{"id":"W2328693804","doi":"10.2118/175906-ms","title":"A Model for Gas Transport in Micro Fractures of Shale and Tight Gas Reservoirs","year":2015,"lang":"en","type":"article","venue":"","topic":"Hydrocarbon exploration and reservoir analysis","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"National Science and Technology Major Project; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China; Alberta Innovates - Technology Futures; CMG Reservoir Simulation Foundation","keywords":"Knudsen diffusion; Knudsen number; Shale gas; Tight gas; Slip (aerodynamics); Mechanics; Collision; Free molecular flow; Knudsen flow; Diffusion; Gaseous diffusion; Flow (mathematics); Petroleum engineering; Chemistry; Materials science; Oil shale; Geology; Thermodynamics; Physics; Hydraulic fracturing; Computer science","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":[0.0003091325,0.000537666,0.0008737876,0.000599725,0.0007770956,0.0008242084,0.001721934,0.002008794,0.001656352],"category_scores_gemma":[0.0007548292,0.0004503145,0.0009179928,0.0005554233,0.001016609,0.001126855,0.0006847421,0.0009352303,0.0002273917],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001812196,"about_ca_system_score_gemma":0.00183461,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03672856,"about_ca_topic_score_gemma":0.01372384,"domain_scores_codex":[0.9998215,0.00002529832,0.000009981687,0.00004622573,0.00005550798,0.0000414918],"domain_scores_gemma":[0.9997715,0.0000835788,0.00004730753,0.00001427175,0.00005080142,0.00003255988],"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":[0.00002270855,0.00002530608,0.0006481259,0.00002053449,0.000008879339,0.0001116099,0.00003163142,0.9862754,0.003236485,0.008414148,0.0001070999,0.001097938],"study_design_scores_gemma":[0.000005494987,0.00001146858,0.0001546874,0.000002357885,0.000003282171,0.00001822143,0.00001147374,0.9986877,0.0002392391,0.0007251689,0.0001359574,0.000004949119],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6518652,0.001006289,0.3308796,0.0006506257,0.00009246801,0.000143902,0.0009674364,0.0004129532,0.0139815],"genre_scores_gemma":[0.9796538,0.0003772459,0.009991947,0.00004120539,0.00001907546,0.0001468609,0.0001547689,0.00004495167,0.009570052],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03672856,"threshold_uncertainty_score":0.07302958,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03063660182413845,"score_gpt":0.2548329604234288,"score_spread":0.2241963585992903,"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."}}