- Flexible tools for accurate angle-dependent wavelet extraction
- FWI-driven workflows for low-frequency model (LFM) building where no well data exist
- Global success demonstrated for broadband 3D and 4D applications
- Comprehensive rock physics-driven CCS storage site characterization
Wells on matched 2D lines can be tied to a 3D survey for both inversion calibration and model-building constraints. In the absence of well data within a survey (or tie-lines), wavelets can be derived statistically, and models can be built using regional rock physics trend information.
Relative and Absolute Simultaneous Inversion Workflow
The PGS (relative and absolute) simultaneous sparse-spike inversion process is decomposed into the following steps
- Wavelet extraction | Wavelets are required for the sparse spike inversion process and may be extracted in different ways. Statistical wavelet extraction is the simplest wavelet estimation. It only relies on the seismic data and requires no well information. Limitations of the method include the assumption that the data is zero phase, and that signal can be robustly separated from the noise. Bayesian wavelet extraction uses an advanced workflow, handles multi-well and multi-stack wavelet extraction, and provides uncertainty in the wavelet estimation (amplitude, best location and well tie). The multi-angle Bayesian wavelet derivation program estimates the wavelet(s) and their uncertainty (seismic noise level) at the available well locations. The availability of reliable well data to which the seismic data has a good correlation is an important workflow dependency.
- Low-frequency model building
- Geostatistical depth conversion
- Seismic inversion QC and production
- Bayesian lithology / fluid prediction
The seismic inversion engine is used to simultaneously invert for P and S impedance and density, if the data allows, at every trace location using any number of input seismic angle stacks (either pre- or post-stack data). Other rock property derivatives can also be calculated including Vp/Vs, Poisson's ratio, Lambda-Rho and Mu-Rho. The results of the simultaneous inversion can be quantitatively integrated with the expected results (probability density functions) from the statistical rock physics and stochastic modeling workflow used for lithology and fluid prediction.
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