Embodiments of the present disclosure provide a method and system for recognizing a mine microseismic event, and belong to the field of mine data processing. The method includes: converting historical microseismic data monitored by a mine microseismic monitoring system into a microseismic waveform image, and then, converting the microseismic waveform image into a four-neighborhood microseismic waveform graph structure; performing area defining on the microseismic waveform graph structure, and extracting a similar feature layer of any node in the microseismic waveform graph structure based on the defined area; and taking the microseismic waveform image as an input layer of an improved convolutional neural network model, and sequentially connecting the input layer with the similar feature layer as well as a convolutional layer, a pooling layer, a fully connected layer and an output layer which are pre-configured for the improved convolutional neural network model to form a recognition model for recognizing the mine microseismic event. By using the recognition model designed in the present disclosure, the similar feature layer can be extracted, so that the mine microseismic event is effectively recognized.

A least one seismic attribute is determined for each voxel of the seismic volume. A first horizon is selected for mapping and a sparse global grid is generated which includes the horizon, at least one constraint point identifying the horizon, and a number of points having a depth in the seismic volume. A value of at least one seismic attribute is determined for each point and their depths are adjusted based on the value of the seismic attribute. A map of the horizon can be generated based on the adjusted depths. Multiple local grids can be generated based on the sparse global grid, and the depths of the local grid points adjusted to generate a map of the horizon at voxel level resolution. The seismic volume can be mapped into multiple horizons, where previously mapped horizons can function as constraints on the sparse global grid.

Geologic modeling methods and systems disclosed herein employ fault face parameterization to constrain and improve the transformation of a faulted physical space geologic model into an unfaulted depositional space geologic model. An illustrative embodiment includes: associating a seismic image with each face of at least one fault in a subsurface region; determining a correspondence map between the seismic images for said at least one fault; parameterizing the faces using the correspondence map to match parameter value assignments for corresponding portions of the faces; creating a displacement map that draws together matching parameter values to align the corresponding portions of the faces; applying the displacement map to the geologic model to create a design space model; modifying the design space model; applying the displacement map in reverse to the modified design space model to obtain a modified geologic model; and outputting the modified geologic model.

Seismic image processing including filtering a three-dimensional (3D) seismic image for random noise attenuation via multiple processors. The filtering includes receiving a 3D image cube of seismic image data, decomposing the 3D image cube into 3D sub-cubes for parallel computation on the multiple processors, designing and applying a two-dimensional (2D) adaptive filter for image points on 2D image slices of the 3D sub-cubes via the multiple processors to give filtered 3D sub-cubes, and summing the filtered 3D sub-cubes to give a filtered 3D image cube.

A method and apparatus for utilizing a structured representation of a subsurface region. A method includes obtaining subsurface data for the subsurface region; and extracting the structured representation from the seismic data by: identifying geologic and fluid objects in the seismic images, wherein each object corresponds to a node of the structured representation; and identifying relationships among the identified geologic and fluid objects, wherein each relationship corresponds to an edge of the structured representation. A method further includes determining object attributes, edge attributes, and/or global attributes from the subsurface data. A method further includes inferring information from the structured representation.

A method of determining a shear-wave attenuated vertical component vertical seismic profile (VSP) dataset is disclosed. The method includes, obtaining a multi-component VSP dataset, including a vertical and a horizontal component, transforming the vertical component into a vertical spectrum and the horizontal component into a horizontal spectrum, and designing a band-pass filter based, at least in part, on an energetic signal of the horizontal spectrum. The method further includes determining a muted vertical amplitude spectrum by applying the pass-band filter to an amplitude spectrum of the vertical spectrum, determining an estimated noise model based on the muted vertical amplitude spectrum and the vertical spectrum; and determining the shear-wave attenuated vertical component VSP dataset by adaptively subtracting the estimated noise model from the vertical component of the multi-component VSP dataset. A system including a seismic source, a plurality of seismic receivers, and a seismic processor for executing the method is disclosed.

A machine-implemented method, at least one non-transitory computer-readable medium storing instructions, and a computing system are provided for attenuating noise. A computing system receives a seismic image and generates a first image using a first neural network configured to identify low-frequency ground roll in a seismic image, and a second image using a second neural network configured to identify reflections in the seismic image. A combined image is generated by combining the first image and the second image. The first neural network and the second neural network are adjusted to reduce a difference between the combined image and the seismic image using frequency constraint to guide separation of the seismic image into the first image and the second image.

A method for performing a formation-related operation based on corrected vertical seismic profile (VSP) data of an earth formation includes performing a VSP survey and applying a normal moveout (NMO) correction equation to the survey data that is a function of source offset to wellhead. The method also includes solving the NMO correction equation using a simulated annealing algorithm having an object function that is a coherence coefficient of semblance analysis of an NMO corrected reflection event within a time window to provide NMO corrected data. The method further includes performing the formation-related operation at at least one of a location, a depth and a depth interval based on the VSP NMO corrected data.

A method can include rendering a graphical user interface (GUI) to a display where the GUI includes graphical controls that correspond to windows and objects of a computational framework and a windows builder panel; responsive to receipt of instructions via the graphical controls, generating specifications for the windows and the objects; and storing the specifications for the windows and the objects as a template file.

A system for seismic imaging of a subterranean geological formation, the system includes a receiver configured to obtain seismic data comprising a data volume representing a post-stacked image. The system includes a filtering module configured to: apply frequency-wavenumber (F-K) filter to the data volume extract a negative-dip structure image and apply the frequency-wavenumber (F-K) filter to the data volume extract a positive-dip structure image. The system includes a diffraction rendering module configured to: multiply the positive-dip structure image with the negative-dip structure image and generate a diffraction-enhanced seismic image representing a geological formation of the data volume.