{"id":"W2774214862","doi":"10.1002/cjce.23096","title":"Real‐time feedback control of SAGD wells using model predictive control to optimize steam chamber development under uncertainty","year":2017,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Reservoir Engineering and Simulation Methods","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Model predictive control; Multivariable calculus; Steam injection; Controller (irrigation); Control theory (sociology); Optimal control; Engineering; Petroleum engineering; Injection well; Control engineering; Control (management); Computer science; Mathematical optimization; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":false,"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":[0.0003931468,0.0006105079,0.0004290095,0.0002304698,0.0002870902,0.0007792172,0.0004580225,0.000396248,0.0007235707],"category_scores_gemma":[0.000738419,0.0002734084,0.0003403486,0.000232834,0.0005611468,0.0002933714,0.0005111007,0.0005083021,0.00007885164],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005850814,"about_ca_system_score_gemma":0.000719243,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01004662,"about_ca_topic_score_gemma":0.007085769,"domain_scores_codex":[0.9998357,0.00004022585,0.000008303829,0.00003138507,0.00005126324,0.00003304978],"domain_scores_gemma":[0.999607,0.0001880425,0.00008752065,0.00002389708,0.00007237238,0.00002120793],"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":[0.00003760604,0.00002651144,0.0002964392,0.00001968531,0.000007176199,0.00003724371,0.00001809703,0.9898223,0.005129443,0.0003967844,0.00007280451,0.004135882],"study_design_scores_gemma":[0.000004547798,0.00002674656,0.00009531649,0.000001037781,0.000002343338,0.000001647548,0.00000366361,0.9982332,0.001463559,0.0001102394,0.00005560467,0.000002063221],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6077114,0.0001964453,0.3843336,0.0001869556,0.00004116445,0.00007936796,0.0001076865,0.0007334264,0.006610164],"genre_scores_gemma":[0.9963779,0.00001623263,0.00334267,0.000004717814,0.000001233851,0.00001521887,0.00001406487,0.000004735936,0.0002233188],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01004662,"threshold_uncertainty_score":0.01997632,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01785600847313926,"score_gpt":0.2409728704327379,"score_spread":0.2231168619595986,"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."}}