The present invention discloses systems and methods for attenuation of coherent environmental and source-generated noise in a continuously recorded domain of seismic survey testing. Rather than applying universal de-noising techniques to conventional gathers after source de-blending, the system and methods discussed herein focus on estimating and removing noise directly on continuous records by leveraging the noise characteristics in the domain of natural recording. Such techniques may equally be applied to coherent environmental and source-generated noises on seismic data as well as other data and noise types. Driven by the noise types encountered in the field, the methods of noise attenuation may be based upon time-frequency domain rank reduction techniques. Further, to model signal and/or noise, low-rank approximations are employed in conjunction with other techniques such as operator design and unsupervised learning.

The present invention discloses systems and methods for attenuation of coherent environmental and source-generated noise in a continuously recorded domain of seismic survey testing. Rather than applying universal de-noising techniques to conventional gathers after source de-blending, the system and methods discussed herein focus on estimating and removing noise directly on continuous records by leveraging the noise characteristics in the domain of natural recording. Such techniques may equally be applied to coherent environmental and source-generated noises on seismic data as well as other data and noise types. Driven by the noise types encountered in the field, the methods of noise attenuation may be based upon time-frequency domain rank reduction techniques. Further, to model signal and/or noise, low-rank approximations are employed in conjunction with other techniques such as operator design and unsupervised learning.

Methods and systems for identifying near-surface heterogeneities in a subterranean formation using surface seismic arrays can include: recording raw seismic data using sensors at ground surface; applying a band bass filter to the raw seismic data using a central frequency; picking a phase arrival time for the filtered data; generating an initial starting phase velocity model for tomographic inversion from the raw seismic data; applying tomographic inversion to the filtered data to generate a dispersion map associated at the central frequency; repeating the applying a band bass filter, picking a phase arrival time, generating an initial starting velocity model, and applying tomographic inversion steps for each of a set of central frequencies; and generating a three-dimensional dispersion volume representing near-surface conditions in the subterranean formation by combining the dispersion maps.

A system and method are provided for automatically correlating geologic tops. The system receives well logs from different well bores and each of the picks is added to a priority queue ordered by each pick's quality measure. User selected picks are assigned the highest level of quality measure. The system performs correlation by selecting a window of well log data about a pick selected from the top of the priority queue and then finding the best optimal match with a corresponding window in a neighboring wellbore.

A method or system is configured for determining a seismic attenuation quality factor Q for intervals of subsurface formations by performing actions including receiving vertical seismic profile traces. The actions include filtering the vertical seismic profile traces with an inverse impulse response of a downhole receiver. The actions include transforming the vertical seismic profile data from the particle motion measured by the downhole receiver to the far-field particle motions represented by the source wavelet. The actions include determining a ratio of the spectral amplitudes of the direct arrival event of the transformed vertical seismic profile data and the source Klauder wavelet. A quality factor Q is generated representing an attenuation of the seismic signal between the source at ground level surface and the downhole receiver.

Embodiments provide for a method that utilizes the azimuthally spaced receivers of a sonic logging tool. Signals from monopole and dipole sources are reflected from the geologic interfaces and recorded by arrays of receivers of the same tool. For the incident P-waves from the monopole source, phase arrival times for the azimuthal receivers are compensated for stacking using properties of wave propagation in the borehole, and for the incident SH-waves from the dipole source, signs of waveforms for the receivers are changed for specified azimuths.

Seismic data are obtained by recording simultaneously in seismic streamer, acquired by activating approximately simultaneously two or more seismic sources towed at two positions in the vicinity of seismic streamers. A residual is updated iteratively for an inversion solution for the activations of the two or more seismic sources. The iterative updating of the residuals utilizes a sequence of overlapping temporal windows containing reflection events and utilizes normal moveout corrections based on largest reflection events in each temporal window. A final updated residual is added to a final updated model result.

Seismic data are obtained by recording simultaneously in seismic streamer, acquired by activating approximately simultaneously two or more seismic sources towed at two positions in the vicinity of seismic streamers. A residual is updated iteratively for an inversion solution for the activations of the two or more seismic sources. The iterative updating of the residuals utilizes a sequence of overlapping temporal windows containing reflection events and utilizes normal moveout corrections based on largest reflection events in each temporal window. A final updated residual is added to a final updated model result.

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 frequency response estimation method to compensate for channel differences in distributed acoustic sensing systems include two compensation algorithms, online and offline, and these two compensation algorithms are presented to generate standardized mel-frequency features, as an input to neural networks. By this scheme, the variance of mel-frequency feature space is decreased and normalized among different channels, which enables to use less training data and smaller architectures for classification and anomalous event detection tasks.