Seismic Signal Processing TRIZ Cases

A deghost operator removes ghost noise from seismic data to improve frequency band and signal-to-noise ratio.

A processor stacks waveform data using linear and sinusoidal moveout to determine wavefront slowness.

Accumulated wavefield energy minimizes parameter differences, resolving waveform inversion inefficiencies.

Complex wavelet transforms separate kinematics from dynamics to reduce cycle-skip errors and improve convergence reliability.

Simultaneous inversion of direct and reflected seismic arrivals determines anisotropy parameters for vertical transversely isotropic models.

Direct Poisson impedance estimation eliminates accumulative errors from indirect calculations, improving hydrocarbon prediction reliability.

Segmenting composite slip-sweep records isolates specific sweep segments to remove harmonic interference while maintaining data quality.

Calculates seismic sensor orientation by estimating wave properties and applying boundary conditions, resolving noise interference in seabed environments.

Probabilistic techniques assimilate prior geological information with survey data to estimate subterranean properties.

A seismic inversion method uses a matching filter to remove source wavelet dependency from the misfit function.

A seismic processing system generates multiple-generator traces to predict interbed multiples for removal from pre-stack datasets.

Retrieves reflection and transmission responses from enclosed subsurface volumes by eliminating interference from overburden and underburden structures.

Shot encoding separates matched and unmatched seismic data components, enabling full aperture waveform inversion without muting receiver variations.

Transforms geophysical data into images via edge detection, bypassing bandwidth limits of conventional seismic processing.

Minimizes amplitude sums across velocity-shifted surveys to deduce reservoir changes without cross-correlation.

Direct migration of simultaneous-source survey data reduces crosstalk artifacts by synthesizing unwanted contributions via Full Wavefield Inversion.

A refraction-based method calculates surface-consistent amplitude residuals using first arrival events to correct seismic trace amplitudes.

Neural networks correlate seismic and wellbore data to generate high-resolution rock property cubes.

Branch-stacking techniques resolve orientation ambiguity and instability in anisotropic reservoir characterization while reducing computational complexity.

A 2D frequency coherence map identifies low-frequency asymptotes to extract formation slowness values from acoustic borehole signals.

Transforms seismic data into a time-indexed flattened space to resolve mesoscopic details limited by suboptimal image quality.

Method determines notional seismic source signatures using near field measurements and ghost reflections.

Interpolating stochastic seismic inversion data preserves inter-property correlations, resolving uncertainty in volumetric calculations.

Segmented angle-dependent parameters in full waveform inversion resolve measurement precision versus device complexity trade-offs.

Segmenting the formation into discrete elements captures spatial heterogeneities to estimate precise elastic constants and horizontal stresses.

A computer-implemented method uses extended quantization to merge four or more seismic attributes into a single composite image.

Broadband sparse Bayesian learning extracts slowness dispersion from acoustic waveforms using an overcomplete dictionary.

Seismic migration generates semblance panels that define lower and upper velocity bounds across depths, resolving discrete well data limitations.

Combines pre-stack inversion with neural networks to generate high resolution rock property volumes.

A Fourier finite difference migration method processes three dimensional seismic data in tilted transversely isotropic media.

Pairwise Hankel tensor completion recovers interpolated seismic frequency slices, handling noisy sparse data to improve 5D interpolation speed.

True-3D AVA inversion models subsurface dip fields to generate accurate digital seismic images.

Curvelet thresholding separates signal from noise in the transform domain, resolving low signal-to-noise discrimination accuracy in deep subsurface structures.

Iterative waveform inversion adds high-resolution velocity perturbations to ray-based tomography images, improving subsurface structural conformity.

A marine seismic offset determination method calculates travel times from selected trace pairs to derive an offset shift value.

A method identifies underground pipe locations by inducing controlled acoustic waves and measuring resulting vibration responses across a frequency range.

A method extracts downgoing wavelets and attenuation parameters from vertical seismic profile data using spectral subtraction.

Continuous inclusion sets with varying aspect ratios approximate complex pore geometry, reducing systematic modeling errors in subsurface characterization.

Separates pressure and vertical components into up-going and down-going wave-fields to adaptively subtract multiple models, resolving noise contamination.

Angle-domain filtering removes post-critical reflection artifacts from seismic images without increasing processing time.

Automated fault extraction on clean stratigraphic seismic traces reduces manual editing needs and eliminates artifacts from traditional volumes.

Attenuates receiver data noise before matrix inversion to separate vibratory signals from multiple seismic sources.

A quasi-Newton preconditioner accelerates full-wavefield inversion convergence using Krylov-space iterative solvers.

Multi-vintage seismic energy mapping harmonizes disparate survey geometries, preserving only subsurface changes while eliminating geometry-induced noise.