Model‐based optimization of source locations for 3D acoustic seismic full‐waveform inversion. (1st November 2022)

• Record Type: Journal Article
• Authors: Winner, Valérie; Edme, Pascal; Maurer, Hansruedi
• Is Part Of: Geophysical prospecting. Volume 71:Number 1(2023)
• Page Start: 3
• Page End: 16
• Publication Date: 2022-11-01
• Subjects: Acquisition -- full waveform -- inversion -- seismics -- survey design; Prospecting -- Geophysical methods -- Periodicals; 622.15
• DOI: 10.1111/1365-2478.13264
• Languages: English
• ISSNs: 0016-8025

Abstract

Abstract: Besides classical imaging techniques, full‐waveform inversion is an increasingly popular method to derive elastic subsurface properties from seismic data. High‐resolution velocity models can be obtained, and spatial sampling criteria are less strict than for imaging methods, because the entire information content of the seismic waveforms is used. As high operational costs arise from seismic surveys, the acquirable data volume is often limited by economic criteria. By selecting optimal locations for seismic sources, the information content of the data can be maximized, and the number of sources and thus the acquisition costs can be reduced compared with standard acquisition designs. The computation of such optimized designs for large‐size 3D inverse problems at affordable computational cost is challenging. By using a sequential receiver‐wise optimization strategy, we substantially reduce the computational requirements of the optimization process. We prove the applicability of this method by means of numerical 3D acoustic examples. Optimized source designs for different receiver patterns are computed for a realistic subsurface model, and the value of the designs is evaluated by comparing checkerboard inversion tests with different acquisition designs. Our examples show that inversion results with higher accuracy can be obtained with the optimized designs, regardless of the number of sources, the number of receivers, or the receiver distribution. Larger benefits of the optimized designs are visible when a sparse receiver geometry is used.