Provided is a seismic vulnerability analysis system of a user's living space. The system includes: an image receiving unit configured to receive image information obtained by photographing a living space, where various things are disposed, through a camera; an image signal processing unit configured to recognize the thing photographed in the image information as an object, extract a position and size of the object in a three-dimensional space, and convert the extracted position and size into spatial information; and an earthquake simulation unit configured to simulate motion phenomena of the objects in the space when an earthquake occurs according to simulated seismic conditions based on the spatial information.

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 multi-wavefield seismic detection method and system based on construction noise of a shield machine. Multi-wavefield seismic information such as a body wave and a surface wave formed during propagation of a seismic wave generated by excitation in a stratum is obtained by using noise information caused by the construction of a shield machine as a seismic source, a stratum velocity model along a tunnel is constructed through joint inversion, and reflection wave information or the like is used for migration imaging, to eventually implement relatively accurate detection of a geological condition in front of a tunnel face of shield construction.

A computer-implemented method and computing system apparatus programmed to perform operations of the computer-implemented method for obtaining a subsurface stack image, subsurface angle gathers, and a subsurface velocity model over an entire survey region having high velocity contrast geo-bodies. Particularly, user inputs, input velocity models, and surface-seismic data are obtained by fixed source and receiver pairs and then used by the computer program product embedded within the computing system apparatus to minimize the number of iterations, required to obtain a final velocity model, a final stack image, and final angle gathers wherein their flatness deviation is equal to, or less than, a user-defined flatness value. Therefore, the attributes developed by said computer-implemented method and system can help solve the imaging problem of sub high velocity contrast geo-bodies like subsalt, or salt overhung deep mini basins.

System and methods of random noise attenuation are provided. A first model may be trained to extract random noise from seismic datasets. A second model may be trained to reconstruct leaked signals from the random noise extracted by the first model. A seismic dataset corresponding to a subsurface reservoir formation and including random noise may be obtained. Using the trained first model, at least a portion of the random noise may be extracted from the first seismic dataset. Using the trained second model, a leaked signal, which includes a portion of the seismic dataset, may be reconstructed from the extracted random noise. A cleaned seismic dataset is generated based on the reconstructed leaked signal and the extracted random noise. The cleaned seismic dataset may include a quantity of random noise that is less than that of the original seismic dataset.

Systems, methods, and computer-readable media for designing a microseismic monitoring project. The method includes receiving data representing the microseismic monitoring project for at least one subterranean volume, the data including data representing a plurality of factors associated with a design of the microseismic monitoring project. The method also includes conducting a sensitivity analysis to determine a relative sensitivity between at least two of the plurality of factors, and determining whether to update a modelling scenario for the microseismic monitoring project based on the relative sensitivity.

A method, including: obtaining Earth models including velocity, anisotropy, and attenuation reconstructing a source wavefield using the Earth models; reconstructing a receiver wavefield using the Earth models, wherein the reconstructing the source wavefield and the receiver wavefield each include applying an attenuation operator that increases an amplitude of down-going wavefields within an attenuation body and that decreases an amplitude of up-going wavefields within the attenuation body; applying an imaging condition to the source wavefield and receiver wavefield for a plurality of shots; and generating a subsurface image by stacking images for the plurality of shots.

A method of obtaining an equivalent tool model includes obtaining a set of known well data, in which the known well data includes sensor data measured by a logging tool and an actual dispersion response, and the logging tool has an actual tool size. The method also includes obtaining one or more well parameters from the known well data, and inputting the one or more well parameters and a model tool size into a rigid tool model. The method further includes obtaining an estimated dispersion response from the rigid tool model, and fitting the estimated dispersion response to the actual dispersion response by adjusting the model tool size.

A horizontal component of marine seismic survey data from an ocean bottom seismic survey can be migrated using a primary wave velocity model. The horizontal component can comprise a shear converted wave. An image of a subsurface location can based on the migration can be produced. Migrating the horizontal component can comprise wave-equation migrating the horizontal component, where the horizontal component is input as both a source wavefield and a receiver wavefield.

Systems and methods for modeling dispersion curves are disclosed. The method includes obtaining an acoustic dataset along a well that accesses a hydrocarbon reservoir. The method further includes determining a set of depth windows along the well and determining a first subset of dispersion curves for a first subset of depth windows using a dispersion model. The method still further includes initializing a second subset of dispersion curves for a second subset of depth windows using a nearest neighbor search of the first subset of dispersion curves. The method still further includes determining slowness-frequency pairs for the second subset of depth windows using the acoustic dataset and updating the second subset of dispersion curves using a recursive scanning method. The method still further includes characterizing rock properties near the well based, at least in part, on the first subset of dispersion curves and the second subset of dispersion curves.