A method for enhanced dispersion analysis begins with obtaining a plurality of measured waveforms, for example from two or more receivers of an acoustic logging tool placed in a borehole. The measured waveforms are divided into common gathers, and waveforms of each common gather are enhanced. The enhancement begins by calculating a travel time curve for a selected target mode of the common gather waveforms. Using the travel time curve, waveforms of the selected target mode are aligned to have zero apparent slowness. The aligned waveforms are filtered to suppress non-target mode waves. The aligned waveforms are then enhanced, and used to generate an enhanced dispersion curve of the selected target mode.

Disclosed are systems and methods for processing acoustic logging information with automatic dispersion matching. The method comprises obtaining, from an acoustic logging tool, acoustic waveforms from within a borehole, applying dispersion analysis to the acoustic data to extract a slowness-frequency response, calculating a slowness density log of the slowness-frequency response, obtaining an initial shear slowness estimate based on the slowness density, generating a dispersion model comprising model parameters, and performing a dispersion response auto match inversion to minimize the difference between the slowness-frequency response and the dispersion model in order to obtain a final shear slowness estimate.

Acoustic waves are obtained from an acoustic logging tool within a borehole passing through a formation. Signal properties in a time domain, frequency domain, or both are determined based on the obtained acoustic waves. A machine learning analysis is used to determine formation slowness based on the determined signal properties and a downhole operational parameter is adjusted based on the determined formation slowness.

A method for enhanced dispersion analysis begins with obtaining a plurality of measured waveforms, for example from two or more receivers of an acoustic logging tool placed in a borehole. The measured waveforms are divided into common gathers, and waveforms of each common gather are enhanced. The enhancement begins by calculating a travel time curve for a selected target mode of the common gather waveforms. Using the travel time curve, waveforms of the selected target mode are aligned to have zero apparent slowness. The aligned waveforms are filtered to suppress non-target mode waves. The aligned waveforms are then enhanced, and used to generate an enhanced dispersion curve of the selected target mode.

A method, system and non-transitory computer-readable medium for forming a seismic image of a geological structure are provided. After obtaining seismic wave data including a plurality of seismic wave traces at a first region of the geological structure, a predicted time dispersion error of an actual time dispersion error that results from a use of a finite difference approximation in calculating predicted seismic wave data at a second region of the geological structure as if a seismic wave propagates from the first region to the second region of the geological structure, is calculated. A corrected predicted seismic wave data at the second region of the geological structure is calculated by applying the finite difference approximation to the seismic wave data at the first region of the geological structure compensated with the predicted time dispersion error. A seismic image of the second region of the geological structure is generated using the corrected predicted seismic wave data, such that the actual time dispersion error is negated by the predicted time dispersion error.

Methods, apparatus, and articles of manufacture are disclosed to characterize acoustic dispersions in a borehole. An example apparatus includes a dispersion analyzer to characterize an acoustic wave dispersion in a borehole in a formation by calculating a quality indicator corresponding to the acoustic wave dispersion, and a report generator to prepare a report including a recommendation to perform an operation on the borehole based on the quality indicator.

Device and method for calculating a set of surface wave dispersion curves. The method includes receiving seismic data recorded with seismic sensors over an area to be surveyed; selecting region units that cover the area to be surveyed; gathering traces for the region units; processing in a computing device the traces to obtain a set of candidate measurements for each region unit; teaching a decision algorithm based on a first subset of the set of candidate measurements; and calculating the set of surface wave dispersion curves by running the decision algorithm on a second subset of the set of candidate measurements.

A method is presented wherein inversion for formation anisotropic constants is achieved using borehole sonic data.

Methods, apparatus, and articles of manufacture are disclosed to characterize acoustic dispersions in a borehole. An example apparatus includes a dispersion analyzer to characterize an acoustic wave dispersion in a borehole in a formation by calculating a quality indicator corresponding to the acoustic wave dispersion, and a report generator to prepare a report including a recommendation to perform an operation on the borehole based on the quality indicator.

Disclosed are systems and methods for processing acoustic logging information with automatic dispersion matching. The method comprises obtaining, from an acoustic logging tool, acoustic waveforms from within a borehole, applying dispersion analysis to the acoustic data to extract a slowness-frequency response, calculating a slowness density log of the slowness-frequency response, obtaining an initial shear slowness estimate based on the slowness density, generating a dispersion model comprising model parameters, and performing a dispersion response auto match inversion to minimize the difference between the slowness-frequency response and the dispersion model in order to obtain a final shear slowness estimate.