22 citations · 27 across the 4 of their papers we have counts for
5 papers
Using machine learning to reduce ensembles of geological models for oil and gas exploration
Anna Roubícková, Lucy MacGregor, Nick Brown +2
Exploration using borehole drilling is a key activity in determining the most appropriate locations for the petroleum industry to develop oil fields. However, estimating the amount…
Machine Learning for Gas and Oil Exploration
Vito Alexander Nordloh, Anna Roubícková, Nick Brown
Drilling boreholes for gas and oil extraction is an expensive process and profitability strongly depends on characteristics of the subsurface. As profitability is a key success fac…
Machine learning on Crays to optimise petrophysical workflows in oil and gas exploration
Nick Brown, Anna Roubickova, Ioanna Lampaki +3
The oil and gas industry is awash with sub-surface data, which is used to characterize the rock and fluid properties beneath the seabed. This in turn drives commercial decision mak…
Case-Based Merging Techniques in OAKPLAN
Anna Roubíčková, Ivan Serina
Case-based planning can take advantage of former problem-solving experiences by storing in a plan library previously generated plans that can be reused to solve similar planning pr…
Parameterized Complexity Results for Plan Reuse
Ronald de Haan, Anna Roubíčková, Stefan Szeider
Planning is a notoriously difficult computational problem of high worst-case complexity. Researchers have been investing significant efforts to develop heuristics or restrictions t…