a weighted source-focusing operator Pik† (zn, zn); in the common-detector gathers, conducting source point focusing analysis on an focus point at (xj, zn) in each source point gather to obtain a detector focal-beam gather; Loop all the focus points at a depth zn, and conducting computation on a weighted detector-focusing operator Pik (zn, zn); and conducting computation on a normalized resolution function of a single focus point so as to obtain a horizontal resolution and a definition.

Abstract: A method, a system, and a device for full-waveform inversion deghosting for a marine variable depth streamer data acquisition are provided for solving existing problems that deghosted seismic data has low accuracy and is accompanied by artifacts due to a large error in ghost prediction. The provided method includes: acquiring seismic data, jointly solving Lippmann-Schwinger equations to obtain normal derivatives of an incident wave field and a wave field of a receiver surface, performing a wave field extrapolation by a Kirchhoff equation that includes only an integral on the receiver surface to obtain a wave field of a sea surface recorded by a horizontal streamer, calculating a ghost operator, and subjecting the ghosted wave field of the sea surface recorded by the horizontal streamer to full-waveform inversion deghosting to obtain deghosted seismic data. The provided method improves the accuracy and signal-to-noise ratio (SNR) of deghosted seismic data.

Abstract: The present invention relates to a target-oriented seismic acquisition method and apparatus, a medium and a device. The target-oriented seismic acquisition method comprises the steps of: giving parameters of an initial velocity model and a three-dimensional seismic layout aiming to an underground target position; conducting wave field continuation and focusing analysis on the three-dimensional seismic layout, and calculating distribution of seismic energy on the ground in an underground target region; conducting normalization processing on distribution of the seismic energy on the ground, and then conducting level partitioning to obtain a primary energy region and a secondary energy region; adding the number of shot points in the primary energy region to achieve target-oriented acquisition, and obtaining a target-oriented inhomogeneous laying acquired data imaging result.

Abstract: The present disclosure belongs to the technical field of seismic exploration imaging, and relates to an interpretive-guided velocity modeling seismic imaging method and system, a medium and a device. The method comprises the following steps: S1. performing first imaging on a given initial velocity model to obtain a first imaging result; S2. performing relative wave impedance inversion on the first imaging result to obtain a relative wave impedance profile; S3. performing Curvelet filtering on the relative wave impedance profile to obtain a first interpretation scheme; S4. superposing the first interpretation scheme and the initial velocity model to obtain a new migration velocity field; S5. performing second imaging on a new migration velocity field to obtain a second imaging result; and S6. repeating steps S2-S4 for the obtained second imaging result until a final seismic imaging result is obtained.

Abstract: The present invention discloses a physical embedded deep learning formation pressure prediction method, device, medium and equipment, the present invention characterizes seismic attenuation by logging impedance quality factor Q, based on the Q value and rock physics model of formation pressure, the physical mechanism of this kind of certainty replace Caianiello convolution neurons of the nonlinear activation function, using the convolution neurons, build deep learning convolution neural networks (CCNNs), can greatly increase the stress inversion precision and learning efficiency, get accurate formation pressure prediction results. Compared with the prior art, the present invention uses acoustic attenuation instead of the traditional acoustic velocity to characterize formation pressure, and solves the problem that the traditional pressure prediction method based on velocity has strong multiple solutions due to high gas content and complex structure.

Abstract: The present disclosure belongs to the technical field of seismic exploration imaging, and relates to an interpretive-guided velocity modeling seismic imaging method and system, a medium and a device. The method comprises the following steps: S1. performing first imaging on a given initial velocity model to obtain a first imaging result; S2. performing relative wave impedance inversion on the first imaging result to obtain a relative wave impedance profile; S3. performing Curvelet filtering on the relative wave impedance profile to obtain a first interpretation scheme; S4. superposing the first interpretation scheme and the initial velocity model to obtain a new migration velocity field; S5. performing second imaging on a new migration velocity field to obtain a second imaging result; and S6. repeating steps S2-S4 for the obtained second imaging result until a final seismic imaging result is obtained.

Abstract: This disclosure relates to geophysical exploration and seismic imaging, and more particularly to a seismic imaging method, system, and device based on pre-stack high-angle fast Fourier transform (FFT). The method includes: acquiring seismic data acquired during seismic exploration; extracting a common shot point gather from the seismic data followed by conversion into a frequency wavenumber domain common offset gather; calculating wave propagation angles; dividing an imaging region into a first region and a second region; solving constant coefficients of the first region and the second region; performing frequency-division layer-by-layer wavefield continuation on a frequency-wave number domain common offset gather to obtain imaging results at different depths and frequencies; subjecting the imaging results to integration followed by transformation to a spatial domain to obtain common offset imaging profiles; and subjecting the common offset imaging profiles to superposition obtain final imaging results.