A method of seismic modeling using an elastic model, the elastic model including a grid having a grid spacing sized such that, when synthetic seismic data is generated using the elastic model, synthetic shear wave data exhibits numerical dispersion, the method including: generating generated synthetic seismic data using the elastic model, wherein the generated synthetic seismic data includes synthetic compression wave data and synthetic shear wave data, and modifying the generated synthetic seismic data to produce modified synthetic seismic data by attenuating at least some of the synthetic shear wave data in order to attenuate at least some of the numerically dispersive data.

A method for generating a seismic image representing a subsurface includes receiving seismic data for the subsurface formation, including receiver wavelet data and source wavelet data. Source wavefield data are generated based on a forward modeling of the source wavelet data. Receiver wavefield data are generated that compensate for distortions in the seismic data by: applying a dispersion-only model to the receiver wavelet data to generate a first reconstructed back-propagated receiver wavefield portion, applying a dissipation-only model to the receiver wavelet data to generate a second reconstructed back-propagated receiver wavefield portion, and combining the first back-propagated receiver wavefield portion and the second back-propagated receiver wavefield portion into the receiver wavefield data. The method includes applying an imaging condition to the receiver wavefield data and the source wavefield data and generating, based on applying the imaging condition, visco-acoustic reverse time migration (VARTM) result data.

System and method for guiding a drill using a subsurface model generated by successive full waveform inversions (FWI) on surface data and seismic-while-drilling (SWD) data. A server receives surface data from at least one surface sensor that records elastic energy radiated from surface seismic source and SWD data from at least one surface or at least one subsurface crosswell sensor (i.e., deployed in a nearby well). The server also receives top-drive measurements. A drillbit source signature estimation is performed, on the SWD data, by the server by blind deconvolution or by using drill string modeling and top-drive measurements. The server then performs FWI on the surface data by using the background subsurface velocity obtained by kinematic analysis of surface seismic data, to obtain an updated approximation of the subsurface velocity. The new approximation along with the drillbit source signature is then used when performing FWI on the SWD data.

A method is described for full waveform inversion using a b-spline projection that produces an earth model that can be used for seismic imaging. The method may be executed by a computer system.

A method and apparatus for identifying features of a subsurface region, including: obtaining an initial physical property model and survey data for the subsurface region; identifying a current model to be the initial physical property model; and executing one or more iterations of: generating synthetic data and forward wavefields with the current model and the survey data by forward modeling with forward wave equations representing isotropic wave-mode-independent attenuation; generating adjoint wavefields with the synthetic data and the survey data by adjoint modeling with adjoint wave equations representing isotropic wave-mode-independent attenuation; computing an objective function gradient with the forward wavefields and the adjoint wavefields by solving gradient equations with the corresponding wave equations representing isotropic wave-mode-independent attenuation; computing a search direction of the objective function; searching for a possible improved model along the search direction; and updating the current model to be the possible improved model.

Apparatus, methods, and systems for determining body wave slowness values for a target formation zone. A method includes selecting a target axial resolution based on the size of a receiver array, obtaining a plurality of waveform data sets corresponding to a target formation zone and each acquired at a different shot position, reconstructing the plurality of waveform data sets to generate a plurality of subarray data sets corresponding to the target formation zone, determining a slowness value for each subarray data set and determining a slowness versus offset value for each subarray data set. The method may also include generating a borehole model having at least one alteration formation zone and a virgin formation zone and generating a slowness versus offset model based at least in part on the borehole model. The method may also include determining a radial depth of the alteration formation zone.

Systems and methods for generating seismic images of subterranean features including: receiving raw seismic data of a subterranean formation; selecting a portion of the raw seismic data; transforming the selected portion of the raw seismic data from a first domain to a second domain; generating soft constraint data corresponding to the selected portion of the raw seismic data; calculating at least one weight using the generated soft constraint data; generating a weighted transformed data set by applying at least one weight to the transformed selected portion of the raw seismic data; selecting at least one data point of the generated weighted transformed data set; and removing the selected at least one data point from the weighted transformed data set to generate revised seismic data.

A system and method for forming a seismic image of a subterranean region of interest are provided. The method includes obtaining an observed seismic dataset for the subterranean region of interest and determining a plurality of common-offset sections from the observed seismic dataset. The method further includes determining stochastically migrated common-offset sections for each of the common-offset sections and forming a stochastic image gathers from the plurality of stochastically migrated common-offset sections. The method still further includes forming the seismic image by stacking each of the plurality of stochastically migrated common-offset sections.

The systems and methods described in this specification relate to generating a low frequency model of a subterranean formation for performing a seismic inversion. The systems and methods receive seismic data for a first region of the subterranean formation and well log data of one or more wells located at the first region. The systems and methods determine one or more relative layer attributes of the first region, one or more first input values for a machine learning model, and one or more second input values for the machine learning model. The systems and methods generate, a first relative low frequency model for the first region, and extrapolate, by executing the machine learning model by the processor, the first relative low frequency model to a second region of the subterranean formation.

The present disclosure belongs to the field of capture, utilization, and storage of carbon dioxide, particularly relates to a method and system for intelligently identifying a carbon storage box based on a GAN network, and aims at solving the problem that the analysis accuracy of a fault zone area in the prior art is insufficient. The method comprises the steps: delineating seismic waveform data of a stable sedimentary area through a GAN network, and removing seismic waveform data points in the fault zone area; obtaining a stable sedimentary background seismic waveform data invertomer; obtaining a three-dimensional wave impedance prediction data volume; making a difference to obtain an abnormal wave impedance data volume; retaining abnormal wave impedance data of fault-karst in the three-dimensional variance attribute volume to obtain a fault-karst wave impedance data volume; and then obtaining a carbon storage box interpretation model.