Unravelling the Triassic Mungaroo Formation within North Carnarvon Basin using Regional Stratal Slice Volumes

Chevron has developed a new method for viewing, rendering and interpreting multiple, proportionally-flattened seismic surveys (US patent). The products of this method are referred to as Regional Stratal Slice Volumes (RSSVs). Within the Northern Carnarvon Basin (NCB), local RSSVs contain a patchwork of 22 3D seismic surveys covering an area of approximately 68 000 km2 and comprising a 4+ km-thick succession of alluvial to shallow-marine deposits of the Late Triassic Mungaroo Formation. Seismic slices for each constituent volume were spliced together, correlated with adjacent volumes and combined with supporting structural, cultural and well-based data. This has created a temporal series of unbroken, regionally-extensive, seismic snapshots which, when viewed successively, capture the evolving geomorphology and palaeogeography of the basin from east of Gorgon and Wheatstone out to the Exmouth Plateau. Through the integration of the RSSVs and well data, the shoreline and marginal marine to non-marine transitions were identified and accurately mapped at an approximately 20 m vertical spacing throughout the Mungaroo Formation. This work resulted in an in-depth understanding of changing depositional environments at a regional scale. Observed, temporally-systematic fluctuations of the shoreline on the RSSVs provide a highly predictive stratigraphic framework for the basin. Additionally, RSSVs have been used to provide insight into regional NCB studies and to support localised prospect and field scale evaluations. Over the past three years, RSSVs combined with automatically generated closures have been used to identify significant additions to Chevron’s prospect portfolio.

Thickness imaging for high-resolution stratigraphic interpretation by linear combination and color blending of multiple-frequency panels

Despite routine demand from petroleum explorationists and field developers, interpreting (inverting) seismic data for reservoir thickness from acoustic impedance (AI) or lithology volume requires a high-quality, unbiased well database and the special skills of elite geophysicists. I have developed a new method, based on linear combination and color blending of multiple-frequency panels, to estimate AI and thickness without the strict implementation of complex mathematics and extensive well control. Aimed at readjusting the thin-bed tuning effect in a formation of normal thickness range (up to [Formula: see text]; [Formula: see text] = dominant wavelength), a linear combination of three frequency panels from [Formula: see text] data would lead to a reasonable visual match between a sandstone (shale) body and its seismic event, should the combined amplitude spectrum roughly match the AI spectrum. A red-green-blue blending of frequency panels further extends the interpretive benefits by illustrating the thickness in color, adding a sense of thickness cyclicity on the vertical view and that of sandstone thickness map on stratal-slice view. Tests using a simple wedge model and a complex, geologically realistic multi-thin-bed model demonstrate that the proposed workflow may achieve decent geometry (thickness) estimation and reasonably high correlation ([Formula: see text]) for AI prediction with minimal or no well control. The results are similar to colored inversion in the fast-track principle, with improved stability and less error (at least in this study). More complex procedures — such as linear regression and model-based inversion — may lead to minor to moderate improvement with adequate well control. An application to a field data set confirmed the value of the methods in high-resolution reservoir-thickness imaging, with a strong potential for stratigraphically oriented studies, such as seismic chronostratigraphy, sequence stratigraphy, and seismic sedimentology.