In order to monitor the subsoil of the earth under a target zone, seismic waves coming from an identified mobile noise source are recorded by means of at least one pair of sensors disposed on either side of the target zone, time periods are selected corresponding to the alignments of the pairs of sensors with the noise source, a seismogram of the target zone is reconstructed by interferometry based on the recorded seismic waves and on the selected time periods and an image of the subsoil of the target zone is generated using the seismogram.

Method for source localization for cable cut prevention using distributed fiber optic sensing (DFOS)/distributed acoustic sensing (DAS) is described that is robust/immune to underground propagation speed uncertainty. The method estimates the location of a vibration source while considering any uncertainty of vibration propagation speed and formulates the localization as an optimization problem, and both location of the sources and the propagation speed are treated as unknown. This advantageously enables our method to adapt to variances of the velocity and produce a better generalized performance with respect to environmental changes experienced in the field. Our method operates using a DFOS system and AI techniques as an integrated solution for vibration source localization along an entire optical sensor fiber cable route and process real-time DFOS data and extract features that are related to a location of a source of vibrations that may threaten optical fiber facilities.

A new method for iteratively picking the seismic first breaks and conducting imaging of the near-surface velocity structures in an iterative fashion is provided that the first-break picks of the input seismic data are applied to image the near-surface velocity structures and the calculated travel times associated with the updated velocity structures are applied to help refine the first-break picks in the first break picking process until first-break picks satisfy a number of quality control criteria, statics solutions are optimized, and the near surface imaging reaches an acceptable data misfit. This invention produces a velocity model that can be used for near surface statics corrections or for the prestack depth migration.

The present invention relates generally to an apparatus and method for calculating efficient 3-dimensional (3D) traveltime by using coarse-grid mesh for a shallow depth source. More particularly, the present invention relates to an efficient 3D traveltime calculation method for a shallow depth source by combining a suppressed wave equation estimation of traveltime (SWEET) algorithm and an equivalent source distribution (ESD) algorithm, wherein the SWEET algorithm is a traveltime calculation algorithm using an damped wave equation and the ESD algorithm is for equivalently distributed sources; and to an apparatus and method for calculating efficient 3D traveltime by using coarse-grid mesh for a shallow depth source which may need less calculation time compared with that of a conventional SWEET algorithm.

A system (100) for monitoring a subterranean structure comprises an array (10) with n acoustic sensors capable of detecting P-waves and/or S-waves from the subterranean structure and a central controller (120) for receiving a signal (X) from the sensors. The system further comprises a lookup table (20) comprising a pre-computed travel time curve (24) expressed as relative arrival times of a signal from a location (L.sub.m) to each of the sensors (1-n); a comparison unit for comparing the received signal (X) with the pre-computed travel time curve (24), and means for raising an alarm if the received signal (X) matches the precomputed travel time curve (24). Preferably, the alarm is raised if a computed semblance value (26, 27) exceeds a predefined threshold. The system may monitor several locations (L.sub.m) in parallel using a fraction of the computer resources and time required by prior art techniques.

A method may include obtaining seismic data regarding a geological region of interest. The seismic data may correspond to a seismic survey that is divided into various bins in a predetermined bin grid. The method may further include determining a first multiblock bin within the seismic survey. The first multiblock bin may correspond to a source bin and a receiver bin among the bins. The method may further include determining traveltime table data using the seismic data and various multiblock bins that include the first multiblock bin. The method further includes determining migrated data using the seismic data, the traveltime table data, a velocity model, a migration function, and various parallel processors. The method further includes generating a seismic image of the geological region of interest using the migrated data.

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.

Computing systems, computer-readable media, and methods for seismic processing. The method includes receiving seismic data including acquired seismic waveforms that were acquired from a seismic receiver and represent a subterranean area, generating synthetic waveforms based on an initial model of the subterranean area, determining a model error by minimizing a local travel time shift error between one or more of the acquired seismic waveforms and one or more of the synthetic waveforms, and adjusting the initial model based on the model error to generate an adjusted model.

A method for estimation of water properties from seismic data can include determining a number of travel times for at least one event based, at least in part, on predefined values for a plurality of water properties, determining an alignment of data values for each of the number of travel times determined for the at least one event, and determining an estimation of a plurality of undetermined water property values based, at least in part, on the alignment of the data values for each of the number of travel times producing a high quantitative measure of a coherence value.

Method for characterizing a subterranean formation includes: obtaining azimuth-dependent observed travel-times from measured seismic data; inverting observed travel-times to calculate a fracture attribute selected from the group consisting of: magnitude and orientation; identifying presence of fracture based on calculated fracture magnitude; identifying fracture direction based on calculated fracture orientation; calculating predicted travel-times; calculating differences or residual errors between observed travel-times and predicted travel-times; identifying potential fault locations based on residual errors; inverting fracture magnitude and orientation using travel-time differences between a shallower horizon to a deeper horizon of interest to minimize overburden artifacts.