Geophysical reservoir characterization in a complex geologic environment remains a challenge. Conventional amplitude inversion assumes reliable seismic amplitudes. In a complex environment, inadequate illumination of the subsurface due to complex geology or the acquisition geometry has detrimental effects on the amplitudes and phase of the migrated image. Such effects are not compensated for in conventional seismic inversion techniques. Consequently, an imprint of various nongeological effects will manifest themselves in the results of seismic inversion, leading to a less reliable estimation of the resultant acoustic and elastic parameters. The depth domain inversion workflow uses point spread functions to capture the dip-dependent illumination effects due to acquisition geometry and complex geology. The amplitude inversion is performed in the depth domain and the output is an acoustic impedance volume corrected for illumination effects. This paper presents the results of a field data example with the objective of comparing the results of the time domain inversion and the depth domain inversion, identifying and explaining both differences and similarities. This leads to an assessment of what should be expected from the depth domain inversion approach, including key advantages and limitations.
Multisensor streamer acquisition records both pressure and acceleration in the vertical and crossline directions. It enables the reconstruction of a dealiased representation of the upgoing pressure wavefield at any location within the streamer array. This is achieved by joint reconstruction and deghosting using a generalised matching pursuit (GMP) algorithm. To achieve an independent and quantified evaluation of the reconstruction quality, recorded seismic data is compared with the reconstructed seismic data at a witness streamer location. This paper presents the concept and results of this witness streamer experiment. The results show that mitigations can significantly reduce the impact of the main assumption of the GMP algorithm, which could otherwise compromise the quality of the early-time reconstruction in shallow water. Using these techniques, the reconstruction quality compared with an independent witness streamer is consistent from the shallow part to the deeper part of the data, with a very good match between the recorded and reconstructed data.
The amount of available data to help us characterise the subsurface is ever increasing. Large seismic surveys, long offsets, multi- and full-azimuth datasets, including 3D and 4D, marine, ocean-bottom nodes and extremely high fold land surveys, are now common. In parallel, computing power is also increasing and, in combination with better data, this enables us to develop better tools and to use better physics to build models of the subsurface. Wave-equation based techniques, such as full waveform inversion (FWI), have therefore become a lot more practical. FWI uses the entire wavefield, including refractions and reflections, primaries and multiples, to generate a refined, high resolution Earth model. This technique is now commonly used at lower frequencies (up to 12 Hz) to derive more accurate models for improved seismic imaging and reduced depth conversion uncertainty. By including higher frequencies in FWI, we can attempt to resolve for finer and finer details. FWI models using the entire bandwidth of the seismic data constitute an interpretation product in itself, with applications in both structural interpretation and reservoir characterisation. Incorporating more physics within the FWI implementation, combined with modern supercomputer facilities, promises to increase the focus on very high frequency FWI in the coming years. In this paper, through a series of field examples, we illustrate the applications and rewards of high frequency FWI: from improved imaging, improved quantitative interpretation and depth conversion to a direct interpretation of the FWI models.
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