{"id":{"repo_id":"texas","oai_identifier":"oai:repositories.lib.utexas.edu:2152/81138"},"canonical_url":"https://search.dev.ndltd.org/etd/texas/oai:repositories.lib.utexas.edu:2152/81138","repository":{"repo_id":"texas","name":"University of Texas","base_url":"https://repositories.lib.utexas.edu/server/oai/request"},"display":{"title":"A New Analog for Numerical Flow Simulations Application to Direct Assessment of Reservoir Flow Performance Uncertainties","abstract":"The ultimate objective of this thesis is to develop a technique for directassessment of reservoir flow performance uncertainties, as compared to manytraditional, computationally expensive techniques such as Monte Carlo simulations. This is achieved via a single stochastic flow simulation that combineslocal geologic uncertainty with a new simple flow transfer model to estimate a joint uncertainty distribution that characterizes flow uncertainty. Our methodprovides the framework to go directly from local uncertainty, derived using simple spatial interpolation techniques, to flow uncertainty, skipping the intermediate step of stochastic sequential simulations and not requiring any detailed fine-scale flow simulations.","abstract_html":"The ultimate objective of this thesis is to develop a technique for directassessment of reservoir flow performance uncertainties, as compared to manytraditional, computationally expensive techniques such as Monte Carlo simulations. This is achieved via a single stochastic flow simulation that combineslocal geologic uncertainty with a new simple flow transfer model to estimate a joint uncertainty distribution that characterizes flow uncertainty. Our methodprovides the framework to go directly from local uncertainty, derived using simple spatial interpolation techniques, to flow uncertainty, skipping the intermediate step of stochastic sequential simulations and not requiring any detailed fine-scale flow simulations.","abstract_has_math":false,"creators":["Leung, Juliana Yuk Wing"],"institution":"University of Texas at Austin","degree_name":"Masters of Science in Engineering","degree_level":"Masters","degree_discipline":"Petroleum Engineering","degree_department":null,"school":null,"contributors":[],"advisors":["Srinivasan, Sanjay"],"committee_chairs":[],"committee_members":[],"year":2004,"date_issued":"2004-08","date_published":"2004-08","updated_at":"2026-07-24T05:01:04Z","subjects":["Reservoir flow","Monte Carlo"],"languages":["eng"],"rights":["Copyright © is held by the author. Presentation of this material on the Libraries&apos; web site by University Libraries, The University of Texas at Austin was made possible under a limited license grant from the author who has retained all copyrights in the works."],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://dx.doi.org/10.26153/tsw/8151"],"render_values":[{"text":"http://dx.doi.org/10.26153/tsw/8151","href":"http://dx.doi.org/10.26153/tsw/8151","code":true}]}]},"links":{"outbound_url":"https://hdl.handle.net/2152/81138","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Srinivasan, Sanjay"]},{"key":"dc:creator","label":"Author","values":["Leung, Juliana Yuk Wing"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2020-04-30T00:01:49Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2020-04-30T00:01:49Z"]},{"key":"dc:date.issued","label":"Date","values":["2004-08"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Petroleum Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Masters"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Masters of Science in Engineering"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Texas at Austin"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Reservoir flow","Monte Carlo"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright © is held by the author. Presentation of this material on the Libraries&apos; web site by University Libraries, The University of Texas at Austin was made possible under a limited license grant from the author who has retained all copyrights in the works."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/2152/81138","http://dx.doi.org/10.26153/tsw/8151"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["The ultimate objective of this thesis is to develop a technique for directassessment of reservoir flow performance uncertainties, as compared to manytraditional, computationally expensive techniques such as Monte Carlo simulations. This is achieved via a single stochastic flow simulation that combineslocal geologic uncertainty with a new simple flow transfer model to estimate a joint uncertainty distribution that characterizes flow uncertainty. Our methodprovides the framework to go directly from local uncertainty, derived using simple spatial interpolation techniques, to flow uncertainty, skipping the intermediate step of stochastic sequential simulations and not requiring any detailed fine-scale flow simulations."]},{"key":"dc:format.medium","label":"Dc Format Medium","values":["electronic"]},{"key":"dc:title","label":"Title","values":["A New Analog for Numerical Flow Simulations Application to Direct Assessment of Reservoir Flow Performance Uncertainties"]}]}],"canonical_facts":{"dc:contributor.advisor":["Srinivasan, Sanjay"],"dc:creator":["Leung, Juliana Yuk Wing"],"dc:date.accessioned":["2020-04-30T00:01:49Z"],"dc:date.available":["2020-04-30T00:01:49Z"],"dc:date.issued":["2004-08"],"dc:description.abstract":["The ultimate objective of this thesis is to develop a technique for directassessment of reservoir flow performance uncertainties, as compared to manytraditional, computationally expensive techniques such as Monte Carlo simulations. This is achieved via a single stochastic flow simulation that combineslocal geologic uncertainty with a new simple flow transfer model to estimate a joint uncertainty distribution that characterizes flow uncertainty. Our methodprovides the framework to go directly from local uncertainty, derived using simple spatial interpolation techniques, to flow uncertainty, skipping the intermediate step of stochastic sequential simulations and not requiring any detailed fine-scale flow simulations."],"dc:format.medium":["electronic"],"dc:identifier.uri":["https://hdl.handle.net/2152/81138","http://dx.doi.org/10.26153/tsw/8151"],"dc:language.iso":["eng"],"dc:rights":["Copyright © is held by the author. Presentation of this material on the Libraries&apos; web site by University Libraries, The University of Texas at Austin was made possible under a limited license grant from the author who has retained all copyrights in the works."],"dc:subject":["Reservoir flow","Monte Carlo"],"dc:title":["A New Analog for Numerical Flow Simulations Application to Direct Assessment of Reservoir Flow Performance Uncertainties"],"dc:type":["Thesis"],"thesis:degree_discipline":["Petroleum Engineering"],"thesis:degree_level":["Masters"],"thesis:degree_name":["Masters of Science in Engineering"],"thesis:institution_name":["University of Texas at Austin"]},"updated_at":"2026-07-24T05:01:04Z"}