DETERMINATION OF MINIMUM DATA DENSITY REQUIREMENTS TO CHARACTERIZE THE HETEROGENEITY OF THE YELLOW SEA CONTINENTAL MARGIN

A 2-D, high-resolution seismic surveys consisting of over 6000 Km were conducted in 1996 and 1999 within the Yellow Sea (YS) Basin. Data from the surveys are used in this investigation to determine the minimum density data (MINDDA) required to accurately characterize the heterogeneity of Quaternary stratigraphic units of YS depositional systems. The YS Basin is part of a broad, epicontinental seaway that receives sediment from the Huanghe (Yellow) River, the worlds second largest in terms of sediment supply. Sediment distribution is influenced by a high tidal regime (equal to or greater than 2m), along with a high frequency of intense tropical and extra-tropical storms. Compared to the Mississippi River, which has confined lowstand deposits and laterally extensive highstand deposits, the YS has both laterally extensive lowstand and highstand deposits. This is due to the large avulsion events of the Huanghe River during times of lowered sea level.

To establish the nature of the relationship between data density and variation in facies distribution during oxygen isotope stages 1 and 2, hand and computer drafted isopach and structure maps were generated at 4.7, 9.4, 18.8, 37.6, 75.6, and 150.4 km sample intervals. Using both qualitative and quantitative analyses, the rate of change of the distribution of map attributes from one sample interval to the next are related to the diminishing returns curve to determine if stratigraphic units in the YS have points of diminishing returns, and at which of these data sample intervals they occur. The point of diminishing returns is determined by plotting the percentage of difference between maps on the y-axis versus sample interval on the x-axis. This point represents the MINDDA required to accurately characterize components of the YS stratigraphy. Determination of MINDDA for the YS is compared to different end member environments to improve our understanding of MINDDA through a range of environmental conditions. MINDDA may then be used to provide additional cost and time efficiency for future studies.