Seismic data acquisition is a trade-off between cost and data quality subject to operational constraints. Due to budget limitations, 3D seismic acquisition usually does not have a dense spatial sampling in all dimensions. This causes artefacts in the processed images, velocity models, or other physical properties. However, we rely on, for example, the accurate images in determining the location of oil and gas-bearing geological structures, and the accurate elastic properties to characterise the reservoir. In this thesis, we propose new methods to improve existing technologies that can optimise marine seismic acquisition. In Part I, we aim at obtaining dense data in less time by improving the so-called blended seismic acquisition techniques. In Part II, we aim at obtaining an improved target illumination with a limited number of sources and receivers by developing an acquisition optimisation framework.
|Award date||14 Jul 2020|
|Publication status||Published - 2020|
- acquisition design
- simultaneous source
- genetic algorithm