A method of predicting parameters of an earthquake uses an array of ionosondes to scan an observed volume of an ionosphere located above a seismically active zone. The method includes monitoring ionograms provided by the array of ionosondes; detecting the presence of at least one seismic-induced irregularity (SII); determining a first predicted parameter corresponding to an epicenter location; and determining one or more predicted parameters selected from a group consisting of a magnitude, a time of occurrence, and a hypocenter depth. Algorithms for calculating the predicted parameters are presented in detail.

Example methods and systems for wavefield travel-time inversion using eikonal solver are disclosed. One example method includes obtaining multiple first-arrival times of a seismic wavefield measured at multiple receiver locations. Multiple synthetic first-arrival times corresponding to the multiple measured first-arrival times of the seismic wavefield are determined based on an eikonal solver and a near surface velocity model of the seismic wavefield. The near surface velocity model of the seismic wavefield is updated using a wavefield traveltime inversion (WTI) process and based on the multiple synthetic first-arrival times and the multiple measured first-arrival times. The updated near surface velocity model of the seismic wavefield is provided for well location determination.

A computer-implemented method includes: accessing a set of seismic data comprising a plurality of data traces received at the receivers in response to an acoustic wave being launched into a subterranean region of interest at the geophysical exploration site; estimating local traveltime operators, each associated with a sample point on the plurality of data traces; correcting at least one local traveltime operator based on, at least in part, statistical features of other local traveltime operators associated with sample points that are adjacent to the sample point associated with the at least one local traveltime operator; reconstructing a stack of wavefronts described by the at least one corrected local traveltime operator; and performing a weighted sum of the reconstructed stack of wavefronts so that an image of a wavefield in the subterranean region of interest is formed and visualized with sufficient clarity to facilitate decision making at the geophysical exploration site.

A method for estimating uncertainty in seismic-derived depth prognoses of a subsurface region includes receiving an initial velocity model of a subsurface region based on seismic data associated with the subsurface region, performing a seismic de-migration on initial post-migration seismic data obtained from the initial velocity model to obtain pre-migration seismic data, and perturbing one or more of the components of the initial velocity model to produce a plurality of perturbed velocity models that are each different from the initial velocity model. The method further includes performing a seismic migration of the pre-migration seismic data using the perturbed velocity model to obtain perturbed post-migration seismic data for each of the plurality of perturbed velocity models, estimating a depth error from a depth prognosis obtained from a selected subset of the perturbed velocity models based on characteristics of the perturbed post-migration seismic data, and estimating a depth uncertainty from the estimated depth error.

A method of predicting parameters of an earthquake uses an array of ionosondes to scan an observed volume of an ionosphere located above a seismically active zone. The method includes monitoring ionograms provided by the array of ionosondes; detecting the presence of at least one seismic-induced irregularity (SII); determining a first predicted parameter corresponding to an epicenter location; and determining one or more predicted parameters selected from a group consisting of a magnitude, a time of occurrence, and a hypocenter depth. Algorithms for calculating the predicted parameters are presented in detail.

Methods and systems for estimating converted-wave statics are disclosed. The methods include obtaining a multicomponent seismic dataset for a subterranean region, determining an array of PP-source statics and an array of PP-receiver statics for the PP-seismic dataset, generating a PP-receiver stack based on the PP-seismic dataset, the array of PP-source statics, and the array of PP-receiver statics, and generating a PS-receiver stack based on the PS-seismic dataset and the array of PP-source statics. The methods also include identifying a PP-target event on the PP-receiver stack, forming a space-time window of the PS-receiver stack guided by the PP-target event, determining an objective function, and determining an array of PS-receiver statics based on an extremum of the objective function. The methods further include forming a statics-corrected PS-seismic dataset based on the array of PS-receiver statics and the array of PP-source statics, and forming a seismic image based on the statics-corrected PS-seismic dataset.

A method can include receiving seismic data of a subsurface region; performing an iterative full waveform inversion using at least a portion of the seismic data to generate a model of the subsurface region, where the performing includes, after one or more iterations of the full waveform inversion, automatically selecting one or more parts of the seismic data for inclusion in the at least a portion of the seismic data based on data classification using one or more quality attributes; and outputting the model of the subsurface region.

Systems and methods are provided for subsurface characterization from seismic data. The system can receive seismic data comprising travel time values and offset values for a subsurface area of interest. An algorithm can perform a grid search across the seismic data using travel time detectability criteria in an interval time domain to determine high and low bounds of NMO velocity and a anisotropic anellipticity parameter. The system can generate depth functions based on the high and low bounds of the NMO velocity and the anisotropic anellipticity parameter. The depth functions can be used to determine the depth uncertainty. A graphical representation of the depth uncertainty can be generated. The system can characterize the subsurface area of interest based on the depth uncertainty.

This disclosure discloses a velocity identification method and apparatus for interbed multiples, including: obtaining a velocity spectrum and propagation paths of interbed multiples in a stratum; collecting, from the velocity spectrum, velocities of a plurality of energy clusters, and obtaining propagation velocities and propagation duration of a plurality of primaries; calculating propagation velocities and propagation duration of an interbed multiples corresponding to each primary order by order, to obtain propagation velocities and propagation duration of low-order interbed multiples; and determining a horizon at which a low-order interbed multiples are generated and an order of the low-order interbed multiples; and identifying the interbed multiples based on the propagation velocities and the propagation duration of the low-order interbed multiples, the horizon at which the low-order interbed multiples are generated, and the order of the low-order interbed multiples, and in combination with the velocity spectrum.

Techniques for determining subsurface conditions in a multi-well system may include detecting, at time t.sub.1, a tube wave at a first well system of the multi-well system. The techniques may further include detecting, at time t.sub.2, the tube wave at a second well system of the multi-well system. The techniques may further include determining a time differential t.sub.d between t.sub.1 and t.sub.2. The techniques may further include determining, based at least in part on t.sub.d, that the first well system and the second well system are in fluid communication via a formation.