A fully automated method for correcting errors in one interpretation (13) of seismic data based on comparison to at least one other interpretation (14) of the same subsurface region. The errors may occur in any feature of the seismic data volume, for example a horizon, surface, fault, polyline, fault stick, or geo-body. In some embodiments of the invention, an error may be a hole in a horizon (53), and the whole is patched by a piece of a horizon in another interpretation (55). In an alternative embodiment of the invention, a single interpretation may be used to repair itself, for example by identifying similarly shaped, adjacent horizons (67), and merging them (68).

A method may include obtaining seismic data for a geological region of interest. The method may further include determining various velocity semblance values for the geological region of interest using a time window and the seismic data. The method may further include determining, automatically by a computer processor, one or more stacking velocities for the geological region of interest using a traced path based on the velocity semblance values and a path tracing algorithm. The path tracing algorithm may recursively determine an accumulated amplitude array based on the velocity semblance values. The path tracing algorithm may further determine the traced path among the velocity semblance values and the accumulated amplitude array, the traced path corresponding to the one or more stacking velocities. The method may further include generating a velocity model of the geological region of interest using the one or more stacking velocities.

Device and method for calculating a set of surface wave dispersion curves. The method includes receiving seismic data recorded with seismic sensors over an area to be surveyed; selecting region units that cover the area to be surveyed; gathering traces for the region units; processing in a computing device the traces to obtain a set of candidate measurements for each region unit; teaching a decision algorithm based on a first subset of the set of candidate measurements; and calculating the set of surface wave dispersion curves by running the decision algorithm on a second subset of the set of candidate measurements.

Device and method for calculating a set of surface wave dispersion curves. The method includes receiving seismic data recorded with seismic sensors over an area to be surveyed; selecting region units that cover the area to be surveyed; gathering traces for the region units; processing in a computing device the traces to obtain a set of candidate measurements for each region unit; teaching a decision algorithm based on a first subset of the set of candidate measurements; and calculating the set of surface wave dispersion curves by running the decision algorithm on a second subset of the set of candidate measurements.

The disclosed technology provides solutions for identifying noise in seismic profile data sets. In some aspects, a process of the disclosed technology includes steps for receiving wellbore data including seismic measurements, processing the wellbore data to generate a seismic input image including visual representations of the one or more seismic measurements, and processing the seismic input image to identify a noise region in the seismic input image. Systems and machine-readable media are also provided.

In one embodiment, a reverse time migration module is configured with a visco-acoustic wave equation for media with heterogeneous attenuation solved using a pseudo-analytical method. Seismic data is obtained for a zone of interest, and a model is created for the zone of interest. The model has spatial variability in velocity and quality factor. Pseudo-analytic Q-compensating reverse time migration (PA-Q-RTM) is performed using the reverse time migration module and the model for the zone of interest to obtain PA-Q-RTM seismic data. In another embodiment, a system for processing seismic data includes a reverse time migration module configured with a visco-acoustic wave equation that is solved from the pseudo-analytical method. The system operates to obtain seismic data for a zone of interest and perform PA-Q-RTM using a model for the zone of interest to obtain PA-Q-RTM seismic data for the zone of interest. Other embodiments and features are also disclosed.

The present invention provides a seismic signal processing method, device and system. The method comprises: obtaining an offset of a reflected seismic signal at a sampling point and the corresponding reflected wave arrival time; constructing a non-hyperbolic dynamic correction formula based on Pade approximation according to the offset of the reflected seismic signal at the sampling point and the corresponding reflected wave arrival time; extracting a vertical propagation velocity and anisotropy parameters of the reflected seismic signal according to the non-hyperbolic dynamic correction formula constructed based on Pade approximation.

An apparatus for enhancing an input phase distribution (I(x.sub.i)) is configured to retrieve the input phase distribution (I(x.sub.i)) and compute a baseline estimate (ƒ(x.sub.i)) as an estimate of a baseline (I.sub.2 (x.sub.i)) in the input phase distribution (I(x.sub.i)). The apparatus is further configured to obtain an output phase distribution (O(x.sub.i)) based on the baseline estimate (ƒ(x.sub.i)) and the input phase distribution (I(x.sub.i)).

A method of low-frequency seismic data enhancement for improving the characterization precision of a deep carbonate reservoir includes: first performing inversions on an input seismic data set to obtain the corresponding reflection coefficients and average seismic wavelet; then constructing a seismic wavelet with rich low-frequency information; and finally, performing convolution on the seismic wavelet with rich low-frequency information and the reflection coefficients to obtain seismic data with rich low-frequency information and enhanced low-frequency energy. In the present invention, changes of the seismic data in a work area in transverse and longitudinal directions are taken into consideration, and processing parameters can be quickly determined according to actual conditions of the work area to obtain an optimal processing effect. In this way, the characterization quality of geological anomalies, such as a fault, a fracture system, or the like, in a deep carbonate reservoir can be improved significantly.

A method of low-frequency seismic data enhancement for improving the characterization precision of a deep carbonate reservoir includes: first performing inversions on an input seismic data set to obtain the corresponding reflection coefficients and average seismic wavelet; then constructing a seismic wavelet with rich low-frequency information; and finally, performing convolution on the seismic wavelet with rich low-frequency information and the reflection coefficients to obtain seismic data with rich low-frequency information and enhanced low-frequency energy. In the present invention, changes of the seismic data in a work area in transverse and longitudinal directions are taken into consideration, and processing parameters can be quickly determined according to actual conditions of the work area to obtain an optimal processing effect. In this way, the characterization quality of geological anomalies, such as a fault, a fracture system, or the like, in a deep carbonate reservoir can be improved significantly.