Third EAGE Workshop on Advanced Seismic Solutions in the Gulf of Mexico
- Conference date: October 16-17, 2024
- Location: Mexico City, Mexico
- Published: 16 October 2024
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Shallow Water Imaging Using Ocean Bottom Cable Data with Time-lag FWI in Southern Gulf of Mexico
More LessAuthors X. Zhang, B. Wray, W.L. Chan, H. Zhu, R.P. Salvador, J.C.R. Gutiérrez, S.D. Garcia and K.A.H. RiveraSummaryThe study area is in a shallow water region with water bottom depth ranging from approximately 10 m to 100 m. Building an accurate velocity model in the study area has been challenging due to complex geology. There are two major velocity model building tools: tomography and full waveform inversion (FWI). Geological complexity reduces ray tracing stability and degrades migrated gathers, making tomography-based model building ineffective. In contrast, FWI does not depend on ray tracing or gather quality. It updates the velocity model by minimizing the data misfit between full waveform synthetic and real data. In this case study, we use Time-lag FWI (TLFWI), a cross-correlation based FWI algorithm, as the core of velocity model building. With the velocity updated from TLFWI, some structures are still not well imaged. Due to the sparsity of the OBC data and complex geology, there are illumination problems from shallow to deep. Reverse time migration (RTM) images have suboptimal coherency in poorly illuminated areas. We derived the FWI Image from the TLFWI velocity model. The FWI Image utilizes full wave fields, including primary and multiples, which provide better illumination. FWI Image offers superior imaging for complex structures compared to RTM.
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Improving Complex Mesozoic Structure Imaging with WAZ and OBC Iterative TLFWI in the Gulf of Mexico
More LessSummaryThis project aimed at imaging complex Mesozoic structures in the offshore shallow water area of the southern Gulf of Mexico. It used both WAZ and OBC datasets as input, with WAZ covering the northern side and OBC covering the southern side. Both datasets were used simultaneously in the velocity model building (VMB) to update the velocity across the entire project area. The VMB workflow, consisting of iterative TLFWI and velocity scenarios based on the interpretation of RTM and FWI image, was employed to handle challenges posed by complex local geology and limited diving waves penetration. This approach built a seamless velocity model, overcoming input geometry differences and leading to significant improvements over the legacy RTM volume. Additionally, the FWI image further improved the result by providing better defined complex structures than the RTM image.
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