Methods and systems for determining an image of a subterranean region of interest are disclosed. The method includes obtaining a seismic dataset and a geological dip model for the subterranean region of interest and determining a set of input seismic gathers from the seismic dataset. The method further includes determining a central seismic gather and a set of neighboring seismic gathers in a vicinity of the central seismic gather from the set of seismic gathers, determining a set of dip-corrected neighboring seismic gathers based, at least in part, on the set of neighboring seismic gathers and a geological dip from the geological dip model, and determining a noise-attenuated central seismic gather by combining the dip-corrected neighboring seismic gathers and the central seismic gather. The method still further includes forming the image of the subterranean region of interest based, at least in part, on the noise-attenuated central seismic gather.

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.

A plurality of sensors and a controller are disposed in a marine seismic streamer. Each of the sensors comprises an enclosure having two opposing interior walls, first and second piezoelectric elements disposed on the opposing interior walls, a third piezoelectric element disposed on a flexible substrate within the enclosure between the opposing interior walls, a pressure signal output node and an acceleration signal output node disposed on the exterior surface of the enclosure. A combined pressure signal derived from the pressure signal output nodes of the plural sensors is coupled to a pressure signal input of the controller. A combined acceleration signal derived from the acceleration signal output nodes of the plural sensors is coupled to an acceleration signal input of the controller. The streamer may be towed, and the combined pressure and acceleration signals may be recorded in a computer-readable medium.

One or more first sensors may be configured to sense seismic signals and one or more second sensors may be configured to sense electromagnetic crosstalk signals. The second sensors are not responsive to the seismic signals. The data from the first and second sensors may be recorded as first data and second data, respectively. The first data may be modified based on the second data to remove the electromagnetic crosstalk noise form the seismic data.

A method includes receiving seismic data including signals collected using a receiver, separating a downgoing wavefield from an upgoing wavefield in the signals, generating a modified downgoing wavefield by removing direct arrivals from the downgoing wavefield, estimating a first-order multiple reflection signal at least partially by deconvolving the modified downgoing wavefield and the downgoing wavefield, and generating a seismic image based at least in part on the estimated first-order multiple reflection signals.

Aspects of the present disclosure describe dynamic road traffic noise mapping using DFOS over a telecommunications network that enables mapping of road traffic-induced noise at any observer location. DFOS is used to obtain instant traffic data including vehicle speed, volume, and vehicle types, based on vibration and acoustic signal along the length of a sensing fiber along with location information. A sound pressure level at a point of interest is determined, and traffic data associated with such point is incorporated into a reference noise emission database and a wave propagation theory for total sound pressure level prediction and mapping. Real-time wind speed using DFOS—such as distributed acoustic sensing (DAS)—is obtained to provide sound pressure adjustment due to the wind speed.

A distributed acoustic sensor is positioned within a wellbore of a geologic formation. Seismic waves are detected using the distributed acoustic sensor. A raw seismic profile is generated based on the detected seismic waves. Resonant noise is identified and reduced in seismic data associated with the raw seismic profile.

Techniques are disclosed for reducing noise when computing time-lapse differences between two or more geophysical surveys performed over the same region. In some computer-implemented embodiments, a time-lapse difference is determined between first and second data representing the first and second surveys, respectively. Based on geometry information corresponding to the second survey, first estimated data is generated representing how the first data would have looked if the second survey geometry had been used during the first survey. A noise model is generated based on differences between the first data and the first estimated data. The time-lapse difference is then adjusted using the noise model, thereby reducing noise in the time-lapse difference caused by differences between the geometries of the first and second surveys.

Systems and methods for filtering interface waves from single component seismic data are disclosed. In one embodiment, a method of filtering seismic data includes comparing amplitude coefficients of a matrix storing the seismic data in a time-frequency domain against an amplitude threshold, and comparing frequencies of the matrix against a maximum expected frequency of noise. The method further includes, for each amplitude coefficient having less than the amplitude threshold and an associated frequency less than the maximum expected frequency of noise, scaling the amplitude coefficient to reduce its value. The method also includes performing an inverse time-frequency transformation on the matrix to generate a noise model in a time domain, and subtracting the noise model from the seismic data in the time domain to generate filtered seismic data.

Seismic image processing including filtering a three-dimensional (3D) seismic image for random noise attenuation via multiple processors. The filtering includes receiving a 3D image cube of seismic image data, decomposing the 3D image cube into 3D sub-cubes for parallel computation on the multiple processors, designing and applying a two-dimensional (2D) adaptive filter for image points on 2D image slices of the 3D sub-cubes via the multiple processors to give filtered 3D sub-cubes, and summing the filtered 3D sub-cubes to give a filtered 3D image cube.