{"id":"W2912173455","doi":"10.1190/geo2017-0376.1","title":"Matrix-fluid decoupling-based joint PP-PS-wave seismic inversion for fluid identification","year":2019,"lang":"en","type":"article","venue":"Geophysics","topic":"Seismic Imaging and Inversion Techniques","field":"Earth and Planetary Sciences","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Petro-Canada","funders":"","keywords":"Amplitude versus offset; Decoupling (probability); Poromechanics; Geology; Inversion (geology); Fluid dynamics; Seismic inversion; Bulk modulus; Matrix (chemical analysis); Mechanics; Amplitude; Porosity; Porous medium; Seismology; Geotechnical engineering; Mathematics; Physics; Materials science; Optics; Geometry; 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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003103171,0.0001679262,0.0001934491,0.00009186179,0.0001763177,0.00008289135,0.0001857873,0.00008768237,0.0003426374],"category_scores_gemma":[0.00002640067,0.0001584242,0.0001450057,0.0002025999,0.00005075651,0.0002827594,0.00001422648,0.0001122607,0.001631193],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001699121,"about_ca_system_score_gemma":0.00008296242,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001307321,"about_ca_topic_score_gemma":0.00000417696,"domain_scores_codex":[0.9987769,0.00002767069,0.0002636891,0.0003650855,0.0002557515,0.00031087],"domain_scores_gemma":[0.9991872,0.00009824715,0.0001411174,0.0003807222,0.0001086147,0.00008408934],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000651469,0.0002929295,0.04786211,0.001073733,0.0001409498,0.00001554877,0.0008186707,0.06020902,0.07684993,0.001201476,0.4715414,0.3393427],"study_design_scores_gemma":[0.0004223368,0.0001464695,0.004276657,0.00003843779,0.00002414162,0.000001750748,0.00007967396,0.9103281,0.04867052,0.00387247,0.03188998,0.0002494263],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9711125,0.0002008052,0.02504659,0.0007926272,0.001066915,0.0006387066,0.0001279901,0.0002893241,0.0007245472],"genre_scores_gemma":[0.9936203,0.00003417876,0.00242501,0.002243766,0.0001456142,0.000004754838,0.000644578,0.00001052717,0.0008712455],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8501191,"threshold_uncertainty_score":0.9991462,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01812003434619434,"score_gpt":0.2209621375168429,"score_spread":0.2028421031706486,"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."}}