Cristin-resultat-ID: 2057185
Sist endret: 11. oktober 2022, 15:49
NVI-rapporteringsår: 2022
Resultat
Vitenskapelig artikkel
2022

Improving pseudo-optimal Kalman-gain localization using the random shuffle method

Bidragsytere:
  • Paulo Henrique Ranazzi
  • Xiaodong Luo og
  • Marcio Augusto Sampaio

Tidsskrift

Journal of Petroleum Science and Engineering
ISSN 0920-4105
e-ISSN 1873-4715
NVI-nivå 2

Om resultatet

Vitenskapelig artikkel
Publiseringsår: 2022
Volum: 215
Artikkelnummer: 110589

Importkilder

Scopus-ID: 2-s2.0-85130131450

Klassifisering

Vitenskapsdisipliner

Petroleumsteknologi

Emneord

Ensemble based methods

Beskrivelse Beskrivelse

Tittel

Improving pseudo-optimal Kalman-gain localization using the random shuffle method

Sammendrag

In present days, Iterative ensemble smoothers (IES) are among the main methods to perform ensemble-based history matching in petroleum reservoirs. Generally, some localization technique is applied to the IES to prevent ensemble collapse, which is the consequence of an excessive reduction of the posterior ensemble variance. When the standard distance-based localization is applied, the assimilation of non-local parameters is difficult, and besides that, this kind of methodology has also several intrinsic parameters that need to be defined before the assimilation. In contrast, adaptive localization methods aim to overcome the noticed problems of distance-based localization, by using some statistical method to define the localization. This article proposes a novel adaptive localization scheme, on top of two preexisting techniques: pseudo-optimal and correlation-based localizations. The motivation here is to further improve the adaptive localization scheme, by combining the strengths of these two preexisting techniques. The efficacy of the proposed localization scheme is tested in one 2D and one 3D case studies, whereas the latter case study involves a field-scale reservoir model with both local and non-local parameters, which often impose challenges on the conventional localization schemes. In comparison to other evaluated localization schemes, our results indicate that the proposed adaptive localization scheme achieves improved history matching performance.

Bidragsytere

Paulo Henrique Ranazzi

  • Tilknyttet:
    Forfatter
    ved Universidade de São Paulo

Xiaodong Luo

  • Tilknyttet:
    Forfatter
    ved NORCE Energi og teknologi ved NORCE Norwegian Research Centre AS

Marcio Augusto Sampaio

  • Tilknyttet:
    Forfatter
    ved Universidade de São Paulo
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