Seismic Signal Processing TRIZ Cases

Correlating stimulated reservoir volume parameters with fracture network geometry using microseismic event data.

Aggregate blurring function corrects plane-wave reflection coefficients for accurate subsurface imaging.

Automated seismic interpretation uses machine learning to identify facies and resolve processing time bottlenecks in complex subsurface volumes.

Generalized sampling expansion algorithms process sparse crossline data from multicomponent sensors to resolve aliasing in towed-marine surveys.

A sampling probe extracts seismic data perpendicular to reflection surfaces for high resolution visualization.

Classifies reservoir portions using production data and correlates elastic properties to generate a spatial distribution function.

A method derives converted wave expressions from P-wave reflection coefficients using the Zoeppritz equation and parameter correction.

Kriging with external drift interpolates average velocity controls using potential fields data, maintaining resolution away from sparse seismic control points.

A wavelet cross-correlation method separates seismic components in the time-frequency-wavenumber domain to generate virtual source gathers.

A transducer transmits encoded ultrasonic waves and uses correlation processing to determine signal similarity for object detection.

Adaptive subtraction isolates noise components using correlation-based masking and template refinement to preserve signal integrity in marine survey data.

Offset vector tile gathers suppress cable footprint artifacts and ensure uniform illumination for accurate 3D imaging.

Parameterized acquisition effects as time functions to isolate subsurface signals in marine survey measurements.

A computer-implemented method maps seismic skeleton points to stratigraphic grid cells for reservoir model correction.

Sliding stack processing detects shooting sequences downhole without consuming uplink bandwidth during tripping operations.

Synthesizes virtual receivers at deeper datum levels using seismic interferometry to compute precise subsurface velocities.

Neural networks generate initial geologic models incorporating AVO behaviors to resolve non-uniqueness in subsurface modeling.

Instantaneous frequency analysis of seismic traces guides iterative velocity model updates, resolving discrepancies between observed and simulated datasets.

Computes uniform geophysical attribute values within zones to determine reservoir facies.

A borehole logging method uses acoustic wave resonance to measure formation permeability.

A weighted stack of up- and down-going wave-fields suppresses non-repeatable noise in seismic surveys.

Cross-correlation of adjacent sensor traces isolates direct phases from sonic data, resolving measurement precision trade-offs to extract clear event signals.

A Bayesian method calculates positive and negative polarity probabilities from noisy time series data to quantify measurement uncertainty.

Processing direct arrivals from production streamers generates reliable source signatures up to 80 Hz, eliminating complex deep-water measurement setups.

Full waveform inversion updates long and short wavelength components via iterative relaxation to enhance velocity model resolution.

Bayesian inversion estimates interval velocities from RMS data using geological constraints.

A joint preconditioning full waveform inversion method computes separate baseline and monitor preconditioners to enhance subsurface model resolution.

Geobody ensembles capture measurement uncertainty for accurate hydrocarbon risk assessment.

Iterative scoring selects representative seismic horizon surfaces, reducing computational burden and interpretation time.

Measuring frequency-dependent energy decay in seismic traces identifies hydrocarbon accumulations without relying on reflection amplitude.

Decomposed full waveform inversion gradient preserves low wavenumber components to resolve incomplete subsurface property characterization at greater depths.

Computing matching operators between co-located sensors separates down-going ghost energy from up-going signals for clearer imaging.

Deriving a ghost-free model using linear operators resolves imaging inaccuracies caused by variable receiver depths in three-dimensional surveys.

Self-adjoint pseudoacoustic equations propagate seismic wavefields using nonzero shear velocity to mitigate instabilities in tilted transverse isotropic media.

A seismic data processing method calculates dominant frequency and energy loss above this frequency to locate hydrocarbon reservoirs.

Convolutional filters transform seismic data to minimize coefficient misfit, resolving cycle-skipped convergence in subsurface exploration.

A backpropagation-enabled neural network infers subsurface pore-filling fluids and lithologies from geophysical data sets.

Compensate source signature effects in seismic data using a transform operator derived from moving source position and velocity.

Cross-migration rescaling aligns mismatched seismic grids from different processing methods, eliminating costly re-processing for accurate wellbore placement.

A seismic processing system detects slope changes in source wavelets to determine geological layer attributes.

Algorithms compute direct hydrocarbon indicators across seismic volumes to identify prospects.

A dip-constrained tomography method updates velocity models using offset-dependent dip information from migrated seismic data.

A seismic wave analysis method separates reflected and diffracted waves using dispersion properties to generate distinct cross-sectional images.

A label propagation technique generates dense subsurface surfaces by assigning dip and azimuth vectors to geophysical data samples.

Travel-time cost functions mitigate cycle-skipping and amplitude discrepancies in subsurface imaging.

Interpolating multicomponent seismic data enables wider cable spacing, reducing survey costs while maintaining signal detection accuracy.

Convert vector image partition gathers into angle gathers using approximate velocity models.

An anisotropy matching filtering algorithm constructs operators using wave-equation propagation engines to enhance seismic image illumination.

Segmenting the weathered layer into discrete sub-layers resolves velocity inversions from high-velocity stringers, enabling accurate depth models.

An acoustic tool calculates shear wave slowness using pseudo-Rayleigh mode correlations.