G01V2210/51

REVERSE TIME MIGRATION IMAGING METHOD FOR CASED-HOLE STRUCTURE BASED ON ULTRASONIC PITCH-CATCH MEASUREMENT
20230033271 · 2023-02-02 ·

A reverse time migration imaging method for cased-hole based on ultrasonic pitch-catch measurement, including: calculating a theoretical dispersion curve; expanding original Lamb data of two receivers into array waveform data based on phase-shift interpolation; establishing a two-dimensional migration velocity model including density, P-wave velocity and S-wave velocity of a target area; generating and storing a forward propagating ultrasonic wavefield for each time step; reversing a time axis; generating and storing a reversely propagating ultrasonic Lamb wavefield for the two receivers after phase-shift interpolation; calculating envelopes of the forward propagating ultrasonic Lamb wavefield and the reversely propagating ultrasonic Lamb wavefield; applying a zero-lag cross-correlation imaging condition to obtain reverse time migration imaging results; and applying Laplace filtering to suppress low-frequency imaging noises in the imaging results.

Prestack least-square reverse time migration on surface attribute gathers compressed using depth-independent coefficients

Methods and apparatuses for seismic data processing perform a least-squares reverse time migration method in which surface-attribute-independent coefficients for the surface attribute gathers are demigrated to reduce the computational cost.

RTM using equal area spherical binning for generating image angle gathers
11487033 · 2022-11-01 · ·

Seismic exploration of an underground formation uses seismic excitations to probe the formation's properties such as reflectivity that can be imaged using reverse time migration. Using an equal area spherical binning at reflection points improves and simplifies RTM imaging together with adaptability to the data acquisition geometry, while overcoming drawbacks of conventional cylindrical binning.

METHOD AND SYSTEM FOR SUPER RESOLUTION LEAST-SQUARES REVERSE TIME MIGRATION
20220350042 · 2022-11-03 · ·

A method may include obtaining seismic data regarding a geological region of interest. The method may further include obtaining a property model regarding the geological region of interest. The method may further include determining an adjoint migration operator based on the property model. The method may further include updating the property model using the seismic data and a conjugate gradient solver in a least-squares reverse time migration to produce a first updated property model. The conjugate gradient solver is based on the adjoint migration operator. The method may further include updating the first updated property model using a threshold shrinkage function to produce a second updated property model. The threshold shrinkage function comprises a sign function and a maximum function that are applied to the first updated property model. The method may further include generating a seismic image of the geological region of interest using the second updated property model.

Methods and devices performing adaptive quadratic Wasserstein full-waveform inversion
11635540 · 2023-04-25 · ·

Methods and devices for seismic exploration of an underground structure apply W.sup.2-based full-wave inversion to transformed synthetic and seismic data. Data transformation ensures that the synthetic and seismic data are positive definite and have the same mass using an adaptive normalization. This approach yields superior results particularly when the underground structure includes salt bodies.

UNCERTAINTY ANALYSIS FOR NEURAL NETWORKS
20230122128 · 2023-04-20 ·

A method includes receiving geophysical data representative of a geophysical structure; providing the geophysical data as one or more input data to a neural network; training the neural network to reconstruct the geophysical structure that was received and provide one or more uncertainty metrics for one or more features of the geophysical structure that is reconstructed; reconstructing, using the neural network that has been trained, the geophysical structure;

and determining, using the neural network that has been trained, the one or more uncertainty metrics by implementing a second drop out condition on the one or more nodes of the one or more hidden layers of the neural network. The training is performed at least partially by implementing a first drop out condition on one or more nodes of one or more hidden layers of the neural network to randomly set an output of the one or more nodes to zero.

COMPUTER-IMPLEMENTED METHOD AND SYSTEM FOR OBTAINING A SUBSURFACE STACK IMAGE, SUBSURFACE ANGLE GATHERS, AND A SUBSURFACE VELOCITY MODEL, OVER AN ENTIRE SURVEY REGION HAVING HIGH VELOCITY CONTRAST GEO-BODIES

A computer-implemented method and computing system apparatus programmed to perform operations of the computer-implemented method for obtaining a subsurface stack image, subsurface angle gathers, and a subsurface velocity model over an entire survey region having high velocity contrast geo-bodies. Particularly, user inputs, input velocity models, and surface-seismic data are obtained by fixed source and receiver pairs and then used by the computer program product embedded within the computing system apparatus to minimize the number of iterations, required to obtain a final velocity model, a final stack image, and final angle gathers wherein their flatness deviation is equal to, or less than, a user-defined flatness value. Therefore, the attributes developed by said computer-implemented method and system can help solve the imaging problem of sub high velocity contrast geo-bodies like subsalt, or salt overhung deep mini basins.

METHOD AND APPARATUS FOR IMPLEMENTING A HIGH-RESOLUTION SEISMIC PSEUDO-REFLECTIVITY IMAGE
20230103668 · 2023-04-06 · ·

A method for generating a high-resolution pseudo-reflectivity image of a subsurface region includes receiving seismic data associated with a subsurface region and captured by one or more seismic receivers, constructing a velocity model of the subsurface region based on the received seismic data, performing a seismic migration of the received seismic data based on the constructed velocity model to obtain migrated seismic data, computing polarized normal vectors associated with one or more subsurface reflectors of the subsurface region based on the migrated seismic data, and generating a pseudo-reflectivity image of the subsurface region based on both the computed polarized normal vectors.

Computer-implemented method and system for obtaining a subsurface stack image, subsurface angle gathers, and a subsurface velocity model, over an entire survey region having high velocity contrast geo-bodies

A computer-implemented method and computing system apparatus programmed to perform operations of the computer-implemented method for obtaining a subsurface stack image, subsurface angle gathers, and a subsurface velocity model over an entire survey region having high velocity contrast geo-bodies. Particularly, user inputs, input velocity models, and surface-seismic data are obtained by fixed source and receiver pairs and then used by the computer program product embedded within the computing system apparatus to minimize the number of iterations, required to obtain a final velocity model, a final stack image, and final angle gathers wherein their flatness deviation is equal to, or less than, a user-defined flatness value. Therefore, the attributes developed by said computer-implemented method and system can help solve the imaging problem of sub high velocity contrast geo-bodies like subsalt, or salt overhung deep mini basins.

Interpretive-guided velocity modeling seismic imaging method and system, medium and device

The present disclosure belongs to the technical field of seismic exploration imaging, and relates to an interpretive-guided velocity modeling seismic imaging method and system, a medium and a device. The method comprises the following steps: S1. performing first imaging on a given initial velocity model to obtain a first imaging result; S2. performing relative wave impedance inversion on the first imaging result to obtain a relative wave impedance profile; S3. performing Curvelet filtering on the relative wave impedance profile to obtain a first interpretation scheme; S4. superposing the first interpretation scheme and the initial velocity model to obtain a new migration velocity field; S5. performing second imaging on a new migration velocity field to obtain a second imaging result; and S6. repeating steps S2-S4 for the obtained second imaging result until a final seismic imaging result is obtained.