{"id":"W2336711289","doi":"10.3968/8270","title":"Geometry Matching Technology of Non-Repeating Acquired Time-Lapse Seismic Data Processing","year":2016,"lang":"en","type":"article","venue":"Advances in petroleum exploration and development","topic":"Reservoir Engineering and Simulation Methods","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Offset (computer science); Seismic to simulation; Azimuth; Oil field; Gaussian; Geology; Seismic attribute; Data processing; Seismic inversion; Computer science; Seismology; Geometry; Petroleum engineering; Mathematics; Database","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.0003965737,0.0004251236,0.0003310302,0.000793818,0.0002391856,0.0006674162,0.0007957061,0.0004165304,0.00258635],"category_scores_gemma":[0.001575385,0.0003071302,0.0005478384,0.0009828985,0.0003381828,0.001060029,0.0007175475,0.0003915585,0.0007770531],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003385089,"about_ca_system_score_gemma":0.0006863794,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001375857,"about_ca_topic_score_gemma":0.001321755,"domain_scores_codex":[0.9994181,0.00007709031,0.00003445724,0.0001318622,0.0002917224,0.00004667633],"domain_scores_gemma":[0.9995928,0.00007291282,0.00006904102,0.0001119752,0.0001327963,0.00002058054],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002626733,0.0001208292,0.005545673,0.0001641111,0.00008467848,0.0003169055,0.0004535139,0.0738981,0.2914087,0.02059197,0.002473377,0.6046795],"study_design_scores_gemma":[0.00002018036,0.0001828637,0.007229277,0.00001026864,0.00003929186,0.0005838287,0.0001673669,0.7696834,0.2041801,0.007175653,0.01067466,0.00005309054],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02347229,0.0000408777,0.9745845,0.00005514226,0.0000242614,0.00003096489,0.0000676761,0.0005289653,0.001195277],"genre_scores_gemma":[0.3238837,0.0002558245,0.6717662,0.00006696731,0.00004200438,0.000100514,0.0004594323,0.00019645,0.003228982],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00258635,"threshold_uncertainty_score":0.00865227,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01912158018931938,"score_gpt":0.2838159907338868,"score_spread":0.2646944105445674,"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."}}