A method for generating a merged survey dataset, that includes obtaining a plurality of survey datasets, calculating edges between survey datasets of the plurality of survey datasets, modifying the plurality of survey datasets, based on the edges, to obtain a plurality of modified survey datasets, and generating the merged survey dataset using the plurality of modified survey datasets.

A method for conditioning seismic data includes receiving unconditioned seismic data. The method also includes introducing transformations into the unconditioned seismic data to produce transformed seismic data. The method also includes training a neural network model using the transformed seismic data to attempt to reproduce the unconditioned seismic data. The method also includes conditioning the unconditioned seismic data using the trained neural network model to produce conditioned seismic data.

A method is described for seismic imaging of the subsurface using dip-guided optimized stacking. The method computes weighting functions for a plurality of single-shot migrated images, unstacked seismic images, or partially stacked seismic images based on a slant stack performed using an input dip dataset; applying the plurality of weighting functions to the plurality of single-shot migrated images, unstacked seismic images, or partially stacked seismic images, or a plurality of dip-filtered images to create a plurality of weighted images; and summing the plurality of weighted images into a stacked seismic image. The method may be executed by a computer system.

Method for estimating reflector dips in a window of post stack image traces (51) of seismic data for use in velocity tomography (57). The method iteratively (56) flattens (55) the image traces against a specified reference trace through the application of conjugate-gradient least-squares inversion (53). Different from other dip estimation methods which emphasize on strong-amplitude reflectors, the inventive method automatically inverts for the reflector dip for every grid point in the image window.

A method for estimating uncertainty in seismic-derived depth prognoses of a subsurface region includes receiving an initial velocity model of a subsurface region based on seismic data associated with the subsurface region, performing a seismic de-migration on initial post-migration seismic data obtained from the initial velocity model to obtain pre-migration seismic data, and perturbing one or more of the components of the initial velocity model to produce a plurality of perturbed velocity models that are each different from the initial velocity model. The method further includes performing a seismic migration of the pre-migration seismic data using the perturbed velocity model to obtain perturbed post-migration seismic data for each of the plurality of perturbed velocity models, estimating a depth error from a depth prognosis obtained from a selected subset of the perturbed velocity models based on characteristics of the perturbed post-migration seismic data, and estimating a depth uncertainty from the estimated depth error.