A method and apparatus for generating a geophysical data product by a process of: acquiring standard-offset survey data for a subterranean formation with a standard-offset survey spread towed at a standard-offset spread depth; acquiring long-offset survey data for the subterranean formation with a long-offset streamer towed at a long-offset streamer depth; and assembling the long-offset survey data into a set of grouped-long-offset survey data characterized by a plurality of receiver groupings and a group length. A method, includes: towing a standard-offset survey spread at a standard-offset spread depth; acquiring standard-offset survey data for a subterranean formation with the standard-offset survey spread; towing a long-offset streamer with a vessel at a long-offset streamer depth; acquiring long-offset survey data for the subterranean formation with the long-offset streamer; and assembling the long-offset survey data into a set of grouped-long-offset survey data characterized by a plurality of receiver groupings and a group length.

Techniques for determining a drill bit location includes identifying a plurality of acoustic energy signals received at a plurality of sets of acoustic receivers from a passive acoustic energy source that is part of a wellbore drilling system; processing the plurality of acoustic energy signals; determining a location of a drill bit of the wellbore drilling system based on the processed plurality of acoustic signals; and updating a geo-steering path of the drill bit based on the determined location of the drill bit.

A computer implemented method for denoising a set of seismic datasets, specifically belonging to different 3D subsets of a 4D survey the method including: (a) receiving a baseline and a monitor seismic dataset which were acquired by surveying over the same subsurface formation over different periods of time; (b) cross-equalizing the monitor seismic dataset to match to the baseline seismic dataset in terms of amplitude, frequency, phase and timing of events; (c) computing an initial 4D difference between the monitor and baseline seismic datasets; (d) formulating a common noise template from the initial 4D difference; (e) de-noising the baseline and monitor seismic datasets, independently, using the common noise template in a curvelet domain; (f) updating the initial 4D difference to form an updated 4D difference, which reflects de-noised baseline and monitor datasets from step (e); and iterating the steps (d) through (F) until the updated 4D difference satisfies a predetermined criteria.

A method for processing vertical seismic profiling (VSP) data is provided. The method includes receiving VSP data in response to seismic energy applied to the formation, processing a down-going portion of the VSP data associated with a down-going wave field, outputting a first set of estimation values based on processing the down-going portion of the VSP data, the first set of estimation values estimating at least one of slowness or velocity, processing an up-going portion of the VSP data associated with an up-going wave field, outputting a second set of estimation values based on processing the up-going portion of the VSP data, the second set of estimation values estimating at least one of slowness or velocity, and determining an estimation associated with the formation based on the first and second sets of estimation values.

The present disclosure provides a prestack separating method for a seismic wave, including: receiving P-wave, S1-wave and S2-wave of the seismic wave, wherein the P-wave, S1-wave and S2-wave are reflected from different points; projecting the P-wave, S1-wave and S2-wave into a Z-R-T coordinate system, so as to generate a projection matrix, wherein Z is a vertical component, R is a component of a source-to-receiver azimuth and T is a component orthogonal to the R component; forming vectors of the P-wave, S1-wave and S2-wave as a composite vector; transforming the composite vector to an anisotropic wave vector matrix according to base vectors on the vector directions of the P-wave, S1-wave and S2-wave; and performing a rotation transformation of an affine coordinate system on the anisotropic wave vector matrix to generate a wave separation matrix, thereby solving a problem of error prediction result of fracture parameters caused by the mode leakage phenomenon.

Seismic data processing using one or more non-linear stacking enabling detection of weak signals relative to noise levels. The non-linear stacking includes a double phase, a double phase-weighted, a real phasor, a squared real phasor, a phase and an N-th root stack. Microseismic signals as recorded by one or more seismic detectors and transformed by transforming the signal to enhance detection of arrivals. The transforms enable the generation of an image, or map, representative of the likelihood that there was a source of seismic energy occurring at a given point in time at a particular point in space, which may be used, for example, in monitoring operations such as hydraulic fracturing, fluid production, water flooding, steam flooding, gas flooding, and formation compaction.

A system provides seismic images of the subsurface by enhancing pre-stack seismic data. The system obtains seismic data comprising a plurality of seismic traces that are generated by measuring reflections of seismic waves emitted into a geological formation. The system sorts seismic data into at least one multidimensional gather comprising a data domain. The system determines local kinematical attributes of a seismic trace. The system forms an ensemble of seismic traces, each representing a reference point. The system applies local moveout corrections to each seismic trace of the ensemble. The system applies residual statics and phase corrections for each seismic trace that is corrected by the local moveout corrections. The system sums the seismic traces of the ensemble to obtain an output seismic trace having an increased signal-to-noise ratio (SNR) relative to the seismic trace that represents the reference point for the ensemble of seismic traces.

A surface-consistent refraction analysis method to automatically derive near surface corrections for seismic data processing. The method uses concepts from surface-consistent analysis applied to refracted arrivals. The method includes the use of CMP-offset-azimuth binning, evaluation of mean travel time and standard deviation for each bin, rejection of anomalous first break (FB) picks, derivation of CMP-based travel time-offset functions, conversion to velocity-depth functions, evaluation of long wavelength statics and calculation of surface-consistent residual statics through waveform cross-correlation. Residual time lags are evaluated in multiple CMP-offset-azimuth bins by similarity analysis with a pilot trace for all the other traces in the gather where the correlation window is centered at the refracted arrival. The similarity analysis may take the form of computerized cross-correlation, or other criteria such as semblance. The residuals are then used to build a system of linear equations that is simultaneously inverted for surface-consistent shot and receiver time shift corrections plus a possible subsurface residual term. All the steps are completely automated and require a fraction of the time needed for conventional near surface analysis.

A method of enhancing seismic images includes receiving a seismic gather. The seismic gather includes a plurality of seismic traces. A feature trace is generated based on the plurality of seismic traces in the seismic gather. For each of the plurality of seismic traces in the seismic gather, a correlation trace is generated based on that seismic trace and the feature trace, the correlation trace is modified using an activation function, and an enhanced trace is generated by multiplying that seismic trace with the modified correlation trace.

Disclosed is a method of, and computer program and apparatus for, identifying reflected signals, subsequent to their reflection within a medium. The method comprises obtaining return signals (100), resulting from measurements being performed over a measurement period. The measurement period comprises sub-periods, the return signals comprising reflected signals and noise. The plurality of return signals are partitioned into plural sets (220) of equal cardinality or as equal as possible such that their cardinality differs by no more than one. A stacked correlation value is determined (130) for the return signals by determining the mean of the return signals across the plural sets (230) and determining a correlation value of the plural sets over each of the time sub-periods (240). Peaks in the variation of the stacked correlation value over time can then be identified and each of the peaks in the variation of the stacked correlation value over time can be attributed to a reflected signal.