Methods include receiving a set of seismic data including a seismic signal generated over the course of a set period of time as a time scale, partitioning the seismic signal into a predetermined integer number greater than one of partitioned seismic signals each associated with a respective fixed position associated with a respective time interval as a portion of the time scale, applying a pulse compression technique to each partitioned seismic signal of the predetermined number of partitioned seismic signals to generate a compressed partitioned seismic signal corresponding to each partitioned seismic signal of the predetermined number of partitioned seismic signals, and inserting the compressed partitioned seismic signal corresponding to each partitioned seismic signal of the predetermined number of partitioned seismic signals in parallel into a velocity model builder. In addition, the methods include summing generated results therefrom to model the seismic signal for the time scale.

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.

A method of realizing an shear wave propagation velocity anisotropy characterization within a display for a wellbore region including, obtaining a shear wave propagation velocity anisotropy intensity, and a shear wave propagation velocity anisotropy azimuth. A directional line segment is determined to represent the anisotropy for each of a plurality of measured depth points along the wellbore, and plotted on the display as a plurality of directional line segments to produce a 1-dimensional anisotropy characterization plot.

Systems and methods for determining shear failure of a rock formation are disclosed. The method includes receiving, by a processor, a plurality of parameters related to physical properties of the rock formation, applying the plurality of parameters to a predetermined failure criterion, and determining shear failure of the rock formation based on the failure criterion. In some embodiments the failure criterion is a modified Hoek-Brown failure criterion that takes into consideration an intermediate principal stress, and the difference between normal stresses and an average confining stress.

Geologic modeling methods and systems disclosed herein employ an improved simulation gridding technique. For example, an illustrative geologic modeling method may comprise: obtaining a geologic model representing a faulted subsurface region in physical space; mapping the physical space geologic model to a design space model representing an unfaulted subsurface region; gridding the design space model to obtain a design space mesh; partitioning cells in the design space mesh with faults mapped from the physical space geologic model, thereby obtaining a partitioned design space mesh; mapping the partitioned design space mesh to the physical space to obtain a physical space simulation mesh; and outputting the physical space simulation mesh.

A dip angle-steering median filtering method based on a niche differential evolution algorithm, comprising the following steps: dividing a data to be processed into a series of overlapping time-space windows; obtaining an event energy curve in a time-space window and obtaining an event position according to a local maximum value of the event energy curve; obtaining event dip angles and coherence values of the event dip angles through the niche differential evolution algorithm at the event position; filtering the event dip angles according to the event dip angles and the coherence values of the event dip angles; and performing a median filtering sequentially along a filtering dip angle. The disclosure can simultaneously obtain all dip angles of intersecting events and a true three-dimensional feature enable the present disclosure to obtain a better filtering effect.

Disclosed are methods, systems, and computer-readable medium to perform operations including: generating, using a source wavelet and a current velocity model, modeled seismic data of the subterranean formation; applying a pre-condition to a seismic data residual calculated using the modeled seismic data and acquired seismic data from the subterranean formation; generating a velocity update using the source wavelet and the pre-conditioned seismic data residual; updating, using the velocity update, the current velocity model to generate an updated velocity model; determining that the current velocity model satisfies a predetermined condition; and responsively determining that the updated velocity model is the velocity model of the subterranean formation.

This disclosure describes a system and method for generating a subsurface model representing lithological characteristics and attributes of the subsurface of a celestial body or planet. By automatically ingesting data from many sources, a machine learning system can infer information about the characteristics of regions of the subsurface and build a model representing the subsurface rock properties. In some cases, this can provide information about a region using inferred data, where no direct measurements have been taken. Remote sensing data, such as aerial or satellite imagery, gravimetric data, magnetic field data, electromagnetic data, and other information can be readily collected or is already available at scale. Lithological attributes and characteristics present in available geoscience data can be correlated with related remote sensing data using a machine learning model, which can then infer lithological attributes and characteristics for regions where remote sensing data is available, but geoscience data is not.

A method to model a subterranean formation of a field. The method includes obtaining a seismic volume comprising a plurality of seismic traces of the subterranean formation of the field, computing, based on the seismic volume, a seismically-derived value of a structural attribute representing a structural characteristic of the subterranean formation, computing, based on a structural model, a structurally-derived value of the structural attribute, the structural model comprising a plurality of structural layers of the of the subterranean formation, comparing the seismically-derived value and the structurally-derived value to generate a difference value representing a discrepancy of modeling the structural attribute at a corresponding location in the subterranean formation, and generating a seismic interpretation result based on the difference value and the corresponding location.

A method for surveying, may include receiving, by a processor, first survey data from a first source, the first source comprising a first signal generated by a subsurface earth formation in response to a passive-source electromagnetic signal, wherein the electromagnetic signal is generated by an electroseismic or seismoelectric conversion of the passive-source electromagnetic signal. The method may also include receiving, by the processor, second survey data from a second source and processing the first survey data and the second survey data to determine one or more properties of a subsurface earth formation.