The laterally constrained multitrace impedance inversion (LCI) is superior to trace-by-trace inversion, because it can explore spatial coherence among traces and produce a more realistic image of geological structures. However, when the traces are numerous, we have to deal with a large-scale matrix in the multitrace inversion. As usual, this processing has expensive computational cost and high storage requirement, which makes the effectiveness and applicability of the existing multitrace inversion algorithm to be restricted. Here, we introduce a computationally well-behaved algorithm called blocky coordinate descent (BCD), to solve the equation of laterally constrained multitrace impedance inversion. The new method is fast and can be implemented without considering the size of the seismic data. In addition, in order to improve the fidelity of formation boundaries and obtain a more focused solution, we introduce a minimum gradient support (MGS) regularization into the BCD-based laterally constrained inversion (BCD-based LCI) and propose a new method called BCD-based sharp LCI. The new approach can resolve sharp layer boundaries and keep the spatial coherence. At last, we illustrate the capability of the proposed approach on synthetic data and field seismic data.
Presentation Date: Wednesday, September 27, 2017
Start Time: 3:55 PM
Location: 370D
Presentation Type: ORAL
