Seismic velocity analysis using maximum‐likelihood weighted eigenvalue ratios

1987 ◽  
Author(s):  
Scott C. Key ◽  
R. Lynn Kirlin ◽  
Scott B. Smithson
Keyword(s):  
Maximum Likelihood ◽  
Seismic Velocity ◽  
Velocity Analysis

High-resolution seismic velocity analysis by sign-based weighted semblance

Geophysics ◽  
2021 ◽  
pp. 1-35
Author(s):  
M. Javad Khoshnavaz
Keyword(s):  
Seismic Velocity ◽  
Resolution Enhancement ◽  
Synthetic Data ◽  
Correlation Coefficients ◽  
Velocity Model ◽  
Seismic Attenuation ◽  
Velocity Analysis ◽  
Velocity Models ◽  
Amplitude Versus Offset ◽  
Amplitude Versus

Building an accurate velocity model plays a vital role in routine seismic imaging workflows. Normal-moveout-based seismic velocity analysis is a popular method to make the velocity models. However, traditional velocity analysis methodologies are not generally capable of handling amplitude variations across moveout curves, specifically polarity reversals caused by amplitude-versus-offset anomalies. I present a normal-moveout-based velocity analysis approach that circumvents this shortcoming by modifying the conventional semblance function to include polarity and amplitude correction terms computed using correlation coefficients of seismic traces in the velocity analysis scanning window with a reference trace. Thus, the proposed workflow is suitable for any class of amplitude-versus-offset effects. The approach is demonstrated to four synthetic data examples of different conditions and a field data consisting a common-midpoint gather. Lateral resolution enhancement using the proposed workflow is evaluated by comparison between the results from the workflow and the results obtained by the application of conventional semblance and three semblance-based velocity analysis algorithms developed to circumvent the challenges associated with amplitude variations across moveout curves, caused by seismic attenuation and class II amplitude-versus-offset anomalies. According to the obtained results, the proposed workflow is superior to all the presented workflows in handling such anomalies.

Can anisotropy parameters derived by seismic velocity analysis improve PSDM image?

2007 ◽  
Author(s):  
Ray Gedaly* ◽  
Qingbo Liao
Keyword(s):  
Seismic Velocity ◽  
Velocity Analysis ◽  
Anisotropy Parameters

Thermal maturity evaluation by sonic log and seismic velocity analysis in parts of Upper Assam Basin, India

1995 ◽  
Vol 23 (10) ◽  
pp. 871-879 ◽  
Author(s):  
R.K. Mallick ◽  
S.V. Raju
Keyword(s):  
Seismic Velocity ◽  
Velocity Analysis ◽  
Thermal Maturity ◽  
Sonic Log ◽  
Maturity Evaluation

Seismic velocity analysis case study: Geostatistical contributions

1985 ◽  
Author(s):  
T. K. Young ◽  
A. J. Davis ◽  
D. R. Palmore ◽  
D. H. Thorson
Keyword(s):  
Seismic Velocity ◽  
Velocity Analysis

CSEM-regularized seismic velocity inversion: A multiscale, hierarchical workflow for subsalt imaging

Geophysics ◽  
2018 ◽  
Vol 83 (5) ◽  
pp. B241-B252 ◽  
Author(s):  
Daniele Colombo ◽  
Diego Rovetta ◽  
Ersan Turkoglu
Keyword(s):  
Seismic Velocity ◽  
Fundamental Problem ◽  
Velocity Model ◽  
Seismic Inversion ◽  
Velocity Fields ◽  
Coupling Mechanism ◽  
Correct Result ◽  
Velocity Analysis ◽  
Velocity Inversion ◽  
Velocity Models

Seismic imaging in salt geology is complicated by highly contrasted velocity fields and irregular salt geometries, which cause complex seismic wavefield scattering. Although the imaging challenges can be addressed by advanced imaging algorithms, a fundamental problem remains in the determination of robust velocity fields in high-noise conditions. Conventional migration velocity analysis is often ineffective, and even the most advanced methods for depth-domain velocity analysis, such as full-waveform inversion, require starting from a good initial estimate of the velocity model to converge to a correct result. Nonseismic methods, such as electromagnetics, can help guide the generation of robust velocity models to be used for further processing. Using the multiphysics data acquired in the deepwater section of the Red Sea, we apply a controlled-source electromagnetic (CSEM) resistivity-regularized seismic velocity inversion for enhancing the velocity model in a complex area dominated by nappe-style salt tectonics. The integration is achieved by a rigorous approach of multiscaled inversions looping over model dimensions (1D first, followed by 3D), variable offsets and increasing frequencies, data-driven and interpretation-supported approaches, leading to a hierarchical inversion guided by a parameter sensitivity analysis. The final step of the integration consists of the inversion of seismic traveltimes subject to CSEM model constraints in which a common-structure coupling mechanism is used. Minimization is performed over the seismic data residuals and cross-gradient objective functions without inverting for the resistivity model, which is used as a reference for the seismic inversion (hierarchical approach). Results are demonstrated through depth imaging in which the velocity model derived through CSEM-regularized hierarchical inversion outperforms the results of a seismic-only derived velocity model.

scholarly journals A braver approach to seismic velocity analysis in the Taranaki Basin, New Zealand

2000 ◽  
Vol 31 (1-2) ◽  
pp. 267-269
Author(s):  
Denise Humphris ◽  
Jonathan Ravens
Keyword(s):  
New Zealand ◽  
Seismic Velocity ◽  
Velocity Analysis

scholarly journals Application of Velocity Analysis Picking for 2D Seismic Data Processing in West An-Najaf Are

2021 ◽  
pp. 555-564
Author(s):  
Kamal K. Ali ◽  
Ahmed Wanas ◽  
Mohanad E. Mahdi
Keyword(s):  
Seismic Data ◽  
Seismic Velocity ◽  
Velocity Analysis ◽  
Seismic Data Processing ◽  
Root Mean Square Velocity ◽  
Seismic Section ◽  
Sorting Data ◽  
Omega System ◽  
Analysis Application ◽  
Amplitude Compensation

     In the current study, 2D seismic data in west An-Najaf (WN-36 line) were received after many steps of processing by Oil Exploration Company in 2018. Surface Consistent Amplitude Compensation (SCAC) was applied on the seismic data. The processing sequence in our study started by sorting data in a common mid-point (CMP) gather, in order to apply the velocity analysis using Interactive Velocity Analysis Application (INVA) with Omega system. Semblance of velocity was prepared to preform normal move-out (NMO) vs. Time. Accurate root mean square velocity (VRMS) was selected, which was controlled by flatness of the primary events. The resultant seismic velocity section for the study area shows that the velocity analysis became smother and provided an accurate seismic section.

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