{"id":"W4392726836","doi":"10.2118/218078-ms","title":"A Quick Decline Method for Forecasting Multiple Wells Using Sparse Functional Principal Component Analysis","year":2024,"lang":"en","type":"article","venue":"","topic":"Reservoir Engineering and Simulation Methods","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Principal component analysis; Component (thermodynamics); Computer science; Component analysis; Econometrics; Artificial intelligence; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008503071,0.0001901443,0.0002912643,0.0004136413,0.00007079852,0.0001054537,0.00008734648,0.00008631952,0.0001610345],"category_scores_gemma":[0.000128216,0.0001759749,0.0003016844,0.0007322958,0.000008666789,0.000122698,0.00004005253,0.0001434841,0.000008585964],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001029482,"about_ca_system_score_gemma":0.00001877231,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005262917,"about_ca_topic_score_gemma":0.00002670913,"domain_scores_codex":[0.9988285,0.00004134301,0.0003808872,0.000262938,0.0001968526,0.0002895298],"domain_scores_gemma":[0.998562,0.001065332,0.00001856084,0.0001877117,0.00006042466,0.0001059296],"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":[0.00001293531,0.000008717704,0.000662568,0.0001626904,0.000559772,0.000003388162,0.00004749291,0.9925866,0.003431149,0.0003380071,0.0001228169,0.002063863],"study_design_scores_gemma":[0.0003192837,0.00001095086,0.0005266899,0.00002325159,0.0002816445,0.000006736065,0.0000181212,0.9853041,0.001458571,0.0001220119,0.0117239,0.0002047439],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1404629,0.0002479295,0.8576608,0.00003230441,0.0005674866,0.000179477,0.00002181445,0.0005801388,0.0002471464],"genre_scores_gemma":[0.4210349,0.000003622913,0.5784018,0.00001318885,0.0001996144,0.0000196409,0.00004325805,0.00003652965,0.0002474603],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2805719,"threshold_uncertainty_score":0.7176046,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1011167224734608,"score_gpt":0.3379861946832856,"score_spread":0.2368694722098248,"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."}}