{"id":"W2898030524","doi":"10.2118/191790-18erm-ms","title":"An Integrated Approach to Optimize Perforation Cluster Parameters for Horizontal Wells in Tight Oil Reservoirs","year":2018,"lang":"en","type":"article","venue":"","topic":"Hydraulic Fracturing and Reservoir Analysis","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Alberta Innovates; Energi Simulation","keywords":"Perforation; Cluster (spacecraft); Hydraulic fracturing; Fracture (geology); Petroleum engineering; Completion (oil and gas wells); Geology; Materials science; Geotechnical engineering; Computer science; Composite material","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"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":[0.0005920776,0.0007609979,0.0006662428,0.0007131796,0.0004337586,0.0007968006,0.0008420399,0.0007320651,0.00106147],"category_scores_gemma":[0.0008858623,0.0004886504,0.0004921465,0.000488642,0.0003196961,0.0008082388,0.0008163751,0.0003782584,0.0001326996],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008187048,"about_ca_system_score_gemma":0.001632864,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006010711,"about_ca_topic_score_gemma":0.007243903,"domain_scores_codex":[0.9996928,0.00004370758,0.00002142331,0.00006625333,0.0001058049,0.00006995145],"domain_scores_gemma":[0.9996986,0.00008674802,0.0000723365,0.0000274439,0.00009393715,0.00002095945],"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":[0.000061669,0.00007147435,0.001435102,0.00008109237,0.00002023537,0.00005758212,0.00005486828,0.9410436,0.02272497,0.001300699,0.0002028494,0.03294595],"study_design_scores_gemma":[0.00000942063,0.00008175746,0.0003322299,0.000004474613,0.00001647744,0.00001261153,0.00003036496,0.9942093,0.004745677,0.0003660804,0.0001815542,0.00001004647],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1837965,0.0001857283,0.8126399,0.00007144188,0.00001043374,0.00008879747,0.00005461927,0.0003914612,0.002761101],"genre_scores_gemma":[0.9196869,0.00006566697,0.07949103,0.00001332795,0.00000342175,0.00007432694,0.0000322291,0.00003100329,0.0006021085],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006010711,"threshold_uncertainty_score":0.01195145,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01272889092101672,"score_gpt":0.2366332951548894,"score_spread":0.2239044042338726,"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."}}