Bulletin of the Geological Society of Malaysia, Volume 73, May 2022, pp. 13 – 22

Diving wave tomography: Velocity modelling using first arrival traveltime

Amatul Syafi Abdul Basit^1,*, Abdul Rahim Md Arshad¹, Arulini Permalu²

1 Centre of Excellence in Seismic Imaging & Hydrocarbon Prediction (CSI), Universiti Teknologi PETRONAS, 32610 Bandar Seri Iskandar, Perak, Malaysia
2 Department of Geoscience, Universiti Teknologi PETRONAS, 32610 Bandar Seri Iskandar, Perak, Malaysia
* Corresponding author email address: amatulsyafi@gmail.com

Abstract: In hydrocarbon exploration, information carried by diving waves and post-critical reflections that are used to reconstruct the long-to-intermediate wavelength of the subsurface is an integral part of successful velocity model building. Diving wave tomography (DWT) is one of the tools for shallow velocity assessment particularly when seismic data has poor signal-to-noise ratio (SNR) with complex geologic settings where no clear reflector is present. Considering the relationship between velocity with time and space, the output from tomography plays a crucial role to align data between time and depth domain and produce a reliable image of the deeper structure where hydrocarbon reservoir is typically located. In geophysics, tomography is primarily used to correct seismic trace alignment to produce a reliable stack section. In advanced imaging it is used as an initial model for waveform inversion in an integrated workflow. In the post-processing stage, it is used to correct the misfit between well logs and seismic data and is crucial for the quantitative analysis of rock physics. In this paper, we focus on tomography and its working principle on near-surface velocity modelling. We restricted our workflow to 2D synthetic data simulating the shallow gas occurrence that is prominent in the offshore Malay Basin to demonstrate how tomography works in velocity reconstruction. Results from synthetic and real data example shows that DWT can recover local large-scale structure and improved stacked data, considering no other seismic data and constraint from well data is included in the iterative process.

Keywords: Traveltime tomography, diving wave, shallow gas, forward modelling, traveltime inversion, Malay Basin

DOI: https://doi.org/10.7186/bgsm73202202

0126-6187; 2637-109X / Published by the Geological Society of Malaysia.
© 2022 by the Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution (CC-BY) License 4.0.