Synthesizing Outcrop Data to Develop Vertical Facies Proportion Curves That Capture the Internal Variability of Depositional Elements

Abstract

Stratigraphic measured section data collected from outcropping deposits is typically used for describing reservoir properties of sedimentary successions. Such data is increasingly being coupled with UAV-based Structure-from-Motion digital terrain models (DTMs) to quantify the dimensions of sedimentary bodies, as well as capture length scales and spatial relationships of facies distributions within and between depositional bodies. These robust characterizations are: 1) supporting interpretations of formative sedimentary processes; 2) aiding better quantification of stratigraphic architecture; and 3) providing statistical constraints that help reduce uncertainty in subsurface prediction.

We present a method that utilizes measured section data within interpreted stratigraphic frameworks from DTMs to quantify facies distributions. The results are outcrop-constrained vertical facies proportion curves (VFPs) defined by their position within a depositional element (e.g., channel axis or margin). The VFPs capture the fundamental nature of heterogeneity within depositional elements and provide a basis for comparing internal element architecture across and between depositional environments. For example, fluvial channel belts exhibit high probabilities of flow barriers at the tops of sedimentary packages while deep-water counterparts reveal flow barriers at the margins and bases. Furthermore, VFPs can be used to define the probability of flow connectivity between depositional packages as a function of package thickness or stacking pattern. Proportion curves also serve as input constraints for subsurface sector models, which are used to elucidate the impacts of bed-scale stratigraphic architecture on fluid flow.

Extracting statistical data from outcrops is becoming routine in comprehensive stratigraphic characterization of sedimentary systems – these data are critical for optimizing transfer of sedimentological information into predictive subsurface models for hydrocarbon recovery. DTMs, when coupled with measured section data, enhance and support correlations and hierarchical interpretations of strata, and enable comparison within and across deposits from various depositional settings. To date, simplistic workflows and tools to integrate field data, DTMs and active interpretations and analyses are still lacking, our analysis provides an important step forward to demonstrate where the science of quantitative stratigraphy is heading.

AAPG Datapages/Search and Discovery Article #90323 ©2018 AAPG Annual Convention and Exhibition, Salt Lake City, Utah, May 20-23, 2018