FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4234920758> ?p ?o ?g. }

• W4234920758 abstract "Characterizing Permeability Distributions with Integral Autocorrelation Estimators G.B. Savioli; G.B. Savioli University of Buenos Aires Search for other works by this author on: This Site Google Scholar A.F. Saccomano; A.F. Saccomano University of Buenos Aires Search for other works by this author on: This Site Google Scholar M.S. Bidner M.S. Bidner University of Buenos Aires Search for other works by this author on: This Site Google Scholar Paper presented at the Latin American and Caribbean Petroleum Engineering Conference, Caracas, Venezuela, April 1999. Paper Number: SPE-53884-MS https://doi.org/10.2118/53884-MS Published: April 21 1999 Cite View This Citation Add to Citation Manager Share Icon Share Twitter LinkedIn Get Permissions Search Site Citation Savioli, G.B., Saccomano, A.F., and M.S. Bidner. Characterizing Permeability Distributions with Integral Autocorrelation Estimators. Paper presented at the Latin American and Caribbean Petroleum Engineering Conference, Caracas, Venezuela, April 1999. doi: https://doi.org/10.2118/53884-MS Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex Search Dropdown Menu nav search search input Search input auto suggest search filter All ContentAll ProceedingsSociety of Petroleum Engineers (SPE)SPE Latin America and Caribbean Petroleum Engineering Conference Search Advanced Search Permeability distributions of very heterogeneous reservoir rocks are analyzed by applying different autocorrelation estimators: the classical semivariance estimator (CSV) and two moving window semivariance estimators (MW1 and MW2), introduced by Li and Lake 1 in 1994. The goal of this work is to compare the ability of Simulated Annealing (SA) to represent actual heterogeneity, when each one of the three estimators is introduced in the objective function. The objective function is minimized by the Metropolis algorithm. With that aim, the generated image of permeabilities is compared with core measurements. Although MW1 and MW2 are more robust and resistant than CSV, they only present minor advantages when introduced into SA to describe permeability distributions Keywords: objective function, machine learning, saccomano, semivariance, normal distribution, lag distance, university, flow in porous media, permeability distribution, upstream oil & gas Subjects: Reservoir Characterization, Reservoir Fluid Dynamics, Flow in porous media This content is only available via PDF. 1999. Society of Petroleum Engineers You can access this article if you purchase or spend a download." @default.
• W4234920758 created "2022-05-12" @default.
• W4234920758 creator A5000843819 @default.
• W4234920758 creator A5006691378 @default.
• W4234920758 creator A5007585468 @default.
• W4234920758 date "1999-04-01" @default.
• W4234920758 modified "2023-10-18" @default.
• W4234920758 title " Characterizing Permeability Distributions with Integral Autocorrelation Estimators " @default.
• W4234920758 doi "https://doi.org/10.2523/53884-ms" @default.
• W4234920758 hasPublicationYear "1999" @default.
• W4234920758 type Work @default.
• W4234920758 citedByCount "0" @default.
• W4234920758 crossrefType "proceedings-article" @default.
• W4234920758 hasAuthorship W4234920758A5000843819 @default.
• W4234920758 hasAuthorship W4234920758A5006691378 @default.
• W4234920758 hasAuthorship W4234920758A5007585468 @default.
• W4234920758 hasConcept C105795698 @default.
• W4234920758 hasConcept C113505986 @default.
• W4234920758 hasConcept C161191863 @default.
• W4234920758 hasConcept C185429906 @default.
• W4234920758 hasConcept C23123220 @default.
• W4234920758 hasConcept C2778805511 @default.
• W4234920758 hasConcept C33923547 @default.
• W4234920758 hasConcept C41008148 @default.
• W4234920758 hasConcept C5297727 @default.
• W4234920758 hasConcept C94747663 @default.
• W4234920758 hasConceptScore W4234920758C105795698 @default.
• W4234920758 hasConceptScore W4234920758C113505986 @default.
• W4234920758 hasConceptScore W4234920758C161191863 @default.
• W4234920758 hasConceptScore W4234920758C185429906 @default.
• W4234920758 hasConceptScore W4234920758C23123220 @default.
• W4234920758 hasConceptScore W4234920758C2778805511 @default.
• W4234920758 hasConceptScore W4234920758C33923547 @default.
• W4234920758 hasConceptScore W4234920758C41008148 @default.
• W4234920758 hasConceptScore W4234920758C5297727 @default.
• W4234920758 hasConceptScore W4234920758C94747663 @default.
• W4234920758 hasLocation W42349207581 @default.
• W4234920758 hasOpenAccess W4234920758 @default.
• W4234920758 hasPrimaryLocation W42349207581 @default.
• W4234920758 hasRelatedWork W2006698650 @default.
• W4234920758 hasRelatedWork W2024653370 @default.
• W4234920758 hasRelatedWork W2028259685 @default.
• W4234920758 hasRelatedWork W2120633375 @default.
• W4234920758 hasRelatedWork W2384888906 @default.
• W4234920758 hasRelatedWork W2613513259 @default.
• W4234920758 hasRelatedWork W2783283813 @default.
• W4234920758 hasRelatedWork W3018864627 @default.
• W4234920758 hasRelatedWork W4323028429 @default.
• W4234920758 hasRelatedWork W345919397 @default.
• W4234920758 isParatext "false" @default.
• W4234920758 isRetracted "false" @default.
• W4234920758 workType "article" @default.