A method can include receiving seismic survey data of a subsurface environment from a seismic survey that includes a source arrangement of sources that is spatially denser than a receiver arrangement of receivers; processing the seismic survey data using the principle of reciprocity for performing interpolation across the receivers to generate processed seismic survey data; and generating an image of at least a portion of the subsurface environment using the processed seismic survey data.

Waves from cement bond logging with a sonic logging-while-drilling tool (LWD-CBL) are often contaminated with tool waves and may yield biased CBL amplitudes. The disclosed LWD-CBL wave processing corrects the first echo amplitudes of LWD-CBL before calculating the BI. The LWD-CBL wave processing calculates a tool wave amplitude and a phase angle difference as the difference of the phases between the tool waves and casing waves. The tool waves are then used to correct the LWD-CBL casing wave amplitude and remove errors introduced from tool waves. In conjunction with the sets of operations described, the LWD-CBL wave processing also include array preprocessing operations. Array preprocessing may employ variation of bandpass filtering and frequency-wavenumber (F-K) filtering operations to suppress tool wave.

A method for performing a formation-related operation based on corrected vertical seismic profile (VSP) data of an earth formation includes performing a VSP survey and applying a normal moveout (NMO) correction equation to the survey data that is a function of source offset to wellhead. The method also includes solving the NMO correction equation using a simulated annealing algorithm having an object function that is a coherence coefficient of semblance analysis of an NMO corrected reflection event within a time window to provide NMO corrected data. The method further includes performing the formation-related operation at at least one of a location, a depth and a depth interval based on the VSP NMO corrected data.

One method interpolates simulated seismic data of a coarse spatial sampling to a finer spatial sampling using a neural network. The neural network is previously trained using a set of simulated seismic data with the finer spatial sampling and a subset thereof with the coarse spatial sampling. The data is simulated using an image of the explored underground formation generated using real seismic data. The seismic dataset resulting from simulation and interpolation is used for denoising the seismic data acquired over the underground formation. Another method demigrates seismic data at a sparse density and then increases density by interpolating traces using a neural network.

Processes and systems for generating images of a subterranean formation from recorded seismic data obtained in a marine survey are described. Processes and systems compute reverse-time receiver-motion-corrected upgoing and downgoing pressure wavefields at different locations of corresponding upgoing and downgoing observation levels based on the recorded seismic data. The reverse-time receiver-motion-corrected upgoing and downgoing pressure wavefields are time forwarded and extrapolated to obtain a corresponding receiver-motion-corrected upgoing and downgoing pressure wavefields at locations of a static observation level. An image of the subterranean formation is generated based at least in part on the receiver-motion-corrected upgoing pressure wavefield and the receiver-motion-corrected downgoing pressure wavefield.

Embodiments deal with a method, a computer program as well as an apparatus for detecting one or more objects in the sea floor. The method comprises obtaining a receiver signal. The receiver signal is based on a scattering of multiple acoustic signals at the one or more objects in the sea floor. The receiver signal is generated by a plurality of receivers. The method further comprises grouping portions of the receiver signal to points of a detection grid. The detection grid represents a grid at the points of which the one or more objects are being localized. The method further comprises performing a travel time correction of the portions of the receiver signal with respect to the points of the detection grid. The method further comprises combining the travel time corrected portions of the receiver signal at the points of the detection grid. The method further comprises detecting the one or more objects at the points of the detection grid based on the combination of the travel time corrected portions of the receiver signal. The detection of the one or more objects is based on the scattering of the multiple acoustic signals at the one or more objects.

Systems, methods, and apparatuses for generating a subsurface image using diffraction energy information are disclosed. The systems, methods, and apparatuses may include converting a shot gather into one or more plane-wave gather using a Radon transform. The plane-wave gathers may be extrapolated into source-side wavefields and receiver-side wavefields and further generate a pseudo dip-angle gather. The diffraction energy information may be extracted from the pseudo dip-angle gather, and an image containing subsurface features may be generated from the extracted diffraction energy information. The receiver-side wavefields may be decomposed using a recursive Radon transform.

A fully automated method for correcting errors in one interpretation (13) of seismic data based on comparison to at least one other interpretation (14) of the same subsurface region. The errors may occur in any feature of the seismic data volume, for example a horizon, surface, fault, polyline, fault stick, or geo-body. In some embodiments of the invention, an error may be a hole in a horizon (53), and the whole is patched by a piece of a horizon in another interpretation (55). In an alternative embodiment of the invention, a single interpretation may be used to repair itself, for example by identifying similarly shaped, adjacent horizons (67), and merging them (68).

A method may include obtaining various seismic traces for a geological region of interest. The method may further include determining an offset attribute and an azimuthal attribute. The method may further include determining, using the offset attribute and the azimuthal attribute, a virtual trace bin for the geological region of interest. The method may further include generating a virtual trace using a subset of the seismic traces and corresponding to the virtual trace bin. The method may further include generating a velocity model for the geological region of interest using a virtual shot gather including the virtual trace and various virtual traces. A respective virtual trace among the virtual traces may correspond to a respective virtual trace bin among various virtual trace bins. The method may further include generating a seismic image of the geological region of interest using the velocity model.

A system and method for determining a set of first breaks of a seismic dataset are disclosed, the method including obtaining the seismic dataset composed of a plurality of seismic traces and a provisional first break for each seismic trace. The method further includes selecting a plurality of proximal picks for each seismic trace, determining a near-offset pick for each seismic trace starting with shortest offset and sequentially selecting traces in order of increasing offset, and determining a far-offset pick for each seismic trace starting with the farthest offset and sequentially selecting traces in order of decreasing offset. The method further includes determining a set of coincident picks based on the near-offset and the far-offset picks for each seismic trace, fitting a curve to the set of coincident picks, and determining the set of first breaks of the seismic dataset from the curve.