Abstract: A system provides seismic images of the subsurface by enhancing pre-stack seismic data. The system obtains seismic data comprising a plurality of seismic traces that are generated by measuring reflections of seismic waves emitted into a geological formation. The system sorts seismic data into at least one multidimensional gather comprising a data domain. The system determines local kinematical attributes of a seismic trace. The system forms an ensemble of seismic traces, each representing a reference point. The system applies local moveout corrections to each seismic trace of the ensemble. The system applies residual statics and phase corrections for each seismic trace that is corrected by the local moveout corrections. The system sums the seismic traces of the ensemble to obtain an output seismic trace having an increased signal-to-noise ratio (SNR) relative to the seismic trace that represents the reference point for the ensemble of seismic traces.

Abstract: Disclosed are methods, systems, and computer-readable medium to perform operations including: receiving prestack single sensor seismic data; representing traveltime moveout of the prestack single sensor seismic data locally as a second-order curve; calculating, using the prestack single sensor seismic data, local kinematic parameters that define the second-order curve; and performing, based in part on the local kinematic parameters, wavefield transformation on the single sensor seismic data to generate enhanced prestack single sensor seismic data.

Abstract: The disclosure provides systems and methods to enhance pre-stack data for seismic data analysis by: sorting the reflection seismic data acquired from cross-spread gathers into sets of data sections; performing data enhancement on the sets of data sections to generate enhanced traces by: (i) applying forward normal-moveout (NMO) corrections such that arrival times of primary reflection events become more flat, (ii) estimating beamforming parameters including a nonlinear traveltime surface and a summation aperture, (iii) generating enhanced traces that combine contributions from original traces in the sets of data sections, and (iv) applying inverse NMO corrections to the enhanced traces such that temporal rearrangements due to the forward NMO corrections are undone.

Abstract: Methods, systems, and computer-readable medium to perform operations including: generating a first time-frequency spectrum of a first seismic trace from an original seismic dataset; generating a second time-frequency spectrum of a second seismic trace from an enhanced seismic dataset, where the second seismic trace; calculating a difference between the first time-frequency spectrum and the second time-frequency spectrum to generate a noise estimate in the first seismic trace; constructing, based on (i) the noise estimate, (ii) the first time-frequency spectrum, and (iii) the second time-frequency spectrum, a time-frequency mask (TFM); and using the constructed TFM to generate a third time-frequency spectrum of an output trace that corresponds to the first and second seismic traces.

Abstract: Methods, systems, and computer-readable medium to perform operations including: generating a first time-frequency spectrum of a first seismic trace from an original seismic dataset; generating a second time-frequency spectrum of a second seismic trace from an enhanced seismic dataset, where the second seismic trace corresponds to the first seismic trace; and re-combining an amplitude spectrum of the first time-frequency spectrum and a phase spectrum of the second time-frequency spectrum to generate a third time-frequency spectrum of an output trace that corresponds to the first and second seismic traces.

Abstract: Methods, systems, and computer-readable medium to perform operations including: generating a first time-frequency spectrum of a first seismic trace from an original seismic dataset; generating a second time-frequency spectrum of a second seismic trace from an enhanced seismic dataset, where the second seismic trace corresponds to the first seismic trace; calculating a difference between the first time-frequency spectrum and the second time-frequency spectrum to generate a noise estimate in the first seismic trace; characterizing the initial noise estimate as White Gaussian Noise (WGN); calculating, based on the characterization of the initial noise estimate, a third time-frequency spectrum of a refined noise estimate; constructing, based on the first time-frequency spectrum, the second time-frequency spectrum, and the third time-frequency spectrum, a time-frequency mask (TFM); and using the constructed TFM to generate a fourth time-frequency spectrum of an output trace that corresponds to the first and second

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining a velocity model for a geological region. In one aspect, a method comprises: obtaining a current velocity model for the geological region; obtaining pre-stack and post-stack seismic data characterizing the geological region; and for each of a plurality of iterations: identifying a plurality of reflection events from the post-stack seismic data and the current velocity model; determining a respective observed travel time for each of the plurality of reflection events, comprising, for each reflection event, determining the respective observed travel time for the reflection event based at least in part on kinematic features derived from a respective seismic trace included in the pre-stack seismic data; and updating the current velocity model based at least in part on the observed travel times of the plurality of reflection events.

Abstract: A system provides seismic images of the subsurface by enhancing pre-stack seismic data. The system obtains seismic data comprising a plurality of seismic traces that are generated by measuring reflections of seismic waves emitted into a geological formation. The system sorts seismic data into at least one multidimensional gather comprising a data domain. The system determines local kinematical attributes of a seismic trace. The system forms an ensemble of seismic traces, each representing a reference point. The system applies local moveout corrections to each seismic trace of the ensemble. The system applies residual statics and phase corrections for each seismic trace that is corrected by the local moveout corrections. The system sums the seismic traces of the ensemble to obtain an output seismic trace having an increased signal-to-noise ratio (SNR) relative to the seismic trace that represents the reference point for the ensemble of seismic traces.

Abstract: A system, a method, and a computer program for modelling a subsurface region of the earth for hydrocarbon exploration, development, or production, including receiving a seismic prestack dataset, determining one or more multiparameter attributes on a sparse grid based on the seismic prestack dataset, associating the one or more multiparameter attributes with color image pixels, encoding the associated one or more multiparameter attributes to generate a low-resolution colored image, inpainting the low-resolution colored image by a deep neural network to build a high-resolution colored image, and decoloring the high-resolution image.

Abstract: The disclosure provides systems and methods to enhance pre-stack data for seismic data analysis by: sorting the reflection seismic data acquired from cross-spread gathers into sets of data sections; performing data enhancement on the sets of data sections to generate enhanced traces by: (i) applying forward normal-moveout (NMO) corrections such that arrival times of primary reflection events become more flat, (ii) estimating beamforming parameters including a nonlinear traveltime surface and a summation aperture, (iii) generating enhanced traces that combine contributions from original traces in the sets of data sections, and (iv) applying inverse NMO corrections to the enhanced traces such that temporal rearrangements due to the forward NMO corrections are undone.

Abstract: A system, a method, and a computer program for modelling a subsurface region of the earth for hydrocarbon exploration, development, or production, including receiving a seismic prestack dataset, determining one or more multiparameter attributes on a sparse grid based on the seismic prestack dataset, associating the one or more multiparameter attributes with color image pixels, encoding the associated one or more multiparameter attributes to generate a low-resolution colored image, inpainting the low-resolution colored image by a deep neural network to build a high-resolution colored image, and decoloring the high-resolution image.

Abstract: A geologic survey system includes a plurality of acoustic sources spaced at intervals over a target area of a terranean surface. Each of the plurality of acoustic sensors is configured to generate a seismic energy wave. The system also includes a plurality of acoustic sensors positioned in a plurality of boreholes formed in a geologic formation, where the boreholes have a depth sufficient to reach a geologic datum. The system also includes a control system communicably coupled to the plurality of acoustic sensors and configured to perform operations including receiving, from the plurality of acoustic sensors, data associated with reflected acoustic signals generated by the plurality of acoustic sources and received by the plurality of acoustic sensors; determining, based on the received data, a subsurface topology of the geologic formation; and generating a subsurface model of the geologic formation based on the determined subsurface topology.

Abstract: A geologic survey system includes a plurality of acoustic sources spaced at intervals over a target area of a terranean surface. Each of the plurality of acoustic sensors is configured to generate a seismic energy wave. The system also includes a plurality of acoustic sensors positioned in a plurality of boreholes formed in a geologic formation, where the boreholes have a depth sufficient to reach a geologic datum. The system also includes a control system communicably coupled to the plurality of acoustic sensors and configured to perform operations including receiving, from the plurality of acoustic sensors, data associated with reflected acoustic signals generated by the plurality of acoustic sources and received by the plurality of acoustic sensors; determining, based on the received data, a subsurface topology of the geologic formation; and generating a subsurface model of the geologic formation based on the determined subsurface topology.

Abstract: A geologic survey system includes a plurality of acoustic sources spaced at intervals over a target area of a terranean surface. Each of the plurality of acoustic sensors is configured to generate a seismic energy wave. The system also includes a plurality of acoustic sensors positioned in a plurality of boreholes formed in a geologic formation, where the boreholes have a depth sufficient to reach a geologic datum. The system also includes a control system communicably coupled to the plurality of acoustic sensors and configured to perform operations including receiving, from the plurality of acoustic sensors, data associated with reflected acoustic signals generated by the plurality of acoustic sources and received by the plurality of acoustic sensors; determining, based on the received data, a subsurface topology of the geologic formation; and generating a subsurface model of the geologic formation based on the determined subsurface topology.

Abstract: A geologic survey system includes a plurality of acoustic sources spaced at intervals over a target area of a terranean surface. Each of the plurality of acoustic sensors is configured to generate a seismic energy wave. The system also includes a plurality of acoustic sensors positioned in a plurality of boreholes formed in a geologic formation, where the boreholes have a depth sufficient to reach a geologic datum. The system also includes a control system communicably coupled to the plurality of acoustic sensors and configured to perform operations including receiving, from the plurality of acoustic sensors, data associated with reflected acoustic signals generated by the plurality of acoustic sources and received by the plurality of acoustic sensors; determining, based on the received data, a subsurface topology of the geologic formation; and generating a subsurface model of the geologic formation based on the determined subsurface topology.