Summary
Two methods for characterizing reservoir pore pressure and reservoir
permeability during UBD while applying active tests are presented and
evaluated. Both methods utilize a fast, dynamic well fluid-flow model that is
extended with a transient reservoir model. Active testing of the well is
applied by varying the bottomhole pressure in the well during the drilling
operations.
The first method uses the Levenberg-Marquardt optimization algorithm to
estimate the reservoir parameters by minimizing the difference between
measurements from the drilling process and the corresponding model states. The
method is applied after the drilling process is finished, using all the
recorded measurements. The second method is the
ensemble Kalman filter, which simulates the drilling process using the
dynamic model while drilling is performed, and updates the model states and
parameters each time new measurements are available. Measurements are used that
usually are available while drilling are used, such as pump rates, pump
pressure, bottomhole pressure, and outlet rates.
The methods are applied to different cases, and the results indicate that
active tests might improve the estimation results. The results also show that
both estimation methods give useful results, and that the ensemble Kalman
filter calculates these results during the UB operation.
Introduction
During UBD, the well pressure is kept below the reservoir pore pressure, and
reservoir fluids flow into the well. The flow rate from the reservoir depends
on the pressure difference between the reservoir pore pressure and the well
pressure, in addition to other reservoir parameters, such as permeability and
porosity. The viscosity and compressibility of the reservoir fluids also
influence the influx rate.
The influx of reservoir fluids causes variations in the annulus section of
the well, because of changes in well fluid composition and well fluid-flow
rate. By measuring some of the fluid-flow parameters of the well, such as
pressures changes and rate changes, the reservoir parameters causing the influx
might be identified. This is the principal idea that also is the basis for well
testing and transient reservoir analysis. Identification of the reservoir
properties close to the well gives important information for planning the
well-completion design. If highly productive zones can be located, then the use
of smart completion can be better utilized.
Reservoir characterization during UBD has received attention from several
research groups in recent years. Kardolus and van Kruijsdijk (1997) developed a
transient reservoir model based on the boundary-element method. This model was
compared with a transient analytical reservoir model. One of their findings was
that the transient analytical reservoir model could be used for evaluation of
the parameters in the reservoir. In a following study, van Kruijsdijk and Cox
(1999) presented a method for identifying the permeability in a horizontal
reservoir based on measurements of the reservoir inflow. The flow effects
caused by the reservoir boundaries were included in the flow calculations.
© 2006. Society of Petroleum Engineers
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History
- Original manuscript received:
26 August 2003
- Revised manuscript received:
26 May 2005
- Manuscript approved:
29 November 2005
- Version of record:
20 June 2006
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