In a method to transform logs, an acoustic logging tool inserted into a borehole includes a source and an array of receiver stations. Each station includes a receiver spaced along the tool from the source by successively greater distances. In the method, the source emits energy (I) to cause the propagation towards the stations of plural signals exhibiting paths characteristic of first and second respective modes and (II) to stimulate a receiver of each station to generate an output signal per station that indicates the signal packets and represents the modes in combination with one another. In the method, the output signals are transformed into transformed signals containing phase/amplitude information of each mode. The phase/amplitude are linked by an operator to the slowness and attenuation of the mode and the transmitter-receiver distance of the station. The phase/amplitude are used to extract slowness and attenuation information for each mode.

Computing device, computer instructions and method for processing input seismic data d. The method includes receiving the input seismic data d recorded in a first domain by seismic receivers that are towed in water, the input seismic data d including pressure data and/or and particle motion data; generating a model p in a second domain to describe the input data d; processing the model p to generate an output particle motion dataset; and generating an image of the surveyed subsurface based on the output particle motion dataset.

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.

Computing device, computer instructions and method process input seismic data d recorded in a first domain by seismic receivers that travel in water, the input seismic data d including pressure and particle motion measurements, including up-going and down-going wave-fields. A model p is generated in a second domain by solving an inverse problem for the input seismic data d, wherein applying an L transform to the model p describes the input data d. An L′ transform, which is different from the L transform, is then applied to the model p to obtain an output seismic data in the first domain, the output seismic data having a characteristic imparted by the transform L′. The characteristic is related to pressure wave-fields and/or particle motion wave-fields interpolated at positions in-between the input seismic receivers. An image of the surveyed subsurface is generated based on the output seismic dataset.

Methods to estimate formation slowness from multi-borehole modes and multi-mode dispersion estimation systems are presented. The method includes obtaining waveform data of a plurality of waves traversing through a downhole formation, wherein each wave of the plurality of waves has a different threshold cutoff frequency, and performing a multimode dispersion analysis of the waveform data to generate a semblance map of the wave comprising the plurality of waves. The method also includes obtaining a slowness dispersion of a wave of the plurality of waves, and determining a formation type of the wave based on one or more properties of the plurality of waves. The method further includes determining an initial body wave slowness estimate of the wave, generating a modeling of the wave, and reducing a mismatch between the modeling of the wave and the slowness dispersion of the wave to improve the modeling of the wave.

Methods are provided for determining properties of an anisotropic formation (including both fast and slow formations) surrounding a borehole. A logging-while-drilling tool is provided that is moveable through the borehole. The logging-while drilling tool has at least one dipole acoustic source spaced from an array of receivers. During movement of the logging-while-drilling tool, the at least one dipole acoustic source is operated to excite a time-varying pressure field in the anisotropic formation surrounding the borehole. The array of receivers is used to measure waveforms arising from the time-varying pressure field in the anisotropic formation surrounding the borehole. The waveforms are processed to determine a parameter value that represents shear directionality of the anisotropic formation surrounding the borehole.

Methods are provided for determining properties of an anisotropic formation (including both fast and slow formations) surrounding a borehole. A logging-while-drilling tool is provided that is moveable through the borehole. The logging-while drilling tool has at least one dipole acoustic source spaced from an array of receivers. During movement of the logging-while-drilling tool, the at least one dipole acoustic source is operated to excite a time-varying pressure field in the anisotropic formation surrounding the borehole. The array of receivers is used to measure waveforms arising from the time-varying pressure field in the anisotropic formation surrounding the borehole. The waveforms are processed to determine a parameter value that represents shear directionality of the anisotropic formation surrounding the borehole.

A method of generating geophysical data using at least one source. The method may include the steps of generating a geophysical wavefield with a varying signature using at least one source, wherein the signature is varied in a periodic pattern.

Systems and methods are provided for determining a formation body wave slowness from an acoustic wave. Waveform data is determined by logging tool measuring the acoustic wave. Wave features are determined from the waveform data and a model is applied to the wave features to determine data-driven scale factors The data-driven scale factors can be used to determine a body wave slowness within a surrounding borehole environment and the body wave slowness can be used to determine formation characteristics of the borehole environment.

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.