About This Item
- Full text of this item is not available.
- Abstract PDFAbstract PDF(no subscription required)
Share This Item
The AAPG/Datapages Combined Publications Database
Houston Geological Society Bulletin
Abstract
Abstract: How to Lower the Migration Risk using
Basin Modeling: 3D Fluid-Flow
Chevron Energy Technology Co.
Fluid-flow modeling is in many cases the most challenging and
time-consuming task in an integrated basin modeling
approach. Because of this the chemistry and physics
are often
simplified in standard fluid-flow modeling
workflows. Compositional changes and variation
of dependent physical properties, such as
viscosities and densities, are not often taken
into account. The standard approach for
fluid-flow modeling often includes bulk
petroleum or one oil and one gas component
and using methods such as the black-oil
models for chemo-physical description.
The black-oil model is based on two pseudo
components describing predefined properties. Using predefined
properties reduces the predictive ability of fluid-flow modeling
significantly because it forces the model to a decisive (and
predefined) outcome. However, it is well known that accurate
modeling of the reservoir fluids’ densities is not only necessary
for API gravity prediction but also for break-through analysis.
Thus compositional effects cannot be neglected in general in
migration modeling.
One way to increase the predictability in fluid-flow modeling is to use multi-component description together with flash calculations to describe the fluid during all stages of migration. This analysis must include all stages of migration from expulsion, secondary migration, entrapment and breakthrough to dismigration.
This talk will show and compare an implementation of multicomponent
methodologies into fluid flow algorithms. The
modeling methods used are
1. Darcy flow modeling;
2. ray-tracing-based flow modeling;
3. a combination of Darcy flow and raytracing
(hybrid); and
4. invasive percolation.
Focus is put on multi-component implementations of these methods. The same PVTanalysis algorithm is applied in all models. This enables better comparison of the fluid flow methods themselves. A result from a case study clearly shows the necessity of applying multi-component fluid flow modeling with advanced PVT-property prediction as a “standard” method. This example shows the advantages and disadvantages of the individual methods, although statements concerning the superiority of one method compared with another cannot be made because each method has its own advantages and disadvantages.
End_of_Record - Last_Page 11---------------