{"id":"W2765973974","doi":"10.1016/j.jngse.2017.10.016","title":"Numerical investigation of two-phase fluid flow in a perforation tunnel","year":2017,"lang":"en","type":"article","venue":"Journal of Natural Gas Science and Engineering","topic":"Hydraulic Fracturing and Reservoir Analysis","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":false,"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada; Memorial University of Newfoundland; Research and Development Corporation of Newfoundland and Labrador; Texas A and M University","keywords":"Perforation; Drilling fluid; Petroleum engineering; Fluid dynamics; Volumetric flow rate; Porosity; Drilling; Materials science; Flow (mathematics); Permeability (electromagnetism); Viscosity; Porous medium; Computer simulation; Geotechnical engineering; Mechanics; Geology; Composite material; Engineering; Simulation; Chemistry","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005825419,0.00007511635,0.0001678898,0.0003004022,0.00008278368,0.00008350872,0.000219175,0.00002813655,0.000001942598],"category_scores_gemma":[0.0002880119,0.00005878279,0.00003877858,0.0002207043,0.00007976329,0.000799797,0.00001917816,0.0002243843,3.61296e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006117553,"about_ca_system_score_gemma":0.00003641984,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001561913,"about_ca_topic_score_gemma":0.000003335042,"domain_scores_codex":[0.9992355,0.000004706773,0.0002512474,0.00006899888,0.000295136,0.0001444018],"domain_scores_gemma":[0.9995785,0.00001930804,0.00008525673,0.0001121573,0.0001132798,0.00009145746],"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":[0.000004882465,0.000004512011,0.0006222708,0.00003222104,0.000008007209,0.000008687171,0.000256389,0.8349794,0.1601918,0.000004383638,0.00001564607,0.003871783],"study_design_scores_gemma":[0.0004194302,0.00003656708,0.01290182,0.0001003618,0.00000916815,0.00003311146,0.00002142983,0.9553706,0.03098873,0.0000252907,0.00002577838,0.00006771696],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9969361,0.0003979796,0.002150978,0.0001643356,0.0002807372,0.00002149275,2.803137e-7,0.000009200995,0.00003893813],"genre_scores_gemma":[0.9975907,0.00008441504,0.002218093,0.00000532967,0.00009231789,4.413058e-7,2.53045e-7,0.000005101874,0.000003325298],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1292031,"threshold_uncertainty_score":0.2397093,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009939199430576034,"score_gpt":0.251492477235217,"score_spread":0.241553277804641,"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."}}