{"id":"W7125674251","doi":"10.22564/19cisbgf2025.422","title":"Evaluating the Impact of Processing Variants on 4D Seismic Inversion and Interpretation: Case study in the Brazilian Pre-salt","year":2025,"lang":"","type":"article","venue":"","topic":"Seismic Imaging and Inversion Techniques","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Universidade Estadual de Campinas; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Energi Simulation; Shell Brasil; U.S. Department of Energy","keywords":"Inversion (geology); Workflow; Seismic inversion; Data processing; Seismic to simulation; Reservoir modeling; Data quality","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":[0.003360663,0.001001297,0.0005467198,0.001052388,0.000648507,0.001307549,0.0008348234,0.001200014,0.0008222962],"category_scores_gemma":[0.009947796,0.0003356892,0.0008311927,0.001189385,0.001073087,0.0008971128,0.001071528,0.0007333586,0.0002895551],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006746484,"about_ca_system_score_gemma":0.001293422,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02697141,"about_ca_topic_score_gemma":0.03640974,"domain_scores_codex":[0.9988237,0.0003493565,0.0001125551,0.0002581862,0.000301261,0.0001549273],"domain_scores_gemma":[0.9955877,0.00265386,0.0002419129,0.0005260268,0.0008436233,0.0001468893],"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":[0.002390777,0.0008532182,0.1300151,0.0010028,0.0006544521,0.004754373,0.002860839,0.4918359,0.07785034,0.005042249,0.003064986,0.2796749],"study_design_scores_gemma":[0.0002161131,0.0007134376,0.09343413,0.0002016016,0.0003658809,0.001369991,0.003350072,0.8348352,0.05022079,0.005545289,0.009560334,0.0001871302],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9350805,0.0002397696,0.0600662,0.0004680438,0.00005695077,0.0001426831,0.0007965043,0.00065021,0.002499198],"genre_scores_gemma":[0.9083815,0.0001798309,0.08973102,0.00007534739,0.00002028938,0.00005351875,0.000878612,0.0001688538,0.0005110754],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02697141,"threshold_uncertainty_score":0.0536288,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03653449285478752,"score_gpt":0.3666933401580617,"score_spread":0.3301588473032742,"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."}}