**Evaluation of Sealing Properties to Faults and Cap Rocks and its Influence on Fluid Pressure Distribution - Using a Monte Carlo Simulation Approach**

**Ane E. Lothe and Arnt Grøver**

*SINTEF Petroleum Research, Trondheim, Norway*

During the last years more focus has been set on quantification of uncertainties in pressure and basin modelling, this is due to larger computer utilities. One is able to calculate the range of possible outcome for larger study areas and more complex geological models.

The water fluid pressure build up in a sedimentary basin is mainly dependent on the sealing properties to the cap rock (often shales) for the vertical fluid flow, and of the fault properties for the lateral fluid flow between pressure compartments. The vertical fluid flow can be calculated using explicit numerical solution of the Darcy flow equation, where the Kozeny-Carman is used to define the relation between porosity and permeability. The fault seal capacity is related to percentage of sand/clay in a sequence that has been faulted past a point on a fault, termed the Shale Gouge Ratio (SGR). By using SGR values on the model fault surfaces calculated from fault throw and volume shale logs (Vsh), can fault permeability and fault transmissibilites be calculated (Lothe et al. 2008). The pressure build up is simulated over geological time scale, using a pressure simulator named PRESSIM. The numerical solution employs the “Forward Euler” technique, which is stabilized by using minimum volume during dissipation.

As outlined in Sylta & Krogstad (2003) and Sylta (2004), 3D basin simulations can be carried out with a Monte Carlo simulation loop. The same methods can be used to simulate pressures (Lothe & Tømmerås 2006).

In this work we will vary the input parameters and try to quantify the uncertainty in the input, and thereby see the spread in the resulting simulated pressure distribution. We will run a large number of simulations and test systematically which parameters have the largest effect on the pressure build up and the magnitude of uncertainties that can be expected. The pressure prediction will be compared with measured pressures from wells in the area.

**References:
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Sylta, Ø. 2004: A probabilistic approach to improved geological knowledge and reduced exploration risks using hydrocarbon migration modelling. Petroleum Geoscience, 10, 187-198.

Sylta, Ø. and W. Krokstad 2003: Estimation of oil and gas column heights in prospects using probabilistic basin modelling methods." Petroleum Geoscience, 9, 243-254.

Lothe, A.E. & Tømmerås, A. 2006: Stochastic Monte-Carlo simulations of overpressure probability distribution in the Halten Terrace area, AAPG Conference, Perth, November, 2006.

Lothe, A.E., Tømmerås, A. & Helset, H.M. 2008: Clay smear (SGR) along faults and the implications on water flow and fluid overpressures. AAPG Conference, Cape Town, October 2008.

AAPG Search and Discovery Article #90091©2009 AAPG Hedberg Research Conference, May 3-7, 2009 - Napa, California, U.S.A.