The harmonic wave, which is oscillation of a physical value along one direction of propagation in a homogeneous medium, is recorded by means of sensors along the direction of propagation of the oscillation at least at five points equally spaced from each other. The output signals of the sensors are converted into the corresponding complex spectral amplitudes corresponding to the frequency decomposition of the output signals. A model of harmonic wave propagation in a homogeneous medium is created, in which for any oscillation frequency the wave is represented as descending and ascending exponentially decaying harmonic waves propagating in opposite directions. The absolute values of the complex spectral amplitudes of the output signals of the sensors at each frequency are used as input data for equations comparing the absolute values of the complex amplitudes with the created model of wave propagation. By solving the obtained equations, the total complex amplitudes of the descending and ascending waves and the complex propagation constant of oscillations at each frequency are determined and the characteristics of the boundaries of the homogeneous medium are determined basing on the ratio of the complex amplitudes of the descending and ascending waves, and the characteristics of the homogeneous medium are determined basing on the phase velocity and attenuation coefficient of the wave.

A method for automatically picking up seismic velocity based on depth learning is disclosed. The method includes obtaining a seismic data and labels, and inputting the seismic data and the labels into a pre-trained depth learning model to obtain a velocity pick-up result. A structure of the depth learning model includes a residual network composed of three residual blocks. And after the residual network, a long-short term memory network and a full connection layer are further added. Each of the residual blocks is composed of three convolutional layers. An activation function between each residual block and each convolutional layer of the residual block is a Relu function. An activation function between the long-short term memory network and the full connection layer is a Relu function. The method for automatically picking up seismic velocity based on depth learning provided by the disclosure effectively improves the efficiency of seismic velocity pick-up.

A method for applying separated wave-field imaging onshore (1) by artificially creating up-going and down-going fields and (2) by using these fields in a migration algorithm. If there are any surface multiples in the data, the resulting image created using the migration algorithm will be distorted by the unknown free-surface reflection coefficient. In fact, the surface multiples may be generated with a complex series of reflection coefficients. The distortions found in the resulting image created using the migration algorithm are then removed.

Computing device, computer instructions and method for up-down separation of seismic data. The method includes receiving the seismic data, which includes hydrophone data and particle motion data; performing a first up-down separation, which is independent of a ghost model, using as input the hydrophone data and the particle motion data, to obtain first up-down separated data; performing a second up-down separation by using as input a combination of (i) the hydrophone data and/or the particle motion data and (ii) the first up-down separated data, wherein an output of the second up-down separation is second up-down separated data; and generating an image of the subsurface based on the second up-down separated data.

Systems and methods that include receiving reservoir data of a hydrocarbon reservoir, receive an indication related to selection of a wavefield propagator, application of the wavefield propagator utilizing Fourier Finite Transforms and Finite Differences to model a wavefield associated with a Tilted Orthorhombic media representative of a region of a subsurface comprising the hydrocarbon reservoir, and processing the reservoir data in conjunction the wavefield propagator to generate an output for use with seismic exploration above a region of a subsurface comprising the hydrocarbon reservoir and containing structural or stratigraphic features conducive to a presence, migration, or accumulation of hydrocarbons.

Fracture orientation ambiguity in the results of amplitude variation with offset and azimuth inversion is overcome by using additional geological information. Methods, apparatus and executable codes stored on non-transitory media cause, for each interface encountered by traces in a CMP gather, calculating angle-dependent azimuthal Fourier coefficients, performing a nonlinear inversion of amplitude versus offset and azimuth, AVOAz, equations built using the angle-dependent azimuthal Fourier coefficients to determine possible fracture orientations, and selecting one of the possible fracture orientations using constraints based on the additional geological information.

Techniques involve obtaining acoustic data (including waves reflected from the casing, the annular fill material, the formation, and/or interfaces between any of the mud, the casing, and the annular fill material) from an acoustic logging tool. Techniques include normalizing the acoustic wave to result in a normalized wave having a comparable spectral shape with a reference wave, and comparing the normalized wave with the reference wave. The reference wave may be generated or modeled or produced from a look-up table or database, and may be estimated based on initial estimates of wellbore parameters. Based on the comparison of the normalized wave with the reference wave, a best-fit reference wave substantially matching the normalized wave may be identified. The best-fit reference wave may correspond with a thickness of the casing, an acoustic impedance of the annular fill material, and an acoustic impedance of mud.

Techniques involve obtaining acoustic data from an acoustic logging tool, where the acoustic data includes waves reflected from the casing, the annular fill material, the formation, and/or interfaces between any of the casing, the annular fill material, one or more interfaces between any of the mud, the casing, and the annular fill material. Techniques include normalizing the acoustic wave to result in a normalized wave having a comparable spectral shape with a reference wave, and comparing the normalized wave with the reference wave. The reference wave may be generated or modeled or produced from a look-up table or database, and may be estimated based on initial estimates of wellbore parameters. Based on the comparison of the normalized wave with the reference wave, a best-fit reference wave substantially matching the normalized wave may be identified. The best-fit reference wave may correspond with a thickness of the casing, an acoustic impedance of the annular fill material, and an acoustic impedance of mud.

Fracture orientation ambiguity in the results of amplitude variation with offset and azimuth inversion is overcome by using additional geological information. Methods, apparatus and executable codes stored on non-transitory media cause, for each interface encountered by traces in a CMP gather, calculating angle-dependent azimuthal Fourier coefficients, performing a nonlinear inversion of amplitude versus offset and azimuth, AVOAz, equations built using the angle-dependent azimuthal Fourier coefficients to determine possible fracture orientations, and selecting one of the possible fracture orientations using constraints based on the additional geological information.

Computing device, computer instructions and method for up-down separation of seismic data. The method includes receiving the seismic data, which includes hydrophone data and particle motion data; performing a first up-down separation, which is independent of a ghost model, using as input the hydrophone data and the particle motion data, to obtain first up-down separated data; performing a second up-down separation by using as input a combination of (i) the hydrophone data and/or the particle motion data and (ii) the first up-down separated data, wherein an output of the second up-down separation is second up-down separated data; and generating an image of the subsurface based on the second up-down separated data.