Transcript Enhanced Oil Recovery using Couple Electromagnetics and Flow

Enhanced Oil Recovery using Coupled Electromagnetics and
Flow Modelling
E. Haber, UBC ([email protected])
E. Holtham Computational Geosciences Inc
([email protected])
INTRODUCTION
FLOW and ELECTROMAGNETICS
Enhanced Oil Recovery (EOR) is a process in which gas or fluid is injected into a reservoir in
order to push oil into a production well. A sketch of this process is shown below. There are
several aspects for such a process. One of the most important issues is the ability to control
the flow and direct it into the direction that would lead to the recovery of crude oil.
In principle, the flow of water/gas/oil can be modeled using variety of techniques and
therefore, the flow can be predicted. However, in practice, the flow equations contain
parameters that are unknown and therefore, prediction is difficult and in many cases, highly
inaccurate.
Injection Event
porosity
hydraulic conductivity
capillary pressure
mobility functions
initial conditions1
Update next
injection events
to improve
recovery
Flow modelling
as initial
prediction of
fluid movement
Improved
understanding
of fluid and oil
movement
EM survey
design and data
collection
3D EM inversion
incorporating
flow constraints
Enhanced Oil Recovery: Water and CO2 are flooded
through an injection well. The CO2 mobilizes additional oil
that can be recovered at a production well. Figure from the
Kansas Geological Survey.
• Layered conductive model with a thin resistive reservoir.
• Grounded electrodes, one end down the bore-hole and the other
end grounded 2km away
• Transmitter position moved in 7.5 m increments along the bore-hole
• Current injection below the reservoir, inside the reservoir, and
above the reservoir.
• Synthetic data at four different time steps of the injection process
were modeled.
• Data inverted in 3D
1 km
Initial
5 days
10 days
15 days
Inverted conductivity models at different time steps
CONCLUSIONS
Simulations of a flooding event were modeled using geologic and hydraulic
parameters of an oil field. The flow simulations demonstrate the capability to
accurately predict the movement of CO2 in the reservoir given a good
estimate of the hydrological parameters of a reservoir. To enhance the EM
inversion results, the outputs of the flow simulation software were used as
constraints for the electromagnetic inversions. Once the constraint model was
constructed, the data were inverted in 3D. The changes in the inverted
conductivity models image the injection event over time. Given a sufficient
conductivity difference between the different CO2 injection time steps, along
with an appropriate survey geometry, the modeling results demonstrate that
EM methods are feasible for monitoring oil recovery processes.
To alleviate this problem and to better control the flow, imaging can be used. In particular,
remote time lapse monitoring of reservoirs can provide valuable information to meet
production goals. Remote monitoring requires technology that can detect movement and
changes in the reservoir during production and flooding events. Flooding events can be
modeled and monitored. Here we present a methodology combining flow simulation
software and electromagnetic data that can yield accurate control of the flow. First the
injection event is simulated to predict the fluid flow. This information is then used as a
constraint when inverting the collected geophysical data. The combination of flow
simulation and electromagnetic data inversion provides an enhanced monitoring
technique for reservoir characterization.
FLOW Modelling
REFERENCES
Modeling the flow can be done by using the pressure-saturation equations. This is a
highly coupled systems of PDE's. Here, we consider the formulation suggested by Friis
and S. Evje (2012).
•
•
•
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Discretize the equations in space first using a cell-centered controlled volume
Integrate in time using Implicit Pressure Explicit Saturation (IMPES) algorithm
First solve the pressure equation to compute velocity
Integrate the hyperbolic equation for the saturation using an implicit upwind
method
• Yields an effective flow simulator that can be used for electromagnetic inversion
EM MODELLING
Time lapse images of the injection using the flow simulation software
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