The advent of multiple-point geostatistics (MPS) gave rise to the integration of complex
subsurface geological structures and features into the model by the concept of training …

Assessing uncertainty of a spatial phenomenon requires the analysis of a large number of
parameters which must be processed by a transfer function. To capture the possibly of a …

Benchmark problems have been generated to test a number of issues related to predicting
reservoir behaviour (eg Floris et al., 2001, Christie and Blunt, 2001, Peters et al., 2010) …

In order to make the field development decision making and planning process tractable, the
decision-makers usually need a few representative models (for example, P10, P50, P90 …

Modeling uncertainty for future prediction requires drawing multiple posterior models. Such
drawing within a Bayesian framework is dependent on the likelihood (data-model …

Surface-based models imitate a sequence of depositional events in time. By considering
sedimentation processes, these algorithms produce highly realistic subsurface structures …

A novel polynomial chaos proxy-based history matching and uncertainty quantification
method is presented that can be employed for complex geological structures in inverse …

Different interpretation of sedimentary environments lead to “scenario uncertainty” where the
prior reservoir model has a high level of discrete uncertainty. In a real field application, the …

The inversion of large-scale ill-posed problems introduces multiple challenges. These
include, identifying appropriate noise model, prescription of suitable prior information …

Accounting for geological scenario uncertainty is one of the contemporary challenges in
reservoir prediction modelling. Multi-point statistics approach allows distinguishing between …