G01V2210/20

DETECTING STRUCTURAL AND STRATIGRAPHIC INFORMATION FROM SEISMIC DATA
20190361137 · 2019-11-28 ·

The present disclosure relates to a method of processing seismic signals comprising: receiving a set of seismic signals, applying a wavelet transformation to the set of signals and generating transformed signals across a plurality of scales. Then for each scale determining coherence information indicative of the transformed signals and generating a comparison matrix comparing the transformed signals, then outputting seismic attribute information based on combined coherence information.

Noise removal for distributed acoustic sensing data

An example method includes at least partially positioning within a wellbore an optical fiber of a distributed acoustic sensing (DAS) data collection system. Seismic data from the DAS data collection system may be received. The seismic data may include seismic traces associated with a plurality of depths in the wellbore. A quality factor may be determined for each seismic trace. One or more seismic traces may be removed from the seismic data based, at least in part, on the determined quality factors.

Detecting structural and stratigraphic information from seismic data

The present disclosure relates to a method of processing seismic signals comprising: receiving a set of seismic signals, applying a wavelet transformation to the set of signals and generating transformed signals across a plurality of scales. Then for each scale determining coherence information indicative of the transformed signals and generating a comparison matrix comparing the transformed signals, then outputting seismic attribute information based on combined coherence information.

Method and apparatus for directional designature

Methods and apparatuses for directional designature in shot domain are provided. Azimuth and take-off angles are calculated for each record in the seismic data. Directional designature is then applied to the seismic data using a source signature dependent on the azimuth and take-off angles.

DE-ALIASED SOURCE SEPARATION METHOD

Methods are described for separating the unknown contributions of two or more sources from a commonly acquired aliased wave field signals including the determination of models with reduced support in the frequency-wavenumber domain which reconstruct the wave fields of independently-activated sources after a coordinate-transform of the acquired wave field data and/or in a coordinate-transformed domain.

Televiewer image wood-grain reduction techniques

Systems, devices, and methods for evaluating an earth formation intersected by a borehole using signals produced at a plurality of borehole depths by an ultrasonic transducer in the borehole, the signals produced by the transducer including ringdown signals from the ultrasonic transducer and echo signals from a wall of the borehole from a plurality of azimuthal orientations. Methods include using peak amplitude values and arrival time values from the signals to construct a background modulation template corresponding to at least one depth; estimating, for each respective depth of the plurality of borehole depths, an azimuthally varying interference pattern predominantly resulting from a ringdown signal for each respective depth by mapping the modulation template to arrival time values corresponding to the respective depth; and subtracting, for each respective depth, the estimated varying interference pattern from the peak amplitude values corresponding to the respective depth to generate adjusted peak amplitudes.

SOURCE SEPARATION METHOD

A method and apparatus for separating the unknown contributions of two or more sources from a commonly acquired wave field including the determination of a wavenumber dependent model which reconstructs the wave field of the sources independently below a frequency set by the slowest physical propagation velocity, and applying an inversion based on the model to the commonly acquired wave field to separate the contributions.

METHODS AND SYSTEMS TO SEPARATE SEISMIC DATA ASSOCIATED WITH IMPULSIVE AND NON-IMPULSIVE SOURCES

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.

Geological Imaging and Inversion Using Object Storage

Prestack images from the object store are hierarchically combined to generate a hierarchically stacked image. The hierarchically stacked image library stored in an object store, a set of prestack image is generated by combining stacked images that includes a stacked image. The stacked image is generated by combining at least the prestack images. Based at least on the hierarchically stacked image, a quality measure of a prestack image is generated. Prior to deleting at least a subset of the prestack images from the object store and based at least on the quality measure, the prestack images are further combined to generate an enhanced stacked image. The stacked image is substituted using the enhanced stacked image. Subsequent to the substituting and prior to deleting at least the subset of the stacked images from the object store, the stacked images are combined to generate an enhanced hierarchically stacked image. The enhanced stacked image and the enhanced hierarchically stacked image are generated using failure recovery metadata. The enhanced hierarchically stacked image is presented.

Machine learning enhanced borehole sonic data interpretation

The subject disclosure relates to the interpretation of borehole sonic data using machine learning. In one example of a method in accordance with aspects of the instant disclosure, borehole sonic data is received, and machine learning is used to interpret the borehole sonic data.