--> Impact of Reservoir Anisotropy in the Volumetric Quantification of Marlim Oilfield, Zagotto, Eric; Fernandes, Flávio; Rostirolla, Sidnei; Araújo, Armando; Landau, Luiz , #90100 (2009)

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Impact of Reservoir Anisotropy in the Volumetric Quantification of Marlim Oilfield

Zagotto, Eric1
 Fernandes, Flávio1
 Rostirolla, Sidnei1
 Araújo, Armando1
 Landau, Luiz2

1GEEXP, Vale E&P, Rio de Janeiro, Brazil.
2
COPPE, Universidade Federal do
Rio de Janeiro, Rio de Janeiro, Brazil.

During the lifetime of a hydrocarbon field an accurate geological model shows up as a fundamental tool to predict its fluid behavior as well as to perform its volumetric evaluation. The biggest challenge in building a geological reservoir model is represented by the mapping of structural and stratigraphic architectural elements in space, such as their facies and stratigraphic discontinuities, seismic and subseismic faults, hydrodynamic anisotropy and petrophysical properties related to primary and secondary basin evolution processes.

Using the Marlim Oilfield reservoir as an example of this work, we demonstrate several methodological approaches to define the distribution of facies and petrophysical properties along the reservoir and their implications in the hydrocarbon volume calculation and its uncertainties.
The Marlim Oilfield was discovered in 1985 and is located on the central-eastern sector of the
Campos Basin. It represents the largest Brazilian production oil field, containing approximately 6.4 billion STB (Oliveira et al., 2005). The producing reservoir is composed of Upper Oligocene sandstones deposited in a large and complex submarine fan system, comprising a set of individual lobes with great lateral extension (Guardado et al., 1989).

The reservoir model construction starts with the reservoir top and base seismic mapping. After that, a facies is recognized using neural networks on the wells, and, after several “practices”, the facies that best fits the geological model are selected and classified. Once this classification has been finished, the facies data is extrapolated within the reservoir using a stochastic algorithm oriented to pixel, embedded in Petrel software (Schlumberger). Following the facies distribution process, the petrophysical attributes calculated from the logs and associated with the facies are previously classified, and are distributed in the reservoir area, also using a stochastic algorithm oriented to pixel. Once the oil-water contact is determined, it is possible to determine an in-place hydrocarbon volume.

In addition, it is known that all the factors above have uncertainties. Considering this premise, this work also presents an analysis of uncertainties about the factors that control the Marlim Oilfield architecture, resulting in a more accurate geological reservoir model and thus a more controlled hydrocarbon volume quantification.

AAPG Search and Discover Article #90100©2009 AAPG International Conference and Exhibition 15-18 November 2009, Rio de Janeiro, Brazil