摘要:
Generating spectrally enhanced seismic data expresses seismic data as a convolution of reflectivity and a seismic source wavelet. This seismic source wavelet varies over a sampling interval and defining a total amount of energy over the sampling interval. An enhanced seismic source wavelet that is a single-valued energy spike that yields the total amount of energy over the sampling interval is generated. In addition, the reflectivity is modified to preserve amplitude variation with angle. The reflectivity is convoluted with the enhanced seismic source wavelet and residual energy is added to the convolution to generate the spectrally enhanced seismic data.
摘要:
Multi-vintage energy mapping selects a first seismic survey data and a second seismic survey dataset from a plurality of seismic survey datasets. The first seismic survey dataset includes a set of first energies associated with a first seismic survey geometry, and the second seismic survey dataset includes a set of second energies associated with a second seismic survey geometry. The first set of energies are mapped from the first seismic survey geometry to the second seismic survey geometry, and the second set of energies are mapped from the second seismic survey geometry to the first seismic survey geometry. An updated first seismic dataset and an updated second seismic dataset are generated such that only energies from the first and second seismic datasets associated with changes in a subsurface are preserved in the updated first and second seismic datasets.
摘要:
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.
摘要:
Property values inside an explored underground subsurface are determined using hybrid analytic and machine learning. A training dataset representing survey data acquired over the explored underground structure is used to obtain labels via an analytic inversion. A deep neural network model generated using the training dataset and the labels is used to predict property values corresponding to the survey data using the DNN model.
摘要:
Simultaneous inversion of multi-vintage seismic data obtains seismic data for vintages and generates an initial earth model for each vintage. A cost function includes a data norm term having for at least one pair of vintages of seismic data a difference norm between a difference in obtained seismic data for the at least one pair of vintages and a difference in modeled seismic data for the at least one pair of vintages. The cost function also includes a model norm term for each pair of vintages selected from at least three vintages of seismic data. Each model norm term includes a difference norm between earth models for a given pair of vintages. A closure relationship is imposed on all earth models. The earth models are adjusted for the vintages to drive the cost function to a minimum and to produce updated earth models.
摘要:
A method for spectral analysis of seismic data obtains imaged seismic data and generates orthogonally shifted imaged seismic data gathers. The orthogonally shifted imaged seismic data gathers are processed to generate a spectrally processed imaged seismic data. Alternatively, the imaged seismic data are obtained using a spectral processing filter that is a function of a magnitude of a total wavenumber of the imaged seismic data in three dimensions and a spatially variable velocity function.