A logging tool for performing well logging activities in a geologic formation has one or more transmitters, one or more receivers, and a tool wave propagating factor which differs from a formation wave propagating factor. The one or more transmitters excite a tool wave and formation wave. The tool wave is reduced by the one or more transmitters transmitting an acoustic wave which causes the tool wave to be reduced. Additionally, or alternatively, the tool wave is reduced by generating an inverse estimate of the tool wave based on waveform data associated with the tool wave and formation wave received by each of the one or more receivers.

A method and apparatus for data acquisition including: acquiring a first set of data for a survey area with streamer receivers on a streamer spread; and simultaneously acquiring a second set of data for the area with ocean bottom receivers, the first and second sets of data together forming a complete dataset for velocity modeling and imaging. A method including: navigating a first propulsion source along a first path in the area, wherein a streamer spread and a first seismic source are coupled to the first propulsion source; navigating a second propulsion source along a second path in the area, wherein a second seismic source is coupled to the second propulsion source; while navigating the first and second propulsion sources, activating at least one of the first and second seismic sources; and acquiring data with receivers on the streamer spread and with ocean bottom receivers distributed throughout the area.

A method may include obtaining an input gather regarding a geological region of interest. The method may further include obtaining parameterization data regarding a seismic processing operation. The parameterization data may correspond to a first set of process parameter values that are different from a second set of process parameter values that are used to generate the input gather. The method may further include generating a predicted output gather using a machine-learning model, the input gather, and the parameterization data. The machine-learning model may include an encoder model and a decoder model. The method may further include generating a seismic image of the geological region of interest using the predicted output gather.

System and techniques to position a first source array at a fixed first inline distance from a vessel, position a second source array at a fixed second inline distance from a vessel, wherein the fixed second horizontal inline distance differs from the fixed first horizontal distance, generating a spatial coding, fire the first source array, and fire the second source array.

A multi-stage inversion method for deblending seismic data includes: a) acquiring blended seismic data from a plurality of seismic sources; b) constructing an optimization model that includes the acquired blended seismic data and unblended seismic data; c) performing sparse inversion, via a computer processor, on the optimization model; d) estimating high-amplitude coherent energy from result of the performing sparse inversion in c); e) re-blending the estimated high-amplitude coherent energy; and f) computing blended data with an attenuated direct arrival energy.

Methods and systems to separate seismic data associated with impulsive and non-impulsive sources are described. The impulsive and non-impulsive sources may be towed through a body of water by separate survey vessels. Receivers of one or more streamers towed through the body of water above a subterranean formation generate seismic data that represents a reflected wavefield produced by the subterranean formation in response to separate source wavefields generated by simultaneous activation of the impulsive source and the non-impulsive source. Methods and systems include separating the seismic data into impulsive source seismic data associated with the impulsive source and non-impulsive source seismic data associated with the non-impulsive.

Techniques for processing of seismic data. A seismic data set is received, wherein the seismic data set comprises a first data subset associated with a first seismic source and a second data subset associated with a second seismic source. An input is received indicating that a distance between the first seismic source and the second seismic source is greater than or equal to a threshold value. The second data set is filtered from the seismic data set to remove the second data subset from seismic data set to generate a filtered seismic data set in response to receiving the input and a coherence volume is generated based on the filtered seismic data set.

A multi-stage inversion method for deblending seismic data includes: a) acquiring blended seismic data from a plurality of seismic sources; b) constructing an optimization model that includes the acquired blended seismic data and unblended seismic data; c) performing sparse inversion, via a computer processor, on the optimization model; d) estimating high-amplitude coherent energy from result of the performing sparse inversion in c); e) re-blending the estimated high-amplitude coherent energy; and f) computing blended data with an attenuated direct arrival energy.

Techniques are disclosed relating to geophysical surveying. In various embodiments, a computer system may access seismic data for a geological formation, where the seismic data is recorded, using one or more sensors, during a seismic survey in which a first vibratory source was driven using a first digital code for at least a first time interval. The first digital code, in some embodiments, may include a first plurality of subsections corresponding to portions of the first time interval. In some embodiments, the computer system may image a first location of the geological formation using a correlation of only a first sub-section of the first plurality of sub-sections with the seismic data. Further, in some embodiments, the computer system may image a second location of the geological formation using a correlation of two or more of the first plurality of sub-sections with the seismic data.

Methods and systems for seismic data acquisition in a survey area use compressed sensing and take into consideration operational limitations. The operational limitations may be related to the equipment used for the survey, the topography of the surveyed area or limitations that otherwise optimize the survey path.