A method is disclosed for radiaiiy profiling shear velocities of flexural wave modes in a formation. The method includes establishing sensitivity kernels with two non-dimensionalized parameters and using said sensitivity kernels to perform an inversion for radial shear wave velocity profiles. This method may be used for LWD, MWD, or wireline logging operations.

A method for identifying a material behind a pipe string. The method may comprise disposing an acoustic logging tool into a wellbore, insonifying a pipe string within the wellbore with the acoustic logging tool, recording sonic or ultrasonic data. The method may further comprise inputting the sonic or ultrasonic data into trained a machine learning model and identifying the material behind the pipe string using the trained machine learning model.

Systems and methods of the present disclosure are directed to reservoir simulation modeling using upon rock compaction tables derived from physical pore compressibility tests. The illustrative methods transform rock mechanics-based pore compressibility tests into compliant rock compaction tables for reservoir simulators using Dimensionless Stress to Pore Pressure Conversion, to thereby transfer geomechanical changes due to confining stress into expressions of geomechanical changes due to pore pressure.

The present invention belongs to the field of treatment for data identification and recording carriers, and specifically relates to a method and system for evaluating the filling characteristics of a deep paleokarst reservoir through well-to-seismic integration, which aims to solve the problems that by adopting the existing petroleum exploration technology, the reservoir with fast lateral change cannot be predicted, and the development characteristics of a carbonate cave type reservoir in a large-scale complex basin cannot be identified. The method comprises: acquiring data of standardized logging curves; obtaining a high-precision 3D seismic amplitude data body by mixed-phase wavelet estimation and maximum posteriori deconvolution and enhancing diffusion filtering. According to the method and the system, the effect of identifying the development characteristics of the carbonate karst cave type reservoir in the large-scale complex basin can be achieved, and the characterization precision is improved.

Reducing migration distortions in migrated images of the Earth's subsurface. Recorded seismic data may be migrated, using a migration velocity model, to generate a migration image comprising ADCIGs with distortions. Synthetic seismic data may be generated, using the migration velocity model, for a grid of point scatterers. The synthetic seismic data may be migrated, using the migration velocity model, to generate impulse responses for the point scatterers. The impulse responses are used as point spread functions (PSFs) which approximate the blurring operator, e.g., the Hessian. An optimal reflectivity model may be selected using image-domain least-squares migration (LSM), based on the PSFs, with regularization of the difference between the migration image and a reflectivity model and a total variation (TV) regularization of the reflectivity model in the spatial and angular domains. An image of the optimal reflectivity model may be generated with reduced migration distortions compared to the original migration image.

A method for a marine seismic survey can include towing streamers that are spaced apart in a cross-line direction by a streamer separation (L) and towing seismic source elements that are spaced apart in the cross-line direction by a source separation based on an integer (k), an inverse of a quantity of the seismic source elements (1/S), and the streamer separation as represented by (k+1/S)L. The seismic source elements can be actuated and seismic signals can be detected at each of a plurality of receivers on the streamers.

A method for a marine seismic survey can include towing streamers that are spaced apart in a cross-line direction by a streamer separation (L) and towing seismic source elements that are spaced apart in the cross-line direction by a source separation based on an integer (k), an inverse of a quantity of the seismic source elements (1/S), and the streamer separation as represented by (k+1/S)L. The seismic source elements can be actuated and seismic signals can be detected at each of a plurality of receivers on the streamers.

A method includes receiving over a network from one or more seismic sensors a data set characterizing a seismic event generating a seismic wave. Based on the data set, a time of arrival and intensity of the seismic wave at a predetermined location is calculated. The predetermined location has one or more mitigation devices. Whether the intensity of the seismic wave exceeds a predetermined seismic intensity threshold is determined. If the intensity of the seismic wave exceeds the predetermined seismic intensity threshold, the one or more mitigation devices are activated.

A method is described for generating a subsurface model using stochastic full waveform inversion by receiving a seismic dataset representative of a subsurface volume of interest; performing stochastic full waveform inversion of the seismic dataset to generate a long wavelength subsurface model; and performing full waveform inversion of the seismic dataset using the long wavelength subsurface model as a starting model to generate an improved subsurface model. The method may further include performing seismic imaging of the seismic dataset using the improved subsurface model to generate a seismic image and identifying geologic features based on the seismic image. The method may be executed by a computer system.

A method is described for generating a subsurface model using stochastic full waveform inversion by receiving a seismic dataset representative of a subsurface volume of interest; performing stochastic full waveform inversion of the seismic dataset to generate a long wavelength subsurface model; and performing full waveform inversion of the seismic dataset using the long wavelength subsurface model as a starting model to generate an improved subsurface model. The method may further include performing seismic imaging of the seismic dataset using the improved subsurface model to generate a seismic image and identifying geologic features based on the seismic image. The method may be executed by a computer system.