Chrome Extension
WeChat Mini Program
Use on ChatGLM

Seismic characterization of submarine gas-hydrate deposits in the Western Black Sea by acoustic full-waveform inversion of ocean-bottom seismic data

GEOPHYSICS(2019)

Cited 12|Views1
No score
Abstract
Evidence for gas-hydrate occurrence in the Western Black Sea is found from seismic measurements revealing bottom-simulating reflectors (BSRs) of varying distinctness. From an ocean-bottom seismic data set, low-resolution traveltime-tomography models of P-wave velocity V-P are constructed. They serve as input for acoustic full-waveform inversion (FWI), which we apply to derive high-resolution parameter models aiding the interpretation of the seismic data for potential hydrate and gas deposits. Synthetic tests indicate the applicability of the FWI approach to robustly reconstruct VP models with a typical hydrate and gas signature. Models of S-wave velocity VS containing a hydrate signature can only be reconstructed when the parameter distribution of VS is already well-known. When we add noise to the modeled data to simulate field-data conditions, it prevents the reconstruction of V-S completely, justifying the application of an acoustic approach. We invert for V-P models from field data of two parallel profiles of 14 km length with a distance of 1 km. Results indicate a characteristic velocity trend for hydrate and gas occurrence at BSR depth in the first of the analyzed profiles. We find no indications for gas accumulations below the BSR on the second profile and only weak indications for hydrate. These differences in the V-P signature are consistent with the reflectivity behavior of the migrated seismic streamer data of both profiles in which a zone of high-reflectivity amplitudes is coincident with the potential gas zone derived from the FWI result. Calculating saturation estimates for the potential hydrate and gas zones yields values of up to 30% and 1.2%, respectively.
More
Translated text
Key words
Seismic Waveform Inversion,Gas Hydrates,Ambient Seismic,Seismic Data Processing,Seismic Noise
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined