Seismic Signal Processing TRIZ Cases

Computer method identifies edge points in seismic data volumes to classify termination types like truncation, toplap, onlap, and downlap.

A seismic data quality determination system calculates location-specific correlation coefficients to map spatial variability across survey areas.

Statistical moments separate AVO and AVAz properties, resolving orientation ambiguities in seismic data processing.

Computing subsystem segments microseismic events into coplanar subsets to generate histograms representing fracture orientation probability distributions.

Adapting noise templates using complex-valued directional multi-resolution transforms to reduce geophysical survey data interference.

Reverse time migration generates pre-stacked images where coherency analysis isolates artifacts, enabling precise geological feature location.

Self-adapting Radon interpolation estimates signal-to-noise ratios to generate accurate data-domain weights for seismic processing.

A frequency-dependent noise factor stabilizes the transformation matrix in tau-p domain processing.

Hybrid stratigraphic modeling reduces computational demands while resolving heterogeneity representation limits in hydrocarbon exploration.

Self-weighted stacking applies smoothed amplitude weights to seismic traces, reducing noise in complex subterranean formations without manual intervention.

Gaussian slowness period packets decompose non-stationary seismic data to resolve patch boundary errors and improve image continuity.

Cascaded double-square-root wave equations predict internal multiples, reducing computational time by factors of 50 to 100 for 2D applications.

A seismic velocity parameter model refines subsurface images using zero-offset wavefield data and linearized perturbation terms.

Tau-p transform and sparse Radon analysis isolate coherent noise from the Z component, preserving primary signal energy for accurate wavefield separation.

Segmented pairwise correlation matrices map well segments to stratigraphic models.

Frequency domain transformation reconstructs seismic data from irregular sampling grids, reducing computational time while maintaining accuracy.

A summarization method assigns aggregated values to output surface faces based on active cell data along a defined aggregation direction.

Segmenting computation into separate images reduces memory requirements while maintaining high resolution in angle gathers.

Beam steering and coherent stacking improve vertical resolution while mitigating signal attenuation in subsurface imaging.

A seismic processing method selects zones by dip similarity and spacing to apply residual move-out corrections for updated velocity maps.

A seismic processing method calculates incidence vectors from vectorial measurements to correct wavefield components in the time domain.

Hierarchical conditioning with an intermediary objective function handles discontinuities to stabilize adjoint sensitivity analysis for sparse field data.

Coherence-based dictionary learning attenuates spatio-temporally varying noise in seismic surveys through iterative patch processing and sparse coding.

A dynamic filter smooths velocity model anomalies to enable accurate seismic domain conversion, correcting lateral velocity distortions.

Towing streamers at different depths separates up-going and down-going wavefields to mitigate ghost signal interference.

A de-blending device processes simultaneous seismic data using overlapping spatial blocks to separate individual shot recordings.

Prestack seismic inversion generates impedance data to build pore pressure transforms that resolve vertical resolution limits in low permeability rocks.

Low-frequency reverse time migration decomposes seismic wavefields into vertical and horizontal components to enhance spatial resolution.

A microseismic sensor array arranges radial arms, patches, and concentric ovals around a wellbore to improve spatial resolution.

Global inversion scheme generates multiple velocity models using differential evolution to predict seismic impedances ahead of the drill bit.

A spatial context generator creates simulated seismic datasets from partial input data to train machine learning models.

Domain Transformation removes structural deformation from seismic volumes, enabling precise identification of depositional systems.

A modified tau-p transform separates primary and ghost components in seismic data without requiring a velocity field.

Waveform inversion by relative data matching cross-correlates wavefields to resolve cycle skipping and noise inclusion in complex subsurface volumes.

Treats marine survey receivers as virtual sources to compute earth reflectivity, eliminating crosstalk artifacts from multiple wavefields.

Scaling hydrophone and geophone components enables polarization filtering to remove guided wave noise from seismic data.

Iterative signal mask generation identifies and filters swell noise in seismic gather data, resolving detection inconsistencies across local window boundaries.

Full wavefield inversion generates high-resolution velocity and impedance models to estimate subsurface pore pressure.

Constructing a convex hull to determine a minimum bounding box reduces unoccupied space in seismic grids, improving subsurface geological modeling accuracy.

A forward model estimates seabed sediment composition and subbottom structure from single-channel seismic reflection data.

Acoustic tools measure nonlinear harmonic waves generated by linear guided modes to estimate earth formation properties.

Dual sensor arrays detect mixed seismic waves in marine environments, reducing P-wave interference in S-wave data for improved subsurface imaging.

Facies classification system merges seismic signals with well log data to identify subsurface reservoir layers.

Composite seismic traces combine PS1 and PS2 modes to remove subsurface anisotropy, enabling isotropic inversion of fractured media.

Double migration computes aperture indexed CIGs to resolve uneven illumination in complex geology.

Computing frequency-dependent outgoing ray directions using boundary integrals at sub-surface interfaces.

Image-domain full waveform inversion reduces computational complexity while improving velocity estimation accuracy and seismic image resolution.