Various implementations directed to quality control and preconditioning of seismic data are provided. In one implementation, a method may include receiving particle motion data from particle motion sensors disposed on seismic streamers. The method may also include performing quality control (QC) processing on the particle motion data. The method may further include performing preconditioning processing on the QC-processed particle motion data. The method may additionally include attenuating noise in the preconditioning-processed particle motion data.

Systems, computer readable, and methods concern receiving seismic data representing a subsurface volume. The method also includes determining, for the seismic data, analysis coordinates as a function of time. One or more of the analysis coordinates may vary in position over time. The method includes performing at least one of an interpolation or regularization process on the seismic data based at least partially on the analysis coordinates. The method also includes outputting a result of the at least one of the interpolation or regularization process.

One method interpolates simulated seismic data of a coarse spatial sampling to a finer spatial sampling using a neural network. The neural network is previously trained using a set of simulated seismic data with the finer spatial sampling and a subset thereof with the coarse spatial sampling. The data is simulated using an image of the explored underground formation generated using real seismic data. The seismic dataset resulting from simulation and interpolation is used for denoising the seismic data acquired over the underground formation. Another method demigrates seismic data at a sparse density and then increases density by interpolating traces using a neural network.

A method for 2D seismic data acquisition includes determining source-point seismic survey positions for a combined deep profile seismic data acquisition with a shallow profile seismic data acquisition wherein the source-point positions are based on non-uniform optimal sampling. A seismic data set is acquired with a first set of air-guns optimized for a deep-data seismic profile and the data set is acquired with a second set of air-guns optimized for a shallow-data seismic profile. The data are de-blended to obtain a deep 2D seismic dataset and a shallow 2D seismic dataset.

A method for estimating noise in particle motion seismic recordings and upgoing (deghosted) and downgoing components of ecorded wavefields includes inputting pressure related and particle motion related seismic signals. A sparsity promoting transformation is applied to the input seismic signals. A matrix à and column vector {tilde over (b)} are constructed according to the expression:

[00001]$\begin{array}{ccc}\tilde{A}=\left(\begin{array}{ccc}I& I& 0\\ I& -I& \lambda I\end{array}\right)& \tilde{x}=\left(\begin{array}{c}d\\ u\\ n\end{array}\right)& \tilde{b}=\left(\begin{array}{c}{A}^{-1}p\\ A^{-1}z\end{array}\right),\end{array}$

wherein d represents a down-going seismic wavefield, u represents an up-going seismic wavefield, n represents the noise and λ represents a user-chosen scalar to adjust emphasis of the noise. A constrained minimization is solved according to the expression

[00002]$\begin{array}{ccc}\tilde{x}=\arg \min \mu {.Math.\tilde{x}.Math.}_1+\frac{1}{2}{.Math.\tilde{x}.Math.}_2^2& \mathrm{st}& \tilde{A}\tilde{x}\end{array}=\tilde{b}$

for {tilde over (x)}; wherein μ represents a us

In an example implementation, first seismic energy is generated using first seismic sources positioned on an earth's surface. First data including measurements of the first seismic energy is obtained from first geophones positioned at a first depth below the earth's surface. Second data including measurements of the first seismic energy is obtained from second geophones positioned on the earth's surface. Second seismic energy is generated using second seismic sources positioned on an earth's surface and proximal to the second geophones. Third data including measurements of the second seismic energy is obtained from third geophones positioned at the first depth below the earth's surface. A propagation of the first seismic energy along a first path is estimated based on the first, second and third data. One or more characteristics of the target are determined based on the estimate.

A multi-stage inversion method for deblending seismic data includes: a) acquiring blended seismic data from a plurality of seismic sources; b) constructing an optimization model that includes the acquired blended seismic data and unblended seismic data; c) performing sparse inversion, via a computer processor, on the optimization model; d) estimating high-amplitude coherent energy from result of the performing sparse inversion in c); e) re-blending the estimated high-amplitude coherent energy; and f) computing blended data with an attenuated direct arrival energy.

A multi-stage inversion method for deblending seismic data includes: a) acquiring blended seismic data from a plurality of seismic sources; b) constructing an optimization model that includes the acquired blended seismic data and unblended seismic data; c) performing sparse inversion, via a computer processor, on the optimization model; d) estimating high-amplitude coherent energy from result of the performing sparse inversion in c); e) re-blending the estimated high-amplitude coherent energy; and f) computing blended data with an attenuated direct arrival energy.

A method for processing seismic data includes receiving seismic data comprising seismic traces collected from a land-based or marine seismic array, applying a noise mitigation process to the seismic data to generate a first stack volume, identifying, using a machine-learning algorithm, one or more traces of the seismic traces as having a relatively high residual noise, after applying the noise mitigation process, in comparison to other traces of the seismic traces, mitigating noise in the one or more identified traces, and performing a wavefield reconstruction to generate a second stack volume after mitigating the noise in the one or more traces after mitigating the noise in the one or more identified traces, to interpolate a portion of the wavefield corresponding to where the one or more identified traces were located and mitigated.

A method for 2D seismic data acquisition includes determining source-point seismic survey positions for a combined deep profile seismic data acquisition with a shallow profile seismic data acquisition wherein the source-point positions are based on non-uniform optimal sampling. A seismic data set is acquired with a first set of air-guns optimized for a deep-data seismic profile and the data set is acquired with a second set of air-guns optimized for a shallow-data seismic profile. The data are de-blended to obtain a deep 2D seismic dataset and a shallow 2D seismic dataset.