{"id":"W2936851328","doi":"10.2118/195253-ms","title":"Application of Flow Diagnostics to Rapid Production Data Integration in Complex Geologic Grids and Dual Permeability Models","year":2019,"lang":"en","type":"article","venue":"SPE Western Regional Meeting","topic":"Reservoir Engineering and Simulation Methods","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Impact","funders":"","keywords":"Computer science; Streamlines, streaklines, and pathlines; Computation; Grid; Reservoir simulation; Inverse problem; Tracing; Algorithm; Reservoir modeling; Regularization (linguistics); Synthetic data; Computational science; Mathematical optimization; Data mining; Geology; Mathematics; Engineering; Artificial intelligence; Petroleum engineering","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":[0.000694153,0.0004859311,0.0003564593,0.0004559437,0.000234426,0.0008722952,0.0006198936,0.0007552278,0.0006722339],"category_scores_gemma":[0.001809949,0.0002090307,0.000294411,0.0004033554,0.000585293,0.0005690025,0.0008323555,0.0006763016,0.00009154897],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006385643,"about_ca_system_score_gemma":0.0007857262,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007554871,"about_ca_topic_score_gemma":0.003745655,"domain_scores_codex":[0.9997479,0.00007369091,0.0000196777,0.00004033926,0.00009655535,0.00002184999],"domain_scores_gemma":[0.9992126,0.0003665254,0.0001245705,0.0001269993,0.000134888,0.00003438614],"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":[0.00005210387,0.00008295003,0.002779536,0.00003527886,0.00001361852,0.0001441966,0.00006975135,0.9604708,0.01630621,0.003352072,0.0003099006,0.01638358],"study_design_scores_gemma":[0.000004166624,0.00001276448,0.0001468312,0.000001668024,7.98622e-7,0.000007269571,0.000006793922,0.9960013,0.003307601,0.0003689053,0.0001389274,0.000002952788],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4743741,0.0001645211,0.5203694,0.000402799,0.00005919398,0.0000769709,0.0001992508,0.001688464,0.002665299],"genre_scores_gemma":[0.897288,0.00004574304,0.1020374,0.00002665828,0.000007859684,0.00003513833,0.0001013886,0.00005540876,0.0004025067],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007554871,"threshold_uncertainty_score":0.01502174,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07346547224238663,"score_gpt":0.298879147870136,"score_spread":0.2254136756277494,"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."}}