A new look at traditional deterministic flow models and their calibration in the context of randomly heterogeneous media

Shlomo P Neuman, A. Guadagnini

Research output: Contribution to journalArticle

8 Citations (Scopus)

Abstract

We examine the tradition of modelling subsurface flow deterministically from a stochastic viewpoint. In particular, we show that traditional deterministic flow equations do apply to randomly heterogeneous media, albeit in an approximate manner, provided they are interpreted in a non-traditional manner. Our paper explains why parameter estimates obtained by traditional inverse methods tend to vary as one modifies the database. It also makes clear that the traditional Monte Carlo method of assessing uncertainty in the output of a calibrated deterministic model generally overestimates the predictive capabilities of the model. The only valid way to assess predictive uncertainty is by means of a stochastic model.

Original languageEnglish (US)
Pages (from-to)213-221
Number of pages9
JournalIAHS-AISH Publication
Issue number265
StatePublished - 2000

Fingerprint

heterogeneous medium
calibration
subsurface flow
modeling
method

ASJC Scopus subject areas

  • Oceanography
  • Water Science and Technology

Cite this

@article{1fea32f2dcdd4bbeb0c208da3128660f,
title = "A new look at traditional deterministic flow models and their calibration in the context of randomly heterogeneous media",
abstract = "We examine the tradition of modelling subsurface flow deterministically from a stochastic viewpoint. In particular, we show that traditional deterministic flow equations do apply to randomly heterogeneous media, albeit in an approximate manner, provided they are interpreted in a non-traditional manner. Our paper explains why parameter estimates obtained by traditional inverse methods tend to vary as one modifies the database. It also makes clear that the traditional Monte Carlo method of assessing uncertainty in the output of a calibrated deterministic model generally overestimates the predictive capabilities of the model. The only valid way to assess predictive uncertainty is by means of a stochastic model.",
author = "Neuman, {Shlomo P} and A. Guadagnini",
year = "2000",
language = "English (US)",
pages = "213--221",
journal = "IAHS-AISH Publication",
issn = "0144-7815",
number = "265",

}

TY - JOUR

T1 - A new look at traditional deterministic flow models and their calibration in the context of randomly heterogeneous media

AU - Neuman, Shlomo P

AU - Guadagnini, A.

PY - 2000

Y1 - 2000

N2 - We examine the tradition of modelling subsurface flow deterministically from a stochastic viewpoint. In particular, we show that traditional deterministic flow equations do apply to randomly heterogeneous media, albeit in an approximate manner, provided they are interpreted in a non-traditional manner. Our paper explains why parameter estimates obtained by traditional inverse methods tend to vary as one modifies the database. It also makes clear that the traditional Monte Carlo method of assessing uncertainty in the output of a calibrated deterministic model generally overestimates the predictive capabilities of the model. The only valid way to assess predictive uncertainty is by means of a stochastic model.

AB - We examine the tradition of modelling subsurface flow deterministically from a stochastic viewpoint. In particular, we show that traditional deterministic flow equations do apply to randomly heterogeneous media, albeit in an approximate manner, provided they are interpreted in a non-traditional manner. Our paper explains why parameter estimates obtained by traditional inverse methods tend to vary as one modifies the database. It also makes clear that the traditional Monte Carlo method of assessing uncertainty in the output of a calibrated deterministic model generally overestimates the predictive capabilities of the model. The only valid way to assess predictive uncertainty is by means of a stochastic model.

UR - http://www.scopus.com/inward/record.url?scp=0033794554&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0033794554&partnerID=8YFLogxK

M3 - Article

AN - SCOPUS:0033794554

SP - 213

EP - 221

JO - IAHS-AISH Publication

JF - IAHS-AISH Publication

SN - 0144-7815

IS - 265

ER -