A method includes receiving a model representing a real subsoil geological formation. The model includes a stratigraphic layer, which includes a shore line dividing the stratigraphic layer into a continental zone and a marine zone. First and second flow speed fields are received, with the first flow speed field representative of a continental domain for the stratigraphic layer, and the second flow speed field representative of a marine domain for the stratigraphic layer. A global flow speed field is determined and includes a weighted combination of the first and second flow speed fields for each position in the stratigraphic layer. Weights of the combination are based on a distance of the position to the shore line and whether the position is within the continental zone or the marine zone. The real subsoil geological formation for the stratigraphic layer is determined based on the determined global flow speed field.

A surface wave prospecting method for jointly extracting Rayleigh wave frequency dispersion characteristics in a seismoelectric field. A surface wave prospecting method includes following steps of: acquiring jointly acquired data, where the jointly acquired data includes seismic wave data and electric field data; carrying out jointly imaging processing on jointly acquired data to obtain a superposed frequency dispersion spectrum; carrying out extraction processing on superposed frequency dispersion spectrum to obtain a frequency dispersion curve, outperforming inversion processing on frequency dispersion curve to obtain a stratum structure profile. As seismic wave data and electric field data are adopted to carry out combined imaging processing to obtain superposed frequency dispersion spectrum, multi-mode frequency dispersion curve is extracted, multiplicity of solutions of inversion is greatly reduced during inversion, precision and stability of surface wave prospecting are greatly improved.

This specification describes workflows for, but is not limited to, performing full waveform inversion (FWI) to build high resolution velocity models to improve the accuracy of seismic imaging of a subterranean formation. This specification describes processes to automatically edit and enhance S/N quality of seismic data (such as land seismic data) to prepare the datasets for FWI. The methods for automatic corrections and pre-processing include: automatic iterative surface-consistent residual statics calculation, automatic rejection of anomalous traces (such as dead traces), and the automatic correction of surface-consistent amplitude anomalies (such as by scalar or deconvolution approaches). The operations include automatic “muting” of noise before first arrivals.

Disclosed are a multi-scale photoacoustic detection method of geological structure around a borehole and related devices. The method includes: obtaining depth information and direction information of the borehole; generating trajectory data of the borehole according to the depth information and direction information; obtaining an optical image of the geological structure around the borehole; generating a first velocity model according to the optical image and the trajectory data; obtaining low-frequency acoustic wave data and high-frequency acoustic wave data of the geological structure around the borehole; performing a full waveform inversion on the first velocity model according to the low-frequency acoustic wave data and the high-frequency acoustic wave data to obtain a second velocity model; and determining the geological structure around the borehole according to the second velocity model.

Techniques, systems and devices to generate a seismic wavefield solution. This includes receiving a velocity model corresponding to at least one attribute of seismic data, receiving source wavelet data corresponding to the seismic data, generating a guide image based upon at least one attribute of the velocity model, transmitting the velocity model, the source wavelet data, and the guide image to a machine learning system, and training the machine learning system into a trained machine learning system using the velocity model, the source wavelet data, and the guide image.

Disclosed are methods, systems, and computer-readable medium to perform operations including: receiving for a plurality of common midpoint-offset bins each comprising a respective plurality of seismic traces, respective candidate pilot traces representing the plurality of common midpoint-offset bins; generating, based on the respective candidate pilot traces, a respective plurality of corrected seismic traces for each of the plurality of common midpoint-offset bins; grouping the respective pluralities of corrected seismic traces into a plurality of enhanced virtual shot gathers (eVSGs); generating, based on the plurality of common midpoint-offset bins, a common-midpoint (CMP) velocity model; calibrating the CMP velocity model using uphole velocity data to generate a pseudo-3 dimensional (3D) velocity model; performing, based on the plurality of enhanced virtual shot gathers and the pseudo-3D velocity model, a 1.5-dimensional full waveform inversion (FWI); and determining the subsurface velocity model based on the 1.5 dimensional FWI.

Methods and devices for seismic exploration of an underground structure apply W.sup.2-based full-wave inversion to transformed synthetic and seismic data. Data transformation ensures that the synthetic and seismic data are positive definite and have the same mass using an adaptive normalization. This approach yields superior results particularly when the underground structure includes salt bodies.

Methods and systems including computer programs encoded on a computer storage medium, for utilizing equivalent linear velocity for first arrival picking of seismic refraction. In one aspect, a method includes receiving data for the shot gather record, generating a diving wave equation curve for a particular parameter pair of multiple parameter pairs, and integrating the shot gather record data corresponding to the diving wave equation curve over a selected range of offsets of the shot gather to generate an equivalent linear velocity value for the particular parameter pair and the shot gather record data, selecting, from the equivalent linear velocity values for the plurality of parameter pairs, a greatest equivalent linear velocity value of the equivalent linear velocity values, the greatest equivalent linear velocity value corresponding to a first-arrival parameter pair, and determining, using the first-arrival parameter pair, a set of first-arrival onsets for the selected sub-range of offsets.

A computer-implemented method and computing system apparatus programmed to perform operations of the computer-implemented method for obtaining a subsurface stack image, subsurface angle gathers, and a subsurface velocity model over an entire survey region having high velocity contrast geo-bodies. Particularly, user inputs, input velocity models, and surface-seismic data are obtained by fixed source and receiver pairs and then used by the computer program product embedded within the computing system apparatus to minimize the number of iterations, required to obtain a final velocity model, a final stack image, and final angle gathers wherein their flatness deviation is equal to, or less than, a user-defined flatness value. Therefore, the attributes developed by said computer-implemented method and system can help solve the imaging problem of sub high velocity contrast geo-bodies like subsalt, or salt overhung deep mini basins.

A data seismic sensing system and method for obtaining seismic refraction data and tomography data. The system may comprise a subsurface sensor array, wherein the subsurface sensor array is a fiber optic cable disposed near a wellbore, a seismic source, wherein the seismic source is a truck-mounted seismic vibrator comprising a base plate, and a surface sensor array, wherein the surface sensor array is coupled to the seismic source. The method may comprise disposing a surface sensor array on a surface, disposing a subsurface sensor array into a wellbore, activating a seismic source, wherein the seismic source is configured to create a seismic wave, recording a reflected seismic wave with the surface sensor array and the subsurface sensor array, and creating a seismic refraction data and a seismic tomography data from the reflected seismic wave.