{"id":"W2065025714","doi":"10.2118/165387-ms","title":"Simulation Sensitivity Study and Design Parameters Optimization of SAGD Process","year":2013,"lang":"en","type":"article","venue":"SPE Heavy Oil Conference-Canada","topic":"Enhanced Oil Recovery Techniques","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Natural Resources","funders":"","keywords":"Steam-assisted gravity drainage; Oil sands; Petroleum engineering; Asphalt; Steam injection; Unconventional oil; Environmental science; Permeability (electromagnetism); Reservoir simulation; Drainage; Process (computing); Fossil fuel; Geology; Engineering; Waste management; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001799584,0.0009337692,0.0008148348,0.001113866,0.0006008976,0.001239686,0.000666332,0.001346546,0.003817195],"category_scores_gemma":[0.004114235,0.0004609195,0.001131238,0.0005755781,0.0004869252,0.0004291833,0.0007956942,0.001040608,0.0002285324],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001433755,"about_ca_system_score_gemma":0.001116278,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02083716,"about_ca_topic_score_gemma":0.01035546,"domain_scores_codex":[0.9994287,0.0002569719,0.00001930903,0.00006011192,0.0001037474,0.0001311807],"domain_scores_gemma":[0.9966378,0.002617712,0.0001877072,0.0001068144,0.0003961611,0.00005379426],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008040911,0.00003354784,0.0008402932,0.00005608693,0.00002160313,0.00005916208,0.00001745282,0.9961222,0.0008289336,0.0003520096,0.0001232391,0.001465045],"study_design_scores_gemma":[0.0000160976,0.0001463789,0.0007963534,0.00001572535,0.00002486722,0.00001267459,0.00005942386,0.9966651,0.001646177,0.0001859683,0.0004216586,0.000009609191],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8662639,0.0009248398,0.09554987,0.000659829,0.00009933676,0.0004683873,0.001169996,0.0004101369,0.03445359],"genre_scores_gemma":[0.9934221,0.00008744973,0.004836383,0.00002452409,0.000002478847,0.000094091,0.0001373309,0.00001376144,0.001381869],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02083716,"threshold_uncertainty_score":0.04143173,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02154480321527509,"score_gpt":0.2288676761155081,"score_spread":0.207322872900233,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}