Seismic Signal Processing TRIZ Cases

Azimuth angle dependent full waveform inversion decomposes wavefields into directional domains to generate subsurface velocity models.

Bottom-up ray tracing calculates unique apertures per gather, reducing artificial noise and improving computational efficiency in seismic inversion.

Probabilistic algorithms classify sedimentary facies from 3D seismic attribute volumes and frequency decomposition color blend data.

A bandlimited binning function adjusts sampling intervals to generate unaliased 3D angle gathers from sparse seismic node data.

Software tests clock noise floors in seismic sensor nodes to select optimal timing sources, reducing system complexity and power consumption.

A matching filter misfit function stabilizes seismic full waveform inversion, resolving cycle skipping and cross-talk in complex subsurface structures.

Segmenting microseismic events into discrete spatial markers resolves location errors in stimulated reservoir volume estimation.

Segmenting well depth windows enables nearest neighbor initialization of Stoneley dispersion curves for faster rock property characterization.

Automatic focus identification method for Karst cave reservoirs performs velocity replacement on pre-stack time migration models.

Principal component analysis extracts factors from capillary pressure curves to classify them into representative families.

Combines impulsive air guns with non-impulsive marine vibrators to generate distinct seismic wavefields for simultaneous source activation.

A linear least squares Radon formulation separates coherent noise from pure seismic signals in marine acquisition data.

Kinematic demigration extracts invariant attributes from time-migrated seismic data to update velocity models without depth migration complexity.

Complex continuous wavelet transform separates overlapping casing and formation waves in time-frequency domain, enabling accurate slowness analysis.

Merges inconsistent intersection points on orthogonal polylines to eliminate mis-ties and improve salt body boundary accuracy.

Automated artifact identification in flattened seismic images resolves the trade-off between processing speed and mapping accuracy.

Iterative sliding window frames predict internal multiples directly from raw seismic data to remove interference without prior subsurface information.

Wide azimuth seismic data derives anisotropic elastic parameters for geomechanical modeling.

Refracted seismic travel time data estimates azimuthal anisotropy parameters for subsurface reservoir analysis.

Dynamic weight adjustment in geophysical joint inversion escapes local minima and improves convergence accuracy.

Inverts first-break travel times using data covariance matrices to generate pseudo-3D models.

Wavefield extrapolation generates VSP-CMP gathers to resolve limited lateral coverage and low measurement precision in subsurface formation analysis.

Replacing ray-based tomography with pseudo-acoustic full-waveform inversion eliminates shear wave computational costs while improving velocity model accuracy.

A seismic acquisition tool samples geophysical signals and noise using closely spaced sensors along a long cable.

Logging-while-drilling acoustic tools acquire multi-azimuth waveforms to measure shear anisotropy without mechanical rotation limits.

Adaptive gradient schemes modify L-BFGS optimization to resolve scaling and cross-talk issues in seismic inversion.

Segmenting the Hessian matrix into diagonal elements reduces computational cost while maintaining velocity model accuracy for complex subsurface imaging.

Kirchhoff-type datuming operators extrapolate dual-sensor seismic data to separate up-going and down-going wavefields in the time-space domain.

A seismic modeling system creates dynamic 3D earth models using a 4D water velocity library.

Adaptive seismic filter separates ground roll from reflected signals by minimizing mean square error, preserving deep layer integrity.

Conditioning velocity models with gradual transitions and overshoot layers reduces backscattering noise and wavelet distortion in reverse time migration.

Automated seismic denoising partitions data into frequency slices and forms Hankel matrices to separate clean signals from erratic noise.

Computes localization errors via the Cramer-Rao Bound to gauge estimation accuracy and display event positions as error ellipses.

Structure-oriented smoothing and anti-multiple discrimination refine semblance spectrums, resolving velocity jitter issues in complex 3D geological structures.

A method segments subsurface parameter profiles into stratigraphic layers to generate discrete realizations for hydraulic fracturing models.

Selective stacking of similar seismic volumes improves signal-to-noise ratio by eliminating high amplitude noise traces.

Frequency-dependent amplitude correction restores AVO compliance by compensating for near-surface reverberations caused by low-acoustic impedance sand dunes.

A 3D seismic processing method computes maximal correlations between shifted vectors to identify geological features.

A surveying system detects electromagnetic and seismic signals generated by natural earth processes to identify subsurface formation properties.

Machine learning correlates remote sensing and geoscience data to infer subsurface lithology, reducing reliance on extensive manual surveys.

Adaptive focusing technique applies extended imaging conditions with variable time shifts to correct image alignment errors in seismic data processing.

An adaptive frequency filter adjusts its band using polynomial coefficients to estimate formation slowness from acoustic waveform data.

Rock physical model inversion reduces location uncertainties by mapping velocity and attenuation attributes to spatial volume elements.

A method corrects seismic velocity models by identifying structural distortions and applying targeted inversion updates.

Generates virtual seismic shot records from passive data via interferometry and phase shifts, resolving low signal-to-noise ratios without manual time picking.

A trained machine learning model determines velocity boundaries within seismic migration gathers to update subsurface velocity models.

Compensating recorded seismic wavefields for amplitude attenuation using forward and backward propagation modeling through an earth model.

Uniaxial vertical geophones sense earth movements to acquire low frequency passive seismic data across survey areas.