A method is disclosed that includes: obtaining a seismic data volume for a subterranean region of interest; transforming, by a computer processor using a non-stationary series analysis, the seismic data volume into a seismic spectral volume where the seismic spectral volume includes a seismic spectrum for each of a plurality of voxels; and determining a seismic attribute volume composed of a seismic attribute for each of the plurality of voxels. The seismic attribute for a voxel of the plurality of voxels is based, at least in part, on an integral of the seismic spectrum for the voxel over a range bounded by a first frequency and a second frequency. The method further includes determining a presence of hydrocarbon in the subterranean region of interest based on the seismic attribute volume. A system for performing the method is also disclosed and described.

A method for customized canonical data standardization, ingestion, and storage includes: receiving a configuration set defining a formatting parameter, a unit conversion parameter, and a transmission parameter, receiving a data record from a data source, wherein the data record includes oilfield-related data, converting units within the data record to a standardized unit defined based at least partially on the unit conversion parameter, formatting the data record based at least partially on the formatting parameter, wherein the formatting parameter defines one or more modifications to make to the data record, and providing the data record to a cloud hosting system for storage after converting the units and the formatting the data record, wherein the providing the data record comprises transmitting the data record in a manner defined by the configuration set.

A method for customized canonical data standardization, ingestion, and storage includes: receiving a configuration set defining a formatting parameter, a unit conversion parameter, and a transmission parameter, receiving a data record from a data source, wherein the data record includes oilfield-related data, converting units within the data record to a standardized unit defined based at least partially on the unit conversion parameter, formatting the data record based at least partially on the formatting parameter, wherein the formatting parameter defines one or more modifications to make to the data record, and providing the data record to a cloud hosting system for storage after converting the units and the formatting the data record, wherein the providing the data record comprises transmitting the data record in a manner defined by the configuration set.

A non-blended dataset related to a same surveyed area as a blended dataset is used to deblend the blended dataset. The non-blended dataset may be used to calculate a model dataset emulating the blended dataset, or may be transformed in a model domain and used to derive sparseness weights, model domain masking, scaling or shaping functions used to deblend the blended dataset.

A non-blended dataset related to a same surveyed area as a blended dataset is used to deblend the blended dataset. The non-blended dataset may be used to calculate a model dataset emulating the blended dataset, or may be transformed in a model domain and used to derive sparseness weights, model domain masking, scaling or shaping functions used to deblend the blended dataset.

Rock reservoir structure characterization method comprises: acquiring a three-dimensional seismic data volume of a rock reservoir to be characterized; performing a transformation on all the intrinsic mode function components obtained through decomposition to obtain time-frequency spectrum of each intrinsic mode function component, and adding the time-frequency spectrums of all the components to obtain the time-frequency spectrums of the seismic data; performing cross-correlation between each of the time-frequency components of the near-well seismic traces and the synthetic seismic trace obtained by logging data of the same well, and screening out a sensitive component with the highest correlation degree as an input feature, and performing fuzzy C-means clustering and spatial smoothing on the sensitive component with the highest correlation degree to obtain a seismic facies with set standard division; and depicting the rock reservoir according to the seismic facies divided by the set standard.

A method for deblending seismic signals includes entering as input to a computer recorded signals comprising seismic energy from a plurality of actuations of one or more seismic energy sources. A model of deblended seismic data and a blending matrix are initialized. A blending matrix inversion is performed using the initialized model. The inversion includes using a scaled objective function. The inversion is constrained by a thresholding operator. The thresholding operator is arranged to recover coefficients of the model of the deblended seismic data that are substantially nonzero, against a Gaussian white noise background. The thresholded model is projected into data space. Performing the blending matrix inversion is repeated if a data residual exceeds a selected threshold and the inversion is terminated if the data residual is below the selected threshold. At least one of storing and displaying an output of the blending matrix inversion is performed when the blending matrix inversion is terminated.

A method for deblending seismic signals includes entering as input to a computer recorded signals comprising seismic energy from a plurality of actuations of one or more seismic energy sources. A model of deblended seismic data and a blending matrix are initialized. A blending matrix inversion is performed using the initialized model. The inversion includes using a scaled objective function. The inversion is constrained by a thresholding operator. The thresholding operator is arranged to recover coefficients of the model of the deblended seismic data that are substantially nonzero, against a Gaussian white noise background. The thresholded model is projected into data space. Performing the blending matrix inversion is repeated if a data residual exceeds a selected threshold and the inversion is terminated if the data residual is below the selected threshold. At least one of storing and displaying an output of the blending matrix inversion is performed when the blending matrix inversion is terminated.

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.

The invention discloses a method for exploring passive source seismic frequency resonance, which includes the following steps: Step 1: collecting, with a detector, a response signal of underground medium to form seismic time series data; Step 2, transforming the data collected in step 1 into frequency domain data, via Fourier transformation; Step 3, performing frequency domain superposition on the data at a same detection point processed through step 2, to form frequency domain amplitude superposition data; Step 4, converting, through a correction with a standard well parameter, frequency domain data processed through step 3 into depth data; Step 5, processing the data obtained in step 4 to obtain imaging data Image.sub.(d), where the imaging data Image.sub.(d) is apparent wave impedance ratio or apparent wave impedance changing as depth. The method can perform spatial and attribute imaging of the underground medium by using the seismic wave resonance principle.