Giving priori predictions (Taylor et al. 2010, Morad et

Giving us, a sound
understanding of the main controlling factors of many diagenetic processes. Reservoir
quality and heterogeneity of a buried sandstone is mainly controlled by four factors:
(1) depositional composition and internal structure which is strongly
influenced by depositional facies and climate, (2) the depositional porosity
and permeability which are strongly influenced by sorting, grain size, grain shape
and sand/mud ratio (3) the degree of mechanical and chemical compaction; and (4)
the amount and type of pore-filling cement (Worden et al. 2000, Morad et al.
2012). Therefore, all observed
values of reservoir porosity and permeability should be predictable as a
logical consequence of depositional, early diagenetic, and late diagenetic
processes.  Allowing to accurately
predictic where a particular combination of grain size, sorting, rock composition,
early diagenesis, and burial history have acted together to minimize the adverse
effects of compaction and cementation and preserve the greatest amount of
porosity and permeability at depth (Ajdukiewicz et al. 2010).  

Predicting of Reservoir ‘sweet spots’ became a goal of the
petroleum industry in the 1980-1990 (Worden wt al. 2000). In the Past reservoir
quality models have ben based on different scientific principles (e.g. Porosity
depth trends, kinetic geochemical models, thermodynamics) that all have
significant limitations weather it be because statistical correlations as
used in Porosity depth trends can only be
applied effectively to samples close to the observation or to samples of
similar composition and depositional history or because many geochemical models
rely exclusively on laboratory derived data to describe the rate of geochemical
reactions in nature. The latest reservoir quality models have learned from previous
approaches as in that they now use high-quality petrographic data that is liked
to certain geological processes and conditions (e.g. cement generation, timing
of dissolution processes) to calibrate the model and therefor provides an essential
constraint in these models on the types, timing, and rates of key geologic
processes affecting sandstone pore systems (Ajdukiewicz
et al. 2010).

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But even though over the last
40-years reservoir quality and heterogeneity predictions have made enormous
strides, predicting reservoir quality for deeply buried sandstones, remains a major
challenge for geoscientists in the petroleum industry showing the need to find more accurate ways
to identify the key model inputs that drive reservoir quality and heterogeneity
in different geological settings (Taylor et al. 2010). One of the main challenges remaining is that
research has identified various sedimentological and geochemical conditions
that favor or negatively influence the preservation of porosity and
permeability (e.g. chlorite grain coatings, Carbonate cements), but they cannot
be independently predicted which is particularly true for more complex systems
that are affected by early diagenetic features like grain coatings, carbonate
cements, secondary porosity. Today these features are included in current
reservoir models through observations and analogs rather than priori
predictions (Taylor et al. 2010, Morad et al. 2010, Ajdukiewicz et al. 2010).
This highlights the incomplete understanding of the controlling factors of
reservoir heterogeneity.

 

Giving us, a sound
understanding of the main controlling factors of many diagenetic processes. Reservoir
quality and heterogeneity of a buried sandstone is mainly controlled by four factors:
(1) depositional composition and internal structure which is strongly
influenced by depositional facies and climate, (2) the depositional porosity
and permeability which are strongly influenced by sorting, grain size, grain shape
and sand/mud ratio (3) the degree of mechanical and chemical compaction; and (4)
the amount and type of pore-filling cement (Worden et al. 2000, Morad et al.
2012). Therefore, all observed
values of reservoir porosity and permeability should be predictable as a
logical consequence of depositional, early diagenetic, and late diagenetic
processes.  Allowing to accurately
predictic where a particular combination of grain size, sorting, rock composition,
early diagenesis, and burial history have acted together to minimize the adverse
effects of compaction and cementation and preserve the greatest amount of
porosity and permeability at depth (Ajdukiewicz et al. 2010).  

Predicting of Reservoir ‘sweet spots’ became a goal of the
petroleum industry in the 1980-1990 (Worden wt al. 2000). In the Past reservoir
quality models have ben based on different scientific principles (e.g. Porosity
depth trends, kinetic geochemical models, thermodynamics) that all have
significant limitations weather it be because statistical correlations as
used in Porosity depth trends can only be
applied effectively to samples close to the observation or to samples of
similar composition and depositional history or because many geochemical models
rely exclusively on laboratory derived data to describe the rate of geochemical
reactions in nature. The latest reservoir quality models have learned from previous
approaches as in that they now use high-quality petrographic data that is liked
to certain geological processes and conditions (e.g. cement generation, timing
of dissolution processes) to calibrate the model and therefor provides an essential
constraint in these models on the types, timing, and rates of key geologic
processes affecting sandstone pore systems (Ajdukiewicz
et al. 2010).

We Will Write a Custom Essay Specifically
For You For Only $13.90/page!


order now

But even though over the last
40-years reservoir quality and heterogeneity predictions have made enormous
strides, predicting reservoir quality for deeply buried sandstones, remains a major
challenge for geoscientists in the petroleum industry showing the need to find more accurate ways
to identify the key model inputs that drive reservoir quality and heterogeneity
in different geological settings (Taylor et al. 2010). One of the main challenges remaining is that
research has identified various sedimentological and geochemical conditions
that favor or negatively influence the preservation of porosity and
permeability (e.g. chlorite grain coatings, Carbonate cements), but they cannot
be independently predicted which is particularly true for more complex systems
that are affected by early diagenetic features like grain coatings, carbonate
cements, secondary porosity. Today these features are included in current
reservoir models through observations and analogs rather than priori
predictions (Taylor et al. 2010, Morad et al. 2010, Ajdukiewicz et al. 2010).
This highlights the incomplete understanding of the controlling factors of
reservoir heterogeneity.

 

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