Optimized Experimental Design in the Context of Seismic Full Waveform Inversion and Seismic Waveform Imaging

During the past few years, significant improvements have been achieved in high-resolution imaging with seismic data. In particular, seismic full waveform inversion (FWI) has been proven to be a very promising tool. However, this technique requires high-quality data, whose acquisition can be very expensive. Furthermore, FWI is computationally extremely demanding, which currently limits its application to large-scale data sets. Both problems can be alleviated with optimized experimental design (OED) techniques. Using tools from the linearized inversion theory, we outline how source–receiver patterns can be identified that are most suitable for FWI experiments. This is demonstrated by reviewing a laboratory-scale experiment devoted to breast cancer detection with ultrasound data, and with a surface seismic survey study that is concerned with elastic FWI for shallow subsurface structures. By means of a vertical seismic profiling design example, we also show that the OED technology can be adapted to wavefield imaging techniques. Besides identifying optimized source–receiver patterns, OED can be employed for extracting the most useful attributes from a seismic data set, which can reduce the computational costs. For that purpose, we discuss a frequency-domain crosshole FWI experiment, where we quantify the information content of different data representations and identify suitable spatial and temporal sampling strategies. In a second crosshole study, it is inspected that source and receiver components allow the relevant elastic subsurface properties to be resolved. Finally, we outline a more general framework of seismic observables, with which the sensitivity of selected model parameters can be maximized. This is demonstrated with an example of regional earth mantle tomography.