{"id":"W2509331320","doi":"10.1190/segam2016-13866468.1","title":"Inversion of continuous 4D seismic attributes to reveal daily reservoir changes","year":2016,"lang":"en","type":"article","venue":"","topic":"Seismic Imaging and Inversion Techniques","field":"Earth and Planetary Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Shell Canada","keywords":"Geology; Inversion (geology); Visualization; Seismic inversion; Reservoir modeling; Seismology; Petroleum engineering; Computer science; Data assimilation; Artificial intelligence; Meteorology; Geography","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":[0.0002766452,0.0004419479,0.0002522101,0.00120092,0.0001456508,0.0004988018,0.0003531734,0.0003871484,0.001632254],"category_scores_gemma":[0.001167965,0.0003449938,0.0003658348,0.0009587292,0.0002215234,0.0004935796,0.0005217858,0.0004703229,0.0004406737],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002646082,"about_ca_system_score_gemma":0.0005165201,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003170672,"about_ca_topic_score_gemma":0.005006399,"domain_scores_codex":[0.9998994,0.00001371149,0.000005620869,0.00002168145,0.0000411605,0.00001850633],"domain_scores_gemma":[0.9997446,0.00008016733,0.00003441029,0.00003859062,0.0000717168,0.00003042095],"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":[0.0003808536,0.0003704516,0.05884643,0.0002127398,0.0001649144,0.0006170202,0.0005508902,0.5090952,0.2155648,0.00441574,0.0035996,0.2061814],"study_design_scores_gemma":[0.00001490906,0.00003169387,0.01458292,0.000006332267,0.00001327412,0.00005035922,0.00007482351,0.9739656,0.008999513,0.001016259,0.001224344,0.00001986117],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7635713,0.00008414388,0.2255509,0.0004207082,0.00008466726,0.00007824745,0.001895726,0.002265057,0.0060492],"genre_scores_gemma":[0.9405175,0.00007326098,0.05739992,0.00002927504,0.00002701543,0.00002726536,0.00101127,0.0001080623,0.0008063208],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003170672,"threshold_uncertainty_score":0.006304443,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02192948395705158,"score_gpt":0.2239326810888163,"score_spread":0.2020031971317647,"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."}}