A method for generating a geophysical image of a subsurface region includes defining a computational sub-volume for the geophysical image including a predetermined number of seismic traces of a plurality of seismic traces and a predetermined number of samples per each one of the plurality of seismic traces, generating a data matrix corresponding to a first sub-volume of the subsurface region based on the defined computational sub-volume, the data matrix comprising the predetermined number of samples for the predetermined number of traces of a portion of a seismic dataset corresponding to the first sub-volume. The method also includes estimating a coherence between the predetermined number of traces of the data matrix by performing a sum of a variance of the predetermined number of samples of the data matrix, and assigning the estimated coherence to a location in the geophysical image.

A method for generating a geophysical image of a subsurface region includes defining a computational sub-volume for the geophysical image including a predetermined number of seismic traces of a plurality of seismic traces and a predetermined number of samples per each one of the plurality of seismic traces, generating a data matrix corresponding to a first sub-volume of the subsurface region based on the defined computational sub-volume, the data matrix comprising the predetermined number of samples for the predetermined number of traces of a portion of a seismic dataset corresponding to the first sub-volume. The method also includes estimating a coherence between the predetermined number of traces of the data matrix by performing a sum of a variance of the predetermined number of samples of the data matrix, and assigning the estimated coherence to a location in the geophysical image.

Computer-implemented methods, apparatus, and computer programs disclosed herein are for obtaining horizon data, and comprise determining at least one extrema binary volume from a seismic data volume comprising a plurality of voxels and assigning a predetermined extrema value to each one of the found extreme voxels; determining an extrema graph from the at least one extrema binary volume; determining a neighbour graph from the extrema graphs; partitioning the nodes of the neighbour graph into a set of clusters, wherein a cluster contains a plurality of connected nodes representing extrema voxels of the at least one extrema binary volume, and each node is part of one cluster only; for each subset of the set of clusters, identifying whether or not the subset is a contradictory set of clusters according to at least one first predetermined condition; hierarchically partitioning the neighbour graph into a plurality of subgraphs, for example using a minimum cut approach, each subgraph being provided by a separate non-contradictory cluster, which is not part of any contradictory sets of clusters; and obtaining horizon data representing a plurality of horizons from the non-contradictory clusters inducing the plurality of subgraphs of the neighbour graph.

In a display system, each of a plurality of sensor terminals estimates first information based on accumulated first measurement data and transmits the first information to a display device. The display device synchronizes a received plurality of kinds of the first information at time and classifies the plurality of kinds of first information into a plurality of first information groups, estimates, based on position information of the plurality of sensor terminals and the first information included in each of the first information groups, updates the first information group, generates, for each of the updated plurality of first information groups, based on map information including a region where a structure is located, image information including a distribution of values of the first information on a map, and displays an image based on the image information.

In a display system, each of a plurality of sensor terminals estimates first information based on accumulated first measurement data and transmits the first information to a display device. The display device synchronizes a received plurality of kinds of the first information at time and classifies the plurality of kinds of first information into a plurality of first information groups, estimates, based on position information of the plurality of sensor terminals and the first information included in each of the first information groups, updates the first information group, generates, for each of the updated plurality of first information groups, based on map information including a region where a structure is located, image information including a distribution of values of the first information on a map, and displays an image based on the image information.

Techniques, systems and devices to generate a seismic wavefield solution. This includes receiving a velocity model corresponding to at least one attribute of seismic data, receiving source wavelet data corresponding to the seismic data, generating a guide image based upon at least one attribute of the velocity model, transmitting the velocity model, the source wavelet data, and the guide image to a machine learning system, and training the machine learning system into a trained machine learning system using the velocity model, the source wavelet data, and the guide image.

Generally, seismic data may provide valuable information with regard to the description such as the location and/or change of hydrocarbon deposits within a subsurface region of the Earth. The present disclosure generally discusses techniques that may be used by a computing system to analyze a data set including weak-coherence signals (e.g., non-coherent blending noise). In particular, a computing system may detect portion of the weak-coherence signals of a gather due to the overlap of selected seismic source excitations and use a mask to isolate coherent signals and the other weak-coherence signals from the masked portion of weak-coherence signals. The coherent signals and other weak-coherence signals may be iteratively processed and used to predict values of the masked weak-coherence signals.

Systems and methods for detecting a mechanical disturbance are disclosed. One of the method may comprise the operation steps including: transmitting, by a transmitter, a pulse at a preset frequency along a first cable; receiving, by a receiver, a plurality of signals, wherein each of the plurality of signals travels along the first cable and a second cable connected to the receiver for a corresponding span; calculating one or more differential phases, wherein each differential phase is calculated based on respective phases and the corresponding spans of two of the plurality of signals; and determining a localization of the mechanical disturbance based on the one or more differential phases.

The present invention is related to a method for reconstructing at least one trace in a seismic image of a common receiver and time domain, the image comprising traces in time domain with seismic data and one or more traces to be reconstructed. A first aspect of the invention is a method that is characterized by a specific use of a convolutional neural network trained under an unsupervised learning approach with a modified receptive field. A second aspect of the invention is a deblending method based on the use of a reconstructing method according to the first aspect of the invention applied to a denoising step of a deblending process allowing a very effective data acquisition while keeping a high quality output data sets after being processed according to the first and/or second aspects of the invention.

Methods to estimate formation shear wave slowness from multi-firings of different types of acoustic sources and multi-mode dispersion estimation systems are presented. The method includes obtaining waveform data of waves traversing through a downhole formation, where the waves are generated from multi-firings of different types of acoustic sources. The method also includes performing a multimode dispersion analysis of the waveform data for each firing of the multi-firings, and removing one or more tool waves generated from the multi-firings. The method further includes determining a formation type of the formation the waves traverse based properties of the waves and determining an initial shear wave slowness estimate of the waves. The method further includes generating a modeling of the waves, and reducing a mismatch between the modeling of the waves and a slowness dispersion of the waves to improve the modeling of the waves.