Open Research will be unavailable from 10.15am - 11am on Saturday 14th March 2026 AEDT due to scheduled maintenance.
 

How to model visual knowledge: A study of expertise in oil-reservoir evaluation

dc.contributor.authorAbel, Maraen
dc.contributor.authorMastella, Laura S.en
dc.contributor.authorLima Silva, Luís A.en
dc.contributor.authorCampbell, John A.en
dc.contributor.authorDe Ros, Luis Fernandoen
dc.date.accessioned2025-12-17T14:40:56Z
dc.date.available2025-12-17T14:40:56Z
dc.date.issued2004en
dc.description.abstractThis work presents a study of the nature of expertise in geology, which demands visual recognition methods to describe and interpret petroleum reservoir rocks. In an experiment using rock images we noted and analyzed how geologists with distinct levels of expertise described them. The study demonstrated that experts develop a wide variety of representations and hierarchies, which differ from those found in the domain literature. They also retain a large number of symbolic abstractions for images. These abstractions (which we call visual chunks) play an important role in guiding the inference process and integrating collections of tacit knowledge of the geological experts. We infer from our experience that the knowledge acquisition process in this domain should consider that inference and domain objects are parts of distinct ontologies. A special representation formalism, kgraphs+, is proposed as a tool to model the objects that support the inference and how they are related to the domain ontology.en
dc.description.statusPeer-revieweden
dc.format.extent10en
dc.identifier.isbn3540229361en
dc.identifier.isbn9783540229360en
dc.identifier.issn0302-9743en
dc.identifier.scopus35048849122en
dc.identifier.urihttps://hdl.handle.net/1885/733796006
dc.language.isoenen
dc.publisherSpringer Verlagen
dc.relation.ispartofLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)en
dc.relation.ispartofseriesLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)en
dc.subjectExpertiseen
dc.subjectKnowledge acquisitionen
dc.subjectKnowledge representationen
dc.subjectPetroleum explorationen
dc.subjectVisual knowledgeen
dc.titleHow to model visual knowledge: A study of expertise in oil-reservoir evaluationen
dc.typeBook chapteren
dspace.entity.typePublicationen
local.bibliographicCitation.lastpage464en
local.bibliographicCitation.startpage455en
local.contributor.affiliationAbel, Mara; Universidade Federal do Rio Grande do Sulen
local.contributor.affiliationMastella, Laura S.; Universidade Federal do Rio Grande do Sulen
local.contributor.affiliationLima Silva, Luís A.; Universidade Federal do Rio Grande do Sulen
local.contributor.affiliationCampbell, John A.; University College Londonen
local.contributor.affiliationDe Ros, Luis Fernando; Universidade Federal do Rio Grande do Sulen
local.identifier.ariespublicationU3488905xPUB16835en
local.identifier.doi10.1007/978-3-540-30075-5_44en
local.identifier.essn1611-3349en
local.identifier.puref6012779-c01b-47fb-94d7-2fb57835fd73en
local.identifier.urlhttps://www.scopus.com/pages/publications/35048849122en
local.type.statusPublisheden

Downloads