{"id":"W2973745575","doi":"10.2118/196020-ms","title":"Case Studies: Optimizing BHA Performance by Leveraging Data and Advanced Modeling","year":2019,"lang":"en","type":"article","venue":"SPE Annual Technical Conference and Exhibition","topic":"Drilling and Well Engineering","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Apache (Canada)","funders":"","keywords":"Drilling; Tortuosity; Casing; Measurement while drilling; Computer science; Petroleum engineering; Drilling fluid; Mechanical engineering; Geology; Engineering; Geotechnical engineering; Porosity","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002878544,0.001045259,0.0006343013,0.001682629,0.0005556163,0.00156367,0.001047186,0.001179304,0.0008231056],"category_scores_gemma":[0.004697327,0.0005250823,0.0008086062,0.001768695,0.0007047215,0.001432663,0.0008155665,0.0008760305,0.000152704],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001400305,"about_ca_system_score_gemma":0.001226186,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01593054,"about_ca_topic_score_gemma":0.02045712,"domain_scores_codex":[0.9987252,0.0005349847,0.0001154707,0.0001708999,0.000301329,0.0001520537],"domain_scores_gemma":[0.9954799,0.002898119,0.0004168469,0.0004648742,0.0005985874,0.0001415314],"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":[0.000255441,0.0005851573,0.03372845,0.0001772707,0.00008995266,0.0008683767,0.000183017,0.9311918,0.005134271,0.001342788,0.0004974603,0.02594595],"study_design_scores_gemma":[0.00003411808,0.0005232592,0.01050963,0.00003499425,0.00004679891,0.00008979835,0.000486287,0.9769298,0.009063955,0.000849536,0.00138559,0.0000461376],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9777057,0.0002154047,0.01875901,0.0002040772,0.00001104902,0.0001710525,0.0006182684,0.0001819246,0.002133427],"genre_scores_gemma":[0.9784135,0.0001103807,0.02054893,0.00001330782,0.000003631736,0.00007009576,0.0004202665,0.0000200343,0.0003999618],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01593054,"threshold_uncertainty_score":0.03167564,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03646418897910295,"score_gpt":0.2597747026058839,"score_spread":0.2233105136267809,"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."}}