A method can include accessing data associated with a well and one or more offset wells; based on at least a portion of the data, generating a set of distributions via parametric estimation, where the distributions are associated with a well-related activity and time; analyzing individual distributions in the set of distributions with respect to at least a portion of the data to pass or fail each of the individual distributions; and, for one or more passed individual distributions, outputting one of the passed individual distributions for the well.

A system to obtain information about a subsurface formation, in some embodiments, comprises an array of acoustic transmitters in a first well; a distributed acoustic sensing (DAS) fiber in a second well; and processing logic, in communication with the array of acoustic transmitters and the DAS fiber, that activates the array of acoustic transmitters and the DAS fiber so as to use the Doppler effect to obtain information about the subsurface formation.

One embodiment includes receiving distributed acoustic sensing (DAS) data for responses associated with seismic excitations in an area of interest. The area of interest includes a sea surface, the water column, a seafloor, and a subseafloor. The seismic excitations are generated by at least one seismic source in the area of interest. The responses are detected by at least one fiber optic sensing apparatus configured for DAS that is in the water column, on the seafloor, in a wellbore drilled through the seafloor and into the subseafloor, or any combination thereof. The embodiment includes determining a function of speed of sound in water using the DAS data, and correcting a digital seismic image associated with the area of interest using the function of speed of sound in water to generate a corrected digital seismic image.

The current disclosure is directed to methods and systems to determine properties of a subterranean formation located below a body of water. The methods and systems compute synthetic pressure and velocity vector wavefields that represent acoustic energy interactions within a model environment that comprises a model body of water located above a model subterranean formation. The model environment is separated into a stationary region and a time-varying region. The methods and systems include determining properties of the subterranean formation by iteratively adjusting the model environment to approximate the actual subterranean formation. The model environment is iteratively adjusted until a minimum difference between the synthetic pressure and velocity vector wavefields computed for each change to the model environment and actual pressure and velocity wave fields obtained from a marine seismic survey of the subterranean formation is achieved.

Method for acquiring, at reduced acquisition cost, seismic data using simultaneous, field-encoded sources in the field (702), and then constructing pseudo source-records (703) that better meet the requirements for using additional simultaneous computer-encoded sourcing for computer simulations or forward modeling (706) as part of (707) iterative FWI (Full Wavefield Inversion) or RTM (Reverse Time Migration), with additional reduction in computational costs. By better meeting the requirements of simultaneous sourcing for FWI or RTM (701), artifacts and crosstalk are reduced in the output. The method can be used for marine streamer acquisition and other non-fixed spread geometries to acquire both positive and negative offsets and to mitigate the “missing data” problem for simultaneous-source FWI. It can also be used for land data to overcome issues with moving spreads and long continuous records.

A method (1310) for attributing a systems tract to a geological environment, including computing (1314) a shelf break for a geologic environment based at least in part on implicit function values associated with the geologic environment; identifying (1318) sea level variations with respect to geological time for the shelf break; and assigning (1322) at least one systems tract to the geologic environment based at least in part on the sea level variations.

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 computer-implemented method includes receiving a test seismic dataset associated with a known truth interpretation, receiving one or more hard constraints, training a machine learning system based on the test seismic dataset, the known truth interpretation, and the one or more hard constraints, determining an error value based on the training the machine learning system, adjusting the error value based on one or more soft constraints, updating the training of the machine learning system based on the adjusted error value, receiving a second seismic dataset after the updating the training; applying the second seismic dataset to the machine learning system to generate an interpretation of the second seismic dataset, generating a seismic image representing a subterranean domain based on the interpretation of the second seismic dataset, and outputting the seismic image.

A method of estimating a mineral content of a seabed geological structure is provided wherein there is provided at least one geophysical parameter of the geological structure. The method includes inverting the at least one geophysical parameter to estimate the mineral content of the geological structure.

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.