IODP Proceedings    Volume contents     Search


Cuttings-core-log-seismic integration

During Expedition 338, results from cuttings, cores, and mud-gas analyses and trends in LWD data were used to establish accurate ties to the 2006 Kumano 3-D and 2006 IFREE multichannel seismic (MCS) reflection data sets (e.g., Moore et al., 2007, 2009; Park et al., 2008).

At Site C0002, LWD data and cuttings acquired during riser drilling from 860 to 2005.5 mbsf and core samples within the depth ranges 0–204, 200–500, 475–1057, 900–1040, and 1100–1120 mbsf were available to define logging and lithologic units. At Sites C0012, C0018, and C0021, LWD data were correlated to core samples collected during Expeditions 322 and 333. At Site C0022, LWD data were correlated to cores collected during this expedition. The LWD BHA always included the arcVISION, geoVISION, and TeleScope tools. In addition, the sonicVISION tool was used for Holes C0002F and C0012H. For details regarding the analysis techniques of the independent cuttings, cores, and log data sets, refer to “Logging while drilling,” “Lithology,” “Geochemistry,” and “Physical properties.”

Seismic reflection data

Seismic reflection data acquisition along the NanTroSEIZE transect consisted of two phases. The Kumano 3-D data set acquisition was contracted with Petroleum Geo-Services (PGS) in 2006, covering an area ~12 km × 56 km that extends seaward (in the dip direction) from the Kumano Basin to the frontal thrust and extends from ~4 km northeast to ~8 km southwest perpendicular to the NanTroSEIZE drilling transect (Moore et al., 2009). The IFREE 3-D data set was acquired by the JAMSTEC vessel R/V Kairei also in 2006, covering an area 3.5 km × 52 km that extends seaward from the frontal thrust region to the southern edge of Kashinosaki Knoll (Fig. F1 in the “Expedition 338 summary” chapter [Strasser et al., 2014a]; Park et al., 2008; Expedition 322 Scientists, 2010b).

Seismic processing of the Kumano 3-D data set consisted of three stages (Moore et al., 2009). In the first stage, PGS provided 3-D stack and poststack migration to better understand the regional seismic reflection characteristics for choosing parameters for more detailed processing. During the second stage, Compagnie Générale de Géophysique (CGG) in Kuala Lumpur, Malaysia, processed the data set through 3-D prestack time migration (PSTM). Variable streamer feathering and strong seafloor multiples required several processing steps to fill and regularize all of the bins and provide quality imaging. The third stage consisted of 3-D prestack depth migration (PSDM) performed at JAMSTEC IFREE. The 3-D PSDM clearly images details of faults and small-scale structures but lacks velocity resolution deeper than ~4500–5000 m, near the oceanic basement. Vertical resolution (i.e., λ/4) is ~5–7 m for the shallowest subseabed sediment, ~10–20 m for the deepest sediment drilled so far in NanTroSEIZE, and ~90–125 m at the top basement surface. The IFREE 3-D data volume was also processed through PSTM and then PSDM at IFREE (Park et al., 2008).

Integration with cuttings, core, and log data

Specific intervals in the 3-D seismic data sets were examined where complementary cuttings, cores, or log data were available. For Expedition 338, this meant, explicitly,

  • Relating prominent seismic reflections and packages of distinct seismic reflectivity to variations in lithology, unit boundaries, unconformities, or layers with distinct physical and/or geochemical properties;
  • Correlating zones of low P-wave velocity in the seismic data with mud gas occurrence (riser Hole C0002F) or variations in resistivity and other parameters from LWD data; and
  • Linking prominent fault zone reflections (where present) to areas of broken formation in cores, high conductivity in image logs, high density/low porosity in cores and cuttings, and/or age reversals or age gaps defined by biostratigraphy.

Direct comparisons were made between all of the available data using Paradigm’s SeisEarth, Schlumberger’s Petrel, and the Generic Mapping Tools (GMT) (Wessel and Smith, 1998) to enable an overall assessment and integration of the unit boundaries and internal features determined during the analysis of each independent data set.