Quantifying the geometry of high-continuity (relatively unconfined) sand-prone systems in deep-water sedimentary environments is important both for a better understanding of the intrinsic nature of these systems (volumetrics, stacking patterns, etc.) and for the potential application of this data to modeling the depositional characteristics of such systems for basin analysis and reservoir modeling.

A quantitative methodology is presented for defining the geometry of architectural elements within sedimentary systems. This methodology is then applied to a detailed analysis of sand-rich, deep-water systems, with examples from the late Precambrian Kongsfjord Formation, Arctic Norway, and other published outcrop and subsurface data. The efficacy of the scheme is demonstrated by its ability to discriminate effectively between reservoir architectural elements of differing scales within environments (e.g., individual beds, packets of beds) and also between environments (e.g., abyssal plain, outer-fan lobe, and submarine channel deposits). This scheme permits a quantitative, more objective, means of comparing modern and ancient, including subsurface, depositional systems.

The methodology and analysis presented here provide important geometrical and geological information on architectural elements at the subseismic, typical interwell scale. The data produced by this methodology should prove useful for reservoir production and development techniques. This methodology also should have applicability in exploration, through its application to architectural elements at the fan and basin scale. In exploration and production in deep-water clastic systems, the available data, which are commonly extremely expensive to collect, typically consist of seismic data (with high aerial but relatively poor vertical resolution) and generally few wells (with high vertical resolution but extremely low aerial resolution). Therefore, information derived from suitable outcrop analogs on the geometry of fan elements augments significantly the typically sparse available industry data from exploration and production.

In reservoir development and production, standard industry disciplines such as reservoir engineering and reservoir modeling (both deterministic and stochastic) should benefit from the approach taken in this article. This is because this article provides additional information on internal reservoir heterogeneity and architecture that is directly applicable to these disciplines. The application of standard geostatistical techniques to assess the spatial continuity of individual elements (such as variogram analysis) has the potential to further extend the results derived from this methodology and analysis.

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