{"id":{"repo_id":"wvu","oai_identifier":"oai:researchrepository.wvu.edu:etd-2276"},"canonical_url":"https://search.dev.ndltd.org/etd/wvu/oai:researchrepository.wvu.edu:etd-2276","repository":{"repo_id":"wvu","name":"West Virginia University","base_url":"https://researchrepository.wvu.edu/do/oai/"},"display":{"title":"Using waterflood performance to characterize flow-units in a heterogeneous reservoir","abstract":"Simulation of waterflood performance is used to verify the characterization of flow-units in a heterogeneous reservoir. BOAST98 software was used for simulation of waterflood performance. Two adjacent five spot patterns in the Stringtown field in West Virginia were selected to be evaluated in this study.;The predicted permeability along with the porosity from Artificial Neural Network (A.N.N) was used for primary characterization purpose and identification of flow-units in the two five spots patterns.;Two alternate simulation models were developed. The simulation model was developed using the available data and those predicted using A.N.N. to verify that the flow-units model was an accurate description of the field. One model had two layers representing two flow units whereas the second model had three layers representing three flow units.;The output from the simulation runs was compared with 10 years of actual production history of both the wells. A close history matching was obtained with about 15--25% of total volume water injection rates into the individual patterns from each of the 6 wells. Though both the models were good in predicting the output, the second model which was developed for three flow units was better.","abstract_html":"Simulation of waterflood performance is used to verify the characterization of flow-units in a heterogeneous reservoir. BOAST98 software was used for simulation of waterflood performance. Two adjacent five spot patterns in the Stringtown field in West Virginia were selected to be evaluated in this study.;The predicted permeability along with the porosity from Artificial Neural Network (A.N.N) was used for primary characterization purpose and identification of flow-units in the two five spots patterns.;Two alternate simulation models were developed. The simulation model was developed using the available data and those predicted using A.N.N. to verify that the flow-units model was an accurate description of the field. One model had two layers representing two flow units whereas the second model had three layers representing three flow units.;The output from the simulation runs was compared with 10 years of actual production history of both the wells. A close history matching was obtained with about 15--25% of total volume water injection rates into the individual patterns from each of the 6 wells. Though both the models were good in predicting the output, the second model which was developed for three flow units was better.","abstract_has_math":false,"creators":["Alla, Vamsi Krishna"],"institution":null,"degree_name":"MS","degree_level":"Thesis","degree_discipline":"Petroleum and Natural Gas Engineering","degree_department":null,"school":null,"contributors":["Kashayar Aminian."],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2002,"date_issued":"2002-12-01T08:00:00Z","date_published":"2002-12-01T08:00:00Z","updated_at":"2026-07-24T06:15:31Z","subjects":["Petroleum engineering"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["https://researchrepository.wvu.edu/etd/1273"],"render_values":[{"text":"https://researchrepository.wvu.edu/etd/1273","href":"https://researchrepository.wvu.edu/etd/1273","code":true}]}]},"links":{"outbound_url":"https://doi.org/10.33915/etd.1273","outbound_label":"DOI","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Kashayar Aminian."]},{"key":"dc:creator","label":"Author","values":["Alla, Vamsi Krishna"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2019-01-17T08:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Petroleum and Natural Gas Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["MS"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Petroleum engineering"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://doi.org/10.33915/etd.1273","https://researchrepository.wvu.edu/etd/1273"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Simulation of waterflood performance is used to verify the characterization of flow-units in a heterogeneous reservoir. BOAST98 software was used for simulation of waterflood performance. Two adjacent five spot patterns in the Stringtown field in West Virginia were selected to be evaluated in this study.;The predicted permeability along with the porosity from Artificial Neural Network (A.N.N) was used for primary characterization purpose and identification of flow-units in the two five spots patterns.;Two alternate simulation models were developed. The simulation model was developed using the available data and those predicted using A.N.N. to verify that the flow-units model was an accurate description of the field. One model had two layers representing two flow units whereas the second model had three layers representing three flow units.;The output from the simulation runs was compared with 10 years of actual production history of both the wells. A close history matching was obtained with about 15--25% of total volume water injection rates into the individual patterns from each of the 6 wells. Though both the models were good in predicting the output, the second model which was developed for three flow units was better."]},{"key":"dc:title","label":"Title","values":["Using waterflood performance to characterize flow-units in a heterogeneous reservoir"]}]}],"canonical_facts":{"dc:contributor":["Kashayar Aminian."],"dc:creator":["Alla, Vamsi Krishna"],"dc:date.available":["2019-01-17T08:00:00Z"],"dc:description.abstract":["Simulation of waterflood performance is used to verify the characterization of flow-units in a heterogeneous reservoir. BOAST98 software was used for simulation of waterflood performance. Two adjacent five spot patterns in the Stringtown field in West Virginia were selected to be evaluated in this study.;The predicted permeability along with the porosity from Artificial Neural Network (A.N.N) was used for primary characterization purpose and identification of flow-units in the two five spots patterns.;Two alternate simulation models were developed. The simulation model was developed using the available data and those predicted using A.N.N. to verify that the flow-units model was an accurate description of the field. One model had two layers representing two flow units whereas the second model had three layers representing three flow units.;The output from the simulation runs was compared with 10 years of actual production history of both the wells. A close history matching was obtained with about 15--25% of total volume water injection rates into the individual patterns from each of the 6 wells. Though both the models were good in predicting the output, the second model which was developed for three flow units was better."],"dc:identifier":["https://doi.org/10.33915/etd.1273","https://researchrepository.wvu.edu/etd/1273"],"dc:subject":["Petroleum engineering"],"dc:title":["Using waterflood performance to characterize flow-units in a heterogeneous reservoir"],"thesis:degree_discipline":["Petroleum and Natural Gas Engineering"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["MS"]},"updated_at":"2026-07-24T06:15:31Z"}