Seismic Signal Processing TRIZ Cases

Synthetic seismogram filters compensate amplitude distortions in reverse time migration gathers, improving image fidelity without increasing computational cost.

A method integrates seismic traveltime and velocity uncertainties with well marker data to form a unified three-dimensional geological model.

Combines seismic tomography with impedance inversion to resolve drilling hazards by detecting fluid pressure anomalies through full-band modeling.

Neural networks automate geological constraint integration into seismic processing, eliminating manual workflow complexity and reducing exploration time.

Centralized server distributes beam tables to processing nodes, reducing computational burden during depth migration.

A geology-geophysics integrated evaluation standard identifies favorable reef-shoal reservoirs through progressive constraint analysis.

Condition multicomponent seismic data using digital group forming to sum pressure and vertical particle motion components for improved signal processing.

Non-stationary wavelet deconvolution and sparse inversion broaden seismic bandwidth while preserving amplitude variations with angle.

Monitoring seismic velocity changes via time-lapse surveys characterizes fracture networks and gas saturation, resolving poor amplitude precision.

Cross-correlation timing analysis segments composite signals to isolate and remove interference noise, preserving data quality during simultaneous surveys.

A seismic velocity model updates using a validated basin model to incorporate dynamic geological information.

Simultaneous inversion of P-wave velocity and Thomsen parameters using Very Fast Simulated Annealing for tilted transversely isotropic models.

Principal component analysis weights multiple wellbore logs to generate continuous reservoir quality indices, reducing redundancy from binary threshold cutoffs.

Demigration separates illumination irregularities from rock properties to resolve wavefield distortion risks in complex overburden.

Monte Carlo pseudo-well models calibrate seismic attributes to rock properties, reducing time loss in reservoir characterization.

Fuses conditional featurized input channels to produce a combined representation of geophysical data.

A seismic fault filter analyzes planarity, verticality, and centrality to identify discontinuities in data volumes.

L1 inversion reconstructs seismic wavefields using a hybrid Radon dictionary to remove receiver ghost reflections from sparse streamer data.

Pre-trained neural networks interpolate sparse seismic traces to densify spatial sampling, reducing processing time while improving structural image accuracy.

An acoustic sensor measures pressure attenuation in borehole fluid to estimate earth formation permeability.

A first break picking method uses amplitude maxima and energy ratio masks to identify seismic wave arrivals.

Iterative reflection model updates resolve the contradiction between processing efficiency and measurement precision in seismic imaging.

A seismic trace analysis method re-orthogonalizes Fourier coefficients in k-space to regularize irregularly sampled data.

Cross-well sonic logging measures slowness to calculate elastic constants, resolving VTI anisotropy accuracy issues caused by core data reliance.

Independent source emission eliminates synchronization complexity while correlation processing separates overlapping signals to reduce acquisition time.

Machine learning algorithms process seismic attributes to eliminate unwanted noises and validate object location through image data comparison.

A dual-scale interpolation technique separates seismic data into fine and coarse datasets to reconstruct traces with improved spatial resolution.

Computer system generates simulated elastic logs to establish error bounds for conditioning measured well log data.

Asymptote fitting extracts low-frequency slowness to eliminate dispersion effects in dipole acoustic logging.

Estimates lithology from seismic bedform data, reducing reliance on costly core sample analysis.

A joint inversion scheme merges FWI and tomography gradients to update subsurface velocity models.

An iterative inversion method revises estimated source signatures to minimize contamination in separated seismic data.

Method infers fluid saturation and pressure changes using 4D seismic attributes.

Reverse-time migration of passive seismic data locates reservoirs, reducing exploration time and environmental impact.

A hybrid multi-channel prediction operator merges shallow water demultiple with model-based water-layer de-multiple techniques to generate accurate seismic signals.

Envelope-guided low frequency model building eliminates bulls-eye effect in sparse well locations by interpolating least-squares optimized coefficients.

Dividing low-frequency maps by high-frequency maps creates a ratio map that identifies gas reservoirs while filtering loose sands and porous sandstone.

Redatuming operators separate source-side ghosts from seismic data without explicit vertical gradient computation, improving subsurface imaging accuracy.

A heavy acoustic reservoir coupled to the waveguide plate absorbs leakage, reducing reflections and improving measurement accuracy.

Seismic interferometry cross-correlates wave field observations to generate surface consistent data for Ocean Bottom Cable acquisitions.

A multi-scale geological modeling system integrates reflection seismic and well structural data within a graphical user interface.

An adversarial neural network fuses local fault features with global seismic data into a unified feature map.

A fluid substitution method calculates geophysical parameter differences using p-wave velocity data to produce accurate substituted results.

Spatially varying Chi angles adapt seismic projections to local effective stress, resolving interpretation inconsistencies across varying rock compaction zones.

A seismic displacement field calculation method extracts and matches trace features to align baseline and monitor survey data.

Extended sensor carriers with deflectors increase lateral coverage and survey speed while maintaining detection precision.

Multi-frequency inversion of modal dispersions calculates five independent anisotropic elastic constants from single-borehole acoustic data.

Segmented transducer rings eliminate spurious vibrations and harmonics while digital processing accelerates data acquisition.