{"id":"W1988177694","doi":"10.2118/147991-pa","title":"Three-Phase Pore-Network Modeling for Reservoirs With Arbitrary Wettability","year":2012,"lang":"en","type":"article","venue":"SPE Journal","topic":"Enhanced Oil Recovery Techniques","field":"Engineering","cited_by":45,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Eidgenössische Technische Hochschule Zürich; CMG Reservoir Simulation Foundation; Heriot-Watt University","keywords":"Relative permeability; Residual oil; Capillary pressure; Wetting; Petroleum engineering; Saturation (graph theory); Permeability (electromagnetism); Enhanced oil recovery; Multiphase flow; Network model; Work (physics); Phase (matter); Geology; Mechanics; Biological system; Computer science; Materials science; Porous medium; Geotechnical engineering; Engineering; Chemistry; Artificial intelligence; Mechanical engineering; Porosity; Mathematics; Physics; Composite material","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024473,0.0003514019,0.0003999144,0.000381409,0.0003843892,0.0005476591,0.0008689185,0.001342335,0.001462319],"category_scores_gemma":[0.0009351542,0.0002828678,0.0006251905,0.0003627074,0.0006162933,0.0007646803,0.0005683958,0.000599551,0.0001524024],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001091668,"about_ca_system_score_gemma":0.0008469961,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01752524,"about_ca_topic_score_gemma":0.009326009,"domain_scores_codex":[0.9998955,0.00002468992,0.000005634227,0.00002416002,0.00002619551,0.00002382005],"domain_scores_gemma":[0.9995396,0.0002571004,0.00006615359,0.00003614317,0.00006585698,0.00003516891],"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":[0.000005931965,0.000007833721,0.0003540757,0.000004820676,0.000002663922,0.00002051444,0.000008612352,0.997056,0.0009027872,0.001247645,0.00003056456,0.0003586701],"study_design_scores_gemma":[8.14599e-7,0.000001051248,0.00004086947,3.765721e-7,3.882654e-7,0.000001352329,0.000001489218,0.9995776,0.0001125783,0.0002181317,0.00004453175,8.174457e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6121641,0.0002242643,0.3740472,0.0005086436,0.00003959615,0.00008379092,0.0009342394,0.0005503324,0.01144774],"genre_scores_gemma":[0.9766294,0.0001020919,0.0206082,0.00003081044,0.000007850246,0.0001188252,0.0001919792,0.00006562859,0.002245186],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01752524,"threshold_uncertainty_score":0.03484648,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02387993320301329,"score_gpt":0.2741572471665594,"score_spread":0.2502773139635461,"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."}}