A method includes receiving observed seismic data, determining an envelope or magnitude of the observed seismic data as a first observed value, generating a variable noise term based in part upon the first observed value, and utilizing the variable noise term to determine a likelihood function of a stochastic inversion operation. The method also includes utilizing the likelihood function to generate a posterior probability distribution in conjunction with the stochastic inversion operation and applying the posterior probability distribution to characterize a subsurface region of Earth.

Amplitude-versus-angle analysis for quantitative interpretation can include creation of a plurality of angle gathers from imaging a subsurface location with multiples in a near-offset range and imaging primaries outside the near-offset range and application of an amplitude-versus-angle analysis to the plurality of angle gathers to produce a quantitative interpretation pertaining to the subsurface location.

A method for iteratively inverting seismic data to jointly infer a model for at least P-wave velocity and attenuation parameters of the subsurface, the method including: jointly inverting the P-wave velocity and attenuation parameters with an iterative visco-acoustic full wavefield inversion process, wherein the iterative visco-acoustic full wavefield inversion process includes computing a gradient of an objective function, the objective function measuring a misfit between all or part of the seismic data and corresponding model-simulated seismic data; for each of the P-wave velocity and attenuation parameters, computing a search direction in model space from the gradient; determining line search step sizes and for the search directions for the P-wave velocity and attenuation parameters, respectively, wherein a ratio of the step sizes is a function of the P-wave velocity parameter; and using the step sizes and and the search directions for each of the P-wave velocity and attenuation parameters, computing a new search direction in model space, then performing a line search along the new search direction to arrive at a new step size, and using the new step size and the new search direction to generate an updated model for a current iteration of the iterative visco-acoustic full wavefield inversion process.

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.

Marine survey data resulting from a first signal comprising a signal representing a flat spectral far-field pressure generated by a marine vibrator source swept over a frequency range according to a time function of motion such that acceleration of the marine vibrator source is a flat function in a frequency domain can be used to improve full waveform inversion. For example, full waveform inversion can be performed using the marine survey data received from the first signal and from a second signal generated by an impulsive seismic source to estimate a physical property of a subsurface location.

A method for directional Q compensation of seismic data may comprise calculating angle-dependent subsurface travel times; applying directional Q compensation to the prestack seismic data to obtain Q-compensated data in time-space domain, wherein the directional Q compensation is based on the angle-dependent subsurface travel times; and using the Q-compensated data to generate an image of the subsurface. Directional Q compensation may comprise determining an angle-dependent forward E operator and an angle-dependent adjoint E* operator using the angle-dependent subsurface travel times; and applying a sparse inversion algorithm using the angle-dependent operators to obtain a model of Q-compensated data. The angle-dependent operators may be preconditioned by introducing ghost and source effects in a wavelet matrix and a transpose of the wavelet matrix, respectively, such that applying a sparse inversion algorithm using the preconditioned angle-dependent operators is used to obtain a model of Q-compensated, deghosted data without source effects.

A method for processing seismic data includes receiving, by a seismic data processing system, signals representing seismic data recorded at a remote location. In addition, the method includes receiving, by the seismic data processing system, identification of a sensor via which the signals were acquired. Further, the method includes retrieving, by the seismic data processing system, a sensor transfer function that corresponds to the sensor and relates the motion of the sensor to the signals. The method also includes generating, by the seismic data processing system, based on the sensor transfer function and a reference transfer function, an inverse filter that when applied to the signals changes parameters of the signals to correspond to the reference transfer function. Moreover, the method includes applying, by the seismic data processing system, the inverse filter to the signals to conform the parameters of the signals to the reference transfer function.

A system and method combines model-based inversion and supervised neural networks to develop high resolution rock property volumes from surface seismic data. These volumes have higher frequency and are calibrated to fit well log data. In addition to rock volumes, a Reflection Coefficient (RC) volume is derived from the acoustic impedance volume. The RC volume has much higher frequency, better lateral continuity, and ties to the well logs better than conventional seismic or frequency enhanced data. By interpreting and mapping with this RC volume, a much more accurate depth model can be built, which allows for a horizontal well to be accurately drilled.

Inversion for marine seismic imaging of a full reflected wavefield can include generating an image of a subsurface formation by full wavefield migrating a recorded seismic wavefield and generating numerically modeled data using the image. A mismatch between the numerically modeled data and the seismic wavefield can be determined. Responsive to determining that the mismatch exceeds an inversion match threshold, the image can be updated using the mismatch between the numerically modeled data and the seismic wavefield.

Methods for processing seismic data acquired with non-impulsive moving sources are provided. Some methods remove cross-talk noise from the seismic data using emitted signal data and an underground formation's response estimate, which may be iteratively enhanced. Some methods perform resampling before a spatial or a spatio-temporal inversion. Some methods compensate for source's motion during the inversion, and/or are usable for multiple independently moving sources.