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Abstract
Petroleum
Migration Using Invasion Percolation Techniques
3.
Modeling of Secondary
Petroleum
Migration Using Invasion Percolation Techniques
Daniel J. Carruthers
1Permedia Research Group Inc., Ottawa, Ontario, Canada
ACKNOWLEDGMENTS
I would like to acknowledge and thank the following companies for their continued support of this research: ENI Agip Division, BG Technology, BP, Conoco, Norsk Hydro, Shell, and Statoil.
I would also like to thank Norsk Hydro and BG Technology for permission to publish Figure 16 and Figure 19, respectively, and the Genetic Units Project at Heriot-Watt University for use of their outcrop data in creating the model depicted in Figure 18.
I would also like to acknowledge the valuable input of my colleague, Mike de Lind van Wijngaarden, for making these modeling tools as fast (and as accurate) as they are.
ABSTRACT
At the timescales associated with secondary migration, the balance between the gravity and the capillary forces (i.e., the Bond number) overwhelmingly controls the trajectories and characteristics of hydrocarbon flows. At these low flow rates, viscous forces are negligible and can effectively be ignored. From a practical standpoint, this means that techniques used for modeling
petroleum
flows at production timescales introduce computational overkill and may in fact be entirely inappropriate for solving the
petroleum
migration problem.
New invasion-percolation (IP)-based techniques have been developed that take advantage of the special force regime of
petroleum
migration (IP is based on the premise that flow in porous media can be represented by an invasion through a matrix of pores and throats represented by threshold pressures or probabilities; invasion occurs along the
fluid
front by accessing the "pore" with the smallest threshold pressure). The result of this work is the capability to simulate one-phase, constant-composition
petroleum
flow in models containing tens of millions of grid cells in a matter of minutes, while honoring the mechanics of migration transport. Because the calculation is so fast, these simulations may be extended beyond the transport problem to include other, more time-intensive calculations with very little loss in overall simulation performance.
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