Water influx into gas fields can reduce recovery factors by 10 - 40%.
Therefore, information about the magnitude and spatial distribution of water
influx is essential for efficient management of waterdrive gas reservoirs.
Modern geophysical techniques such as gravimetry may provide a direct measure
of mass redistribution below the surface, yielding additional and valuable
information for reservoir monitoring.
In this paper, we investigate the added value of gravimetric observations
for water-influx monitoring into a gas field.
For this purpose, we use data assimilation with the ensemble Kalman filter
(EnKF) method. To understand better the limitations of the gravimetric
technique, a sensitivity study is performed. For a simplified gas-reservoir
model, we assimilate the synthetic gravity measurements and estimate reservoir
permeability. The updated reservoir model is used to predict the water-front
position. We consider a number of possible scenarios, making various
assumptions on the level of gravity measurement noise and on the distance from
the gravity observation network to the reservoir formation. The results show
that with increasing gravimetric noise and/or distance, the updated model
permeability becomes smoother and its variance higher. Finally, we investigate
the effect of a combined assimilation of gravity and production data. In the
case when only production observations are used, the permeability estimates far
from the wells can be erroneous, despite a very accurate history match of the
data. In the case when both production and gravity data are combined within a
single data assimilation framework, we obtain a considerably improved
estimation of the reservoir permeability and an improved understanding of the
subsurface mass flow. These results illustrate the complementarity of both
types of measurements, and more generally, the experiments show clearly the
added value of gravity data for monitoring water influx into a gas field.
© 2011. Society of Petroleum Engineers
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- Original manuscript received:
2 September 2010
- Revised manuscript received:
16 April 2011
- Manuscript approved:
29 April 2011
- Published online:
5 October 2011
- Version of record:
13 March 2012