A method, including: obtaining, with a computer, an initial geophysical model; modeling, with a computer, a forward wavefield based on the initial geophysical model with wave equations including a second order z-derivative in a rotated coordinate system that accounts for a tilted transverse isotropic (TTI) medium; modeling, with a computer, an adjoint wavefield with adjoint wave equations including a second order z-derivative in a rotated coordinate system that accounts for a tilted transverse isotropic (TTI) medium, wherein the wave equations and the adjoint wave equations include relaxation terms accounting for anelasticity of earth in an update of a primary variable and an evolution relationship for the relaxation terms; and obtaining, with a computer, a gradient of a cost function based on a combination of a model of the forward wavefield and a model of the adjoint wavefield.

A method including selecting a forward model based on a modeled well structure and including a single modeled acoustic source located in a modeled wellbore and a plurality of modeled acoustic sensors located in a modeled source area, simulating an acoustic signal generated by the single modeled acoustic source and received by each modeled acoustic sensor, calculating phases of the simulated acoustic signals received at each modeled acoustic sensor, obtaining with a principle of reciprocity a plurality of modeled acoustic sources in the modeled source area and a single modeled acoustic sensor in the modeled wellbore, calculating phase delays of the simulated acoustic signals between each modeled acoustic source and the single modeled acoustic sensor, detecting acoustic signals generated by a flow of fluid using acoustic sensors in a wellbore, and processing the acoustic signals using the phase delays to generate a flow likelihood map.

A method of predicting pore pressure based on seismic data can include obtaining seismic inversion data based in part on seismic data collected from a formation. The method also includes calculating a pore-pressure transform, wherein the pore-pressure transform comprises parameters derived using measured pore pressure data, upscaled sonic logs, and density logs, wherein the pore-pressure transform comprises an objective function to reduce unphysical variations in predicted pore pressure corresponding to depth. Additionally, the method can include adjusting the pore-pressure transform for sampling bias caused by pore pressure measurements being restricted to a plurality of lithologies by accounting for a difference between upscaled seismic velocities and average sonic velocities within each of the lithologies. Furthermore, the method can include generating pore pressure prediction values based on the pore-pressure transform for the lithologies and the seismic inversion data, and modifying a seismic model based on the generated pore pressure prediction values.

Methods for full waveform inversion (FWI) in the midpoint-offset domain include using a computer system to sort seismic traces into common midpoint-offset bins (XYO bins). For each XYO bin, a linear moveout correction is applied to a collection of seismic traces within the XYO bin. The collection of seismic traces is stacked to form a pilot trace. The computer system determines a surface-consistent residual static correction for each seismic trace. The computer system determines that the surface-consistent residual static correction for each seismic trace is less than a threshold. Responsive to the determining that the surface-consistent residual static correction is less than the threshold, the computer system stacks the collection of seismic traces to provide the pilot trace. The computer system groups the pilot traces for the XYO bins into a set of virtual shot gathers. The computer system performs one-dimensional FWI based on each virtual shot gather.

The present disclosure relates generally to signal comparison in seismic/acoustic imaging and data processing. In particular, this disclosure relates to a new nonlinear signal comparison (NLSC) approach which obtains a uniform resolution across a frequency band. The overall resolution in NLSC can be controlled over the frequency band by an adjustable parameter.

Systems and methods for generating seismic images of a subsurface formation include obtaining seismic data representing the subsurface formation. Velocity models are generated for the subsurface formation based on the seismic data. Green's functions for the subsurface formation are predicted using a neural network, where the inputs to the neural network include the velocity models, and seismic images of the subsurface formation are generated based on the seismic data and the predicted Green's functions.

Logging of data by a downhole tool disposed in a borehole may be affected by tool wave effects. The tool waves appear in the first echo of casing wave arrivals and the amplitudes may be much larger than casing wave arrivals. The estimates of casing wave amplitude are biased due to these tool wave arrivals when using conventional cement-bond logging (CBL) processing. An automated adaptive inversion-based array processing for CBL evaluation using a downhole tool provides an improvement in the calculation of a bonding index.

A method for determining a shear slowness of a subterranean formation includes receiving waveforms data acquired by receivers in an acoustic measurement tool in response to energy emitted by at least one dipole source. The waveforms are processed to extract a formation flexural acoustic mode and a tool flexural acoustic mode. The processing includes transforming the time domain waveforms to frequency domain waveforms, processing the frequency domain waveforms with a Capon algorithm to compute a two-dimensional spectrum over a chosen range of group slowness and phase slowness values; and processing the two-dimensional spectrum to extract the multi-mode slowness dispersion. The method further includes selecting a plurality of slowness-frequency pairs from the formation flexural mode of the extracted multi-mode dispersion wherein each slowness-frequency pair comprises a slowness value at a corresponding frequency and processing the selected slowness frequency pairs to compute the shear slowness of the subterranean formation.

A method is presented for predicting which shape and/or amplitude of seismic wave or wave pulse would cause an increase in oil relative permeability when a seismic wave or wave pulse with that shape and/or amplitude is applied to a region of interest. The method comprises: (a) obtaining one or more parameter values for the region of interest; (b) inputting the one or more parameter values into a model which predicts changes in oil relative permeability for the region of interest for different seismic wave or wave pulse shapes and/or amplitudes; (c) repeating step (b) one or more times for different seismic wave or wave pulse shapes and/or amplitudes; and (d) determining which seismic wave or wave pulse shape and/or amplitude causes an increase or the greatest increase in oil relative permeability based on the output of the model.

A method and a system for implementing the method are disclosed wherein the seismic input data and land acquisition input data may be obtained from a non-flat surface, sometimes mild or foothill topography as well as the shot and receiver lines might not necessarily be straight, and often curve to avoid obstacles on the land surface. In particular, the method and system disclosed, decomposes the cross-spread data into sparse common spread beams, then maps those sparse beams into common-spread depth domain, in order to finally stack them to construct the subsurface depth images. The common spread beam migration and processing have higher signal to noise ratio, as well as faster turn-around processing time, for the cross-spread land acquisition over the common-shot or common offset beam migration/processing. The common spread beam migration method and system disclosed, will eventually help illuminate and interpret the hydro-carbonate targets for the seismic processing.