Optimizing the value of reservoir simulation through quality-assured initialization

摘要

The initialization of a reservoir simulator calls for the populating of a three-dimensional dynamic grid-cell model using subsurface data and interrelational algorithms that have been synthesized to be fit for purpose. These prerequisites are rarely fully satisfied in practice. This paper sets out to strengthen initialization through four key thrusts, all of which seek to optimize the bridgehead between reservoir geoscience and reservoir engineering, and thereby maximize value from reservoir simulation. The first addresses representative data acquisition, which includes the key-well concept as a framework for the cost-effective incorporation of free-fluid porosity and permeability within an initialization database. The second concerns the preparation of these data and their products for populating the static and dynamic models. Important elements are dynamically conditioned net-reservoir cut-offs, recognition of primary flow units, and establishing interpretative algorithms at the simulator grid-cell scale for application over net-reservoir zones. The third thrust is directed at the internal consistency of capillary character, relative permeability properties and petrophysically-derived hydrocarbon saturations over net reservoir. This exercise is central to the simulation function and it is an integral component of hydraulic data partitioning. The fourth concerns the handling of formation heterogeneity and anisotropy, especially from the standpoint of directional parametric averaging and interpretative algorithms. These matters have been synthesized into a workflow for optimizing the initialization of reservoir simulators. In so doing, a further important consideration is the selection of the appropriate procedures that are available within and specific to different software packages. It is the authors' experience that implementation of these thrusts has demonstrably enhanced the authentication of reservoir simulators through more readily attainable history matches with less required tuning. This outcome is attributed to a more systematic initialization process with a lower risk of artefacts. Of course, these benefits feed through to more assured estimates of ultimate recovery and, thence, hydrocarbon reserves.