4 research outputs found
Modelling and quantification of structural uncertainties in petroleum reservoirs assisted by a hybrid cartesian cut cell/enriched multipoint flux approximation approach
Efficient and profitable oil production is subject to make reliable predictions about
reservoir performance. However, restricted knowledge about reservoir distributed
properties and reservoir structure calls for History Matching in which the reservoir
model is calibrated to emulate the field observed history. Such an inverse problem
yields multiple history-matched models which might result in different predictions of
reservoir performance. Uncertainty Quantification restricts the raised model
uncertainties and boosts the model reliability for the forecasts of future reservoir
behaviour. Conventional approaches of Uncertainty Quantification ignore large scale
uncertainties related to reservoir structure, while structural uncertainties can influence
the reservoir forecasts more intensely compared with petrophysical uncertainty.
What makes the quantification of structural uncertainty impracticable is the need for
global regridding at each step of History Matching process. To resolve this obstacle, we
develop an efficient methodology based on Cartesian Cut Cell Method which decouples
the model from its representation onto the grid and allows uncertain structures to be
varied as a part of History Matching process. Reduced numerical accuracy due to cell
degeneracies in the vicinity of geological structures is adequately compensated with an
enhanced scheme of class Locally Conservative Flux Continuous Methods (Extended
Enriched Multipoint Flux Approximation Method abbreviated to extended EMPFA).
The robustness and consistency of proposed Hybrid Cartesian Cut Cell/extended
EMPFA approach are demonstrated in terms of true representation of geological
structures influence on flow behaviour. In this research, the general framework of
Uncertainty Quantification is extended and well-equipped by proposed approach to
tackle uncertainties of different structures such as reservoir horizons, bedding layers,
faults and pinchouts. Significant improvements in the quality of reservoir recovery
forecasts and reservoir volume estimation are presented for synthetic models of
uncertain structures. Also this thesis provides a comparative study of structural
uncertainty influence on reservoir forecasts among various geological structures