A method, including: generating a velocity model for a subsurface region of the Earth by using a full wavefield inversion process; generating an impedance model for the subsurface region of the Earth by using a full wavefield inversion process; and estimating pore pressure at a prediction site in the subsurface region by integrating the velocity model and the impedance model with a velocity-based pore pressure estimation process.

A method and system for modeling a subsurface region include applying a trained machine learning network to an initial petrophysical parameter estimate to predict a geologic prior model; and performing a petrophysical inversion with the geologic prior model, geophysical data, and geophysical parameters to generate a rock type probability model and an updated petrophysical parameter estimate. Embodiments include managing hydrocarbons with the rock type probability model. Embodiments include checking for convergence of the updated petrophysical parameter estimate; and iteratively: applying the trained machine learning network to the updated petrophysical parameter estimate of a preceding iteration to predict an updated rock type probability model and another geologic prior model; performing a petrophysical inversion with the updated geologic prior model, geophysical seismic data, and geophysical elastic parameters to generate another rock type probability model and another updated petrophysical parameter estimate; and checking for convergence of the updated petrophysical parameter estimate.

Systems and methods are disclosed that include generating reservoir property profiles corresponding to reservoir properties for pseudo wells based on reservoir data, generating seismic attributes for the pseudo wells, and training a machine learning model by comparing the reservoir property profiles against the seismic attributes. In this manner, the machine learning model may be used to predict reservoir properties for use with seismic exploration above a region of a subsurface that contains structural or stratigraphic features conducive to a presence, migration, or accumulation of hydrocarbons.

A method includes receiving a first transition probability matrix (TPM) of a subsurface region, wherein the TPM defines, for a given lithology at a current depth sample (or micro-layer), a probability of particular lithologies at a next depth sample (or micro-layer), receiving seismic data for the subsurface region, utilizing the first TPM and the seismic data to generate first pseudo wells, calculating a second TPM from the first pseudo wells, determining whether the second TPM is consistent with the first TPM, and utilizing the first pseudo wells to characterize a reservoir in the subsurface region when the second TPM is determined to be consistent with the first TPM.

A method, including performing, with a computer, up/down separation of geophysical data, which produces an approximate up-going wavefield and an approximate down-going wavefield; creating an areal source based at least in part on the down-going wavefield; and performing, with a computer, a full wavefield inversion process with the areal source, and an objective function measuring a misfit between modeled up-going wavefields and recorded up-going wavefields, wherein the full wavefield inversion process generates a final subsurface physical property model.

A method for estimating surface waves generates incident, back-scattered, virtual back-scattered and super-virtual back-scattered traces. The stacked super-virtual back-scattered traces are an estimate of the surface waves.

Surface wave coda in seismic data recorded with a data acquisition system over an underground formation is estimated using time-reversal experiments. First time-reversal experiments use a first time-reversal mirror including a target source and one or more other sources to obtain estimates of surface waves traveling from other receivers to a target receiver. Second time-reversal experiments obtain a coda estimate for a surface wave traveling from the target source to the target receiver using a second time-reversal mirror including the target receiver and the other receivers.

A method includes receiving information for a subsurface region; based at least in part on the information, identifying sub-regions within the subsurface region; assigning individual identified sub-regions a dimensionality of a plurality of different dimensionalities that correspond to a plurality of different models; via a model-based computational framework, generating at least one result for at least one of the individual identified sub-regions based at least in part on at least one assigned dimensionality; and consolidating the at least one result for multiple sub-regions.

A method may include obtaining a P-wave velocity model and velocity ratio data regarding a geological region of interest. The method may further include generating, based on the P-wave velocity model and the velocity ratio data, an initial S-wave velocity model regarding the geological region of interest. The method may further include determining various velocity boundaries within the initial S-wave velocity model using a trained model. The method may further include updating the initial S-wave velocity model using the velocity boundaries, an automatically-selected cross-correlation lag value based on various seismic migration gathers, and a migration-velocity analysis to produce an updated S-wave velocity model. The method further includes generating a combined velocity model for the geological region of interest using the updated S-wave velocity model and the P-wave velocity model.

A method includes the steps of receiving a wavefield generated by reflections in a subsurface region and recorded by a plurality of seismic receivers and compensating the recorded wavefield for amplitude attenuation. The method further includes modelling a propagation of a source wavefield forward in time, from an initial time-state to a final time-state through an earth model that is representative of the subsurface region, wherein the modelling includes phase and amplitude effects of attenuation and modelling a propagation of the compensated recorded wavefield backward in time from a final time-state to an earlier time-state through the earth model, wherein the subsurface region has an absorption characteristic that dampens the recorded wavefield wherein the modelling includes phase and amplitude effects of attenuation.