Abstract
<p>The existing conventional inversion algorithm does not provide satisfactory results due to the complexity of propagated wavefield though the gas cloud. Acoustic full waveform inversion has been developed and applied to a realistic synthetic offshore shallow gas cloud feature with Student-t approach, with and without simultaneous sources encoding. As a modeling operator, we implemented the grid based finite-difference method in frequency domain using second order elastic wave equation. Jacobin operator and its adjoint provide a necessary platform for solving full waveform inversion problem in a reduced Hessian matrix. We invert gas cloud model in 5 frequency band selected from 1 to 12 Hz, each band contains 3 frequencies. The inversion results are highly sensitive to the misfit. The model allows better convergence and recovery of amplitude losses. This approach gives better resolution then the existing least-squares approach. In this paper, we implement the full waveform inversion for low frequency model with minimum number of iteration providing a better resolution of inversion results.</p>
Highlights
A two-step approach is applied in seismic exploration: (1) firstly, the acquired data is processed for primaries only for structured imaging; (2) secondly, to derive the lithological and fluid properties derived through AVO inversion
The use of least-squares, Student’s and simultaneous source encoding in frequency domain full waveform inversion (FWI) highlight the sensitivity of the optimization convergence toward the true model
(a) In the first scenario, the application with leastsquares technique in a gas cloud model intrinsically amplifies the weight of the high residuals during inversion, causing divergence during the optimization
Summary
A two-step approach is applied in seismic exploration: (1) firstly, the acquired data is processed for primaries only for structured imaging; (2) secondly, to derive the lithological and fluid properties derived through AVO (amplitude versus offset) inversion. Many of the hydrocarbon bearing reservoir in the SE Asia have poor imaging [Ghosh et al 2010, Ghazali 2011], resulting from gas leakages and other complex geology. An example of such imaging problem (Figure 1). The obvious approach is through Q-compensation [Reilly et al 2008], which uses a tandem velocity Q model in pre-stack depth imaging to compensate for travel time delay, amplitude loss and phase distortion. Where he developed an “equivalent media” model to account for time delays and amplitude losses using inverse scattering concept In first step he solves the kinematics to account for travel time and uses an inverse approach to account for amplitude losses.
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