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To mitigate and manage such scenarios, the modern workflows optimize field recovery
performance by combining major disciplines of reservoir geosciences,
e.g.
geology,
geophysics and petrophysics with numerical simulations into integrated flow models for a
variety of field development operations. To maximize reservoir profitability, quantification
of the effect of stratigraphic and structural uncertainties on its dynamic performance
becomes of principal importance (Charles
et al.
, 2001; Seiler
et al.
, 2009). However, it
continues to be an issue in geological modeling that the underlying structural frameworks
do not correctly portray the true reservoir structure configuration or size, and this
uncertainty impacts an accurate evaluation of hydrocarbon gross volumes. It is therefore
essential to validate accordingly the role of individual components of high-resolution
geological model (HRGM; see Fig. 1) and rank their impact on the uncertainty of HRGM at
various levels (Fig. 1).
Structural model
defines gross volumes
Structural model
defines gross volumes
Structural model
defines gross volumes
Uncertainty impact
Uncertainty impact
Structural
Model
Structural
Model
Structural
Model
Structural
Model
Higher
Higher
Stratigraphic
Model
Stratigraphic
Model
Stratigraphic
Model
Stratigraphic
Model
Stratigraphic model
layering controls lateral connectivity
variogram range controls vertical connectivity
Stratigraphic model
layering controls lateral connectivity
variogram range controls vertical connectivity
Stratigraphic model
layering controls lateral connectivity
variogram range controls vertical connectivity
Facies
Model
Facies
Model
Facies
Model
Facies
Model
High Resolution
Geological Model
High Resolution
Geological Model
High Resolution
Geological Model
High Resolution
Geological Model
High Resolution
Geological Model
Facies model
controls depositional continuity
Facies model
controls depositional continuity
Facies model
controls depositional continuity
(HRGM)
(HRGM)
(HRGM)
(HRGM)
(HRGM)
Petrophysical
Model
Petrophysical
Model
Petrophysical
Model
Petrophysical
Model
Lower
Lower
Petrophysical model
defines property distribution
Petrophysical model
defines property distribution
Petrophysical model
defines property distribution
Fig. 1. Generation of High-resolution Geological Model, schematic depiction. The central
panel outlines the role of individual phases in overall workflow sequence, with the impact
on overall modeling uncertainty ranked to the right.
This paper focuses on recent advances in the technology for building high-resolution,
geocellular models and its role in state-of-the-art and future EOR workflows. We first
introduce some very basic tools and concepts of geostatistical spatial analysis and modeling,
relevant for further understanding of the subject. Furthermore, we highlight what are
perceived as some of the outstanding capabilities that differentiate the DecisionSpace
Desktop Earth Modeling, as the next-generation geological modeling tool, from standard
industrial approaches and workflows. Current geomodeling practice uses grids to represent
3D reservoir volumes. Estimating gridding parameters is a difficult task and commonly
results in artifacts due to topological constraints and misrepresentation of important aspects
of the structural framework which may introduce substantial difficulties for dynamic
reservoir simulator later in the workflow. We describe a fundamentally novel method that
has a potential to resolve most of the common geocellular modeling issues by implementing
the concept of interpolation or simulation of reservoir properties using Local Continuity
Directions (Yarus
et al.
, 2009; Maučec
et al.
, 2010). Finally, we address some latest
developments in the integration of next-generation geological modeling into advanced
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