An apparatus includes a signal acquisition part acquires oscillation signals from sensors provided under lanes of a bridge and close to an expansion joint, a signal separation part applies BSS to the oscillation signals to estimate source oscillation signals respectively separated in the plurality of lanes, and adjusts amplitude of the source oscillation signals to output amplitude adjusted oscillation signals, and a vehicle estimation part estimates, from the amplitude adjusted oscillation signal, a response oscillation due to a vehicle passing on the lane of interest to detect and count vehicles passing on the lane.

A seismic time-frequency analysis method based on generalized Chirplet transform with time-synchronized extraction, which has higher level of energy aggregation in the time direction and can better describe and characterize the local characteristics of seismic signals, and is applicable to the time-frequency characteristic representation of both harmonic signals and pulse signals, comprising the steps of processing generalized Chirplet transform with time-synchronized extraction for each seismic signal to obtain a time spectrum by: carrying out generalized Chirplet transform, calculating group delay operator and carrying out time-synchronized extraction on seismic signals, thereby the boundary and heterogeneity structure of the rock slice are more accurately and clearly shown and subsequence seismic analysis and interpretation are facilitated.

A system can be provided for applying a dynamic filter to a velocity model for converting the domain of seismic data. The system can receive a velocity model for a geological area of interest. The system can apply a dynamic filter to the velocity model for smoothing an anomaly included in the velocity model. The system can apply the velocity model with the smoothed anomaly to seismic data associated with the geological area of interest for converting the domain of the seismic data.

A method for classifying a microseismic event, including: analyzing microseismic event files through a combination of two fault tolerant machine learning pipelines, an acoustic machine learning pipeline and a visual machine learning pipeline; and generating a classification prediction for the microseismic event files by combining predictions from the acoustic machine learning pipeline and the visual machine learning pipeline.

System and methods for automated seismic processing are provided. Historical seismic project data associated with one or more historical seismic projects is obtained from a data store. The historical seismic project data is transformed into seismic workflow model data. At least one seismic workflow model is generated using the seismic workflow model data. Responsive to receiving seismic data for a new seismic project, an optimized workflow for processing the received seismic data is determined based on the at least one generated seismic workflow model. Geophysical parameters for processing the seismic data with the optimized workflow are selected. The seismic data for the new seismic project is processed using the optimized workflow and the selected geophysical parameters.

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).

Seismic survey data is received, indexed into index sets, and each index set partitioned into data blocks. For each particular data block of a particular index set, the particular data block is sliced into frequency slices. For each particular frequency slice of the particular data block, the particular frequency slice is processed to remove random and erratic noise by: forming a Hankel matrix from the particular frequency slice: determining an optimal rank for the Hankel matrix, determining a clean signal and erratic noise from the ranked Hankel matrix, and returning the clean signal and erratic noise for the particular frequency slice. A clean signal is assembled from the index sets.

Systems, methods, and computer-readable media for estimating a component of a seismic wavefield. The method may include accessing marine seismic data comprising a plurality of discrete measurements of a seismic wavefield; processing the marine seismic data to determine a relationship between a plurality of components of the seismic wavefield and each of the discrete measurements; and estimating from the marine seismic data processed via the one or more processors, each component of the seismic wavefield separated from each of the other plurality of components of the seismic wavefield and evaluated at a predetermined position.

Limitations in accuracy and computing power requirements impeding conventional Kirchhoff migration and reverse time migration are overcome by using the wave-equation Kirchhoff, WEK, technique with Kirchhoff migration. WEK technique includes forward-propagating a low-frequency wavefield from a shot location among pre-defined source locations, calculating an arrival traveltime of a maximum amplitude of the low-frequency wavefield, and applying Kirchhoff migration using the arrival traveltime and the maximum amplitude.

A seismic survey method comprising a vessel, a seismic acquisition system for collecting geophysical seismic data, a marine navigation system for generating positioning data from the location of the vessel and the location of the seismic acquisition system, a seismic data storage engaged with the seismic acquisition system for collecting and storing the seismic data and a seismic data processor engaged with said seismic data storage for seismic processing of the seismic data. The seismic data is acquired along a non-linear acquisition path or sail line. The data consists of CMP lines that follow the non-linear acquisition path. A binning grid covering the CMP lines of the acquired data such that the in-lines follow parallel to the acquisition path and the cross-lines are perpendicular to the in-lines is created. The binning grid comprises a straight portion and a curved portion. Bins for each portion of the binning grid is calculated.