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.

The present disclosure describes methods and systems, including computer-implemented methods, computer program products, and computer systems, for suppressing noises in seismic data. One computer-implemented method includes receiving, at a data processing apparatus, a set of seismic data associated with a subsurface region; flattening, by the data processing apparatus, the set of seismic data according to an identified seismic event; dividing, by the data processing apparatus, the set of seismic data into a plurality of spatial windows; randomizing, by the data processing apparatus, the set of seismic data according to a random sequential order; filtering, by the data processing apparatus, the randomized seismic data; and reorganizing, by the data processing apparatus, the filtered seismic data according to a pre-randomization order.

Methods and apparatus are described for reducing noise in measurements made by one or more pressure sensors disposed in a cable having a generally longitudinal axis. Estimated axial vibration noise at a location along the cable is determined based at least in part on measurements from one or more motion sensors disposed along the cable. The estimated axial vibration noise is subtracted from pressure sensor measurements corresponding to the location. The result is noise-attenuated pressure sensor measurements corresponding to the location.

Seismic exploration methods and data processing apparatuses employ a deep neural network to remove seismic interference (SI) noise. Training data is generated by combining an SI model extracted using a conventional model from a subset of the seismic data, with SI free shots and simulated random noise. The trained DNN is used to process the entire seismic data thereby generating an image of subsurface formation for detecting presence and/or location of sought-after natural resources.

A method. In one embodiment there is provided a method in which a direction from a sensor position to a noise source is determined. A coordinate rotation is applied to a first set of signal values, wherein each signal value of the first set of signal values is based on an output of a corresponding component of a three-component particle motion sensor at the sensor position. The applying generates a rotated set of signal values. The coordinate rotation comprises a coordinate rotation transforming a first set of coordinate axes to a second set of coordinate axes, wherein the first set of coordinate axes has each coordinate axis aligned with a corresponding component of the three-component particle motion sensor at the sensor position, and the second set of coordinate axes comprises a first axis pointed in a direction opposite the direction from the sensor position to the noise source.

Seismic survey data is received, indexed into index sets, and each index set partitioned into data blocks. For each particular data block of a particular index set, the particular data block is sliced into frequency slices. For each particular frequency slice of the particular data block, the particular frequency slice is processed to remove random and erratic noise by: forming a Hankel matrix from the particular frequency slice: determining an optimal rank for the Hankel matrix, determining a clean signal and erratic noise from the ranked Hankel matrix, and returning the clean signal and erratic noise for the particular frequency slice. A clean signal is assembled from the index sets.

A method of reducing surface-scattered noise includes receiving seismic data associated with a marine region, where the marine region includes an ocean bottom, a first zone including water above the ocean bottom, and a second zone including earth subsurface layers below the ocean bottom, and the received seismic data includes signals reflected from the earth subsurface layers and surface-scattered noise reflected from the ocean bottom and an ocean surface; determining a water velocity for the first zone; determining bathymetric values of the ocean bottom; based on the determined water velocity and the bathymetric values, determining a velocity model for the marine region; based on the determined velocity model and wavelet functions of seismic source signals, calculating the surface-scattered noise by solving a wave equation; and determining the signals reflected from the earth subsurface layers by subtracting the calculated surface-scattered noise from the received seismic data.

Systems and methods include a computer implemented method for evaluating rock physical properties. Drilling acoustic signals are received in real time during a drilling operation through rock at a drilling location. Transformed data is generated in a frequency domain from the drilling acoustic signals. The transformed data includes frequency and amplitude information for the drilling acoustic signals. De-noised transformed data is generated from the transformed data by filtering noise including background noise generated in a recording system and top drive rotation generated traces. A lithological significant frequency range that includes de-noised significant data points is determined from the de-noised transformed data. Physical properties of the rock are determined in real time using drill bit rotation rates and the amplitudes of the de-noised significant data points.

A technique includes receiving data indicative of a first measurement acquired by a rotation sensor on a seismic streamer and based on the first measurement, estimating a torque noise present in a measurement acquired by a second sensor on the streamer. The technique includes attenuating the torque noise based on the estimate.

Computing device, computer instructions and method for removing cross-talk noise from seismic data and generating an image of a surveyed subsurface. The method includes receiving input seismic data D generated by firing one or more seismic sources so that source energy is overlapping, and the input seismic data D is recorded with seismic sensors over the subsurface; generating a cross-talk noise model N by replacing at least one original shot gather with a reconstructed shot gather; subtracting the cross-talk noise model N from the input seismic data D to attenuate coherent cross-talk noise to obtain processed seismic data D.sub.p; deblending the processed seismic data D.sub.p with a deblending algorithm to attenuate a residual noise to obtain deblended seismic data D.sub.d; and generating the image of the subsurface based on the deblended seismic data D.sub.d.