Work

Accelerated ensemble optimization using momentum methods

Year: 2024

Type: article

Abstract: We investigate the use of various momentum methods in combination with an ensemble approximation of gradients, for accelerated optimization. Although momentum gradient descent methods are popular in machine learning, it is unclear how they perform when applied to time-consuming dynamic problems such as production optimization for petroleum reservoir management. Four different momentum methods are extensively tested on a reservoir test case in one deterministic and one robust setting. The numerical experiments show that momentum strategies yield, on average, a higher net present value with fewer simulations needed.

Source: Scientific Reports

DOI: 10.1038/s41598-024-76916-7

Authors: Mathias M. Nilsen, Andreas S. Stordal, Rolf J. Lorentzen, Patrick N. Raanes, Kjersti S. Eikrem

Institutions: NORCE Research AS, University of Bergen

Language: English

Topic: Reservoir Engineering and Simulation Methods

Subfield: Ocean Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $2,590

Funders: Equinor, Universitetet i Bergen, Norges Forskningsråd, Wintershall Dea