{"id":"W2023794621","doi":"10.2118/68839-ms","title":"Simulation Based Dimensionless Type Curves for Predicting Waterflood Recovery","year":2001,"lang":"en","type":"article","venue":"SPE Western Regional Meeting","topic":"Reservoir Engineering and Simulation Methods","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Phoenix Technologies (Canada)","funders":"","keywords":"Computer science; Sensitivity (control systems); Dimensionless quantity; Reservoir simulation; Field (mathematics); Ranking (information retrieval); Discretization; Petroleum engineering; Geology; Machine learning; Mathematics; Engineering; Mechanics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004252195,0.0001738642,0.0001912411,0.0001025456,0.00008654651,0.00003845142,0.0001078924,0.00008750593,0.00001225667],"category_scores_gemma":[0.0003786694,0.0001727722,0.00008172706,0.000182737,0.00001212648,0.0001641429,0.00001629569,0.0001157947,0.00001098072],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004736219,"about_ca_system_score_gemma":0.0000145834,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000642212,"about_ca_topic_score_gemma":0.000004479762,"domain_scores_codex":[0.9989566,0.00004369516,0.0003026594,0.0002040396,0.0002151514,0.0002778402],"domain_scores_gemma":[0.9984825,0.00107729,0.00004991507,0.0001895775,0.0001247295,0.00007600039],"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":[0.00003636995,0.000008267316,0.008243511,0.000243283,0.00002078944,0.000002486647,0.00002698906,0.9893485,0.0009836863,0.00000480372,0.000100223,0.0009810313],"study_design_scores_gemma":[0.0004661623,0.00004321287,0.001170602,0.000650689,0.00001945528,0.000002768363,0.00001091888,0.9904269,0.0007101442,0.00008825,0.006205735,0.0002051409],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6799927,0.0008532885,0.3172005,0.0002238111,0.0006031939,0.0002735701,0.000004911839,0.0005006128,0.0003474161],"genre_scores_gemma":[0.9701762,0.0001531201,0.02866503,0.0001465146,0.0004426602,0.00002162338,0.00007621995,0.00007639482,0.0002422987],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2901834,"threshold_uncertainty_score":0.7045447,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04466618529646547,"score_gpt":0.296312692173986,"score_spread":0.2516465068775205,"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."}}