Avoid early optimization
Make sure your model captures the essential features of the reservoir.
You don't need a fine details model to verify the correctness and accuracy
of your reservoir characterization. Fine details take a lot of effort and
time, and won't fix the model if key features were not properly caught.
Check if your model does not miss key physical concepts.
Model Net to Gross
Not all geo-modeling software allows you to easily model the Net to Gross
value for each 3D cell, GeolOil does.
Unless you have an extremely high
vertical resolution 3D grid, your Net to Gross for each cell should be
a number between 0.0 and 1.0, rather than exactly zero or one.
By keeping an accurate Net to Gross model, you can easily verify
storage petrophysics properties (porosity and water saturation) over
the reservoir rocks instead the cell's upscaled whole value. For instance,
if you are working with clastic heavy-oil or bitumen reservoirs, it is typical
to have porosity values around 0.25-0.32, but if the cell contains some
proportion of very shaly sands, the upscaled whole cell porosity might
be reduced to 0.15-0.24 depending upon the whole cell Net to Gross.
It is far easier and understandable to handle a joint porosity
and net-to-gross pair with values of 0.30 and 0.70 than to handle a single
upscaled porosity cell value of 0.21 with an implicit net-to-gross of 1.0.
Furthermore, if you a have a client request to change the petrophysical
VCL threshold cutoff, you will see immediately how the net-to-gross
ratio is affected.
You don't have to reproduce legacy values of former reservoir volumetrics,
but in many cases those old volumetrics reports, provide a valuable
guide to understand reservoir storage. If the legacy volumetrics report and
your current static model were built on the same lease or polygon outline,
values might be close. If they don't agree, you should ask yourself why.
Is it the porosity?, the water saturation?, the net-to-gross?, the
gross thickness?, the threshold cutoff values?
Why my simulation model forecasts so much water?
This is very typical. Even after a carefully built 3D geomodel,
the simulation forecasts too much water compared to production history.
Why?, you have build several shaly SW water saturation models, Simanduoux,
Fert, etc., and all yield high water saturation.
There are limitations to the shaly sand water saturation models. If that
if your case, you could try to adjust a cation-exchange water saturation
model instead, but then you can not estimate its parameters with log data alone.
In other cases, even if special carbon-oxygen logs are ordered,
they report also a lot of water.
If you don't have reliable core SW water saturation lab measurements to calibrate
your logs, and all petrophysical analysis, Rw and sensibilities point to a
high water saturation, consider to review the relative permeability curve to
the water (as one client from Thailand have suggested us).
Where did you get the relative permeability curves your are using in
the simulator?. Are they reliable?. Did you get them from a reputable
laboratory or published literature?. If you don't have a trusted source
for the relative perm curves, then you could try to perform sensibilities
on then. For instance, you can keep the same endpoints, and specifically
the same irreducible water saturation and yet achieve different water production
forecasts by just keeping the water relative perm curve close to the origin
while honoring a fixed SWirr.
Other approach could also be to handle several simulation rock type zones
include file (different relative perm indexes) for different lithologies,
instead of using a single, unique relative perm set of curves throughout
the reservoir. The GeolOil scripting language
used in the technology screening module
allows you to define and compute your own rock types, based on combinations
of petrophysical properties. You may for example, classify the reservoir
rock into a factorial combination of two levels of Vclay and two levels of
porosities, to define a set of four rock types, each one with a relative
perm curve, then GeolOil will yield you a 3D grid include file with the four
rock types 1,2,3 and 4.
The static geo-cellular model should be a dynamic one!
Your geo-modeling team should work in close interaction with the
simulation engineers team throughout the project's life. It is no
longer valid to have a team of geologists and petrophycisists working
on a project for serveral months, only to discover there is no
way the geomodel passes even a basic simulation history match.
If you have to outsource the reservoir modeling studies, consider
to hire a solid consulting company that offers you a real integration of
the static and the dynamic modeling stages.
Avoid early optimization of the static modeling. Deliver a quick,
preliminary version of the geo-cellular model to the simulation
team and quickly assess its fluids production profile. Then iterate
again until a stable and consistent model is achieved.
Make sure you are using a consistent structural model
It happens all the time. You used the latest structural model provided
by a geo-phycisist, but its surface top does not pass through the
current well tops. That does not necessarily mean that the structure
model is inherently wrong.
In most of the cases, the structural model was build simply before
current wells were drilled. In other cases, the structural model
serves only as a general guide for major low res trends of the geometry.
Whatever be the case, the 3D grid has to have surfaces honoring well tops.
If you use a legacy structural model, make sure you apply smooth, gentle
surface deformations so the structural model surface passes perfectly through
the well tops. Check also for spikes, ripples and abnormal behaviours.
Is you reservoir model capturing the correct barriers to vertical flow?
It is not enough to rely on a high resolution 3D vertical model to capture
vertical barriers to flow and pressure communication. Check the cap rock
and its integrity well by well. If you have a horizontally continuous thin
shale or a very compacted carbonate, it could behave as a vertical seal,
yet it was bypassed and ignored by the 3D geo-cellular model.
You should verify carefully the vertical seals to fluid flow and pressure,
and if needed, apply correct transmissibility factors between vertically
adjacent cells to ensure a sound simulation model.
The GeolOil petrophysical summaries
module allows you to compute and interpolate coalescence and vertically
continuous shale thickness between reservoir
beds to specify transmissbilities. If you are simulating a coupled
thermal-geomechanical process, like SAGD (Steam Assisted Gravity Drainage),
take into account that shales up to 50 cm thickness (or even more),
could be dehydrated and broken under the normal thermal process operations,
allowing vertical communication.
Get the right properties for exploitation technology screening
When you study which exploitation technologies are suitable to exploit
a reservoir, you not only have to answer if a particular technology is
applicable to the reservoir, but also where in the reservoir you can apply
Make sure you got the right property. For instance, if you are screening
if a SAGD process is applicable, the key property to study is the
continuous-pay thickness, not the regular net-pay. Some packages
allows to build maps of net-pay, but GeolOil petrophysical
summaries module allows you to
compute a continuous-pay thickness, and the technology
screening module allows to compute
where in reservoir you may apply SAGD.
Check the rock wettability. Is it water or oil wet?
All reservoirs are complex. The impression that a reservoir is simple
is probably because it has not been studied in full detail.
A common example is the use of synthetic relative permeability curves
and capillary pressure curves. If someone is performing a simulation
history match production, odds are that laboratory curves are not available.
In those cases, make sure that if synthetic curves are used as replacement,
they represent the correct physics wettability. While usually many clastic
sandstone reservoir rocks are water-wet, carbonate reservoirs can be
oil-wet based. Hence the right wettability physics can improve dramatically
water history match.