Modelling, Migration, and Inversion for Angle Domain Common Image Gathers

Angle Domain Common-Image Gathers (ADCIGs) are crucial for seismic amplitude-versus-angle analysis, facilitating the prediction of lithology, fluid properties. ADCIGs, which represent angle-dependent reflectivities, are challenging to compute accurately due to the high accuracy requirements of migration and inversion algorithms. This thesis focuses on developing an new algorithm to integrate the modeling, migration, and inversion of ADCIGs. The modeling of ADCIGs is based on acoustic and elastic wave equations, and the results are compared with the exact Zoeppritz equations to validate the accuracy of the modeling process. The migration of ADCIGs is based on reflection angle extraction methods in Reverse Time Migration (RTM) fullfilling the requirement of the true amplitude migration. The inversion of ADCIGs predicts both velocity and angle-dependent reflectivity based on Full Waveform Inversion (FWI). Advances in high-performance computing and FWI algorithms have significantly improved the generation of accurate velocity models and other parameters across diverse geological settings. However, the FWI sensitivity kernel in acoustic variable-density media differs by parameterization method, and the time-domain gradient equation in velocity-density media has multiple arguments. I tested several velocity-density gradient equations in time-domain full waveform inversion (FWI) for acoustic variable-density media. Additionally, I derived a new FWI sensitivity kernel based on scattering theory, and proposed an iterative non-linear inversion method to predict both velocity and amplitude-preserved reflectivity. This method combines angle domain RTM migration with FWI. The iterative inversion method is based on time-domain FWI using the nonlinear conjugate-gradient method. The results demonstrate that the new FWI sensitivity kernel has higher resolution in certain high-dip structures compared to previously published methods, and the angle domain FWI can predict ADCIGs in shallow zones with high accuracy.

Name thesis:degree_name

Master of Science (MSc)

Discipline thesis:degree_discipline

Geoscience

Grantor dc:publisher.institution

Graduate Studies

Year dc:date.issued

2025

Author dc:creator

• Su, Ziguang

Advisor dc:contributor.advisor

• Trad, Daniel

Committee members dc:contributor.committeemember

• Trad, Daniel
• Innanen, Kris
• Gilbert, Hersh

• ADCIG
• Inversion
• Migration
• Modeling
• Seismic

Statement dc:rights

• University of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.

Language dc:language.iso

en

DOI

https://dx.doi.org/10.11575/PRISM/48430

OAI identifier oai:identifier

oai:ucalgary.scholaris.ca:1880/120824