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                RAVVA
    Celebrating 16 Years of Technical Excellence

    Innovating Development | 3D Geocellular Model
Ravva | Innovating Development


Ravva 3D Geocellular Model

Building geological models is one of the most
important phases in field development. The static
description both in terms of geometry and
petrophysical properties coupled with structural
parameters and fluid contacts are the most critical
factors used to develop the field optimally and
improve recovery from the reservoirs. The primary
goal of building a static model is to capture the
subsurface heterogeneity both vertically and
horizontally at the well and field scale, which can
be used as a tool for accurate estimation of
hydrocarbon in-place, well planning, field
development planning, and reservoir management for optimum recovery.

Seismic data contains a wealth of information about the reservoir properties between the wells, and also
away from the well locations. Well data and seismic data are complementary to each other. Well data has
a very high vertical resolution, while the seismic data has higher spatial resolution. The combination of
well data and seismic characters help in representing the reservoir in 3D space more accurately
particularly between the well and away from the well. The variation in the lithological and petrophysical
characteristics and fluid content of the reservoir rock has an impact over the recorded seismic signal and
this is used to interpret rock characteristics during inversion.

The middle Miocene reservoirs such as M20, M30, M32, M33 and M34 are the main reservoirs producing
in the RAD and REFB blocks of the Ravva Field. The 3D static geocellular model building activity was
carried out in 2004 for the first time for middle Miocene reservoirs of Ravva. Fine scale geocellular models
were developed for both the blocks, RAD and REFB, based on structural inputs from the reservoir
mapping of new 3D seismic data. The model has indicated upside potential of the field EUR of 255 MMstb
and was used for planning and drilling infill development wells, which were drilled during the 2006-2008
period.

In 2008, the 3D Geocellular Model was revised by integrating all geoscientific information from newly
drilled wells along with core data from RD-7. In this revision, stochastically inverted properties derived
from 3D OBC seismic data were used for the first time in the reservoir model to capture the reservoir
details with a greater accuracy. The basic idea behind using inverted seismic data is to guide the
distribution of the reservoir parameters between the wells. The main subsurface uncertainties in building
3D geocellular reservoir models are addressing structural and petrophysical uncertainty. Integrating the
stochastically inverted reservoir characterisation in reservoir modeling approach leads to reduced
variance among the geo-statistical realisations and reduces overall uncertainty. As the model more
accurately matches both well and seismic data, history matching can usually be achieved more quickly
than with traditional geostatistical based 3D models. The revised models show a further upside potential
of EUR of 278 MMstb from the field.


The models were then upscaled for reservoir simulation studies. The history matched reservoir model
could then be used to plan further development opportunities in the field.

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Ravva | 3D Geocellular Model

  • 1.                           RAVVA Celebrating 16 Years of Technical Excellence Innovating Development | 3D Geocellular Model
  • 2. Ravva | Innovating Development Ravva 3D Geocellular Model Building geological models is one of the most important phases in field development. The static description both in terms of geometry and petrophysical properties coupled with structural parameters and fluid contacts are the most critical factors used to develop the field optimally and improve recovery from the reservoirs. The primary goal of building a static model is to capture the subsurface heterogeneity both vertically and horizontally at the well and field scale, which can be used as a tool for accurate estimation of hydrocarbon in-place, well planning, field development planning, and reservoir management for optimum recovery. Seismic data contains a wealth of information about the reservoir properties between the wells, and also away from the well locations. Well data and seismic data are complementary to each other. Well data has a very high vertical resolution, while the seismic data has higher spatial resolution. The combination of well data and seismic characters help in representing the reservoir in 3D space more accurately particularly between the well and away from the well. The variation in the lithological and petrophysical characteristics and fluid content of the reservoir rock has an impact over the recorded seismic signal and this is used to interpret rock characteristics during inversion. The middle Miocene reservoirs such as M20, M30, M32, M33 and M34 are the main reservoirs producing in the RAD and REFB blocks of the Ravva Field. The 3D static geocellular model building activity was carried out in 2004 for the first time for middle Miocene reservoirs of Ravva. Fine scale geocellular models were developed for both the blocks, RAD and REFB, based on structural inputs from the reservoir mapping of new 3D seismic data. The model has indicated upside potential of the field EUR of 255 MMstb and was used for planning and drilling infill development wells, which were drilled during the 2006-2008 period. In 2008, the 3D Geocellular Model was revised by integrating all geoscientific information from newly drilled wells along with core data from RD-7. In this revision, stochastically inverted properties derived from 3D OBC seismic data were used for the first time in the reservoir model to capture the reservoir details with a greater accuracy. The basic idea behind using inverted seismic data is to guide the distribution of the reservoir parameters between the wells. The main subsurface uncertainties in building 3D geocellular reservoir models are addressing structural and petrophysical uncertainty. Integrating the stochastically inverted reservoir characterisation in reservoir modeling approach leads to reduced variance among the geo-statistical realisations and reduces overall uncertainty. As the model more accurately matches both well and seismic data, history matching can usually be achieved more quickly than with traditional geostatistical based 3D models. The revised models show a further upside potential of EUR of 278 MMstb from the field. The models were then upscaled for reservoir simulation studies. The history matched reservoir model could then be used to plan further development opportunities in the field.