Geology and Geophysics for ASIAEX: Seismic Stratigraphic and Stochastic Analyses of High Resolution Seismic Data from the Continental Margins of the East China and South China Seas.

摘要

Our research group is collecting and analyzing various levels of high-resolution seismic data and cores, for ground-truthing seismic facies, on continental margins with a spectrum of depositional boundary conditions. The long-term goal of this work is to develop stochastic models of variation of geotechnical and seismic property distribution on margins subjected to a spectrum of depositional regimes. We are also assessing the quantity of data required to recognize the nature of stratigraphic architecture of a continental margin. We refer to this as Minimum Data Density Analysis (MINDDA). The importance of being able to produce these stochastic models is that it provides a means of making predictions (with assignment of statistical risk) of the variation of geotechnical and seismic properties in areas where the only data that may exist for that margin at the time that a prediction is needed is information on physical oceanography or other gross descriptions of depositional conditions on the margin. In the ECS we have a regional data set that we are using for this purpose and we have initiated MINDDA and it appears as though we have established MINDDA for a number of stratigraphic elements of the East China Sea continental margin. However, there are some elements in which it is not clear that a data set that is required to establish MINDDA in the East China Sea (ECS) has been acquired. In order to provide a rigorous test of our hypotheses about MINDDA and geologic processes for the ECS system we planned to acquire a data set consisting of geophysical data (seismic, chirp, and side-scan) and geologic data (cores) in a 40 by 55 km grid with profiles oriented parallel to depositional strike and dip in the ECS at a site where the geology consists of vertical stratification and lateral continuity of layers. Data collected in ECS area are being subjected to seismic stratigraphic analyses, MINDDA and development stochastic models of stratigraphic architecture variability.