Seismic Signal Processing TRIZ Cases

Seismic energy sources move along a path circumscribing a center with monotonically changing distance to vary shot point spacing.

Convolution of reflection coefficients with an enhanced wavelet restores low-frequency energy to resolve absorption attenuation in deep carbonate reservoirs.

Weighted fit to log-amplitude spectra determines interval seismic quality factor Q insensitive to absolute scaling, resolving bandwidth limitations.

Sensitivity kernels invert flexural wave dispersion data to resolve shear velocity profiles in borehole alteration zones with complex acoustic properties.

Deploying sources and sensors in directional wellbores improves measurement precision of geomechanical properties despite increased device complexity.

Correct Doppler shifts and ray-path variations in seismic data acquired by moving non-impulsive sources via spectral transformations.

Segmenting wavelet transform coefficients into discrete zones resolves heterogeneity challenges by enabling accurate, consistent stratigraphic classification.

Estimates clock drift by inverting relative time shifts from cross-correlated seismic traces, eliminating the need for expensive accurate internal clocks.

A neural network calculates shear slowness from frequency domain dispersion curves, eliminating iterative processing bottlenecks in slow formations.

Structure tensor constraints automate local dip and azimuth estimation, resolving the contradiction between measurement precision and processing efficiency.

Radial profiles of three shear moduli enable accurate horizontal stress estimation in subterranean formations.

Elastic full waveform inversion decomposes seismic data into offset groups to reduce parameter crosstalk during multi-parameter estimation.

Updates average velocity surfaces and calculates correction factor surfaces to reconcile depth-converted time horizons with well marker data.

Integrating active and passive seismic data via beam steering resolves fluid movement monitoring limitations in subsurface formations.

Frequency-dependent deconvolution filter removes source signature effects from seismic data using angle-specific weighting.

Corrects pressure and particle velocity signals using time delays based on arrival angles, resolving spatial aliasing and depth variation issues.

Multi-mode inversion methods analyze compressional and flexural waves to resolve shear anisotropy, overcoming precision limits in complex formations.

Visco-acoustic full waveform inversion generates simultaneous velocity and quality factor models using frequency-dependent velocity.

Inverse multi-resolution singular value decomposition recovers high-frequency losses in seismic signals by hierarchically reconstructing detailed components.